Oxygen Conserving Devices Market: Overview

According to the report, the global oxygen conserving devices market was valued at ~US$ 164 Mn in 2018. It is projected to expand at a moderate CAGR during the forecast period. Oxygen therapy is considered to be a highly important tool to help save lives of patients suffering from hypoxemia and other health conditions. Oxygen conservers are used to regulate the supply of oxygen, thus saving the overuse of oxygen by offering precise amount of oxygen. Oxygen conservers are prescribed with ambulatory cylinders, which optimizes the supply for a long duration of up to three days. Pneumatic, electronic, liquid oxygen, and disposable are the various oxygen conserver devices available in the market.

Significant expansion of the oxygen conserving devices market can be attributed to investments in technology, strong product portfolio, and rise in patient pool suffering from pulmonary or non-pulmonary condition. Moreover, increase in geriatric population is another factor fueling the oxygen conserving devices market.

North America dominated the oxygen conserving devices market in 2018, and the trend is anticipated to continue during the forecast period. This can be ascribed to the rise in awareness about hypoxemia that is caused by COPD and other respiratory diseases, presence of key players, increase in patient pool, favorable reimbursement policies, and availability of new oxygen conservers for pediatric patients in the region. However, misdiagnosis or underdiagnoses and high product pricing of certain oxygen conservers are likely to hamper the oxygen conserving devices market in North America during the forecast period.

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Rise in Incidences of COPD and Other Chronic Respiratory Diseases to Drive Market

Rising incidences of chronic obstructive pulmonary disease (COPD) and other respiratory diseases globally is likely to prompt key players to develop oxygen conservers as a supplemental oxygen therapy and subsequently, save wastage of oxygen. COPD is considered to be the third-leading cause of death in the U.S., and fourth-leading cause of death across the world. According to an article published on Verywell Health, COPD affects around 11 million people in the U.S. and commonly occurs in people over the age of 40. This indication drives the need for supplemental oxygen, which is managed by the use of oxygen conserving devices.

According to the Global Burden of Disease Study, in 2016251 million cases of COPD were identified, and 3.17 million deaths were recorded due to this disease, globally. Mostly 90% of deaths by COPD occur in middle or low income countries. A major cause for COPD disease is the increase in incidence of smoking among adults across the globe. Moreover, long-term asthma is also responsible for causing the COPD disease. According to research published in Science Daily, in April 2018, China was home to a significantly large population of adult COPD patients, which is estimated to be 100 million. This number represents around 8.6% of the population of China, which indicates that the prevalence of COPD is considerably high in China.

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Increasing Geriatric Population Fuels Demand for Continuous Innovation in Oxygen Therapy

Rising geriatric population, globally, is fueling the demand for oxygen conserving devices to carry out their daily activities. The geriatric population often suffers from certain chronic respiratory diseases that hamper their mobility; hence, their dependence on oxygen therapy helps improve the quality of their life. For instance, pneumatic, electronic, and disposable oxygen conservers are available for geriatric patients and thus, fulfill the need for devices offering supplemental oxygen. Rise in the geriatric population demands better treatment options, which in turn is likely to provide opportunities to companies that operate in the oxygen conserving devices market. According to the United Nations, the geriatric population, or people above the age of 60, is expected to double by 2050, and triple by 2100. It is projected to rise from 962 million in 2017 to 2.1 billion by 2050 and reach 3.1 billion by 2100. Globally, the geriatric population is the rising at a rapid pace, as compared to the population growth rate of the younger age group.

Rising Prevalence of Chronic Bronchitis Drives Demand for Oxygen Conserving Devices

In terms of indication, the oxygen conserving devices market has been segmented into chronic bronchitis, emphysema, sleep apnea, and others. Chronic bronchitis and emphysema are two major COPD diseases that accounted for considerable deaths and these conditions drive the need for oxygen therapy across globe. Patients suffering from severe COPD require continuous supply of oxygen. According to WHO, COPD is the fourth-leading cause of death in the world, with approximately 2.75 million deaths per annum. The WHO predicts that COPD would be the third-leading cause of death by 2030. According to the CDC, over 16 million people in the U.S. are living with respiratory disorders such as lung cancer, COPD, and heart diseases, caused due to smoking.

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Oxygen Conserving Devices Market: Prominent Regions

In terms of region, the oxygen conserving devices market has been segmented into five major regions: North America, Europe, Asia Pacific, Latin America, and Middle East & Africa. North America dominated the oxygen conserving devices market in 2018, followed by Europe. North America accounted for a major share of the oxygen conserving devices market in 2018, owing to a rise in incidence of COPD and supportive government policies. Moreover, aging baby boomers are estimated to fuel the demand for oxygen therapy, including oxygen conservers, to help them lead a comfortable life.

According to the U.S. Census Bureau, all baby boomers are expected to be older than the age of 65 by the year 2030. Technological advancements and reliable reimbursement policies in the U.S. for oxygen therapy devices helps patients to access these devices. Moreover, presence of key players in the region and a strong product portfolio of supplemental oxygen therapy are projected to drive the market in the region.

The oxygen conserving devices market in Asia Pacific is projected to expand at a notable CAGR from 2019 to 2027. This can be attributed to an increase in healthcare expenditure, rapid increase in rate of adoption of devices used for oxygen therapy, and growing prevalence of chronic respiratory diseases among patient population in developing countries. Moreover, rising geriatric population in countries such as Japan, India, and China is estimated to positively impact the development of innovative oxygen conserver devices in these countries. Furthermore, strong medical devices supply chain in countries such as India, Japan, and China is driving the oxygen conserving devices market in the region.

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Development of Innovative Disposable Oxygen Conservers Offers Significant Growth Opportunities

The oxygen conserving devices market is fragmented, in terms of number of players. Key as well as local players have been offering various oxygen conserving devices, including pneumatic, liquid oxygen, and disposable types in the market for the past few years. Key players operating in the oxygen conserving devices market include Inogen Inc., GCE Group, Precision Medical Inc., Drive DeVilbiss International, Medline Industries, Inc., GF health Products, Inc., Inovo, Inc., Essex Industries, and Krober Medizintechnik. These players have adopted various strategies, such as investments toward the development of oxygen conserving devices, which include disposable oxygen conservers, electronic oxygen conservers, and strengthening their distribution network and product portfolio.

Companies such as Drive Devilbliss Healthcare have introduced disposable oxygen conservers, such as Oxymizer disposable oxygen conserver, which provides and saves oxygen in 4:1 ratio, as compared to that offered by other continuous flow oxygen therapy devices.

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What Is Trelegy Ellipta?

Trelegy Ellipta (fluticasone, umeclidinium, and vilanterol) is an inhaled prescription drug used for the maintenance treatment of adults with asthma or chronic obstructive pulmonary disease (COPD). Maintenance treatment helps to prevent and control symptoms. COPD is a chronic lung disease that includes chronic bronchitis, emphysema, or both.

Trelegy Ellipta contains three drugs. Fluticasone is an inhaled corticosteroid. Umeclidinium is in a drug class called anticholinergics. Vilanterol is in a drug class called long-acting beta-agonists (LABAs). These three ingredients in Trelegy Ellipta work together to relax and open air passages in the lungs, making it easier to breathe.

Trelegy Ellipta is available as an inhaler. 

Drug Facts

Generic Name: Fluticasone, umeclidinium, and vilanterol

Brand Name: Trelegy Ellipta

Drug Availability: Prescription

Therapeutic Classification: Corticosteroid; anticholinergic; LABA

Available Generically: No

Controlled Substance: N/A

Administration Route: Inhalation

Active Ingredient: Fluticasone, umeclidinium, and vilanterol

Dosage Form: Powder for inhalation

What Is Trelegy Ellipta Used For?

The Food and Drug Administration (FDA) approved Trelegy Ellipta for adults (18 years and older) for the maintenance treatment of:

Trelegy Ellipta is not approved for children and does not treat acute bronchospasm (narrowing of the airways, which can cause wheezing and difficulty breathing).

How to Take Trelegy Ellipta

While using this medication, read the prescription label and information leaflet that comes with it. Trelegy Ellipta is administered with an inhaler. Consult your healthcare provider if you have any questions about using the inhaler.

If you are prescribed Trelegy Ellipta, remember the following:

  • Take your medication once a day, at the same time every day. 
  • Rinse with water and spit (do not swallow the water) after using Trelegy Ellipta to help prevent yeast infection in the mouth.
  • Do not take Trelegy Ellipta more than once in 24 hours. 
  • Discard Trelegy Ellipta six weeks after removing it from the foil pouch or if the dose indicator reaches zero (whichever comes first). Write the day you opened the pouch on the label on the inhaler.

It is important to take this medication exactly as prescribed. Trelegy Ellipta is not a rescue inhaler. Use your rescue inhaler for asthma or bronchospasm attacks. 

Call your healthcare provider if you are sick, feeling stressed, or are planning to have surgery. Get medical help if your breathing problems worsen or if it seems like your medicines are not working as well as before. Your healthcare provider will tell you what tests you need, such as vision and bone mineral density. 

Ask your healthcare provider if you have any questions or concerns.


Store Trelegy Ellipta at room temperature (between 68 and 77 degrees Fahrenheit) and away from heat, direct light, and moisture. Keep this medication in its sealed foil package until ready to use. Throw away the inhaler device six weeks after taking it out of the foil pouch or when the dose indicator is zero, whichever comes first.

Keep this medication out of reach and out of sight of children and pets.

How Long Does Trelegy Ellipta Take to Work?

Trelegy Ellipta may start working after the first dose, but it is essential to take it daily to prevent and control symptoms. It may take a few weeks to feel the full effect of Trelegy Ellipta.

What Are the Side Effects of Trelegy Ellipta?

This is not a complete list of side effects and others may occur. A healthcare provider can advise you on side effects. If you experience other effects, contact your pharmacist or a medical professional. You may report side effects to the FDA at www.fda.gov/medwatch or 800-FDA-1088.

Common Side Effects

The most common side effects of Trelegy Ellipta are:

  • Yeast (fungal) infection of the mouth, throat, and/or esophagus
  • Upper respiratory infection (URI) symptoms (e.g., runny or stuffy nose, sore throat, cough)
  • Headache
  • Back or joint pain
  • Altered taste 
  • Mouth sores 
  • Hoarse voice
  • Stomach problems (e.g., nausea, vomiting, constipation, diarrhea)
  • Urinary tract infection (UTI)

Severe Side Effects

Call your healthcare provider right away if you have serious side effects. Call 911 if your symptoms feel life-threatening or if you think you’re having a medical emergency. Serious side effects and their symptoms can include the following:

  • Pneumonia (when Trelegy Ellipta is used for COPD): Call your provider if you have a fever, chills, cough with mucus, or shortness of breath
  • Hypersensitivity reaction or anaphylaxis: Symptoms can include rash, hives, swelling around the lips, tongue, and face, and difficulty breathing, and require emergency medical attention. 
  • Weakened immune system and increased chance of getting infections
  • Osteoporosis (bone thinning or weakness, which can lead to fractures)
  • Nervous system reactions, including tremors and nervousness
  • Changes in blood test values
  • Urinary retention
  • Effects on the heart, including chest pain, increased blood pressure, arrhythmia (irregular heartbeat), cardiac arrest (sudden loss of heart function, breathing, and consciousness)
  • Paradoxical bronchospasm (unexpected airway tightening after using the inhaler)
  • Worsening of asthma
  • Low levels of potassium in the blood (call your provider if you have leg cramps, constipation, chest fluttering, muscle weakness, irregular heartbeat, or numbness and tingling)
  • High levels of blood sugar (call your provider if you have increased thirst and urination)
  • Eosinophilia (high levels of eosinophils, a type of white blood cell)
  • Churg-Strauss syndrome (blood vessel inflammation)
  • Eye problems (including glaucoma and cataracts in COPD patients)

Long-Term Side Effects

While many people tolerate Trelegy Ellipta well, long-term or delayed side effects are possible. Some long-term side effects can be mild, such as:

  • Back pain 
  • Taste disorder
  • Reflux
  • Muscle cramps
  • Anxiety 
  • Mouth pain

Moderate long-term side effects can include:

Severe long-term side effects may include: 

  • Bone fractures
  • Heart attack
  • Asthma-related death
  • Churg-Strauss syndrome
  • Vasculitis (blood vessel inflammation)
  • Increased pressure in the eye

Report Side Effects

Trelegy Ellipta may cause other side effects. Call your healthcare provider if you have any unusual problems while taking this medication.

If you experience a serious side effect, you or your provider may send a report to the FDA's MedWatch Adverse Event Reporting Program or by phone (800-332-1088).

Dosage: How Much Trelegy Ellipta Should I Take?

Drug Content Provided and Reviewed by

IBM Micromedex®

The dose of this medicine will be different for different patients. Follow your doctor's orders or the directions on the label. The following information includes only the average doses of this medicine. If your dose is different, do not change it unless your doctor tells you to do so.

The amount of medicine that you take depends on the strength of the medicine. Also, the number of doses you take each day, the time allowed between doses, and the length of time you take the medicine depend on the medical problem for which you are using the medicine.

  • For inhalation dosage form (powder):

    • For treatment of asthma:

      • Adults—One inhalation once a day. Each inhalation contains 100 or 200 micrograms (mcg) of fluticasone, 62.5 mcg of umeclidinium, and 25 mcg of vilanterol.
      • Children—Use is not recommended.
    • For treatment and prevention of worsening attacks of COPD:

      • Adults—One inhalation once a day. Each inhalation contains 100 micrograms (mcg) of fluticasone, 62.5 mcg of umeclidinium, and 25 mcg of vilanterol.
      • Children—Use is not recommended.


You may need to use caution when taking Trelegy Ellipta if you are 65 years or older or have moderate to severe liver problems. Consult your healthcare provider.

If you are pregnant, planning to become pregnant, or are breastfeeding, consult your healthcare provider.

Missed Dose

Use Trelegy Ellipta as your provider directs, and do not skip doses. Misusing Trelegy Ellipta may cause serious heart problems or death.

If you do miss a dose, take it as soon as possible. Skip the missed dose if it is almost time for the next dose. Do not take two doses together. Do not take more than one inhalation of Trelegy Ellipta in 24 hours.

Overdose: What Happens If I Take Too Much Trelegy Ellipta?

Taking too much Trelegy Ellipta can cause shakiness, chest pain, a fast heart rate, and shortness of breath.

What Happens If I Overdose on Trelegy Ellipta?

If you think you or someone else may have overdosed on Trelegy Ellipta, call a healthcare provider or the Poison Control Center (800-222-1222).

If someone collapses or isn't breathing after taking Trelegy Ellipta, call 911 immediately.


Drug Content Provided and Reviewed by

IBM Micromedex®

If you will be using this medicine for a long time, it is very important that your doctor check your progress at regular visits. This will allow your doctor to see if the medicine is working properly and to check for any unwanted effects.

Tell your doctor about other medicines you are using for your asthma or COPD. Follow your doctor's instructions on how you should take your medicine.

This medicine should not be used if you are having an asthma or COPD attack, or if symptoms of an asthma or COPD attack has already started. Your doctor will prescribe another medicine for you to use in case of an acute attack. If the other medicine does not work as well, tell your doctor right away.

This medicine may increase the chance of asthma-related problems. Be sure to read about these risks in the Medication Guide and talk to your doctor or pharmacist about any questions or concerns that you have.

This medicine may increase the risk of worsening asthma, which may lead to hospitalization, intubation, and death in patients with asthma. Talk to your doctor if you have concerns about this.

This medicine should not be used together with similar inhaled medicines such as arformoterol (Brovana®), formoterol (Foradil®, Perforomist®), indacaterol (Onbrez®), or salmeterol (Serevent®).

Your doctor may want you to carry a medical identification (ID) card stating that you are using this medicine. The card will say that you may need additional medicine during an emergency, a severe asthma or COPD attack or other illness, or unusual stress.

This medicine may weaken your immune system and increase your risk for infections. Tell your doctor about any immune system problems or infections, including tuberculosis or herpes infection in your eye. Tell your doctor right away if you have been exposed to chickenpox or measles.

This medicine may cause a fungus infection of the mouth or throat (thrush). Tell your doctor right away if you have white patches in the mouth or throat, or pain when eating or swallowing.

This medicine may increase your risk of having pneumonia. Call your doctor if you start having increased sputum (spit) production, change in sputum color, fever, chills, increased cough, or an increase in breathing problems.

Using too much of this medicine or using it for a long time may cause may increase your risk of having adrenal gland problems. Talk to your doctor if you have darkening of the skin, diarrhea, lightheadedness, dizziness, or fainting, loss of appetite, mental depression, muscle pain or weakness, nausea, skin rash, unusual tiredness or weakness, or vomiting.

This medicine may cause paradoxical bronchospasm, which means your breathing or wheezing will get worse. This may be life-threatening. Check with your doctor right away if you have coughing, or difficulty breathing after using this medicine.

This medicine may cause serious allergic reactions, including anaphylaxis and angioedema, which can be life-threatening and require immediate medical attention. Tell your doctor right away if you have a rash, itching, hoarseness, trouble breathing, trouble swallowing, or any swelling of your hands, face, or mouth after using this medicine.

This medicine may increase your risk for heart and blood vessel problems, including changes in heart rhythm. Check with your doctor right away if you have dizziness, fainting spells, severe tiredness, chest pain, trouble with breathing, sudden or severe headache, or fast or irregular heartbeat.

This medicine may decrease bone mineral density when used for a long time. A low bone mineral density can cause weak bones or osteoporosis. If you have any questions about this, ask your doctor.

Check with your doctor right away if blurred vision, difficulty in reading, or any other change in vision occurs during or after treatment. Your doctor may want your eyes be checked by an ophthalmologist (eye doctor).

This medicine may affect blood sugar and potassium levels. If you have heart disease or diabetes and notice a change in the results of your blood or urine sugar or potassium tests, check with your doctor.

This medicine may cause a slowed growth in children. Talk with your doctor if you have any concerns about this.

Do not take other medicines unless they have been discussed with your doctor. This includes prescription or nonprescription (over-the-counter [OTC]) medicines and herbal or vitamin supplements.

What Are Reasons I Shouldn’t Take Trelegy Ellipta?

Trelegy Ellipta is not appropriate for everyone.

There are certain reasons that you should not take this medication, such as:

  • If you are allergic to fluticasone, umeclidinium, vilanterol, or any of the inactive ingredients in Trelegy Ellipta
  • If you are allergic to milk protein
  • To attempt to treat an acute attack or a worsening of asthma or COPD
  • If you are taking any other drug that contains an anticholinergic or a LABA

Trelegy Ellipta may be prescribed with caution in some people only if the healthcare provider determines it is safe, including in people who have taken a drug called a monoamine oxidase inhibitor (MAOI) or tricyclic antidepressant within 14 days. This also includes people with:

What Other Medications May Interact With Trelegy Ellipta?

Tell your healthcare provider about the medications you take, including prescription and over-the-counter (OTC) drugs and vitamins or supplements.

Drug interaction studies have not been explicitly done with Trelegy Ellipta, so the available information is for each component—fluticasone, umeclidinium, and vilanterol.

Monoamine oxidase inhibitors should never be taken with Trelegy Ellipta. An MAOI combined with Trelegy Ellipta can cause high blood pressure and heart problems. Examples of MAOIs are:

  • Marplan (isocarboxazid)
  • Nardil (phenelzine)
  • Parnate (tranylcypromine)

Tricyclic antidepressants combined with Trelegy Ellipta can also increase blood pressure and cause heart problems. Examples of TCAs include:

  • Elavil (amitriptyline)
  • Pamelor (nortriptyline)

Beta-blockers should generally not be taken with Trelegy Ellipta (or may be used with caution in some instances) because the combination can lower the efficacy of both drugs. Examples of beta-blockers include:

  • Coreg (carvedilol)
  • Inderal (propranolol)
  • Lopressor, Toprol XL (metoprolol)
  • Tenormin (atenolol)

Other drug interactions may occur with Trelegy Ellipta. Consult your healthcare provider for a complete list of drug interactions.

What Medications Are Similar?

Trelegy Ellipta contains three drugs: a steroid, an anticholinergic drug, and a LABA. It can be used for the maintenance treatment of COPD or asthma.

Breztri Aerosphere is an inhaler that also contains a drug from each of these categories. It contains budesonide (a steroid), glycopyrrolate (an anticholinergic), and formoterol fumarate (a LABA). Breztri Aerosphere is approved for the maintenance treatment of COPD, but it is not approved for asthma.

There are other combination inhaled drugs that contain a steroid and a LABA. Some examples include:

  • Advair Diskus (fluticasone and salmeterol)
  • Breo (fluticasone and vilanterol)
  • Dulera (mometasone and formoterol)
  • Symbicort (budesonide and formoterol)

Inhaled corticosteroid inhalers are available as single-ingredient products as well. Some examples include:

  • Alvesco (ciclesonide)
  • Asmanex (mometasone)
  • Flovent HFA (fluticasone)
  • Pulmicort Flexhaler (budesonide)
  • Qvar RediHaler (beclomethasone-diproprionate HFA)

LABAs are also available as single-ingredient products but should never be taken alone. LABAs should always be taken with an inhaled steroid, as taking them without a steroid can increase the risk of death. This can be done as two individual products or as a combination product. Serevent (salmeterol) is an example of a LABA. 

There are also a variety of other drugs that may be prescribed for asthma or COPD maintenance, such as oral medications like Singulair (montelukast). Biologics, which are injected, are sometimes used in patients with difficult-to-control asthma.

This is a list of drugs also prescribed for asthma and COPD. It is not a list of drugs recommended to take with Trelegy Ellipta. Ask your pharmacist or a healthcare practitioner if you have questions.

Frequently Asked Questions

  • What is Trelegy Ellipta used for?

    Trelegy Ellipta is used in adults 18 years and older for maintenance treatment of COPD or asthma. Trelegy Ellipta does not treat an acute attack.

  • How does Trelegy Ellipta work?

    Trelegy Ellipta contains three drugs: fluticasone (a steroid), umeclidinium (an anticholinergic), and vilanterol (a long-acting beta-agonist). These ingredients help to relax and open the lungs, making it easier to breathe. 

  • What drugs should not be taken with Trelegy Ellipta?

    Monoamine oxidase inhibitors (MAOIs) and tricyclic antidepressants are some examples of drug classes that should not be mixed with Trelegy Ellipta. Beta-blockers generally should not be prescribed with Trelegy Ellipta, but in some cases, a beta-blocker may be used with caution if needed. There are other potential drug interactions as well. Tell your healthcare provider about all of the medications you take before taking Trelegy Ellipta. This includes prescription and OTC drugs as well as vitamins and supplements.

  • How long does it take for Trelegy Ellipta to work?

    Trelegy Ellipta may start to work after the first dose. However, it is important to take Trelegy Ellipta every day to prevent and control symptoms. The full effect may take a few weeks of treatment to be seen.

  • What are the side effects of Trelegy Ellipta?

    The most common side effects of Trelegy Ellipta are cold and flu symptoms, headache, back pain, joint pain, altered taste, mouth sores, hoarseness, urinary tract infection, nausea, vomiting, constipation, diarrhea, and yeast infection of the mouth, throat, and/or esophagus. Other side effects can occur.

  • How do I stop taking Trelegy Ellipta?

    Your healthcare provider will advise you on how long to take Trelegy Ellipta. Do not stop taking the medication without guidance from your provider. Trelegy Ellipta should not be stopped abruptly.

How Can I Stay Healthy While Taking Trelegy Ellipta?

Before taking Trelegy Ellipta, discuss your medical history and all medication you take with your healthcare provider. When taking Trelegy, follow your healthcare provider’s instructions for use. Read the patient information leaflet that comes with your prescription and ask your provider if you have any questions about the drug or how to use the inhaler.

Trelegy Ellipta must be taken once daily, every day, to help prevent and control symptoms. Each time you use Trelegy Ellipta, rinse your mouth with water and spit it out. This will help prevent a fungal infection of the mouth. 

Trelegy Ellipta cannot be used to treat an acute attack. Your rescue inhaler is fast-acting and should be used to treat symptoms of an acute asthma attack or bronchospasm. Common rescue inhalers include ProAir HFA (albuterol), Proventil HFA (albuterol), Ventolin HFA (albuterol), and Xopenex HFA (levalbuterol). If you notice you are using your rescue inhaler more frequently than usual, or feel like it is not working as well as it used to, contact your healthcare provider. 

Always carry your rescue inhaler with you. It can be helpful to have an extra rescue inhaler for work or school. Check the dose counter frequently to make sure your inhaler has enough remaining doses, and always call in your refills a few days early. This will allow extra time in case the pharmacy staff needs to contact your provider for refills, or if the inhaler has to be ordered. Check expiration dates periodically, to make sure your rescue inhaler is not expired.

Medical Disclaimer

Verywell Health's drug information is meant for educational purposes only and is not intended as a replacement for medical advice, diagnosis, or treatment from a healthcare professional. Consult your healthcare provider before taking any new medication(s). IBM Watson Micromedex provides some of the drug content, as indicated on the page.

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Chronic obstructive pulmonary disorder (COPD) is a group of lung diseases that includes chronic bronchitis and emphysema. Smoking or exposure to air pollutants usually causes COPD. It is becoming increasingly common, affecting an estimated 392 million people worldwide.

Some research has identified obesity as a risk factor for COPD. Doctors define obesity as having a body mass index (BMI) of 30 or higher. The number of people with obesity worldwide is also on the rise.

COPD and obesity have a complex and somewhat paradoxical relationship. COPD can make it difficult to manage obesity, and obesity can make breathing with COPD even harder.

But some studies seem to indicate that people with COPD and obesity have better outcomes than those without obesity. It’s unclear why this is. The relationship between the two conditions is not well understood, and study results are conflicting, so more research is needed.

This article will review what we know about how the two conditions affect each other and how you can help manage both.

In a review of studies, researchers found that patients with COPD were more likely to also have obesity than the general population. Meanwhile, obesity seems to be less common in people with severe COPD than in the general population.

Obesity can be a risk factor for developing COPD. One study found that the higher the level of obesity, the greater the risk of COPD in those who have never smoked. Smoking is one of the major causes of COPD.

While obesity may arguably have some protective advantages in certain situations, it also decreases the quality of life for those with COPD. It can make it harder to manage COPD, according to a 2018 study.


Dyspnea means shortness of breath, and can be moderate or severe. COPD causes lung damage, and many people with the condition can have trouble breathing at times because their lungs are not able to function properly. Patients in a 2017 study who had both conditions had worse dyspnea.

Obesity can cause or worsen dyspnea. Too much fat around the lungs can compress them, making them work harder and less effectively.

Dyspnea caused by obesity may not respond to COPD interventions. Reducing the amount of fat around your lungs can help you breathe better. Focusing on ways to get more physical activity can help you manage your weight.

Lung function

There is some indication that those with obesity are less likely to experience lung hyperinflation, but studies have not been conclusive. Hyperinflation happens when air gets trapped in the lungs but can’t get back out due to damage, as is sometimes seen in COPD patients.

But research shows that obesity negatively impacts respiratory disease. Pressure and constriction from a buildup of fat around the heart, lungs, and chest wall change how those organs normally function. That can make respiratory conditions more serious.

Other conditions

Obesity can lead to, or occur with, other serious conditions that could lower the quality of life for people with COPD. These include:

It’s important to manage your weight when you have COPD and obesity. Addressing both conditions can help you feel much better and improve your prognosis and quality of life.

Here are steps you can take to help manage both conditions.

  • Quit smoking. If you’re a smoker, the best thing you can do is quit. Also, avoid secondhand smoke and air pollution. If you need help quitting, make a plan with your healthcare team.
  • Choose the right treatments. COPD treatment options include medications, breathing programs, and other interventions. You’ll need to work with your doctor or healthcare team to choose the right combination for you. Good and consistent medical care is extremely important.
  • Eat a healthy diet. Some foods can help you effectively manage your weight and breathe better. The American Lung Association recommends eating more whole grains, fruits, lean meats, and certain types of fats. You should avoid fatty meat, saturated fats, and simple carbohydrates.
  • Be physically active. Exercise can help you manage your weight and COPD symptoms. If you don’t know where to start, walking can work for you regardless of your BMI. Resistance training can help you improve your body composition.

Can obesity cause COPD?

No, but it can make symptoms worse and cause other problems such as heart disease.

COPD can make it hard to manage obesity because people who have COPD often have trouble breathing. They can also experience fatigue, making exercise and healthy food prep harder.

Smoking is by far the largest cause of COPD. It’s also possible to get COPD from air pollution or working in at-risk occupations.

Can COPD cause me to gain weight?

COPD itself often causes people to lose weight. If you’re gaining weight, it could be due to:

  • quitting smoking
  • getting too little physical activity
  • not getting enough sleep
  • medications you might be taking

Why do people with COPD tend to lose weight?

About 25 to 40 percent of people with COPD have low body weight or are undernourished. About a quarter of people with COPD experience moderate to severe weight loss.

Weight loss in those with COPD can be a sign of severe COPD. When you work harder to breathe, you consume more energy, which can lead to weight loss. Many people with COPD also eat less due to not feeling well.

The American Lung Association has tips on weight gain and proper nutrition.

Is being underweight bad for COPD?

A review of studies indicates that being undernourished reduces your quality of life and increases your risk of serious complications from COPD. A well-balanced diet helps your heart and lung health and lowers cardiovascular and metabolic risk. It will help you feel better, too.

COPD and obesity are preventable and treatable diseases. The relationship between the two is unclear.

Obesity seems to have harmful effects in patients with COPD. But exacerbation and mortality rates are lower for those with obesity. It’s important to both manage your weight and treat COPD with the help of your medical team.

There are effective ways to make sure you stay nourished and maintain a healthy weight, which will improve your overall health and outlook.

COPD can’t be cured, but your medical team can help you develop an individualized plan to slow its progression and address obesity.

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Chronic obstructive pulmonary disease (COPD) has an increasing rate of incidence in recent years and causes three million deaths annually, which brings about a heavy economic burden.1 Currently, there are no effective target drugs applied to clinical practice so it is urgent to mine promising drug targets. Airway inflammation is an important feature and contributes to the pathogenesis and progression of COPD.2 Ferroptosis refers to the programmed cell death induced by lipid peroxidation via iron-dependent pathway with unique morphological and biological features.3 Usually under environmental stresses or intra/inter-cellular signaling, many metabolic products such as reactive oxygen species (ROS) and phospholipid containing polyunsaturated fatty acid chain(s) (PUFA-PL) can trigger phospholipid peroxidation.4 Previous study proved that ferroptosis was involved in the pathogenesis of COPD.5 Stimulated by cigarette smoke, bronchial epithelium produced reactive oxygen species, which induced lipid peroxidation, membrane damage and even ferroptosis.6–8 Glutathione peroxidase 4 (GPX4) – a vital antioxidant regulator – is also impaired during ferroptosis.9 Cigarette smoke extract altered ferroptosis-related genes expression in bronchoalveolar epithelial cells. Hypermethylation of the nuclear factor erythroid 2-related factor 2 (Nrf2) promoter could inhibit Nrf2/GPX4 axis, thus affecting ferroptosis in COPD.10 Otherwise, many studies suggest that various immune cells play vital roles in chronic airway diseases such as COPD. Innate immune cells, which were enhanced in small airways, modulated airway inflammation and remodeling.11 Previous study reported that CD8+ T cells enhanced ferroptosis-specific lipid peroxidation in tumor cells.12 The proliferation of B cells and antibody production was influenced by iron ion regulating the expression of Cyclin E1.13 Macrophages recognized oxidized phospholipids on the cell surface to clear ferroptosis cells via toll-like receptor 2 (TLR2).14 However, the interaction between ferroptosis and immune cells infiltration in COPD pathogenesis remains unclear.

The aim of this research is to identify ferroptosis-related hub genes and their association with immune cells infiltration in COPD lung tissues compared with normal ones. Additionally, we intend to construct interactive networks of hub genes with miRNAs, transcription factors and signal molecules and evaluate the diagnostic values of hub genes.

Materials and Methods

Data Acquisition

The mRNA expression microarray data of GSE38974,15 including 23 patients with COPD and 9 normal controls, were extracted from the Gene Expression Omnibus (GEO) datasets.16 The platform was GPL4133 Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version). Lung tissues from 9 smokers with no evidence of obstructive lung disease and 23 smokers with COPD were examined for mRNA expression. All the clinical information including age, gender, sample source, smoking history, GOLD stage and FVC group was publicly accessible in GEO database (www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSE38974&platform=GPL4133).

The 259 ferroptosis-related genes (FRGs) were downloaded from the FerrDb database.17

Identification of Differentially Expressed FRGs

The GEO2R is a web tool internally stalled in GEO database specialized for analyzing differentially expressed genes between experimental group and control group. The GEO2R analysis between COPD group and control group was performed on the GEO datasets and the result of differential expression analysis was downloaded for further analysis. The cut‐off criteria for differential gene expression were the absolute value of log fold change (FC) >1 and P value <0.05. The gene list of differential expression analysis and FRGs were intersected to obtain the differentially expressed FRGs. The expressions of differentially expressed FRGs were plotted using the R package Complex Heatmap.18 The expression differences of differentially expressed FRGs between COPD group and normal group in GSE38974 were compared using Kruskal–Wallis test and Dunn’s test. The correlation analysis of differentially expressed FRGs was performed using Spearman’s correlation.

Gene Ontology (GO) Terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways Analyses

The GO and KEGG enrichment analyses were conducted using the R package clusterProfiler.19 The screening criteria for significant terms were adjusted P values less than 0.05 and q values less than 0.2. Combined with logFC values, the enrichment analyses were performed by calculating the Z-scores using the R package GOplot.20

STRING Database and Cytoscape Software

The STRING database is an online tool for analyzing protein–protein interaction. The PPI analysis was carried out using the STRING database.21 Cytoscape is a computer software that graphically displays, analyzes and edits the network, which contains multiple plugins. The results were processed and visualized in Cytoscape software (version 3.9.0). The key module was screened by the Molecular Complex Detection (MCODE) plugin. The differentially expressed FRGs were ranked by degrees and the top five genes were considered to be hub genes by cytoHubba plugin.

The Comparative Toxicomics Database

The Comparative Toxicomics Database (CTD) provides integrated information on complex interactions among chemical exposures, genes, proteins and diseases.22 In this study, we used it to estimate the inference scores of hub genes in several respiratory tract diseases.

miRNet, NetworkAnalyst and Encyclopedia of RNA Interactomes (ENCORI)

There are multiple online tools to analyze the interaction between non-coding RNAs and genes and predict target molecules. The miRNet is a useful online tool centering around miRNAs and their interacting molecules.23 The NetworkAnalyst is an integrated and powerful database for gene expression analysis and construction of interacting networks.24 In this article, they were utilized to explore and visualize the networks between hub genes and miRNAs, transcription factors and signal molecules. The ENCORI focuses on predicting RNA interaction.25 Here, it was used to predict the upstream molecules lncRNAs targeting screened miRNAs. The screening criterion was set as strict stringency (the number of Ago CLIP-seq experiments is no less than five) and the top three lncRNAs were selected.

The Receiver Operating Characteristic (ROC) Curves of Hub Genes

The logistic regression model of hub genes was constructed using glm function in R software, and the ROC curves were plotted using R package pROC. The ROC curve of each hub gene can help us determine whether its expression has diagnostic value to some extent. The true positive rate (TPR) or sensitivity refers to the number of true positive samples detected divided by the number of all true positive samples. The false-positive rate (FPR) refers to the number of false-positive samples detected divided by the number of all true negative samples. Specificity refers to the number of true negative samples detected divided by the number of all true negative samples. The abscissa represents 1 – specificity and the ordinate represents sensitivity. The area under the curve (AUC) is used to determine the prediction accuracy. The AUC is usually between 0.5 and 1.0. The ROC curve has low/moderate/high accuracy when the AUC is 0.5~0.7/0.7~0.9/more than 0.9, respectively. The Youden’s index (sensitivity plus specificity minus one) is used to assess the authenticity of the model. As it gets closer to 1.0, the model is much more authentic.


CIBERSORT is an R/web tool for deconvolution of expression matrices of human immune cell subtypes based on the principle of linear support vector regression.26 By the way of the CIBERSORT algorithm, we analyzed the proportions of 22 types of immune cells infiltration in patients with COPD and normal controls. The infiltration differences in patients with COPD and normal controls were compared using Kruskal–Wallis test and Dunn’s test. The Spearman correlation analysis was carried out to show the correlation within differentially infiltrated immune cells and the association between hub genes and differentially infiltrated immune cells.

Statistical Methods

All the statistical calculations were conducted in R software (version 3.6.3). The corresponding R packages were described as above. The statistical significance was marked as follows: ns, p≥0.05; *p< 0.05; **p < 0.01; ***p < 0.001. A p.adjust was the corrected p value obtained by the p value correction method; a q-value was an adjusted p-value, taking into account the false discovery rate (FDR). As the p value/p.adjust/q-value is less than 0.0001, scientific notation (exponent, E) is used. For instance, 0.0000267 is written as 2.67E-05.


Identification of Differentially Expressed FRGs

The design of this research was shown in the flow chart (Figure 1). Principal component analysis (PCA) was conducted to show that there was a good degree of clustering between the two groups (Figure 2A). After intersection, 102 genes were obtained (Figure 2B). Under the condition of absolute values of logFC > 1 and P values <0.05, 15 differentially expressed FRGs were discovered including 11 upregulated genes and 4 downregulated genes (Table 1). The 15 differentially expressed FRGs between COPD and normal groups were presented in volcano plot and heatmap (Figure 2C and D). The volcano plot showed the distribution of gene expression between COPD and normal groups. Genes with an adjusted P-value <0.05 and absolute fold-change value > 1 were considered as differentially expressed genes. Each point represented one gene. Red dots indicated significantly upregulated genes and blue dots indicated significantly downregulated genes. The top three upregulated genes included IL6, ATM and TNFAIP3 and the top two downregulated genes included IL33 and TGFBR1. Furthermore, the expression differences of 15 differentially expressed FRGs between the COPD and normal groups in GSE38974 were shown in box plots (Figure 3A). As shown in Figure 3A, 15 ferroptosis-related genes were all significantly differentially expressed between COPD group and normal samples, which was consistent with Figure 2C and D. To explore the expression correlation of these ferroptosis-related genes, correlation analysis was performed. The Spearman correlation analyses of 15 differentially expressed FRGs were shown in heatmap (Figure 3B). As shown in Figure 3B, the expressions of most up-regulating genes were significantly positively correlated with each other, so were the down-regulating genes. Similarly, the expressions of the most up-regulated genes had a significantly negative correlation with those of the four down-regulated genes.

Table 1 The Differentially Expressed FRGs in COPD Group Compared with Normal Group

Figure 1 Flow chart.

Figure 2 Identification of differentially expressed ferroptosis-related genes (FRGs). (A) The principal component analysis (PCA) plot of samples in GSE38974. (B) Venn diagram of GEO2R result and FRGs. (C) Volcano plot of differential genes between COPD and normal groups. The top five genes were labelled (upregulated-IL6, ATM and TNFAIP3, downregulated-IL33 and TNFBR1). (D) Heatmap of 15 differentially expressed FRGs.

Figure 3 Expression and correlation of differentially expressed FRGs. (A) Box plot of 15 differentially expressed FRGs in COPD group compared with normal group. The significance markers are shown as: *, P<0.05; **, P<0.01; ***, P<0.001. (B) Heatmap of correlation of 15 differentially expressed FRGs.

The GO and KEGG Enrichment Analyses of Differentially Expressed FRGs

To analyze the potential biological functions of these differentially expressed ferroptosis-related genes, we carried out GO and KEGG enrichment analyses by way of R software. In total, 739 biological processes (BPs), 11 cellular components (CCs), 21 molecular functions (MFs) and 26 KEGG pathways were enriched. The GO term results exhibited that differentially expressed FRGs were mainly involved in regulation of smooth muscle cell proliferation, membrane microdomain, membrane raft, caveola, cytokine receptor binding, cytokine activity, and transforming growth factor beta receptor binding. The KEGG analysis indicated that differentially expressed FRGs participated in cell senescence pathway, FoxO signaling pathway and HIF1 signaling pathway (Figure 4A and B, Table 2). After combining with expression levels (logFC), the Z-scores showed that all the significant terms could be positively regulated by differentially expressed FRGs (Z-scores >0) (Figure 4C and D). These findings implied that 15 differentially expressed FRGs may participate in inflammatory responses and airway remodeling in COPD pathogenesis.

Table 2 The Most Significant Terms of GO and KEGG Enrichment Analyses

Figure 4 GO and KEGG enrichment analyses of differentially expressed FRGs. (A) Lollipop plot of significant terms. (B) Circular network of significant terms and genes. Blue nodes represent terms, red nodes represent genes, and connecting lines represent the relationship between terms and genes. (C) Bubble plot of significant terms combined with logFC. A Z-score greater than zero indicates positive regulation, a Z-score less than zero indicates negative regulation, and absolute value of Z-score represents the probability of regulation. (D) Donut plot of significant terms combined with logFC. Each column of the inner circle corresponds to one term, the height of column represents adjusted P value, and the filled color represents Z-score of each term.

Construction of Protein–Protein Interaction (PPI) Network and Identification of Key Module and Hub Genes

To determine the interactive relationship among differentially expressed FRGs, the protein–protein interaction analysis was conducted. The interaction of 15 candidate genes was analyzed in STRING database, and the results were visualized in Cytoscape software. The results showed that these differentially expressed FRGs interacted with each other (Figure 5A) and displayed the interaction number of each gene (Figure 5B, Supplementary Table 1). In total, there existed 15 nodes and 134 edges. The MCODE plugin analysis showed that there existed one key module containing 11 nodes and 50 edges including GDF15, IL6, ATF3, PTGS2, TGFBR1, HIF1A, CDKN1A, ATM, HMOX1, TNFAIP3 and MYB (Figure 5C). The cytoHubba plugin analysis identified five hub genes, including HIF1A, IL6, PTGS2, CDKN1A and ATM (Figure 5D). The Venn diagram indicated the overlap of predicted hub genes (Figure 5E). The detailed information of five hub genes can be seen in Supplementary Table 2.

Figure 5 PPI network, key module and hub genes of differentially expressed FRGs. (A) The PPI among 15 differentially expressed FRGs. (B) The interaction number of each differentially expressed FRG. (C) Key module of the PPI network screened by MCODE plugin. (D) Hub genes screened by cytoHubba plugin. (E) The overlap of predicted hub genes.

Evaluation of Correlation Between Hub Genes and Respiratory Tract Diseases

In order to estimate the theoretical association between predicted hub genes and chemical/environmental exposures, the five hub genes were analyzed in the Comparative Toxicomics Database and four respiratory tract diseases were chosen including COPD, chronic bronchitis, pulmonary emphysema and non-small cell lung cancer (NSCLC). The average inference scores of five hub genes in COPD (46.85) were higher than those in chronic bronchitis (35.72) and pulmonary emphysema (17.17) but lower than those in NSCLC (55.56) (Figure 6). The findings implied that five predicted hub genes might participate in multiple pathophysiological processes in respiratory diseases.

Figure 6 The correlations between hub genes and respiratory tract diseases in comparative toxicomics database.

Construction of the Networks Between Hub Genes with miRNAs, Transcription Factors and Signal Molecules

The hub genes could probably play a role by acting as transcription factors and vital signal molecules or interacting with intracellular non-coding RNAs. In order to predict upstream or downstream molecules of five hub genes and speculate on the mechanism of action of each hub gene, interactive network analysis was conducted. The five hub genes were uploaded to the miRNet online database to analyze the interaction with miRNAs and transcription factors in human lung tissues. In total, 44 miRNAs were predicted and two miRNAs, hsa-let-7b-5p and hsa-miR-1-3p, both targeting five hub genes, were selected for further exploration (Figure 7A, Supplementary Table 3). The transcription factor-hub gene regulatory network consisted of 217 interactions between 164 transcription factors and five hub genes. Five transcription factors including EGR1, NFKB1, RELA, SP1 and STAT3, which had the highest connectivity with hub genes, were selected (Figure 7B, Supplementary Table 3). The ENCORI database was used to screen upstream lncRNAs of the two miRNAs. Six lncRNAs were predicted: NUTM2A-AS19, XIST and NEAT1 (targeting hsa-let-7b-5p); RMRP, MALAT1 and AL162431.2 (targeting hsa-miR-1-3p) (Figure 7C, Supplementary Table 3). Next, five hub genes were uploaded into the NetworkAnalyst database to analyze the interaction with signal molecules. TP53 was prominent due to interacting with three hub genes in a network of signal molecules (Figure 7D, Supplementary Table 3).

Figure 7 The interaction network of hub genes in miRNet and network Analyst. (A) The network of hub genes with miRNAs. (B) The network of hub genes with transcription factors. The fuchsia nodes represent hub genes and the green nodes represent transcription factors. The five transcription factors that connect with at least four hub genes are labelled. (C) The network of hub genes with signal molecules. The signal molecules that connect with at least two hub genes are labelled. (D) The predicted lncRNA-miRNA-hub gene regulatory network. Yellow diamonds represent lncRNAs, green ellipses represent miRNAs, and blue rectangles represent hub genes.

The ROC Curves of Hub Genes

To determine the diagnostic value in discriminating COPD patients from normal controls, the ROC curves of each hub gene were plotted using R software. The logistic regression model of hub genes was constructed based on glm function. The formula was “-88.166 + 3.0089*HIF1A + −2.8988*IL6 + 2.8957*PTGS2 + 3.2435*CDKN1A + 7.3934*ATM”. As shown in Figure 8, the expression levels of HIF1A (AUC: 0.923, CI: 0.804-1.00) and ATM (AUC: 0.976, CI: 0.926-1.000) had high predictive accuracy (Figure 8A and E). The expression levels of IL6 (AUC: 0.826, CI: 0.608-1.000) and CDKN1A (AUC: 0.860, CI: 0.653-1.000) had moderate predictive accuracy (Figure 8B and D). The expression level of PTGS2 had low predictive accuracy (AUC: 0.681, CI: 0.471-0.892) (Figure 8C). The AUC of combination of five hub genes was 0.981 (CI: 0.940-1.000) (Figure 8F). When the cut-off threshold was 1.398, the sensitivity, specificity and Youden index were 0.957, 1.000 and 0.957, respectively. These results indicated that this model had high accuracy and authenticity to distinguish COPD group from normal group.

Figure 8 The receiver operating characteristic (ROC) curves of hub genes. (A) ROC curve of HIF1A. (B) ROC curve of IL6. (C) ROC curve of PTGS2. (D) ROC curve of CDKN1A. (E) ROC curve of ATM. (F) ROC curve of five genes combination.

The Immune Cells Infiltration Characteristics in Patients with COPD and Normal Controls

The infiltrating status of various immune cells in lung tissues had obvious differences (Figure 9A). Monocytes and macrophages accounted for the majority of all infiltrating cells, especially in COPD lung tissues. The infiltration differences in both groups are shown in Figure 9B. Seven types of immune cells, including CD8 T cells, activated NK cells, monocytes, M0 macrophages, M2 macrophages, resting dendritic cells and resting mast cells, had differential infiltration in patients with COPD compared with normal controls. The adjusted P-values of seven kinds of immune cells were 0.002, 0.001, 0.025, <0.001, 0.002, 0.008 and 0.020, respectively. Monocytes and M0 macrophages were upregulated in COPD lung tissues, while CD8 T cells, activated NK cells, M2 macrophages, resting dendritic cells and resting mast cells were downregulated. Figure 10A reveals the correlations between differentially infiltrated immune cells. Monocytes had positive correlations with CD8 T cells, M2 macrophages and resting dendritic cells (r=−0.39, −0.67 and −0.46, respectively). M0 macrophages had inverse correlations with CD8 T cells and activated NK cells (r=−0.38 and −0.58, respectively). However, CD8 T cells had positive correlations with M2 macrophages, resting dendritic cells and resting mast cells (r = 0.54, 0.40 and 0.56, respectively). Resting mast cells were positively associated with M2 macrophages and resting dendritic cells (r = 0.36 and 0.61, respectively). The correlations between the expression of hub genes and differentially infiltrated immune cells are displayed in Figure 10B. Positive associations were observed between monocytes and IL6, monocytes and PTGS2, monocytes and CDKN1A (r = 0.53, 0.42 and 0.62, respectively). M0 macrophages were also positively associated with HIF1A and ATM (r = 0.50 and 0.52, respectively). However, CD8 T cells were strongly negatively associated with HIF1A, IL6, PTGS2 and CDKN1A (r=−0.68, −0.83, −0.72 and −0.79, respectively). The remaining several types of immune cells also had weakly to moderately negative correlations with the expression of most of the hub genes as displayed in the heatmap.

Figure 9 Immune infiltration of COPD lung tissues compared with normal tissues. (A) Stack bar chart of proportions of the immune cells infiltration. (B) Box plot of proportions of the immune cells infiltration. The significance markers are shown as: ns, P>0.05; *, P<0.05; **, P<0.01; ***, P<0.001.

Figure 10 Differentially infiltrated immune cells and hub genes. (A) Heatmap of correlations of differentially infiltrated immune cells. (B) Heatmap of correlations of hub genes with differentially infiltrated immune cells. The significance markers are shown as: *, P<0.05; **, P<0.01.


Accumulating evidence indicates that ferroptosis participates in the pathogenesis of COPD. Previous review summarized that ferroptosis can affect inflammation through immunogenicity and ferroptosis inhibitors may benefit certain diseases through their anti-inflammatory effects.2 However, more research is required to better our understanding of ferroptosis in pathogenesis of COPD. In our study, we obtained 15 differentially expressed FRGs in patients with COPD compared with normal controls through bioinformatics analysis. Several hub genes were reported in the previous study. For instance, HIF1A, as a switch gene, was upregulated in COPD cases using network-based analysis implemented by SWIM software.27 CDKN1A played important functions in the development and progression of COPD.28 In our study, the enrichment analyses of 15 differentially expressed FRGs were conducted to explore their potential functions. The results indicated that they were associated with airway inflammatory response and remodeling. For example, cell senescence occurs in many pathological processes in COPD, which is consistent with previous reports. Cell senescence impedes iron-mediated cell death pathways by impairing ferritinophagy, a lysosomal process that promotes ferritin degradation.29

Next, we constructed a PPI network of 15 differentially expressed FRGs and first identified five ferroptosis-related hub genes, including HIF1A, IL6, PTGS2, CDKN1A and ATM. To further explore the correlation between hub genes and diseases, we analyzed the inference scores for four respiratory tract diseases in CTD and found that five hub genes were closely correlated with COPD and other respiratory tract diseases. These findings reminded us that it was vital to clarify the mechanism of action of these genes in COPD pathogenesis.

Bioinformatics methods provide us with a convenient way to predict crosstalk networks and screen potential biomarkers in COPD. A large number of miRNAs and lncRNAs were reported to be involved in COPD initiation and development. MALAT1/miR-146a/COX2 (namely PTGS2) axis affected the lung function of patients with COPD.30 Some non-coding RNA targets including miR-195, miR-181c and TUG1 are viable for alleviating COPD in vivo.31 However, to our knowledge, previous articles reporting the correlation between non-coding RNAs and ferroptosis mainly focused on multiple cancers. The present study constructed the networks of hub genes with miRNAs and transcription factors in miRNet database and identified two key miRNAs, namely, hsa-let-7b-5p and hsa-miR-1-3p. The hsa-let-7b-5p participated in endothelial mitochondrial dynamics and acted as a biomarker for diagnosing Parkinsonian Syndromes.32,33 The hsa-miR-1-3p inhibited lung adenocarcinoma cell tumorigenesis and improved gefitinib resistance in EGFR mutant lung cancer cell.34,35 Additionally, the upstream lncRNAs of two miRNAs were predicted using ENCORI database and we found six lncRNAs with the most experimental evidence. Among them, NUTM2A-AS19 and AL162431.2 are newly reported in this study. XIST and MALAT1 played an important role in mitochondrial dysfunction, cell senescence and epigenetic alterations in COPD pathogenesis under the condition of tobacco smoke exposure.36 NEAT1 promoted activation of inflammasomes in macrophages.37 RMRP promoted the progression of NSCLC via competing with miR-1-3p.38 Thus, we speculate that the following axes may regulate ferroptosis in COPD pathogenesis including NUTM2A-AS19 or XIST or NEAT1/hsa-let-7b-5p/hub gene axes and RMRP or MALAT1 or AL162431.2/hsa-miR-1-3p/hub gene axes. Moreover, the identification of five important transcription factors including EGR1, NFKB1, RELA, SP1 and STAT3 would be the groundwork for molecular mechanisms of ferroptosis in COPD pathogenesis. EGR1 was indispensable for MUC5AC expression induced by cigarette smoke in human bronchial epithelial cells.39 Genetic knockdown of RELA (NFKB subunit) diminished IL6 production in HBE cells.40 SP1 was crucial for anti-inflammatory molecule IL10 secretion in the phototherapy effect in HBE cells.41 STAT3 was a vital molecule in regulating the expression of inflammatory cytokines in COPD murine model.42 Notably, the signal molecule network revealed that TP53 connected with IL6, CDKN1A and ATM, suggesting that TP53 may be a potential driver of COPD towards lung cancer. This indicated that ferroptosis may also participate in COPD-related carcinogenesis.

Previous studies concentrated on the construction of a ferroptosis-related gene model for prognosis in cancer. For example, researchers screened ten ferroptosis-related genes, which served as potential prognostic biomarkers.43 To testify the diagnostic values of hub genes, we conducted ROC analyses and discovered that each of them varied in predictive accuracy, while combination of five genes could serve as a fine model to distinguish patients with COPD from normal controls (AUC: 0.981, CI: 0.940-1.000).

Although immune infiltration in malignancies keeps attracting the attention of researchers, very few reports explored the immune infiltration in COPD. The spatially confined eosinophil-rich type 2 microenvironments were identified in COPD.44 The proportion of T cells decreased in the lungs of current smokers and patients with COPD, whereas the proportion of macrophages increased.45 In our study, we uncovered the immune infiltration status in patients with COPD compared with normal controls. Monocytes were the majority of immune cells in both groups and increased prominently in COPD group. Monocytes, as an essential part of innate immune system, influence human diseases both by direct effects and by differentiating into macrophages.46 The cytokine response of monocytes to bacteria was compromised in smoking-induced COPD and thus impaired immune response.47 Macrophages are plastic in response to various tissue microenvironment and external stimuli. We found that the proportion of M0 macrophages increased markedly, which could serve as reserves ready for polarization stimuli. M1 macrophages primarily take part in pro-inflammatory responses, however, they were not observed to increase remarkably in this study. M2 macrophages, which primarily participate in anti-inflammatory responses, decreased dramatically in COPD group, suggesting that their functions may be undermined in COPD pathogenesis. CD8 T cells were observed to decrease drastically, which was inconsistent with previous researches. The number of IFN-γ-producing CD8+ and CD4+ lymphocytes increased in the lungs of patients with COPD.48 The frequencies of CD8+ T cell subsets increased observably in patients with COPD compared with normal controls and non-smokers.49 It may be partial due to the difference between statistics-based bioinformatics methods and flow cytometry assays. Activated NK cells decreased in COPD lung tissues. However, evidence from other studies revealed that the proportions of NK cells increased in BAL fluid of patients with COPD.50 Another two researches claimed that the number of NK cells in the lung parenchyma of patients with COPD was at the same level as that in the peripheral blood, and bronchoalveolar lavage fluid in healthy smokers.51,52 It seems that NK cells in lung tissues may have different effects compared with those from blood and BALF. Moreover, we found resting dendritic cells and resting mast cells, which were the minority of infiltrating immune cells, decreased in patients with COPD. Dendritic cells present antigens and activate naive T and B cells.53,54 Mast cells can interact with multiple immune cells and structural cells and thereby facilitate inflammatory responses, airway remodeling and angiogenesis.55,56 The functions of them might be antagonized by monocytes and M0 macrophages in some degree in COPD lung tissues. The proportions of monocytes and M0 macrophages were positively associated with most of hub genes, whereas CD8 T cells, activated NK cells, M2 macrophages, resting dendritic cells and resting mast cells were negatively associated most of the hub genes. It can be inferred that the functions of monocyte and M0 macrophages may be promoted by these hub genes. The other types of infiltrating cells, for instance, CD8 T cells, were likely to be inhibited by these hub genes. HIF1A was validated to drive ferroptosis in clear cell carcinomas and ATM was essential for promoting ferroptosis.57,58 IL6 and PTGS2 were confirmed as the downstream markers of ferroptosis.59,60 CDKN1A was required to suppress ferroptosis.61 We speculate that these high-expressed hub genes in COPD group may get involved in the regulation of ferroptosis in structural cells of pulmonary parenchyma and thus affect the infiltrating immune cells residing in pulmonary interstitium or recruited from peripheral blood, which could lead to differentially histopathological changes in the lungs of patients with COPD. Taken together, the immune cells infiltration contributes to the pathogenesis of COPD in a sophisticated manner and more research is in urgent need to elucidate the situation.

Our study had obvious limitations. The number of cases included in our study was relatively small. Due to the lack of detailed clinical information, correlations between hub genes and clinical characteristics cannot be explored. Another apparent deficiency is that we did not perform basic experiments to validate the expression of hub genes and their correlation with immune cells. For now, our study can provide a theoretical basis for further explorations of ferroptosis-related phenotypes in COPD research.


We identified five ferroptosis-related hub genes (HIF1A, IL6, PTGS2, CDKN1A and ATM) in COPD, a combination of which had diagnostic value. Two miRNAs, five transcription factors and one signal molecule were predicted to target these hub genes, and the lncRNA-miRNA-hub gene regulatory network was constructed. Ferroptosis-related hub genes were significantly associated with immune infiltration in the lung tissues of patients with COPD.


AUC, area under the curve; BP, biological process; CC, cellular component; CI, confidence interval; COPD, chronic obstructive pulmonary disease; CTD, Comparative Toxicomics Database; ENCORI, Encyclopedia of RNA Interactomes; FC, fold change; FRG, ferroptosis-related gene; FVC, forced vital capacity; GEO, Gene Expression Omnibus; GO, Gene Ontology; GOLD, Global Initiative for Chronic Obstructive Lung Disease; GPX4, glutathione peroxidase 4; KEGG, Kyoto Encyclopedia of Genes and Genomes; MCODE, Molecular Complex Detection; MF, molecular function; Nrf2, nuclear factor erythroid 2-related factor 2; NSCLC, non-small cell lung cancer; PCA, principal component analysis; PPI, protein–protein interaction; PUFA-PL, phospholipid containing polyunsaturated fatty acid chain(s); ROC, receiver operating characteristic; ROS, reactive oxygen species; TLR2, toll-like receptor 2.

Ethics Statement

This study was reviewed by Medical Ethics Committee of Qilu Hospital of Shandong University and exempted from ethical approval due to the usage of human data from the open and public Gene Expression Omnibus database.


This study was supported by the National Natural Science Foundation of China (grant No. 81800039) and the Jinan Clinical Research Center for Prevention and Control Project of Major Respiratory Diseases (grant No. 201912011).


The authors report no conflicts of interest in this work.


1. Rabe KF, Watz H. Chronic obstructive pulmonary disease. Lancet. 2017;389(10082):1931–1940. doi:10.1016/S0140-6736(17)31222-9

2. Brightling C, Greening N. Airway inflammation in COPD: progress to precision medicine. Eur Respir J. 2019;54(2):1900651. doi:10.1183/13993003.00651-2019

3. Sun Y, Chen P, Zhai B, et al. The emerging role of ferroptosis in inflammation. Biomed Pharmacother. 2020;127:110108. doi:10.1016/j.biopha.2020.110108

4. Jiang X, Stockwell BR, Conrad M. Ferroptosis: mechanisms, biology and role in disease. Nat Rev Mol Cell Biol. 2021;22(4):266–282. doi:10.1038/s41580-020-00324-8

5. Yoshida M, Minagawa S, Araya J, et al. Involvement of cigarette smoke-induced epithelial cell ferroptosis in COPD pathogenesis. Nat Commun. 2019;10(1):3145. doi:10.1038/s41467-019-10991-7

6. Lian N, Zhang Q, Chen J, Chen M, Huang J, Lin Q. The role of ferroptosis in bronchoalveolar epithelial cell injury induced by cigarette smoke extract. Front Physiol. 2021;12:751206. doi:10.3389/fphys.2021.751206

7. Su LJ, Zhang JH, Gomez H, et al. Reactive oxygen species-induced lipid peroxidation in apoptosis, autophagy, and ferroptosis. Oxid Med Cell Longev. 2019;2019:5080843. doi:10.1155/2019/5080843

8. Yan B, Ai Y, Sun Q, et al. Membrane damage during ferroptosis is caused by oxidation of phospholipids catalyzed by the oxidoreductases POR and CYB5R1. Mol Cell. 2021;81(2):355–369. doi:10.1016/j.molcel.2020.11.024

9. Seibt TM, Proneth B, Conrad M. Role of GPX4 in ferroptosis and its pharmacological implication. Free Radic Biol Med. 2019;133:144–152. doi:10.1016/j.freeradbiomed.2018.09.014

10. Zhang Z, Fu C, Liu J, et al. Hypermethylation of the Nrf2 promoter induces ferroptosis by inhibiting the Nrf2-GPX4 axis in COPD. Int J Chron Obstruct Pulmon Dis. 2021;16:3347–3362. doi:10.2147/COPD.S340113

11. Bu T, Wang LF, Yin YQ. How do innate immune cells contribute to airway remodeling in COPD progression?. Int J Chron Obstruct Pulmon Dis. 2020;15:107–116. doi:10.2147/COPD.S235054

12. Wang W, Green M, Choi JE, et al. CD8+ T cells regulate tumour ferroptosis during cancer immunotherapy. Nature. 2019;569(7755):270–274. doi:10.1038/s41586-019-1170-y

13. Jiang Y, Li C, Wu Q, et al. Iron-dependent histone 3 lysine 9 demethylation controls B cell proliferation and humoral immune responses. Nat Commun. 2019;10(1):2935. doi:10.1038/s41467-019-11002-5

14. Luo X, Gong HB, Gao HY, et al. Oxygenated phosphatidylethanolamine navigates phagocytosis of ferroptotic cells by interacting with TLR2. Cell Death Differ. 2021;28(6):1971–1989. doi:10.1038/s41418-020-00719-2

15. Ezzie ME, Crawford M, Cho JH, et al. Gene expression networks in COPD: microRNA and mRNA regulation. Thorax. 2012;67(2):122–131. doi:10.1136/thoraxjnl-2011-200089

16. Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res. 2013;41(D1):D991–D995. doi:10.1093/nar/gks1193

17. Zhou N, Bao J. FerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis-disease associations. Database. 2020;2020:baaa021. doi:10.1093/database/baaa021

18. Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847–2849. doi:10.1093/bioinformatics/btw313

19. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The gene ontology consortium. Nat Genet. 2000;25(1):25–29. doi:10.1038/75556

20. Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30. doi:10.1093/nar/28.1.27

21. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–287. doi:10.1089/omi.2011.0118

22. Walter W, Sánchez-Cabo F, Ricote M. GOplot: an R package for visually combining expression data with functional analysis. Bioinformatics. 2015;31(17):2912–2914. doi:10.1093/bioinformatics/btv300

23. Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–D613. doi:10.1093/nar/gky1131

24. Davis AP, Grondin CJ, Johnson RJ, et al. Comparative toxicogenomics database (CTD): update 2021. Nucleic Acids Res. 2021;49(D1):D1138–D1143. doi:10.1093/nar/gkaa891

25. Chang L, Zhou G, Soufan O, Xia J. miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology. Nucleic Acids Res. 2020;48(W1):W244–W251. doi:10.1093/nar/gkaa467

26. Zhou G, Soufan O, Ewald J, Hancock REW, Basu N, Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 2019;47(W1):W234–W241. doi:10.1093/nar/gkz240

27. Li JH, Liu S, Zhou H, Qu LH, Yang JH. starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 2014;42(D1):D92–D97. doi:10.1093/nar/gkt1248

28. Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–457. doi:10.1038/nmeth.3337

29. Paci P, Fiscon G, Conte F, et al. Integrated transcriptomic correlation network analysis identifies COPD molecular determinants. Sci Rep. 2020;10(1):3361. doi:10.1038/s41598-020-60228-7

30. Yang D, Yan Y, Hu F, Wang T. CYP1B1, VEGFA, BCL2, and CDKN1A affect the development of chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2020;15:167–175. doi:10.2147/COPD.S220675

31. Masaldan S, Clatworthy SAS, Gamell C, et al. Iron accumulation in senescent cells is coupled with impaired ferritinophagy and inhibition of ferroptosis. Redox Biol. 2018;14:100–115. doi:10.1016/j.redox.2017.08.015

32. Sun L, Xu A, Li M, et al. Effect of methylation status of lncRNA-MALAT1 and microRNA-146a on pulmonary function and expression level of COX2 in patients with chronic obstructive pulmonary disease. Front Cell Dev Biol. 2021;9:667624. doi:10.3389/fcell.2021.667624

33. Mei D, Tan WSD, Tay Y, Mukhopadhyay A, Wong WSF. Therapeutic RNA strategies for chronic obstructive pulmonary disease. Trends Pharmacol Sci. 2020;41(7):475–486. doi:10.1016/j.tips.2020.04.007

34. Hu Q, Li J, Nitta K, et al. FGFR1 is essential for N-acetyl-seryl-aspartyl-lysyl-proline regulation of mitochondrial dynamics by upregulating microRNA let-7b-5p. Biochem Biophys Res Commun. 2018;495(3):2214–2220. doi:10.1016/j.bbrc.2017.12.089

35. Starhof C, Hejl AM, Heegaard NHH, et al. The biomarker potential of cell-free microRNA from cerebrospinal fluid in parkinsonian syndromes. Mov Disord. 2019;34(2):246–254.

36. Li T, Wang X, Jing L, Li Y. MiR-1-3p inhibits lung adenocarcinoma cell tumorigenesis via targeting protein regulator of cytokinesis 1. Front Oncol. 2019;9:120. doi:10.3389/fonc.2019.00120

37. Jiao D, Chen J, Li Y, et al. miR-1-3p and miR-206 sensitizes HGF-induced gefitinib-resistant human lung cancer cells through inhibition of c-met signalling and EMT. J Cell Mol Med. 2018;22(7):3526–3536. doi:10.1111/jcmm.13629

38. Devadoss D, Long C, Langley RJ, et al. Long noncoding transcriptome in chronic obstructive pulmonary disease. Am J Respir Cell Mol Biol. 2019;61(6):678–688. doi:10.1165/rcmb.2019-0184TR

39. Zhang P, Cao L, Zhou R, Yang X, Wu M. The lncRNA neat1 promotes activation of inflammasomes in macrophages. Nat Commun. 2019;10(1):1495. doi:10.1038/s41467-019-09482-6

40. Wang Y, Luo X, Liu Y, Han G, Sun D. Long noncoding RNA RMRP promotes proliferation and invasion via targeting miR-1-3p in non-small-cell lung cancer. J Cell Biochem. 2019;120(9):15170–15181. doi:10.1002/jcb.28779

41. Wang SB, Zhang C, Xu XC, et al. Early growth response factor 1 is essential for cigarette smoke-induced MUC5AC expression in human bronchial epithelial cells. Biochem Biophys Res Commun. 2017;490(2):147–154. doi:10.1016/j.bbrc.2017.06.014

42. Wu YF, Li ZY, Dong LL, et al. Inactivation of MTOR promotes autophagy-mediated epithelial injury in particulate matter-induced airway inflammation. Autophagy. 2020;16(3):435–450. doi:10.1080/15548627.2019.1628536

43. Brito A, Santos T, Herculano K, et al. The MAPKinase signaling and the stimulatory protein-1 (Sp1) transcription factor are involved in the phototherapy effect on cytokines secretion from human bronchial epithelial cells stimulated with cigarette smoke extract. Inflammation. 2021;44(4):1643–1661. doi:10.1007/s10753-021-01448-5

44. Kim SH, Hong JH, Yang WK, et al. Herbal combinational medication of Glycyrrhiza glabra, Agastache rugosa containing glycyrrhizic acid, tilianin inhibits neutrophilic lung inflammation by affecting CXCL2, interleukin-17/STAT3 signal pathways in a murine model of COPD. Nutrients. 2020;12(4):926. doi:10.3390/nu12040926

45. Ren Z, Hu M, Wang Z, et al. Ferroptosis-related genes in lung adenocarcinoma: prognostic signature and immune, drug resistance, mutation analysis. Front Genet. 2021;12:672904. doi:10.3389/fgene.2021.672904

46. Jogdand P, Siddhuraj P, Mori M, et al. Eosinophils, basophils and type 2 immune microenvironments in COPD-affected lung tissue. Eur Respir J. 2020;55(5):1900110. doi:10.1183/13993003.00110-2019

47. Cruz T, López-Giraldo A, Noell G, et al. Multi-level immune response network in mild-moderate chronic obstructive pulmonary disease (COPD). Respir Res. 2019;20(1):152. doi:10.1186/s12931-019-1105-z

48. Kapellos TS, Bonaguro L, Gemünd I, et al. Human monocyte subsets and phenotypes in major chronic inflammatory diseases. Front Immunol. 2019;10:2035. doi:10.3389/fimmu.2019.02035

49. Knobloch J, Panek S, Yanik SD, et al. The monocyte-dependent immune response to bacteria is suppressed in smoking-induced COPD. J Mol Med. 2019;97(6):817–828. doi:10.1007/s00109-019-01778-w

50. Mark NM, Kargl J, Busch SE, et al. Chronic obstructive pulmonary disease alters immune cell composition and immune checkpoint inhibitor efficacy in non-small cell lung cancer. Am J Respir Crit Care Med. 2018;197(3):325–336. doi:10.1164/rccm.201704-0795OC

51. Zhuang H, Li N, Chen S, et al. Correlation between level of autophagy and frequency of CD8+ T cells in patients with chronic obstructive pulmonary disease. J Int Med Res. 2020;48(9):300060520952638. doi:10.1177/0300060520952638

52. Eriksson Ström J, Pourazar J, Linder R, et al. Cytotoxic lymphocytes in COPD airways: increased NK cells associated with disease, iNKT and NKT-like cells with current smoking. Respir Res. 2018;19(1):244. doi:10.1186/s12931-018-0940-7

53. Freeman CM, Stolberg VR, Crudgington S, et al. Human CD56+ cytotoxic lung lymphocytes kill autologous lung cells in chronic obstructive pulmonary disease. PLoS One. 2014;9(7):e103840. doi:10.1371/journal.pone.0103840

54. Hodge G, Mukaro V, Holmes M, Reynolds PN, Hodge S. Enhanced cytotoxic function of natural killer and natural killer T-like cells associated with decreased CD94 (Kp43) in the chronic obstructive pulmonary disease airway. Respirology. 2013;18(2):369–376. doi:10.1111/j.1440-1843.2012.02287.x

55. Freeman CM, Curtis JL. Lung dendritic cells: shaping immune responses throughout chronic obstructive pulmonary disease progression. Am J Respir Cell Mol Biol. 2017;56(2):152–159. doi:10.1165/rcmb.2016-0272TR

56. Givi ME, Redegeld FA, Folkerts G, Mortaz E. Dendritic cells in pathogenesis of COPD. Curr Pharm Des. 2012;18(16):2329–2335. doi:10.2174/138161212800166068

57. Mortaz E, Folkerts G, Redegeld F. Mast cells and COPD. Pulm Pharmacol Ther. 2011;24(4):367–372. doi:10.1016/j.pupt.2011.03.007

58. Soltani A, Ewe YP, Lim ZS, et al. Mast cells in COPD airways: relationship to bronchodilator responsiveness and angiogenesis. Eur Respir J. 2012;39(6):1361–1367. doi:10.1183/09031936.00084411

59. Zou Y, Palte MJ, Deik AA, et al. A GPX4-dependent cancer cell state underlies the clear-cell morphology and confers sensitivity to ferroptosis. Nat Commun. 2019;10(1):1617. doi:10.1038/s41467-019-09277-9

60. Chen PH, Wu J, Ding CC, et al. Kinome screen of ferroptosis reveals a novel role of ATM in regulating iron metabolism. Cell Death Differ. 2020;27(3):1008–1022. doi:10.1038/s41418-019-0393-7

61. Linkermann A, Skouta R, Himmerkus N, et al. Synchronized renal tubular cell death involves ferroptosis. Proc Natl Acad Sci U S A. 2014;111(47):16836–16841. doi:10.1073/pnas.1415518111

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CUMBERLAND, Md., May 23, 2022 (GLOBE NEWSWIRE) -- RS BioTherapeutics, whose mission is to harness its strong and thorough understanding of the endocannabinoid system to research, develop and commercialize interventions to address chronic and acute pulmonary (lung) inflammation-based diseases, is pleased to announce that is has entered into a license agreement with Synthonics, Inc. for the exclusive, worldwide right to use Synthonics’ metal coordinated cannabinoid in nebulized form for the treatment of pulmonary inflammatory disorders. RS BioTherapeutics is developing its lead compound, RSBT-001, as both an alternative and a complement to corticosteroids for the treatment of chronic obstructive pulmonary disease (COPD).

COPD is a chronic inflammatory lung disease that causes obstructed airflow from the lungs and includes emphysema, chronic bronchitis, asthma and more. According to the American Lung Association, 156,045 people died from COPD in 2018, making it the third highest disease-related cause of death behind heart disease and cancer. It is estimated that more than 250 million people globally may have the condition and more than 65 million people around the world have moderate or severe COPD. Experts predict that this number will continue to rise worldwide over the next 50 years. The CDC estimates that 16 million Americans suffer from COPD. People with COPD are at increased risk of developing heart disease, lung cancer, and a variety of other conditions. If chronic pulmonary inflammation is untreated, it can lead to fibrosis, organ damage, and loss of organ function.

Commenting on the potential benefits of this first investigational compound, RSBT-001, Justin Molignoni, CRNP, Chief Strategy Officer and Co-Founder of RS BioTherapeutics, said, “Alternatives to corticosteroids are needed for people with chronic inflammatory diseases. We believe RSBT-001 has the clinical potential to address exacerbation and prevent progression of both acute and chronic pulmonary inflammation related to respiratory diseases including COPD, SARS-COV-2, Cystic Fibrosis, Asthma, Bronchitis, and Acute Respiratory Distress Syndrome.”

John Tinkham, CEO and Co-Founder of Synthonics, added, “We believe that metal coordination can significantly enhance the effectiveness of cannabinoid-based pharmaceuticals and are delighted to partner with RS BioTherapeutics on this project. We look forward to working closely with RS BioTherapeutics to assist on the development of RSBT-001.”

Various sources estimate the global pulmonary drug delivery systems market was approximately $51 billion in 2021, and it is expected to be worth around $92 billion by 2030, with a compound annual growth rate of 6.6 percent within in next 10 years.

About RS BioTherapeutics Founded by experts in pulmonary diseases and the endocannabinoid system, RS BioTherapeutics is a wholly owned subsidiary of Real Science Holdco LLC. The company’s mission is to harness its strong and thorough understanding of the Endocannabinoid System in the research, development, and commercialization of forward-thinking interventions to address chronic and acute pulmonary inflammation-based diseases.   More information on RS Biotherapeutics can be found at www.rsbiotherapeutics.com.

About SynthonicsSynthonics, Inc. is a privately-held specialty pharmaceutical company focused on the discovery and development of patentable drugs that incorporate its proprietary metal coordination chemistry. It binds metals to known pharmaceutical agents to create new products that are better absorbed and thus have greater therapeutic benefits than their predecessors. More information on Synthonics can be found at www.synthonicsinc.com.

Media Contact: David Gutierrez, Dresner Corporate Services, (312) 780-7204, [email protected]


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Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market Overview:

The large scale Chronic Obstructive Pulmonary Disease (COPD) Drug Market report consists of most-detailed market segmentation, thorough analysis of major market players, trends in consumer and supply chain dynamics, and insights about new geographical markets. All the data and statistics covered in this business report lead to an actionable ideas, improved decision-making and better mapping business strategies. This report analyses the Healthcare industry from top to bottom by considering myriad of aspects. Businesses can rely upon this top-notch market report to accomplish an utter success. Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market report offers better solution for refining the business strategies to thrive in this competitive market place.

The data and information regarding Healthcare industry are taken from reliable sources such as websites, annual reports of the companies, and journals etc. and were checked and validated by the market experts. Chronic Obstructive Pulmonary Disease (COPD) Drug Market report helps in planning by providing precise and state-of-the-art information about the consumer’s demands, preferences, attitudes and their changing tastes about the specific product. This report has been prepared by considering various steps for collecting, recording and analysing market data. An influential Chronic Obstructive Pulmonary Disease (COPD) Drug report employs various basic steps of market analysis that include survey, focus groups, personal interviews, observations, and field trials.

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The Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market is expected to witness market growth at a rate of 5.05% in the forecast period of 2022 to 2029.

According to market research study, Chronic Obstructive Pulmonary Disease (COPD) refers to a common, preventable, incurable, and treatable disease which displays persistent respiratory symptoms and airflow limitation. Chronic inflammation in the airways leading to alveolar abnormalities could be caused by long-term exposure to noxious particles or gases such as cigarette smoke and environmental pollution.

Some of most important key factors driving the growth of the Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market are increase in the prevalence of respiratory diseases globally, rise in the prevalence of chronic obstructive pulmonary disease (COPD) among population across the globe, increase in demand for home care therapeutic and treatments for the chronic respiratory disease due to the comfort and ease and rise in demand for the drugs to treat breathing difficulty, cough, mucus production and wheezing.

The Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market is segmented on the basis of Drug Type, Product Type, Type, Diagnosis, Treatment and End-User.

Based on the Drug Type, the chronic obstructive pulmonary disease (COPD) drug market is segmented into phosphodiestrase-4 inhibitors, long-acting bronchodilators, short-acting bronchodilators, methylxanthines and corticosteroids.

Based on the Product Type, the chronic obstructive pulmonary disease (COPD) drug market is segmented into inhalers and nebulizers.

Based on the Type, the chronic obstructive pulmonary disease (COPD) drug market is segmented into chronic bronchitis and emphysema.

Based on the Diagnosis, the chronic obstructive pulmonary disease (COPD) drug market is segmented into pirometry, diagnostic tests and others.

Based on the Treatment, the chronic obstructive pulmonary disease (COPD) drug market is segmented into oxygen therapy, lung transplant, drug therapy, vaccination, surgery and others.

Based on the End-User, the chronic obstructive pulmonary disease (COPD) drug market is segmented into hospitals and clinics, home care settings and others.

In terms of the geographic analysis, North America dominates the chronic obstructive pulmonary disease (COPD) drug market due to the increasing patient population suffering from COPD and the presence of major market players within the region. APAC is expected to witness the fastest growth during the forecast period of 2022 to 2029 because of the high patient population suffering from COPD and the rising prevalence of respiratory disease.

Access Complete Report @ www.databridgemarketresearch.com/reports/global-chronic-obstructive-pulmonary-disease-copd-drug-market .

Top Leading Key in Players Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market: AstraZeneca, GlaxoSmithKline plc, Novartis AG, Boehringer Ingelheim International GmbH, Teva Pharmaceutical Industries Ltd, Aché Laboratórios Farmacêuticos S.A., bioMARCK, Aquinox Pharmaceuticals, Astellas Pharma Inc., Abbott., F. Hoffmann-La Roche Ltd, Adamis Pharmaceuticals Corporation, Sunovion Pharmaceuticals Inc., Mylan N.V., Orion Corporation, Grifols, S.A., Theravance Biopharma, Circassia, ResMed and others. New product launches and continuous technological innovations are the key strategies adopted by the major players.

Region segment: Chronic Obstructive Pulmonary Disease (COPD) Drug Market report is segmented into several key regions, with sales, revenue, market share (%) and growth Rate (%) of Chronic Obstructive Pulmonary Disease (COPD) Drug in these regions, from 2013 to 2025 (forecast), covering: North America, Europe, Asia Pacific, Middle East & Africa and South America

This study answers to the below key questions:

1 What will the market size be in 2029?

2 What are the key factors driving the Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market?

3 What are the challenges to market growth?

4 Who are the key players in the Chronic Obstructive Pulmonary Disease (COPD) Drug Market?

5 What are the market opportunities and threats faced by the key players?

For More Insights Get FREE Detailed TOC of “Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market Report 2022” @ www.databridgemarketresearch.com/toc/?dbmr=global-chronic-obstructive-pulmonary-disease-copd-drug-market .

Major Highlights of TOC: Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market

1 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market Overview

2 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market Competitions by Manufacturers

3 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Capacity, Production, Revenue (Value) by Region (2022-2029

4 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Supply (Production), Consumption, Export, Import by Region (2022-2029)

5 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Production, Revenue (Value), Price Trend by Type

6 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market Analysis by Application

7 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Manufacturers Profiles/Analysis

8 Chronic Obstructive Pulmonary Disease (COPD) Drug Manufacturing Cost Analysis

9 Industrial Chain, Sourcing Strategy and Downstream Buyers

10 Marketing Strategy Analysis, Distributors/Traders

11 Market Effect Factors Analysis

12 Global Chronic Obstructive Pulmonary Disease (COPD) Drug Market Forecast (2022-2029)

13 Research Findings and Conclusion

14 Appendix

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Chronic obstructive pulmonary disease (COPD) claimed more than 3 million lives in 2019 and is now the third leading disease-related cause of death globally, according to the World Health Organization.1 Long-term exposure to tobacco smoke is the most common cause of the disease in the industrialized world, and results in persistent airflow limitation, due to chronic inflammation and remodeling of the airways.2 However, this inflammation is not confined to the airways. Signs of systemic inflammation are also present and are associated with comorbidities of COPD, such as type 2 diabetes mellitus (T2DM).3 Notably, the pathologic glucose homeostasis in T2DM is related to signs of systemic inflammation and this is also true for metabolic syndrome (MetS), another common metabolic comorbidity in COPD.4–7 Furthermore, the prevalence of COPD is increased in patients with T2DM, even after adjustment for risk factors that predispose to both these diagnoses.8,9 In a similar manner, there is evidence that COPD is more prevalent among patients with MetS.10 Despite an expanding body of evidence that clinically relates COPD with T2DM and MetS, there is poor understanding of the underlying pathogenic mechanisms linking these diseases. We reasoned that a more comprehensive characterization of these mechanisms may reveal novel targets for diagnosis or therapy in COPD and metabolic comorbidities.

Excessive mobilization of neutrophils, including both recruitment and activation, is a common and prominent sign of systemic inflammation in COPD.11–13 Interestingly, this type of inflammation is observed in T2DM and MetS as well, and may therefore constitute a unifying pathogenic mechanism in COPD patients with either of these comorbidities.14,15 Specifically, neutrophils comprise the most abundant subset of leukocytes in blood, and are important players in antibacterial host defense and in repair of tissue injury.16,17 Under normal conditions, their mobilization is carefully regulated by numerous mediators, including interleukin-6 (IL-6), IL-8 and interferon-γ (INF-γ).18–21 Moreover, neutrophil products, such as serine proteinases and gelatinases, exert important anti-bacterial functions and regulate inflammation, through proteolytic modification of several cytokines, including IL-6, IL-8 and members of the IL-36 family.16,22,23 Systemic IL-6 is increased and correlates in a positive manner with insulin resistance in patients with COPD,24 which is compatible with excessive neutrophil mobilization constituting a contributing factor. Along the same lines, systemic IL-8 is enhanced in patients with COPD, T2DM and MetS combined with heart failure.25–27 Notably, it was recently demonstrated that certain members of the IL-36 family are involved in local and systemic inflammation in COPD and that these cytokines exert pro-inflammatory effects on neutrophils.28–33 Intriguingly, systemic IL-36γ correlates in a negative manner with glycated hemoglobin (HbA1c) and fasting glucose in obese patients with T2DM.28,34

In parallel with its central role in innate immunity, neutrophil mobilization facilitates the production of cytokines that modulate adaptive immunity, such as C-X-C motif chemokine ligand 10 (CXCL10, also known as interferon-γ-inducible protein 10 or IP-10).16,35,36 It therefore seems rational that the concentration of CXCL10 is increased in the airways of patients with COPD, in particular during exacerbations.37 At the same time, there is evidence that elevated systemic CXCL10 may predispose to development of T2DM.38

The fact that several signs of increased neutrophil mobilization are evident in COPD, T2DM and MetS led us to hypothesize that there is an altered glucose homeostasis in COPD, associated with an increased mobilization of neutrophils. We addressed this hypothesis in a pilot study on current long-term smokers with and without COPD plus a control group of healthy non-smokers. In these subjects, we assessed alterations in glucose homeostasis by quantifying blood glucose after overnight fasting and during an oral glucose tolerance test (OGTT). Furthermore, we characterized neutrophil mobilization in the airways and in blood by determining concentrations of neutrophils, functionally related cytokines and proteinases. Finally, we quantified the concentration of C-reactive protein in blood as a reference for systemic inflammation.

Materials and Methods

Human Study Population and Ethics

We utilized the human study population “KOL-KB 2011”, including healthy non-smokers (HNS), long-term smokers without COPD (LTS) and long-term smokers with COPD (LTS+COPD). The study population was recruited in accordance with the ethical principles of the World Medical Association (the Helsinki Declaration). The study protocol was approved by the Regional Ethical Review Board in Gothenburg, Sweden (Diary No. 968–11). All subjects provided oral and written informed consent prior to study participation. Some data from this study population have previously been published, although in a different scientific context.28,39,40


Screening Visit

The subjects were identified through an advertisement in the regional press or through their contact with the outpatient clinic at the Department of Respiratory Medicine and Allergy, Sahlgrenska University Hospital in Gothenburg, and were then invited to a screening visit. During that visit, the clinical history and the smoking habits of the subjects were recorded, and a physical examination was performed. Height and weight of each subject were measured, and body mass index (BMI) was calculated. In parallel, percutaneous oxygen saturation was determined with a pulse oximeter. Blood tests included hemoglobin (Hb), coagulation parameters, a standard panel of specific Immunoglobulins E (IgE) against common inhaled allergens (Phadiatop®, PhadiaTM, Uppsala, Sweden) and viral serology (hepatitis B and C, HIV). In addition, premenopausal female subjects underwent a testing to exclude ongoing pregnancy.

Ventilatory lung function was assessed using dynamic spirometry with reversibility test and gas exchange was assessed with diffusion capacity for carbon monoxide (DLCO).41,42 The screening visit also included an electrocardiogram (ECG) and a standard chest X-ray, performed, respectively, at the Department of Clinical Physiology and the Department of Radiology at Sahlgrenska University Hospital.

Inclusion Criteria

A negative history of asthma and atopy (with the exception of contact allergy to nickel) was required for all subjects, as well as negative Phadiatop test, negative viral serology and negative pregnancy test, when applicable. Subjects with BMI ≥ 35 kg/m2 or body weight >100 kg were excluded, to ensure medical safety during the bronchoscopy investigation, which was performed for research purposes only. Furthermore, we did not accept more than three respiratory tract infections during the last year. We also required absence of any signs of infection during the screening visit and an infection-free period of at least four weeks prior to the bronchoscopy visit; otherwise, the corresponding visit had to be re-scheduled. We accepted patients with previously diagnosed, compensated cardiac failure, osteoporosis and cured cancer disease (>5 years prior to the inclusion), along with well-treated hypothyroidism, epilepsy, depression and hypertension. No other established diagnoses were accepted, including T2DM, MetS and obstructive sleep apnea (OSA). Subjects on regular treatment with statins, inhaled corticosteroids and/or long-acting inhaled bronchodilators, including both beta-2-agonists and anticholinergics, were excluded. In a similar manner, a regular treatment with immunosuppressive or anti-inflammatory medication was not accepted. Exceptions to this criterion were NSAID and oral steroids when a mandatory wash-out period of four weeks prior to bronchoscopy could be ensured. However, paracetamol treatment was allowed with no restrictions.

Subjects in the HNS group were required to have a negative history of smoking and of lung disease, in addition to a normal chest X-ray and dynamic spirometry indicating normal lung function after bronchodilation (three doses of inhaled terbutaline; 0.5 mg/dose; Bricanyl TurbuhalerTM, AstraZeneca Ltd, Södertälje, Sweden), in terms of forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC) ratio ≥0.70 and FEV1 > 80% of predicted (reference values: European Community for Steel and Coal).41 One included subject in this group had an FEV1/FVC ratio of 0.68, but this subject displayed large lung volumes (FEV1: 106% of predicted, FVC: 127% of predicted) and lacked both clinical and historical signs of lung disease, thus was classified as not having COPD.

Subjects classified as long-term smokers had to meet the requirements of active tobacco smoking of ≥5 cigarettes per day, during the last 5 years, and of a historic tobacco load of ≥20 pack-years. For all long-term smokers, we accepted the presence of chronic bronchitis, defined according to standard criteria.43

The spirometry criteria for inclusion in the group of LTS were a post-bronchodilatory FEV1/FVC ratio ≥0.70.

Subjects in the LTS+COPD group were required to have an FEV1/FVC ratio <0.70 after bronchodilation, corresponding to the criteria for GOLD stage I–III as of 2011.44 For safety reasons related to the bronchoscopy investigation, it was required that all subjects had FEV1 ≥1.0 liter (L), DLCO ≥50% of predicted and percutaneous oxygen saturation >93%. Notably, history and radiological signs of chronic bronchitis and emphysema were accepted in LTS+COPD. This was the only study group also allowed to have an “as needed” treatment with short-acting inhaled beta-2-agonists and/or short-acting inhaled anticholinergics, with a prerequisite of a three-day wash-out prior to bronchoscopy.

Among the included study subjects, one subject in the LTS group attended but did not complete the bronchoscopy, due to poor compliance during this investigation. Consequently, only blood samples were harvested from this subject on the bronchoscopy visit. Moreover, one subject in the LTS+COPD group withdrew from the study prior to the bronchoscopy visit, for personal reasons. Thus, the absence of the certain samples for these two subjects is reflected by the varying n for the different outcomes of the relevant study groups.

Glucose Measurements

The concentration of glucose was assessed during the screening visit, in capillary whole blood harvested from a fingertip with a glucose meter (Freestyle Freedom Lite®, Abbott Diabetes Care Inc., Alameda, CA, USA). Each concentration was measured in doublets and the corresponding average value was used in further analysis. An initial sampling was performed after overnight fasting for 10 hours (hrs) and was followed by an oral glucose tolerance test (OGTT) with 75 grams (g) (200 milliliter (mL)) of a commercial glucose solution (Gluco® 75, TruLaboratories Corporation®, Cubao, Quezon City, Philippines) in accordance with standard clinical routines. The OGTT was finalized after 120 minutes (min), when a second sampling was performed to determine the concentration of capillary blood glucose at the end of OGTT. Accordingly, the change in glucose concentration during OGTT was estimated by the difference in glucose concentration between the end of OGTT and fasting.

Bronchoscopy Visit

Blood Samples

Peripheral venous blood (60 mL) was collected after overnight fasting, prior to bronchoscopy as whole blood (1x4 mL), plasma (4x4 mL) and serum (4x10 mL). A more detailed protocol for the sample collection, process and analysis has been described elsewhere.39

Briefly, the whole blood sample was used to determine the concentration of hemoglobin (Hb), total leukocyte concentration (LPC) and blood cell differential counts, in accordance with accredited standard procedures (Department of Clinical Chemistry, Sahlgrenska University Hospital, Gothenburg, Sweden). The samples intended for the harvesting of plasma and serum were centrifuged (1500 revolutions per min (rpm); 443 gravitational acceleration (g); 10 min at room temperature (RT)), and the acquired plasma and serum samples were frozen (−80 degrees Celsius (°C)) for future analyses.

Quantification of C-Reactive Protein

C-reactive protein (CRP) in serum was quantified in an accredited laboratory (Department of Clinical Chemistry at Sahlgrenska University Hospital). In brief, we utilized a high sensitivity method (CRPHS; Roche/Cobas, No. 04628918190; Roche Diagnostics Scandinavia AB, Solna, Sweden) based upon the agglutination of CRP to latex particles exposed to anti-CRP antibodies and the detection of the formed compounds by a turbidimetric analysis instrument (Cobas® 8000 Roche Diagnostics Scandinavia AB, Solna, Sweden).

Quantification of Cotinine

The nicotine metabolite cotinine was quantified in serum with a competitive immunochemical method (Immulite 2000 XPi Nicotine metabolite; No. L2KNM2 (200 test); Siemens Medical DiagnosticTM, Siemens Healthcare, Upplands-Väsby, Sweden), utilizing a chemiluminescence detector (Immulite 2000 XPi®; Siemens Medical DiagnosticTM, Siemens Healthcare, Upplands-Väsby, Sweden) in an accredited laboratory (Department of Clinical Chemistry at Sahlgrenska University Hospital).39


An experienced specialist in respiratory medicine performed the bronchoscopy during stable clinical conditions and according to the clinical routines at Sahlgrenska University Hospital, as described in detail elsewhere.39 In brief, the study subject was premedicated with ketobemidone hydrochloride (KetoganTM; <7.5 mg intramuscularly or <5 mg intravenously; Apoteket, Solna, Sweden) and local anesthesia with lignocaine (nebulized XylocaineTM 10 mg/dose; oropharyngeal administration of 2 doses, up to 3 times; Apoteket, Solna, Sweden). A flexible bronchoscope was then inserted through the oral cavity into the lower airways and wedged in a segmental bronchus (lingula or middle lobe), while administrating additional local anesthesia through the instrument as needed. Subsequently, a lower airway sample was harvested (either a protected bronchial brush or a BAL sample) and transferred to a sterile tube, which was stored at 4°C, until being transported to an accredited laboratory for further analysis (Department of Microbiology at Sahlgrenska University Hospital). The bronchoscope was then wedged in another segmental bronchus and three portions of 50 mL (a total of 150 mL) phosphate-buffered saline (PBS) at 37°C were instilled into the airways. Bronchoalveolar lavage (BAL) samples were aspirated after each instillation, pooled in a plastic container (SERRES® Polypropylene measuring cup 250 mL, No. 6057257; Mediplast AB, Malmö, Sweden) and kept on ice until further processing at the laboratory.

BAL Samples

The BAL samples were processed as previously described in detail.39 In brief, cells and extracellular fluid were separated from debris by filtration (Woven mesh spacers, Dacron® 124 mm diameter, No. AP3212450; Merck Chemicals and Life ScienceTM AB, Solna, Sweden). Cells were then pelleted by centrifugation (1400 rpm; 378 g; 10 min at 4°C). A second centrifugation (2000 rpm; 771 g; 10 min at 4°C) of the cell-free BAL fluid (BALF) was performed to eliminate any carry over debris before storage at −80°C. After been re-suspended in PBS, the cell pellet was transferred to a Bürker counting chamber to determine the total cell concentration. Türk´s solution (Cat. No. 93770, Sigma-Aldrich Sweden AB, Stockholm, Sweden) was utilized to assess cell viability. Differential cell counts were performed accordingly. Two cell suspensions (100 microliters (µL) of 600 cells/µL each) were loaded on cytospin slides and centrifuged (1000 rpm; 246 g; for 5 min at RT in Cytospin™ 4, Thermo Fisher Scientific™, Shandon, MA, USA). The slides were then air-dried (overnight) and stored frozen (−20°C) prior to May-Grünwald-Giemsa staining and cell counting (200 cells per sample) under a light microscope.

Laboratory Investigations

Quantification of Cytokines

The protein concentrations of IL-6, IL-8, INF-γ and CXCL10 were determined in BALF and plasma from peripheral blood, utilizing the U-Plex assay® (Meso Scale DiscoveryTM platform, cat no K15067-L1, Meso Scale Diagnostics, Rockville, Maryland, USA) in accordance with the manufacturer’s recommendations, as previously described.40

The protein concentrations of the IL-36 family of cytokines, including IL-36α, -β and -γ, were quantified in both BALF and plasma samples, utilizing commercial DuoSet ELISA kits (R&D Systems, Minneapolis, MN, USA) as previously described.45,46

Quantification of Neutrophil Elastase

The protein concentration of neutrophil elastase in BALF was determined using a commercial sandwich ELISA (Human PMN Elastase ELISA; No. 191021100; BioVendor® Laboratorni Medicina A.S., Brno, Check Republic) according to the manufacturer’s instructions, as described elsewhere.39 Data on neutrophil elastase has been previously published for a subgroup of the utilized study population, although in a different scientific context.39

Quantification of Net Gelatinase and Net Serine Proteinase Activity

The net proteolytic activity of gelatinase and serine proteinases was determined in BALF utilizing a fluorometric method, as described elsewhere.47 Briefly, fluorescein labeled dye-quenched (DQ) gelatin and elastin EnzChek® molecular probes were incubated with the BALF (at 37°C for 16 hrs). The fluorescence intensity was then assessed with a multimode microplate reader (CLARIOStar®; BMG Labtech Pty. LtdTM, Ortenberg, Germany), set at 495 nm as absorption maximum and 515 nm as emission maximum. Increasing values of fluorescence intensity corresponded to increasing net activity of gelatinase and serine proteinases. A subset of this data has been previously published in a different scientific context.39

Bacteria in the Airways

The growth of aerobic bacteria was determined in the lower airways of each subject by performing a qualitative and quantitative analysis of samples from this compartment, following standard laboratory procedures as previously described.39 Briefly, a morphological analysis was performed to assess the percentage of squamous epithelial cells in the samples, and a percentage less than 1% was required to judge a sample as representative for the lower airways. Mass spectrometry (MALDI-TOF) was used to identify and quantify (if >100 colony-forming units (CFU)/mL) the 10 most common bacterial species in each of the samples that were judged representative for the lower airways. However, in the samples that were judged as non-representative for the lower airways, MALDI-TOF was utilized to identify and quantify (if >1000 CFU/mL) the potential pathogenic bacteria only.


We applied non-parametric statistical analyses using GraphPad Prism 9.0.1 (GraphPad Software, San Diego, CA, USA). Given the limited statistical power of the material, the statistical analysis of group differences was restricted to the groups of LTS+COPD and HNS. In this sense, here, we utilized Mann–Whitney U-test for group comparisons of continuous variables. Correlation analysis was conducted with Spearman’s rank correlation test and was initially performed in the LTS+COPD group. The statistically significant correlations in this group were then expanded to the groups of LTS and HNS, given the limited statistical power in our study material. A p-value <0.05 was regarded statistically significant.


Human Study Population

The principal clinical characteristics of the included subjects are summarized in Table 1. More specifically, we detected no pronounced differences for age, gender or BMI among the three study groups. The LTS and LTS+COPD groups had very similar exposure to tobacco smoke, in terms of current (cigarettes/day) and historic (pack-years) tobacco smoking, as well as of cotinine concentration in serum. The LTS+COPD group displayed clearly lower FEV1 (% of predicted) and FEV1/FVC ratio compared to the HNS and LTS groups, which is consistent with the study´s inclusion criteria. The concentrations of CRP and Hb in blood were not markedly different among the three study groups. As expected, regular pharmacological treatment was more frequently observed at screening visit in the groups of long-term smokers (LTS and LTS+COPD) compared to HNS. Antidepressants and hypnotic drugs were the most common medications in the two groups of long-term smokers but were not used in the HNS group.

Table 1 Clinical Characteristics of the Human Study Population

Table 2 presents the baseline characteristics of BAL and blood samples. Data on neutrophil concentrations are presented more in-depth below, in the section “Neutrophil concentrations in long-term smokers with COPD”.

Table 2 Characteristics of Blood and BAL Samples

Notably, the bacteriological analysis in samples from the lower airways revealed growth of airway pathogens in HNS mainly and less in LTS, while no such pathogens were detected in LTS+COPD (Table 3).

Table 3 Bacteriological Findings in the Lower Airways

Glucose Homeostasis in Long-Term Smokers with COPD

The LTS+COPD group displayed a lower concentration of fasting blood glucose and a more pronounced change in blood glucose during OGTT compared with the HNS, and these differences were statistically significant (Figure 1A and B). The concentration of blood glucose at the end of OGTT tended to be elevated in the LTS+COPD compared to the HNS group, though this difference did not reach statistical significance (Figure 1C).

Figure 1 (A) Concentration of fasting blood glucose (n= 6–11), (B) change in blood glucose concentration during OGTT (n= 6–11) and (C) concentration of blood glucose at the end of OGTT (120 min) (n= 6–11) measured with a glucose meter in capillary blood of HNS, LTS and LTS+COPD.

Abbreviations: OGTT, oral glucose tolerance test; HNS, healthy non-smokers; LTS, long-term smokers without COPD; LTS+COPD, long-term smokers with COPD.

Notes: Data are presented as observed and as median values. See “Material and methods” regarding the utilized assays. In all three graphs, group comparisons were restricted between the groups of LTS+COPD and HNS, and were performed using the Mann–Whitney U-test. In graph (C), the performed group comparison is presented with a dotted line, due to a difference close to statistical significance. p < 0.05 was regarded as statistically significant.

The concentration of fasting blood glucose in the LTS+COPD group displayed a strong positive correlation with the neutrophil concentration in blood, FEV1 (% of predicted) and FEV1/FVC ratio, (Figure 2A-C respectively). In contrast, the concentration of fasting glucose displayed a strong negative correlation with the IL-36α concentration in BALF (Figure 2D). In a similar manner, the blood glucose concentration at the end of OGTT in the LTS+COPD group correlated in a negative manner with the concentration of CXCL10 in BALF (Figure 2E). Notably, none of the above correlations were observed in LTS or HNS (Figure S1 in the data supplement). Finally, there were no evident correlations between any of the glucose-related outcomes with BMI, the neutrophil concentration in BAL or with the concentrations of IL-36γ, IL-6, IL-8 and INF-γ in BALF or plasma of LTS+COPD, as applicable (data not shown).

Figure 2 Correlation of fasting blood glucose with (A) neutrophil concentration in blood (n= 5), (B) FEV1 (% of predicted) (n= 6) and (C) FEV1/FVC ratio of LTS+COPD (n= 6). Correlation (D) of fasting glucose with IL-36a in BALF (n= 5) and (E) of blood glucose concentration at the end of OGTT (120 min) with CXCL10 in BALF of LTS+COPD (n= 5).

Abbreviations: FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; LTS+COPD, long-term smokers with COPD; IL-36α, interleukin-36α; BALF, cell-free bronchoalveolar lavage fluid; OGTT, oral glucose tolerance test; CXCL10, C-X-C motif chemokine ligand 10.

Notes: See “Material and methods” regarding the utilized assays. Correlation analyses were performed using Spearman’s rank correlation test. p < 0.05 was regarded as statistically significant.

Neutrophil Concentrations in Long-Term Smokers with COPD

The BAL and blood neutrophil concentrations were higher in LTS+COPD than in HNS (Figure 3A and B). Furthermore, the neutrophil concentration in blood samples, but not in BAL, correlated in a strong and positive manner with FEV1 (% of predicted) (Figure 3C) and in a strong and negative manner with IL-36α concentration in BALF of LTS+COPD (Figure 3D), whereas similar correlations were not observed in either the LTS or the HNS group (Figure S2 in the data supplement). We observed no correlations in the LTS+COPD group for BAL or blood neutrophil concentration, with the concentrations of IL-36γ, IL-6, IL-8, INF-γ or CXCL10 either in BALF or plasma, respectively (data not shown).

Figure 3 Neutrophil concentrations (A) in BAL (n= 5–10) and (B) in blood samples of HNS, LTS and LTS+COPD (n= 5–10). Neutrophil concentration in blood correlated (C) positively with FEV1 (% of predicted) (n= 5) and (D) negatively with IL-36α in BALF of LTS+COPD (n= 5).

Abbreviations: BAL, bronchoalveolar lavage; HNS, healthy non-smokers; LTS, long-term smokers without COPD; LTS+COPD, long-term smokers with COPD; FEV1, forced expiratory volume in 1 second; IL-36α, interleukin-36α; BALF, cell-free bronchoalveolar lavage fluid.

Notes: Data in graphs (A) and (B) are presented as observed and median values. See “Material and methods” regarding the utilized assays for all graphs. In graphs (A) and (B), group comparisons were restricted between the groups of LTS+COPD and HNS, and were performed using the Mann–Whitney U-test. In graphs (C) and (D), the correlation analyses were performed using Spearman’s rank correlation test. p < 0.05 was regarded as statistically significant.

Cytokine Concentrations in Long-Term Smokers with COPD

In a previous publication based on the current study material, we showed that the BALF concentrations of IL-36α and IL-36γ were increased in LTS+COPD compared with HNS.28 In the current study, we found that the BALF IL-36α concentration correlated in a strong and negative manner with FEV1 (% of predicted) in the LTS+COPD group (Figure 4), but not in the LTS or the HNS group (Figure S3 in the data supplement). We did not observe any correlation between IL-36γ and ventilatory lung function. Here, neither IL-36α nor IL-36γ correlated with either of the cytokines IL-6, IL-8 or CXCL10 (data not shown). The LTS+COPD group displayed an increased concentration of IL-8 in BALF compared with the HNS group and this difference was statistically significant (Figure 5A). However, the concentration of CXCL10 in the LTS+COPD group did not differ substantially from the HNS group (Figure 6A). Similarly, we observed no pronounced difference in the concentration of IL-6 in BALF between these groups (Figure S4 in the data supplement). Finally, IL-36β and INF-γ were not detectable in BALF.

Figure 4 Correlation of IL-36α in BALF with FEV1 (% of predicted) in LTS+COPD (n= 5).

Abbreviations: IL-36α, interleukin-36α; BALF, cell-free bronchoalveolar lavage fluid; FEV1, forced expiratory volume in 1 second; LTS+COPD, long-term smokers with COPD.

Notes: See “Material and methods” regarding the utilized assays. Correlation analysis was performed using Spearman’s rank correlation test. p < 0.05 was regarded as statistically significant.

Figure 5 Concentration of IL-8 (A) in cell-free BALF (n= 5–10) and (B) in plasma of HNS, LTS and LTS+COPD (n= 4–10).

Abbreviations: IL-8, interleukin-8; BALF, cell-free bronchoalveolar lavage fluid; HNS, healthy non-smokers; LTS, long-term smokers without COPD; LTS+COPD, long-term smokers with COPD.

Notes: Data are presented as observed and median values. See “Material and methods” regarding the utilized assays. In both graphs, group comparisons were restricted between the groups of LTS+COPD and HNS, and were performed using the Mann–Whitney U-test. p < 0.05 was regarded as statistically significant.

Figure 6 Concentration of CXCL10 (A) in cell-free BALF (n= 5–10) and (B) in plasma of HNS, LTS and LTS+COPD (n= 4–10).

Abbreviations: CXCL10, C-X-C motif chemokine ligand 10; BALF, cell-free bronchoalveolar lavage fluid; HNS, healthy non-smokers; LTS, long-term smokers without COPD; LTS+COPD, long-term smokers with COPD.

Notes: Data are presented as observed and as median values. See “Material and methods” regarding the utilized assays.

The plasma concentration of IL-36α was increased in LTS+COPD compared with HNS, but this was not the case for IL-36γ, as previously demonstrated.28 Neither the concentration of IL-36α nor IL-36γ correlated with the concentrations of IL-6, IL-8 and CXCL10 or with FEV1 (% of predicted) (data not shown). We observed no pronounced group differences in the plasma concentrations of IL-8 (Figure 5B), CXCL10 (Figure 6B), IL-6 and INF-γ (Figure S4 - Data supplement). Just like the case for BALF, IL-36β was not detectable in plasma.

Proteinases in Long-Term Smokers with COPD

The protein concentration of neutrophil elastase in BALF did not differ in a statistically significant manner between the LTS+COPD and the HNS group (Figure 7). This was true as well for net serine proteinase and net gelatinase activity (Figure S5 - Data supplement). Finally, we did not observe any hint of correlations for these proteinases with glucose homeostasis in the group of LTS+COPD (data not shown).

Figure 7 Protein concentration of neutrophil elastase in BALF of HNS, LTS and LTS+COPD (n= 4–10).

Abbreviations: BALF, cell-free bronchoalveolar lavage fluid; HNS, healthy non-smokers; LTS, long-term smokers without COPD; LTS+COPD, long-term smokers with COPD; vs, versus.

Notes: Data are presented as observed and median values. See “Material and methods” regarding the utilized assays. The group comparison between LTS+COPD and HNS was performed using the Mann–Whitney U-test. p < 0.05 was regarded as statistically significant.


The results of this pilot study demonstrate that assessments of glucose homeostasis, in terms of fasting blood glucose concentration, change in blood glucose concentration during OGTT and blood glucose concentration at the end of OGTT, differ substantially in long-term smokers with COPD compared to healthy non-smokers. Moreover, these glucose-related outcomes are associated with local and systemic signs of increased neutrophil mobilization in the LTS+COPD group. Collectively, these findings are suggestive of neutrophil mobilization as a unifying pathogenic mechanism associated with alterations of glucose homeostasis in COPD.

In particular, the blood concentration of fasting glucose was markedly decreased in the LTS+COPD group compared with the HNS group, and this decrease was independent of BMI. Notably, this finding is compatible with previous studies showing an accelerated whole-body glycolysis rate in response to increased energy expenditure among patients with COPD.48,49 It is also possible that neutrophils secrete compounds that suppress hepatic glucose production as previously reported in an experimental study in mice and Zucker diabetic fatty rats.50 Along these lines, fasting glucose concentration correlated in a positive manner with FEV1 (% of predicted) and with the FEV1/FVC ratio, in the LTS+COPD group. Thus, our findings are compatible with fasting blood glucose declining as airway obstruction in COPD does progress.2 In addition, we observed that the protein concentration of IL-36α in BALF correlated in a strong and negative manner with fasting glucose and FEV1 (% of predicted) in LTS+COPD; this is interesting given that our previously published data from the same study material demonstrated enhanced concentrations of IL-36α in BALF and blood of this group compared with the HNS group.28 Notably, although IL-36α belongs to the interleukin-1 (IL-1) super family, just like IL-36β and -γ, we failed to detect any correlation between IL-36β and -γ and glucose homeostasis in the current study.29,30 However, to the best of our understanding, this is the first time to describe an association of IL-36α concentration in the airways with fasting blood glucose in smokers with COPD. We interpret this association as a sign that fasting blood glucose decreases in parallel with the progression of local neutrophil mobilization among these patients.

Furthermore, our study showed that the concentration of glucose at the end of OGTT correlated with the concentration of CXCL10 in BALF within the LTS+COPD group, in a strong and negative manner. We find this interesting given that the CXCL10 concentration in BALF was not markedly altered in the LTS+COPD group compared with the HNS group. However, we observed elevated BALF neutrophil concentrations in LTS+COPD compared with HNS, as expected. It is known that neutrophils produce CXCL10, a CXC chemokine, that recruits type 1 T-helper lymphocytes and natural killer cells.35,36,51 Moreover, CXCL10 has previously been related to neutrophil mobilization caused by oxidative stress in an animal airway model and is enhanced in the airways of patients with exacerbation of COPD.37,52,53 Given this and the demonstrated link between CXCL10 and T2DM in a previous publication, we think that our current findings on CXCL10 lend further support to the hypothesis that local neutrophil mobilization in COPD has an impact on glucose homeostasis that may affect the risk of developing T2DM and MetS.38,54

An important observation was that the change in blood glucose concentration during OGTT was more pronounced in the LTS+COPD group than the HNS group. In line with this finding, the LTS+COPD group tended to have a higher concentration of glucose at the end of OGTT than did the HNS group. These findings indicate a trend towards impaired glucose tolerance in COPD, as yet another sign of altered glucose homeostasis in patients with this disease. Moreover, our study showed that the concentration of blood neutrophils in LTS+COPD was increased in comparison with the HNS group and correlated with fasting glucose in a strong and positive manner, which contrasts with our finding of lower fasting glucose in LTS+COPD compared with HNS. Clearly, these seemingly contradictory results motivate further study and evidence for a causative relationship needs to be established. However, this correlation between the blood concentration of neutrophils and fasting glucose indicates that even systemic signs of neutrophil mobilization in COPD are, indeed, associated with altered glucose homeostasis, an alteration that in both of T2DM and MetS can reach pathologic levels.55

The concentration of blood neutrophils correlated with FEV1 (% of predicted) in the LTS+COPD but not in the LTS or the HNS group. Notably, this suggests an association of ventilatory lung function with systemic neutrophil mobilization, due to COPD, rather than with long-term smoking per se. Progressively declining lung function is a common feature of COPD and it has been related in previous studies to the local accumulation of neutrophils in the airways.56 It is of mechanistic interest that this local accumulation is due to the extravasation of systemically circulating neutrophils.16 Given this, our current observation of a positive correlation between blood neutrophil concentration and FEV1 (% of predicted) seems credible, reflecting the increasing tendency of neutrophil transmigration from blood circulation to the airways that follows the impairment of ventilatory lung function as the pathology of COPD progresses. In agreement with the literature, we observed a markedly enhanced concentration of BAL neutrophils in the LTS+COPD in comparison with the HNS group.57 Despite this, we failed to demonstrate statistically significant correlations between BAL neutrophil concentration and lung function in the LTS+COPD group, most likely due to the modest size of our study population.

In addition to our observations of an increased concentration of BAL neutrophils in the LTS+COPD group, we also observed a corresponding enhanced BALF concentration of IL-8 in this study group, reassuring us that our material is representative for COPD. However, the BALF concentration of neutrophil elastase in the LTS+COPD group did not differ in a statistically significant manner from that in the HNS group. Moreover, the net serine proteinase and gelatinase activity did not display any pronounced enhancement in the LTS+COPD group either. Given that neutrophil elastase and other serine proteinases, as well as gelatinases, are released by neutrophils in response to bacterial exposure, we think that these findings reflect the absence of colonization with pathogenic bacteria of the lower airway tract in the LTS+COPD group of the current study population.16 Furthermore, neither neutrophil elastase nor serine proteinase or gelatinase activity in BALF samples correlated with any of the glucose-related outcomes in the LTS+COPD group. This finding suggests that during stable disease, local proteinases are not among the key aspects of neutrophil mobilization that drive the development of metabolic comorbidities of COPD.

Naturally, the modest size of our current study material limited the number of conclusive group comparisons and associations of outcomes. Nevertheless, our careful clinical characterization of subjects and meticulous laboratory investigations enabled the identification of several group differences and correlations that proved statistically significant for outcomes of pathogenic interest, suggesting that the current findings are sound and of noteworthy biological consequence. Most importantly, we ensured stable disease in the LTS+COPD group by addressing signs of exacerbations, infections and change in inflammatory markers. In parallel, we ensured a thorough and reliable characterization of tobacco use in all three study groups, by addressing current and historic tobacco exposure as well as the systemic cotinine concentration. Furthermore, regular treatment with inhaled beta-2-agonists, which is common in patients with COPD, was excluded in this study, not only because of its anti-inflammatory properties, but even due to its potentially confounding effect on glucose homeostasis.58,59 Finally, BMI did not differ markedly in the three study groups and did not correlate with any of our key variables, which indicates that BMI did not act as a confounder in our study and this adds credibility to our findings.


In conclusion, this pilot study forwards the original evidence that altered glucose homeostasis is associated with specific local and systemic signs of neutrophil mobilization in COPD, and this evidence is fully compatible with the increased risk for metabolic comorbidities in this group of patients. Given our novel observations, we postulate that specific aspects of increased neutrophil mobilization constitute a common denominator for type 2 diabetes mellitus/metabolic syndrome and COPD. We think that this new paradigm motivates further mechanistic exploration with more in-depth metabolic phenotyping in larger and dedicated study materials of well-characterized patients with COPD, an exploration that may facilitate the development of novel diagnostic and therapeutic strategies for a large and neglected group of patients.


The project funding for this study was provided by the Swedish Heart-Lung Foundation (AL: No. 20210286, SKL: No. 20200579) and King Gustaf V’s and Queen Victoria’s Freemason Research Foundation (AL). Additionally, federal funding was received from Karolinska Institutet (AL), Stockholm Regional Council (ALF: AL: No. 2018-0088) and Västra Götaland Region (LUA: AL: No. 2014-1851). Additional research funding was obtained via Karolinska Severe COPD Center, through unrestricted grants for research infrastructure from AstraZeneca Nordic AB, GlaxoSmithKline AB and Boehringer-Ingelheim AB, Sweden, respectively. The sponsors’ involvement was limited strictly to their financial support, and none played a role in the execution of the study. Finally, the investigators do not have any financial or other binding to the tobacco industry.

The authors express their gratitude to study nurse Monika Crona BSc and biomedical laboratory scientist Dorota Persson BSc, for their crucial contribution in the collection and processing of the study material at Sahlgrenska University Hospital.


Dr Anders Andersson reports personal fees from Novartis, personal fees from Astra-Zeneca, personal fees from Boehringer-Ingelheim, outside the submitted work. Dr Melissa Kovach reports grants from European Respiratory Society, grants from VINNOVA, during the conduct of the study. The authors report no other conflicts of interest for this work.


1. The top 10 cases of death, World Health Organization. 2020; Available from: www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death. Accessed 23 December, 2021.

2. Hogg JC, Timens W. The pathology of chronic obstructive pulmonary disease. Annu Rev Pathol. 2009;4:435–459.

3. Miller J, Edwards LD, Agusti A, et al. Comorbidity, systemic inflammation and outcomes in the ECLIPSE cohort. Respir Med. 2013;107(9):1376–1384.

4. American Diabetes A. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S13–S27.

5. Spranger J, Kroke A, Mohlig M, et al. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes. 2003;52(3):812–817.

6. Alberti KGMM, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome. Circulation. 2009;120(16):1640–1645.

7. Rutter MK, Meigs JB, Sullivan LM, D’Agostino RB, Wilson PW. C-reactive protein, the metabolic syndrome, and prediction of cardiovascular events in the Framingham Offspring Study. Circulation. 2004;110(4):380–385.

8. Ehrlich SF, Quesenberry CP, Van Den Eeden SK, Shan J, Ferrara A. Patients diagnosed with diabetes are at increased risk for asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, and pneumonia but not lung cancer. Diabetes Care. 2010;33(1):55–60.

9. Hughes MJ, McGettrick HM, Sapey E. Shared mechanisms of multimorbidity in COPD, atherosclerosis and type-2 diabetes: the neutrophil as a potential inflammatory target. Eur Respir Rev. 2020;29:155.

10. Piazzolla G, Castrovilli A, Liotino V, et al. Metabolic syndrome and Chronic Obstructive Pulmonary Disease (COPD): the interplay among smoking, insulin resistance and vitamin D. PLoS One. 2017;12(10):e0186708.

11. Hoenderdos K, Condliffe A. The neutrophil in chronic obstructive pulmonary disease. Am J Respir Cell Mol Biol. 2013;48(5):531–539.

12. O’Donnell RA, Peebles C, Ward JA, et al. Relationship between peripheral airway dysfunction, airway obstruction, and neutrophilic inflammation in COPD. Thorax. 2004;59(10):837–842.

13. Andelid K, Andersson A, Yoshihara S, et al. Systemic signs of neutrophil mobilization during clinically stable periods and during exacerbations in smokers with obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2015;10:1253–1263.

14. Zhang H, Yang Z, Zhang W, et al. White blood cell subtypes and risk of type 2 diabetes. J Diabetes Complications. 2017;31(1):31–37.

15. Buyukkaya E, Karakas MF, Karakas E, et al. Correlation of neutrophil to lymphocyte ratio with the presence and severity of metabolic syndrome. Clin Appl Thromb Hemost. 2014;20(2):159–163.

16. Liew PX, Kubes P. The neutrophil’s role during health and disease. Physiol Rev. 2019;99(2):1223–1248.

17. McDonald B, Kubes P. Innate immune cell trafficking and function during sterile inflammation of the liver. Gastroenterology. 2016;151(6):1087–1095.

18. Phillipson M, Kubes P. The neutrophil in vascular inflammation. Nat Med. 2011;17(11):1381–1390.

19. Johnson JL, Moore EE, Tamura DY, Zallen G, Biffl WL, Silliman CC. Interleukin-6 augments neutrophil cytotoxic potential via selective enhancement of elastase release. J Surg Res. 1998;76(1):91–94.

20. Zeilhofer HU, Schorr W. Role of interleukin-8 in neutrophil signaling. Curr Opin Hematol. 2000;7(3):178–182.

21. Williams JG, Jurkovich GJ, Maier RV. Interferon-gamma: a key immunoregulatory lymphokine. J Surg Res. 1993;54(1):79–93.

22. Pham CT. Neutrophil serine proteases: specific regulators of inflammation. Nat Rev Immunol. 2006;6(7):541–550.

23. Henry CM, Sullivan GP, Clancy DM, Afonina IS, Kulms D, Martin SJ. Neutrophil-derived proteases escalate inflammation through activation of IL-36 family cytokines. Cell Rep. 2016;14(4):708–722.

24. Bolton CE, Evans M, Ionescu AA, et al. Insulin resistance and inflammation - a further systemic complication of COPD. COPD. 2007;4(2):121–126.

25. Di Stefano A, Coccini T, Roda E, et al. Blood MCP-1 levels are increased in chronic obstructive pulmonary disease patients with prevalent emphysema. Int J Chron Obstruct Pulmon Dis. 2018;13:1691–1700.

26. Cimini FA, Barchetta I, Porzia A, et al. Circulating IL-8 levels are increased in patients with type 2 diabetes and associated with worse inflammatory and cardiometabolic profile. Acta Diabetol. 2017;54(10):961–967.

27. Shin MJ, Lee KH, Chung JH, et al. Circulating IL-8 levels in heart failure patients with and without metabolic syndrome. Clin Chim Acta. 2009;405(1–2):139–142.

28. Kovach MA, Che K, Brundin B, et al. IL-36 cytokines promote inflammation in the lungs of long-term smokers. Am J Respir Cell Mol Biol. 2021;64(2):173–182.

29. Bassoy EY, Towne JE, Gabay C. Regulation and function of interleukin-36 cytokines. Immunol Rev. 2018;281(1):169–178.

30. Sims JE, Smith DE, The IL-1. family: regulators of immunity. Nat Rev Immunol. 2010;10(2):89–102.

31. Elias M, Zhao S, Le HT, et al. IL-36 in chronic inflammation and fibrosis - bridging the gap? J Clin Invest. 2021;131:2.

32. Ramadas RA, Ewart SL, Medoff BD, LeVine AM. Interleukin-1 family member 9 stimulates chemokine production and neutrophil influx in mouse lungs. Am J Respir Cell Mol Biol. 2011;44(2):134–145.

33. Ramadas RA, Ewart SL, Iwakura Y, Medoff BD, LeVine AM. IL-36alpha exerts pro-inflammatory effects in the lungs of mice. PLoS One. 2012;7(9):e45784.

34. Giannoudaki E, Hernandez-Santana YE, Mulfaul K, et al. Interleukin-36 cytokines alter the intestinal microbiome and can protect against obesity and metabolic dysfunction. Nat Commun. 2019;10(1):4003.

35. Liu M, Guo S, Hibbert JM, et al. CXCL10/IP-10 in infectious diseases pathogenesis and potential therapeutic implications. Cytokine Growth Factor Rev. 2011;22(3):121–130.

36. Cassatella MA, Gasperini S, Calzetti F, Bertagnin A, Luster AD, McDonald PP. Regulated production of the interferon-gamma-inducible protein-10 (IP-10) chemokine by human neutrophils. Eur J Immunol. 1997;27(1):111–115.

37. Tangedal S, Nielsen R, Aanerud M, et al. Sputum microbiota and inflammation at stable state and during exacerbations in a cohort of chronic obstructive pulmonary disease (COPD) patients. PLoS One. 2019;14(9):e0222449.

38. Chang CC, Wu CL, Su WW, et al. Interferon gamma-induced protein 10 is associated with insulin resistance and incident diabetes in patients with nonalcoholic fatty liver disease. Sci Rep. 2015;5:10096.

39. Padra M, Andersson A, Levanen B, et al. Increased MUC1 plus a larger quantity and complex size for MUC5AC in the peripheral airway lumen of long-term tobacco smokers. Clin Sci (Lond). 2020;134(10):1107–1125.

40. Stockfelt M, Christenson K, Andersson A, et al. Increased CD11b and Decreased CD62L in Blood and Airway Neutrophils from Long-Term Smokers with and without COPD. J Innate Immun. 2020;1:1–10.

41. Quanjer PH, Tammeling GJ, Cotes JE, Pedersen OF, Peslin R, Yernault JC. Lung volumes and forced ventilatory flows. Report Working Party Standardization of Lung Function Tests, European Community for Steel and Coal. Official Statement of the European Respiratory Society. Eur Respir J Suppl. 1993;16:5–40.

42. Salorinne Y. Single-breath pulmonary diffusing capacity. Reference values and application in connective tissue diseases and in various lung diseases. Scand J Respir Dis Suppl. 1976;96:1–84.

43. Definition and classification of chronic bronchitis for clinical and epidemiological purposes. A report to the Medical Research Council by their Committee on the Aetiology of Chronic Bronchitis. Lancet. 1965;1:775–779.

44. Vestbo J, Hurd SS, Agusti AG, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2013;187(4):347–365.

45. Kovach MA, Singer B, Martinez-Colon G, et al. IL-36gamma is a crucial proximal component of protective type-1-mediated lung mucosal immunity in Gram-positive and -negative bacterial pneumonia. Mucosal Immunol. 2017;10(5):1320–1334.

46. Kovach MA, Singer BH, Newstead MW, et al. IL-36gamma is secreted in microparticles and exosomes by lung macrophages in response to bacteria and bacterial components. J Leukoc Biol. 2016;100(2):413–421.

47. Smith ME, Bozinovski S, Malmhäll C, et al. Increase in net activity of serine proteinases but not gelatinases after local endotoxin exposure in the peripheral airways of healthy subjects. PLoS One. 2013;8(9):45.

48. Kao CC, Hsu JW, Bandi V, Hanania NA, Kheradmand F, Jahoor F. Glucose and pyruvate metabolism in severe chronic obstructive pulmonary disease. J Appl Physiol. 2012;112(1):42–47.

49. Creutzberg EC, Schols AM, Bothmer-Quaedvlieg FC, Wouters EF. Prevalence of an elevated resting energy expenditure in patients with chronic obstructive pulmonary disease in relation to body composition and lung function. Eur J Clin Nutr. 1998;52(6):396–401.

50. Liu HY, Collins QF, Moukdar F, et al. Suppression of hepatic glucose production by human neutrophil alpha-defensins through a signaling pathway distinct from insulin. J Biol Chem. 2008;283(18):12056–12063.

51. Palomino DC, Marti LC. Chemokines and immunity. Einstein. 2015;13(3):469–473.

52. Saetta M, Mariani M, Panina-Bordignon P, et al. Increased expression of the chemokine receptor CXCR3 and its ligand CXCL10 in peripheral airways of smokers with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2002;165(10):1404–1409.

53. Michalec L, Choudhury BK, Postlethwait E, et al. CCL7 and CXCL10 orchestrate oxidative stress-induced neutrophilic lung inflammation. J Immunol. 2002;168(2):846–852.

54. Herder C, Baumert J, Thorand B, et al. Chemokines as risk factors for type 2 diabetes: results from the MONICA/KORA Augsburg study, 1984-2002. Diabetologia. 2006;49(5):921–929.

55. Punthakee Z, Goldenberg R, Katz P. Definition, classification and diagnosis of diabetes, prediabetes and metabolic syndrome. Canadian J Diabetes. 2018;42:S10–S15.

56. Stanescu D, Sanna A, Veriter C, et al. Airways obstruction, chronic expectoration, and rapid decline of FEV1 in smokers are associated with increased levels of sputum neutrophils. Thorax. 1996;51(3):267–271.

57. von Scheele I, Larsson K, Dahlen B, et al. Toll-like receptor expression in smokers with and without COPD. Respir Med. 2011;105(8):1222–1230.

58. Barisione G, Baroffio M, Crimi E, Brusasco V. Beta-Adrenergic Agonists. Pharmaceuticals. 2010;3(4):1016–1044.

59. Philipson LH. beta-Agonists and metabolism. J Allergy Clin Immunol. 2002;110(6 Suppl):S313–317.

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The oscillating positive expiratory pressure (OPEP) devices market is expected to grow from US$ 125. 66 million in 2021 to US$ 179. 34 million by 2028; it is estimated to grow at a CAGR of 5. 2% from 2021 to 2028.

New York, May 20, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Oscillating Positive Expiratory Pressure Devices Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Product, Indication , and Distribution Channel" - www.reportlinker.com/p06279456/?utm_source=GNW
The report highlights the key factors driving the market and prominent players with their developments. The growth of the oscillating positive expiratory pressure (OPEP) devices market is primarily attributed to the growing prevalence of chronic obstructive pulmonary disease (COPD) and asthma, and advancements in medical technologies. However, low awareness and limited access to OPEP devices hinder the growth of the market.

Oscillatory positive expiratory pressure (OPEP) devices have been in use as a supplement to traditional chest physiotherapy (CPT) to aid the clearing of respiratory secretions in people who can’t cough, especially those with chronic conditions.The use of OPEP devices is still limited in chronic airway disorders such as cystic fibrosis, bronchiectasis, bronchitis, bronchial asthma, and primary ciliary dyskinesia syndrome.

In chronic obstructive pulmonary disease (COPD), oscillating positive expiratory pressure (OPEP) devices help with sputum clearance.OPEP devices are used to remove mucus from the airways. These devices aid in the relaxation of the lungs’ walls, allowing for easier breathing. The rising prevalence of chronic obstructive pulmonary disease (COPD) and cystic fibrosis is driving the demand for mucous clearing devices.

The oscillating positive expiratory pressure (OPEP) devices market, based on product, is segmented into mouthpiece PEP devices, face mask PEP devices, and bottle PEP devices.The mouthpiece PEP devices segment held the largest share of the market in 2021.

Moreover, it is anticipated to register a CAGR of 5.3% in the market during the forecast period. Mouthpiece PEP helps to remove mucus from the lungs. It can also prevent lung collapse or open up areas that have collapsed. One of the key factors driving the market for mouthpiece PEP devices is the growing elderly population, coupled with higher rates of chronic illnesses such as chronic obstructive pulmonary disease (COPD) and asthma. According to the Centers for Disease Control and Prevention (CDC), ~9 million persons will be diagnosed with chronic bronchitis by 2020, thereby driving the need for mouthpiece devices.

Based on indication, the global oscillating positive expiratory pressure (OPEP) devices market is segmented into chronic obstructive pulmonary disease (COPD), asthma, bronchitis, bronchiectasis, cystic fibrosis, and others.Based on distribution channel, the market is segmented into hospital pharmacies, online pharmacies, and retail pharmacies.

The hospital pharmacies segment held the largest share of the market in 2021. According to research published in the Journal of Allergy and Clinical Immunology in 2020, a rise in the prevalence of chronic diseases is the primary factor contributing to the proliferation of hospital pharmacies.

A few of the major primary and secondary sources referred to while preparing the report on the oscillating positive expiratory pressure (OPEP) devices market are the Centers for Disease Control and Prevention (CDC), Health Promotion and Chronic Disease Prevention, Social Welfare’s National Health Survey, World Heart Federation, Australian Bureau of Statistics, National Center for Biotechnology Information (NCBI), and World Health Organization (WHO).
Read the full report: www.reportlinker.com/p06279456/?utm_source=GNW

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CONTACT: Clare: [email protected] US: (339)-368-6001 Intl: +1 339-368-6001

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Doctors in the UAE have advised people to remain indoors and wear face masks as dust and sandstorms sweep across the country.

The use of air purifiers is also recommended for people with breathing difficulties.

Dr Emad Al Nemnem, a pulmonary disease consultant at Burjeel Medical City, said residents with respiratory diseases are at greater risk and must take extra care.

“Sandstorms are especially dangerous for patients with respiratory disorders, particularly those with chronic bronchitis and asthma,” Dr Nemnem said.

“The symptoms start with an increase in coughing, sputum and chest tightness.”

He advised asthma patients to carry their inhalers at all times and consult a doctor or head to the emergency department if breathing becomes difficult.

“We urge patients to drink lots of water, wear good-quality masks even at home and get an air purifier,” he said.

In a WhatsApp alert, Abu Dhabi Public Health Centre said exposure to sand and dust could be harmful to all.

“However, there are certain groups of people who are more susceptible to such harm caused by sandstorms,” it read.

People with chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease are particularly vulnerable.

Dr Emad Al Nemnem, a consultant for Pulmonary Disease at Burjeel Medical city. Photo: Burjeel Medical city

Other categories include infants, children, the elderly and those with heart disease, plus those with conditions affecting the nose and eyes such as rhinitis, sinusitis and conjunctivitis.

The centre advised people to stay home during sandstorms and close their windows, and suggested they keep their nasal passages moist with the help of petroleum jelly.

“Apply a little amount of non-perfumed Vaseline inside the nostrils to avoid dry mucosa," the message said.

“For most of us the symptoms caused by sandstorms are short-lived, but if you find symptoms persist or worsen you should seek medical attention,” reads the website of Cleveland Clinic Abu Dhabi

“If you have a pre-existing medical condition, you should visit your doctor to develop a management or response plan for dealing with any health changes in the event of a sandstorm.

“Allergy sufferers may want to take an antihistamine.”

The National Centre of Meteorology issued a weather warning at the start of the month that dust and sand storms would sweep across the Emirates.

A weather alert was again issued on Wednesday that the dust

y and windy weather would continue.

The UAE has been in the grip of sandstorms since Tuesday.

Official weather stations have registered hazardous air quality in many areas since, with the scale reaching as high as 684 near Al Ain on Thursday morning.

Experts say anything above 250 has an immediate and heavy effect on health.

As the summer approaches, sandstorms are likely to continue.

Dusty weather in the UAE - in pictures

Updated: May 19, 2022, 1:04 PM

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This announcement is in line with the company’s commitment to helping lung disease sufferers clean mucus out of their lungs with a lightweight device that can improve breathing.

More information is available at lifewellnesshealthcare.com/products/airphysio-device-search

People suffering from any form of chronic lung disease can now carry this small, easy-to-use device wherever they go, so it will be available to them whenever needed.

According to the American Lung Association, nearly 37 million Americans live with chronic lung diseases like COPD (chronic obstructive pulmonary disease – asthma, emphysema, chronic bronchitis), cystic fibrosis, atelectasis, bronchiectasis, and more. Some of these problems are not diagnosed until they are very advanced because many people think that shortness of breath, a symptom of these diseases, is just part of getting older.

The CDC reports that at nearly seven percent of all deaths in the United States, chronic respiratory diseases are a leading cause.

The American Lung Association explains that respiratory illnesses cause the lungs to become inflamed and thick, destroying the tissue where oxygen is exchanged and decreasing the flow of air, resulting in shortness of breath.

Although COPD is chronic and has no cure, it is treatable. The AirPhysio is a mucus clearing device that can improve the user’s breathing. It uses a natural technology called oscillating positive expiratory pressure (OPEP), which breaks the bond of mucus to the airway wall with vibration and then the positive pressure helps to push mucus out of the body.

This device is drug-free and does not need batteries or liquids. When needed, a person can use it once or twice a day for one to five minutes.

This innovative device can help people with asthma, atelectasis, bronchiectasis, COPD, cystic fibrosis, and more. In addition to the regular device, models for athletes and children are also available.

The AirPhysio is from Australia, but for customers in the U.S. and Canada, it will be shipped from the United States.

A satisfied customer wrote, “This device is simple but very effective. I’ve suffered from lung challenges for many years, and I instantly felt an improvement the first day I started using it. It sure works.”

Interested parties can find more information at lifewellnesshealthcare.com/products/airphysio-device-search

Contact Info:
Name: Matthew
Email: Send Email
Organization: Life Wellness Healthcare
Address: PO BOX 6662, Tweed Heads, NSW 2486, Australia
Phone: +61-7-3608-5683
Website: lifewellnesshealthcare.com/

Release ID: 89069588

If you detect any issues, problems, or errors in this press release content, kindly contact [email protected] to notify us. We will respond and rectify the situation in the next 8 hours.

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This announcement is in line with the company’s commitment to helping lung disease sufferers clean mucus out of their lungs with a lightweight device that can improve breathing.

More information is available at lifewellnesshealthcare.com/products/airphysio-device-search

People suffering from any form of chronic lung disease can now carry this small, easy-to-use device wherever they go, so it will be available to them whenever needed.

According to the American Lung Association, nearly 37 million Americans live with chronic lung diseases like COPD (chronic obstructive pulmonary disease – asthma, emphysema, chronic bronchitis), cystic fibrosis, atelectasis, bronchiectasis, and more. Some of these problems are not diagnosed until they are very advanced because many people think that shortness of breath, a symptom of these diseases, is just part of getting older.

The CDC reports that at nearly seven percent of all deaths in the United States, chronic respiratory diseases are a leading cause.

The American Lung Association explains that respiratory illnesses cause the lungs to become inflamed and thick, destroying the tissue where oxygen is exchanged and decreasing the flow of air, resulting in shortness of breath.

Although COPD is chronic and has no cure, it is treatable. The AirPhysio is a mucus clearing device that can improve the user’s breathing. It uses a natural technology called oscillating positive expiratory pressure (OPEP), which breaks the bond of mucus to the airway wall with vibration and then the positive pressure helps to push mucus out of the body.

This device is drug-free and does not need batteries or liquids. When needed, a person can use it once or twice a day for one to five minutes.

This innovative device can help people with asthma, atelectasis, bronchiectasis, COPD, cystic fibrosis, and more. In addition to the regular device, models for athletes and children are also available.

The AirPhysio is from Australia, but for customers in the U.S. and Canada, it will be shipped from the United States.

A satisfied customer wrote, “This device is simple but very effective. I’ve suffered from lung challenges for many years, and I instantly felt an improvement the first day I started using it. It sure works.”

Interested parties can find more information at lifewellnesshealthcare.com/products/airphysio-device-search

Contact Info:
Name: Matthew
Email: Send Email
Organization: Life Wellness Healthcare
Address: PO BOX 6662, Tweed Heads, NSW 2486, Australia
Phone: +61-7-3608-5683
Website: lifewellnesshealthcare.com/

Release ID: 89069588

If you detect any issues, problems, or errors in this press release content, kindly contact [email protected] to notify us. We will respond and rectify the situation in the next 8 hours.

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Chronic Obstructive Pulmonary Disease is a broad term used for defining progressive lung diseases like emphysema, refractory asthma, chronic bronchitis and some other forms of bronchiectasis. The symptoms of Chronic Obstructive Pulmonary Disease are so common that sometimes people fail to understand that they are suffering from Chronic Obstructive Pulmonary Disease and consider it as normal cold, cough and symptoms of aging. Symptoms are sometimes not even visible in the early stages of disease and the disease remains undiagnosed for a long time.

The symptoms of Chronic Obstructive Pulmonary Disease include wheezing, tightness in the chest, frequent coughing and increased breathlessness. Chronic Obstructive Pulmonary Disease can be treated using different types of drugs and therapies including oxygen therapy and pulmonary rehabilitation programs. In case of extreme severity of Chronic Obstructive Pulmonary Disease surgery is recommended which includes lung volume reduction surgery, lung transplant and bullectomy.

According to the data of British Lung Foundation approximately 1.2 billion people were suffering from Chronic Obstructive Pulmonary Disease in the U.K. alone in 2011. Also according to the COPD Foundation approximately 30million Americans were suffering from Chronic Obstructive Pulmonary Disease in 2013. Chronic Obstructive Pulmonary Disease is one of the leading causes of death worldwide. This data demonstrates the ever increasing demand of Chronic Obstructive Pulmonary Disease treatment worldwide and hence also shows the potential that the Chronic Obstructive Pulmonary Disease therapeutics market holds.

Chronic Obstructive Pulmonary Disease Therapeutics Market: Drivers and Restraints

The most important factors that are expected to drive the growth of the Chronic Obstructive Pulmonary Disease market includes the ever increasing number of cases of Chronic Obstructive Pulmonary Disease globally. Also the change in the lifestyle is responsible for increasing the habits like smoking and increase in the number of genetic disorders which in turn are responsible for raising the number of Chronic Obstructive Pulmonary Disease patients.

For more insights into the market, request a sample of this [email protected] www.futuremarketinsights.com/reports/sample/rep-gb-4337

Other factors that can boost the revenue from the Chronic Obstructive Pulmonary Disease therapeutics market are rising expenditures on healthcare that is leading to the adoption of Chronic Obstructive Pulmonary Disease treatments in the emerging economies. Increase in the level of awareness has also lead to the early diagnosis of the Chronic Obstructive Pulmonary Disease so that people can go for the treatment of the disease.

Factors that can limit the growth of the therapeutic enzymes in the forecast period include the fact that not all the patients who are suffering from Chronic Obstructive Pulmonary Disease are aware of the fact that they are suffering from the disease and therefore do not go for the treatment of the disease. Also sometimes people get to know about their disease when the disease can’t be cured by only medication and therapies and surgery becomes mandatory. This factor can also lead to a slow growth in the revenue from the Chronic Obstructive Pulmonary Disease therapeutics market.

Chronic Obstructive Pulmonary Disease Therapeutics Market: Overview

Chronic Obstructive Pulmonary Disease therapeutics market is a growing market and is expected to see an even higher growth in the forecast period. Factors such as increase in the population suffering from Chronic Obstructive Pulmonary Disease worldwide and increasing awareness about Chronic Obstructive Pulmonary Disease are responsible for fueling the growth of the Chronic Obstructive Pulmonary Disease therapeutics market. Betterment of the healthcare infrastructure in Asia Pacific and Middle East and Africa is also responsible for the revenue growth of the Chronic Obstructive Pulmonary Disease therapeutics market in the forecast period.

Chronic Obstructive Pulmonary Disease Therapeutics Market: Region-wise Outlook

Chronic Obstructive Pulmonary Disease therapeutics market is in its growth phase and hence this market is expected to see very high growth in the emerging economies like Latin America and Asia Pacific due to high population growth in these regions. North America Chronic Obstructive Pulmonary Disease therapeutics market is the most developed market in terms of revenue, followed by Europe. Middle East and Africa are also expected to see higher growth due to growing advancement in the healthcare infrastructure.

Chronic Obstructive Pulmonary Disease Therapeutics Market: Key Market Participants

Some of the key participants of Chronic Obstructive Pulmonary Disease therapeutics market include Pfizer Inc, Adamis Laboratories Inc., GlaxoSmithKline plc.

The report covers exhaustive analysis on

  • Market Segments
  • Market Dynamics
  • Historical Actual Market Size, 2012 – 2014
  • Market Size & Forecast 2017 to 2027
  • Supply & Demand Value Chain
  • Market Current Trends/Issues/Challenges
  • Competition & Companies involved
  • Technology
  • Value Chain
  • Aircraft Refurbishing Market Drivers and Restraints

For Information On The Research Approach Used In The Report, Ask Analyst @ www.futuremarketinsights.com/askus/rep-gb-4337 

Regional analysis includes

  • North America
  • Latin America
  • Europe
  • Asia Pacific
  • Middle East & Africa

The report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, inputs from industry experts and industry participants across the value chain. The report provides in-depth analysis of parent market trends, macro-economic indicators and governing factors along with market attractiveness as per segments. The report also maps the qualitative impact of various market factors on market segments and geographies.

Chronic Obstructive Pulmonary Disease Therapeutics Market: Segmentation

Chronic Obstructive Pulmonary Disease Therapeutics Market: Segmentation

Chronic Obstructive Pulmonary Disease therapeutics market can be segmented on the basis of components and end user.

On the basis of component

  • Drug Class
  • Bronchodilators
  • Steroids
  • Phosphodiesterase-4 inhibitors
  • Theophylline
  • Antibiotics
  • Delivery Systems
  • Oral
  • Inhalation

On the basis of end user

  • Hospitals
  • Private clinics
  • Out-patients

About FMI:

Future Market Insights (ESOMAR certified market research organization and a member of Greater New York Chamber of Commerce) provides in-depth insights into governing factors elevating the demand in the market. It discloses opportunities that will favor the market growth in various segments on the basis of Source, Application, Sales Channel and End Use over the next 10-years.

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Chandrapur, India – Gokulbai Sahai, a 60-year-old widow, was waiting at the local government-run clinic in Durgapur in the Chandrapur district of Maharashtra. Dressed in a sari with a blue stole wrapped around her head, Sahai, whose vision is blurred, was being helped by other patients to figure out where she should register for treatment and where to wait till the doctor called her turn.

Gokulbai, who has to beg for food or depend on her neighbours ever since her husband died of asthma a few years ago, blames the pollution from the fumes of the coal-fired power plant near her home for her troubles, including her husband’s death.

“My husband got asthma from the polluted/dark air emanating from the power station,” Sahai told Al Jazeera on a recent April day. With most jobs prevalent in the area, moving out was not an option for her husband who was a construction worker, she says. Pointing to the dark fumes emanating from units of the Chandrapur Super Thermal Power Station (CSTPS) in the Durgapur slum where she lives, she adds, “We cannot see a clear sky, it is always blurred above.”

CSTPS, Maharashtra’s biggest coal power plant with a capacity of 2920MW, is owned by the state-run Maharashtra State Power Generation Company (MAHAGENCO). It accounts for a quarter of the state’s total power needs, one of the most industrialised and urbanised in India. Since its inception in 1983, CSTPS has commissioned nine units of which two are no longer in use.

Since the time he was in his late 30s, Gukulbai’s late husband “would cough all the time, relentlessly” she said. Despite several years of seeking treatment at the local hospital, “he never recovered”, she said, finally dying eight years ago at the age of 50.

According to a February 2022 report by the Centre for Research Clean Energy and Air, an independent research organisation in Helsinki, Finland, that focuses on air pollution, 1,300 people have died prematurely in 2020 (PDF) alone across Maharashtra and neighbouring states because of air pollution from this power plant as pollutants from the tall stacks travel as far as 1,000km (620 miles). About 800,000 people called in sick in and around the state that same year.

Just within Chandrapur and the adjoining city Nagpur, 157 people died prematurely and 64,000 people took sick leave, says Sunil Dahiya, a CREA  researcher and co-author of the report.

Last month MAHAGENCO served a defamation notice to CREA researchers over the report, questioning their methodology and results. CREA is yet to respond to the notice, it said.

Gokulbai Sahai, whose husband died of air pollution, standing in front of a gov't clinic in Maharashtra, India
Gokulbai Sahai (pictured) blames pollution from the local coal-fired power plant for her husband’s death [File: Varsha Torgalkar/Al Jazeera]

High levels of pollution

To tackle the perennial pollution, Chandrapur resident Madhusudan Roongta filed in October 2017 a petition before the Nagpur Bench of Bombay High Court, alleging that the CSTPS was violating the environmental norms laid by the Ministry of Environment, Forest and Climate Change (MoEFCC). The case was transferred to the National Green Tribunal (NGT), India’s court for environment-related cases, which set up a committee to study pollution caused by CSTPS.

The committee found that of the plant’s five units, the emission of sulphur dioxide (SO2) from two units was more than 1,067mg/NM3, close to double the standard of 600mg/Nm3 prescribed by MoEFCC. The other three units emit SO2 five times higher than the standard limit. Besides, the sulphur content in coal used for power generation is higher at 0.58 percent than the subscribed standard of 0.50 percent. SO2 affects the respiratory system, especially the lungs, and increases the risk of asthma and chronic bronchitis.

It also found that CSTPS had not installed a scrubber system, known as flue gas desulphurisation (FGD), which removes the toxic sulphur from its emissions, despite a 2015 government order to do so within two years.

The report further pointed out that the fly ash that was also being spewed by the coal plant, contained SO2, carbon monoxide (CO), and nitrous oxide (N2O), all of which cause respiratory problems, including pneumonia, bronchitis, asthma, stroke, and cough.

Two CSTPS units that are among the biggest contributors to these pollutants are within the city limits, points out Rajesh Bele, a local social activist. Trucks carrying coal to these units also travel through the city and do not bother to cover their cargo, allowing dust from the coal to permeate the air.

Moreover, the thermal power plant discharges its water without filtering out the fly ash – what is left after the coal is burned – polluting the area’s groundwater, added Bele.

Under Indian law, all thermal power plants have to ensure that the fly ash is fully used up. CSTPS is currently not using it 100 percent, and has received multiple extensions on the deadline to do so. As a result, the ambient air quality has exceeded the National Ambient Air Quality Standard (NAAQS) limit of PM10 (inhalable particulate matter with diameters 10 micrometres or less), according to the report.

Based on the committee’s report, NGT ordered CSTPS to carry out a survey to determine if the pollution from the plant was affecting the health of the people living around the coal plant, install sulfur scrubbers and treat the fly ash. If it failed to do so by the given deadline, it would face a penalty of 50 million rupees ($645,266). The power company responded by going to the Supreme Court which has since halted the NGT’s orders while the matter is being debated in the court.

INTERACTIVE- polluted cities

Deteriorating health

Dr Gopal Mundhada, a local paediatrician who runs a non-profit organisation called Save Chandrapur Committee that works to reduce air pollution, among other causes, said the number of people with asthma, and other respiratory diseases like bronchitis, skin allergies, eye allergies, pneumonia, has “doubled” in the last 15 years. “Many babies die prematurely [and] 50 percent of the babies below five years old have asthma,” he told Al Jazeera.

In November, his organisation surveyed more than 450 people and found that three-fourths had asthma, skin problems, and eye problems, all said to be on account of air pollution. He is now worried about how the COVID-19 disease is affecting the area’s residents with their respiratory systems already weakened.

“Research needs to be done whether the number of deaths due to COVID, that affects the lungs, are more in the city as people might have weaker lung capacity due to breathing polluted air for years,” said Dr Mundhada.

Some of the emissions can be reduced and lives can be saved if the government shuts down two of the plant’s older, and most polluting, units, says CREA’s Dahiya. For the rest, it would help to install the FGD scrubbers, a step that can save economic damages of 16.5 billion rupees ($222.9m) a year with fewer people taking sick leave, as per the report.

A MAHAGENCO official who declined to be identified as he was not authorised to speak to the media said CSTPS was planning to install the FGD scrubbers by 2023 and will dispose of its fly ash residue 100 percent by 2025.

But with years of delays – orders to dispose of the fly ash were given in 2009 while orders to install FGDs were first issued in 2015 – “how serious is [the environment ministry] to reduce pollution”, asks Suresh Chopane, an environmental activist in Chandrapur.

The years of delays have affected locals like Ramkrishna Yadav, a 58-year-old labourer who has been working in Chandrapur for the past 34 years and developed asthma about 10 years ago, he says. Despite daily medicines for it, the cough does not stop. “Earlier [my cough] would become intense only in the winter. Nowadays, I always cough,” he told Al Jazeera.

And at least once a year he has to be admitted to a hospital to treat it, including in November last year when he was slapped with a 60,000 rupees ($806) bill. “I cannot work all days of a month nowadays” because of the persistent cough, Yadav says.

“Air in Chandrapur is polluted as compared to other places … Whenever I stay more than four-five days at my native village in Uttar Pradesh, my cough gets reduced. I feel fresh. Once my sons start earning, my wife and I will move to my village,” he said.

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The Oscillating Positive Expiratory Pressure (OPEP) Devices market studied is anticipated to grow with a CAGR of nearly 5.3%, during the forecast period.

Certain factors that are driving the market growth include rising prevalence of chronic pulmonary diseases and growing technological advancements.

Increased geriatric population coupled with higher incidences of chronic conditions drive the OPEP devices market growth. Increasing prevalence of chronic obstructive pulmonary disease (COPD) along with asthma is one of the major driving factors for the industry.

For instance, according to CDC (the Centres for Disease Control and Prevention), in 2018, around 9 million adults were diagnosed with chronic bronchitis which eventually leads to higher requirements for OPEP devices, thus fueling the market. All such factors are likely to drive the growth of the global market.

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Key Market Trends

COPD and Asthma Hold Significant Share in the Global Oscillating Positive Expiratory Pressure (OPEP) Devices Market

Asthma is refered to a chronic respiratory disease which blocks the airways of lung because of mucus production, inflammation, and tightening of muscles. Similarly, Chronic Obstructive Pulmonary Disease(COPD) is caused by the blockade in the airways further resulting in difficulty in breathing, owing to the primary cause as tobacco smoking.

According to the 2018 Global Asthma Report, Auckland, New Zealand, globally, asthma is ranked 16th among the leading causes of years lived with disability and 28th among the leading causes of burden of disease, as measured by disability-adjusted life years. Around 300 million people have asthma worldwide, and it is likely that by 2025 a further 100 million may be affected. There is a large geographical variation in asthma prevalence, severity, and mortality. While asthma prevalence is higher in high income countries, most asthma-related mortality occurs in low-middle income countries.

North America Dominates the Global Oscillating Positive Expiratory Pressure (OPEP) Devices Market

According to the 2019 report published by the Centers for Disease Control and Prevention (CDC), 1 in 13 people have asthma. More than 25 million Americans have asthma. This is 7.7% of adults and 8.4% of children. Asthma has been increasing since the early 1980s in all age, sex and racial groups.

According to the American Academy of Allergy Asthma and Immunology (AAAI), in 2016, approximately 8.3% of children in the United States were found to have asthma. Boys were to some extent more likely to have asthma than girls at a rate of 9.2% and 7.4%, respectively.

Asthma incidence among children increased from 8.7% in 2001 to 9.4% in 2010, and then declined to 8.3% in 2016. Although not all changes were statistically noteworthy, a similar outline was observed among the sub-demographic groups, except the Mexican/Mexican American children, among whom asthma prevalence increased from 5.1% in 2001 to 6.5% in 2016.

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Competitive Landscape

The global Oscillating Positive Expiratory Pressure (OPEP) Devices market is competitive and consists of very few major players. Companies like AirPhysio, Allergan plc., D-R Burton Healthcare, Medica Holdings, LLC., Monaghan Medical Corporation, PARI GmbH, R. Cegla GmbH & Co. KG, Smiths Medical, Inc., WyMedical Pty Ltd, among others, hold the substantial market share in the market.

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Major players in the respiratory devices and equipment (therapeutic) market are Hamilton Medical AG, Koninklijke Philips N. V, Smiths Medica, Ge Healthcare, Philips Health Care, Chart Industries, Invacare Corporation, Fisher & Paykel Healthcare Limited, Resmed, and Dragerwerk AG.

New York, May 16, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Respiratory Devices And Equipment (Therapeutic) Global Market Report 2022" - www.reportlinker.com/p06277169/?utm_source=GNW

The global respiratory devices and equipment (therapeutic) market is expected to grow from $16.33 billion in 2021 to $18.03 billion in 2022 at a compound annual growth rate (CAGR) of 10.4%. The market is expected to grow to $26.83 billion in 2026 at a compound annual growth rate (CAGR) of 10.4%.

The respiratory devices and equipment (therapeutic) market consists of sales of respiratory devices and equipment used to treat patients with acute or chronic respiratory disorders such as chronic obstructive pulmonary disease (COPD), chronic bronchitis, asthma, sleep disorders, etc.

The main products of the respiratory devices and equipment (therapeutic) market are nebulizers, humidifiers, oxygen concentrators, positive airway pressure devices, ventilators, capnographs, and gas analyzers.A nebulizer is a small machine that turns liquid medicine into a mist, sits with the machine, and breathes in by a connected mouthpiece.

The various technologies involved in the respiratory devices and equipment are HEPA filter, electrostatic filtration, microsphere separation, hollow fiber filtration, and others. The market covered in this report is segmented by end-users into home care settings and hospitals.

Asia Pacific was the largest region in the respiratory devices and equipment (therapeutic) market in 2021.Western Europe was the second-largest region in the respiratory devices and equipment (therapeutic) market.

The regions covered in this report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, and Africa.

The market for respiratory devices and equipment is expected to expand rapidly.The fact that COVID-19 is essentially a respiratory ailment has boosted the use of respiratory monitoring devices, in turn contributing to the growth of this market.

Currently, there is a huge demand for respiratory devices including ventilators, especially in developing countries. Companies across the globe are focusing on increasing the availability of ventilators, nebulizers, and other respiratory support devices for patients.

The rising prevalence of respiratory diseases such as Chronic Obstructive Pulmonary Disorder (COPD) and sleep apnea contributed to the growth of the therapeutic respiratory devices and equipment market. According to World Health Organization, one million people die due to chronic obstructive pulmonary diseases caused by smoking among the 4.9 million people who die due to tobacco consumption and 65 million people suffer from moderate to severe COPD. As per its estimates, COPD is predicted to be the third leading cause of death worldwide and potentially fatal respiratory diseases. Tuberculosis, COPD, and lung cancer will account for about one in five deaths worldwide by 2030. According to National Health Interview Survey by the Centers for Disease Control and Prevention (CDC), the number of adults with diagnosed chronic bronchitis in the USA was 9.0 million. In the USA, it is estimated that 22 million Americans suffer from sleep apnea, with 80% of the cases of moderate and severe obstructive sleep apnea undiagnosed. According to epidemiological studies presented at the Associated Professional Sleep Societies in 2019, 37% of adults in North, Central, and South America suffer from Obstructive sleep apnea (OSA). The increased prevalence of COPD and sleep apnea in the geriatric population is driving the market for therapeutic respiratory devices.

Lack of awareness regarding the usage of respiratory devices has always been a major challenge in the therapeutic respiratory device market.Outcomes for patients with chronic respiratory diseases remain poor despite the development of novel therapies.

An International Survey conducted on Noninvasive Ventilation Use for Acute Respiratory Failure in General Non-Monitored Wards in 51 countries from 5 continents revealed that 44% of the GPs and physicians reported that they had never performed spirometry to make a diagnosis of COPD and the NIV application in general wards was reported by only 66% of respondents.Limited training and human resources were the most common reasons for not using NIV in general wards.

The lack of awareness on the use of respiration devices is negatively affecting the respiratory devices and therapeutics market.

The companies in the respiratory devices and equipment therapeutic market are increasingly using AI to develop respiratory devices to treat Asthma and COPD.Artificial intelligence supports the development of innovative sensors-equipped inhalers which help patients to track their dosage intake.

These sensors are durable and consume less power and help caution the patients by noting the differences or fluctuations in respiration.These are used for both add-on and embedded inhalers.

These inhalers with sensors can track data automatically and can alert both the doctors and patients about the health condition of the patients.Also, the companies in developing devices such as AI aided imaging systems and AI aided platforms that will act as voice biomarkers.

For instance, Verbal and Healthymize, two early-stage Israeli AI health tech companies, announced a merger in 2019 to create a joint company (Vocalis Health) that will be a global leader in vocal biomarkers which develops an artificial intelligence-based platform that uses voice interaction through a call center or smart device to passively screen and monitor millions of patients that live with a range of voice-affecting diseases, like chronic respiratory or cardiac conditions or depression.

In March 2020, Masimo, a global leader in noninvasive monitoring technologies acquired NantHealth, Inc’s connected care business for an undisclosed amount.NantHealth is a provider a tablet-optimized application that sits on top of our DCX platform to provide clinicians more convenient and ubiquitous access to capture a wide array of patient vitals such as respiratory rate, blood pressure, and heart rate in addition to performing patient assessments.

This move of Masimo will leverage its capabilities with NantHealth’s solutions that can enable a more efficient patient rounding and assessment workflow by providing a near real-time stream of data from the patient’s bedside unlike periodic sampling typically entered into an EHR hours later.

The countries covered in the respiratory devices and equipment (therapeutic) market are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, and USA.
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(BPRW) Essential Oils that Help You Breathe Better

(Black PR Wire) Chronic obstructive pulmonary disease (COPD) refers to lung illnesses that make breathing challenging. It’s estimated that more than 11 million Americans have COPD. There’s no cure, but remedies can help ease symptoms, stop complications, and slow disease advancement.

Signs of COPD include shortness of breath, needing to clear your throat often, and frequent coughing. Individuals with COPD often have emphysema and chronic bronchitis

COPD can result from long-term exposure to pollutants or toxins, including the toxins found in cigarette smoke. Genetics may also play a part in developing COPD.

Primary therapies for COPD include:

  • Quitting smoking
  • Oxygen therapy
  • Drugs that widen your airway, including nebulizers and inhalers
  • Surgery

Home treatments and holistic therapies may also function to reduce your symptoms. Some research demonstrates that essential oils can treat COPD effectively when paired with traditional medical treatment.

COPD and essential oils

Research indicates essential oils may be useful in treating upper respiratory infections.

Upper respiratory infections include the common cold, sinusitis, and pharyngitis. These are acute disorders, meaning they endure for only a short period, generally a few weeks. By distinction, COPD is a chronic, lifelong condition. Nevertheless, both conditions concern inflammation of your bronchiole tubes.

Eucalyptus Oil

Eucalyptus oil has been used widely for centuries as a home remedy for respiratory conditions. Eucalyptus oil is also an anti-inflammatory and boosts your immune system. Using eucalyptus oil can kill destructive bacteria that worsen your COPD symptoms. It may also soothe your throat and chest and speed up healing.

Lavender Oil

Lavender oil is known for its calming scent and antibacterial effects.

Sweet Orange Oil

Orange oil has anti-inflammatory and anti-oxidant effects. In a study that likened a proprietary oil blend with eucalyptus oil and orange oil, orange oil demonstrated evident capabilities to help with COPD.

Bergamot Oil

Bergamot is another component of the citrus family. It’s famous for the way it smells and its ability to soothe the nervous system. Bergamot may work well to alleviate pain and soreness caused by the coughing symptoms during a COPD flare-up.

Frankincense and Myrrh

These two widespread, ancient essential oils have a long history of treating respiratory conditions. Research has shown their anti-inflammatory effects, and they have many other effects that may increase your health and help you feel better.

But what we know about how frankincense and myrrh help, particularly with symptoms of COPD, is primarily anecdotal. When other essential oils have been demonstrated to work for COPD, these two might rank lower on your list in terms of established remedies.

When to See a Physician

Individuals with COPD are at a more increased risk for other illnesses that affect their lungs, such as the flu and pneumonia. Even the common cold can put you at risk of further damaging your lung tissue. Don’t attempt to use essential oils to self-treat a COPD flare-up that stops you from breathing or results in shortness of breath. If you notice the following symptoms, you should seek out a medical professional within 24 hours: 

  • Presence of blood in your mucus
  • Green or brown mucus
  • Extreme coughing or wheezing
  • New symptoms like severe fatigue or difficulty breathing
  • Unexplained, sudden weight gain or weight loss (more than 5 pounds in a week)
  • Forgetfulness
  • Dizziness
  • Waking up short of breath
  • Swelling in your ankles or wrists

There’s no cure for COPD, but traditional treatment can be complemented by therapy with essential oils to control its symptoms. Research indicates that some essential oils can soothe symptoms, encourage healing, and boost your immune system to help prevent flare-ups for many people with COPD. You can shop for essential oils at your local pharmacy or online.

The content and opinions expressed within this press release are those of the author(s) and/or represented companies, and are not necessarily shared by Black PR Wire. The author(s) and/or represented companies are solely responsible for the facts and the accuracy of the content of this Press release. Black PR Wire reserves the right to reject a press release if, in the view of Black PR Wire, the content of the release is unsuitable for distribution.

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Alembic Pharmaceuticals announced that it has received final approval from the US Food & Drug Administration (USFDA) for its Abbreviated New Drug Application (ANDA) for Arformoterol Tartrate Inhalation Solution, 15 mcg (base)/2 ml Unit-dose Vial.

The approved ANDA is therapeutically equivalent to the reference listed drug product (RlD), Brovana Inhalation Solution, 15 mcg/2 ml, of Sunovion Pharmaceuticals Inc.

Arformoterol Tartarate Inhalation Solution is a longacting beta2-adrenergic agonist (beta2-agonist) indicated for long-term, twice daily (morning and evening) administration in the maintenance treatment of bronchoconstriction in patients with chronic obstructive pulmonary disease (COPD), including chronic bronchitis and emphysema.

This ANDA has been co-developed in partnership with Orbicular Pharmaceutical Technologies.

Arformoterol Tartrate Inhalation Solution, 15 mcg (base)/2 ml Unit-dose Vial, has an estimated market size of US$ 251 million for twelve months ending December 2021 according to IQVIA.

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Eosinophils are proinflammatory granulocytes associated with symptom severity and exacerbation frequency in asthma and chronic obstructive pulmonary disease (COPD).1–3 The degree of eosinophilia (raised eosinophils) in these obstructive lung diseases varies: while eosinophil inflammation due to allergic sensitisation has been considered characteristic of asthma, not all patients with asthma have eosinophilia.1 4 Moreover, while airway inflammation in COPD is typically mediated by neutrophils, some individuals with COPD have raised eosinophils.1 5

The production and survival of eosinophils is partly regulated by interleukin-5 (IL-5), and anti-IL5 therapies (eg, mepolizumab, reslizumab, and the anti-IL5Rα agent, benralizumab) are now licensed in many countries for the treatment of severe eosinophilic asthma.6–12 The decision to treat asthma with these drugs is currently based on blood eosinophil count, among other factors,1 since post-hoc analyses of clinical trials stratified by eosinophil levels have shown increased efficacy of mepolizumab for treating severe asthma in those with higher baseline eosinophils.2 Results from Mendelian randomisation (MR) analyses have also provided evidence for a role of eosinophils in asthma (estimated OR 1.70 (95% CI 1.53 to 1.91).13 MR analyses use genetic variants as instrumental variables (IVs) to investigate causality between exposure and outcome, and under certain assumptions may obviate problems with traditional observational epidemiology (eg, reverse causation, confounding), permitting causal inference.

In addition to asthma, blood eosinophils are associated with quantitative lung function in general populations (ie, including individuals without asthma).14 However, causality has yet to be established: an inverse relationship between eosinophils and lung health has been suggested, yet a previous MR of lung function (plus another including asthma and COPD) were of small sample size, with imprecise estimates precluding confident inference.15 16 Moreover, causality of eosinophils on other respiratory phenotypes, for example, asthma-COPD overlap (ACO), and respiratory infections are yet to be investigated. COPD is diagnosed by spirometry if the ratio of the forced expiratory volume in 1 s (FEV1) to forced vital capacity (FVC), FEV1/FVC, is <0.7, with airflow obstruction graded by predicted FEV1. Therefore, studying eosinophils as determinants of quantitative lung function is a powerful way of understanding their role in the development of fixed airflow obstruction such as in COPD.17 18 Investigating causality between eosinophils and fixed airflow obstruction is pertinent given interest in the potential use of mepolizumab in COPD9–12; evidence for causality of eosinophils in a wider range of respiratory phenotypes could suggest that anti-IL5 agents (designed to lower eosinophils) might be helpful in conditions beyond asthma.

We undertook two-sample MR analyses using summary-level genome-wide association study (GWAS) data to assess causality between eosinophils and conditions encompassing fixed and reversible airflow obstruction, using genetic variants associated with blood eosinophils as IVs.13 We investigated causality of eosinophils on three quantitative lung function spirometry traits, and four clinical phenotypes (moderate-to-severe asthma, acute exacerbations of COPD (AECOPD), ACO and respiratory infections). We used MR approaches relying on different assumptions for validity, and followed up traits showing evidence of possible causality to assess evidence that the IVs affected lung function via eosinophil counts and not via other blood cell types. Overall, our aim was to provide a comprehensive assessment of the causal role of blood eosinophil counts in relation to respiratory health and disease.


We assessed causality between eosinophils and other blood cell counts in relation to respiratory outcomes using MR.19 20 MR involves using genetic variants (here single-nucleotide polymorphisms, SNPs), as IVs for an exposure of interest, in this case eosinophil counts, by comparing the magnitude of the effect of the SNPs on the outcome to the effect of the SNPs on the exposure.19 20 All analyses reported are two-sample MR analyses, since SNP–exposure and SNP–outcome associations were extracted from different (yet overlapping21) samples. Core MR assumptions for inferring causality between are that: (1) the genetic variants are associated with the exposure of interest; (2) there are no unmeasured confounders of the associations between genetic variants and outcome; and (3) the genetic variants affect the outcome only via the exposure of interest (figure 1).19 Additional assumptions for accurate point estimation of effect sizes are discussed in online supplemental file 1, and elsewhere.22

Figure 1
Figure 1

Mendelian randomisation (MR): core assumptions Mendelian randomisation may be used to test for causality between an exposure (eg, eosinophils) and outcome (eg, a respiratory outcome such as FEV1/FVC), if the following core assumptions hold (see 1–3 on the figure): (1) the genetic variation (single nucleotide polymorphisms in this work) used as instrumental variables are associated with the exposure of interest; the genetic variants are not associated with unobserved confounders of the exposure-outcome association (straight dashed arrow). Genetic variants are allocated randomly at conception (Mendel’s law of independent assortment) and so typically should not be associated with these confounding variables; association between the genetic variants and the outcome is via the exposure, and not via an alternate pathway (ie, there is no ‘horizontal pleiotropy’, see curved dashed arrow). While difficult to verify, reassurance that this assumption holds can be provided using biological knowledge of how the SNP functions, and by checking whether multiple MR methods, each relying on different assumptions for validity, give consistent results (known as triangulation).20 FEV1, forced expiratory volume in 1 s, FVC, forced vital capacity; SNP, single-nucleotide polymorphisms.

All GWAS datasets analysed included UK Biobank, a prospective cohort study including spirometry, biological assays, questionnaire data, and linked healthcare records, and 450 000 participants with genotype data.23 Other studies were incorporated where available, and all GWAS data were from individuals of European ancestry. Datasets are summarised below, and descriptions of covariate adjustments, and exposure-outcome GWAS overlap are given in the extended methods (online supplemental file 1).

Exposure GWAS data sets (blood cell parameters)

We used summary-level data from eight published GWASs of blood cell counts13 in the initial release of UK Biobank genetic data (N up to 132,959, that is, around 30% of participants with genotype data), plus the INTERVAL study (N up to 40 521)).13 GWASs were of blood eosinophils, basophils, neutrophils, monocytes, lymphocytes, platelets, red blood cells and reticulocytes, with adjustments for technical and seasonal covariates, plus age, menopausal status, height, weight, smoking and alcohol (online supplemental file 1).

Outcome GWAS data sets (respiratory outcomes)

See also online supplemental file 1.

Quantitative lung function GWASs

We used published summary-level data from three GWAS of FEV1, FVC and FEV1/FVC, in UK Biobank (n=3 21 047) and the SpiroMeta consortium (n=79 055).18 Prior to GWAS, traits were preadjusted for age, age2, sex, height, smoking status and other covariates as appropriate, for example, ancestry principal components. Residuals were inverse-normal rank transformed.

Clinical outcome GWAS

Moderate-to-severe asthma

We used a published GWAS of moderate-to-severe asthma within the Genetics of Asthma Severity and Phenotypes initiative, the U-BIOPRED asthma cohort, and UK Biobank.24 Cases (n=5135) were taking asthma medication, and met criteria for moderate-to-severe asthma (British Thoracic Society 2014 guidelines). Controls (n=25 675) excluded those with a doctor diagnosis of asthma, rhinitis, eczema, allergy, emphysema, or chronic bronchitis, or missing medication data. Analyses were adjusted for 10 ancestry principal components.

Acute exacerbations of COPD

We defined AECOPD in UK Biobank; the eligible sample was restricted to individuals with FEV1/FVC<0.7. Exacerbation cases (n=2771) had an ICD-10 code for AECOPD or a lower respiratory tract infection in Hospital Episode Statistics data (online supplemental table 1). Controls (n=42 052) had FEV1/FVC<0.7, without an AECOPD code. Associations were adjusted for age (at recruitment), age2, sex, smoking status (ever/never), genotyping array and 10 principal components.

Asthma-COPD overlap

We defined ACO in UK Biobank (N=8068) as individuals self-reporting a doctor diagnosis of asthma, with FEV1/FVC<0.7 and FEV1 <80% predicted at any study visit. Controls (N=40 360) were selected in approximately a 5:1 ratio, from participants reporting no asthma or COPD, (FEV1 >80% predicted, FEV1/FVC>0.7). Associations were adjusted for age (at recruitment), sex, smoking status and 10 principal components.25

Respiratory infections

We defined respiratory tract infections requiring hospital admission in UK Biobank, using the ICD-10 codes in online supplemental table 2. Cases had ≥1 admission for respiratory infections (N=19 459). Controls had no admissions for respiratory infections and were selected in approximately a 5:1 ratio (N=101 438). Associations were adjusted for age (at recruitment), age2, sex, smoking status, genotyping array, and 10 principal components.26

Statistical methods

Univariable MR of eosinophils and respiratory traits and diseases

We performed separate MR analyses of eosinophils on three quantitative lung function traits (FEV1, FVC, FEV1/FVC); and four clinical phenotypes (asthma, AECOPD, ACO, respiratory infections) using genetic IVs from the work of Astle and colleagues.13 Selection of 151 eosinophil IVs and harmonisation of SNP-exposure and SNP-outcome datasets is detailed in the online supplemental file 1. The primary MR analysis used the inverse-variance weighted (IVW) method and a random-effects model, which will return a valid causal estimate provided that the average pleiotropic effect is zero. We investigated the ‘no pleiotropy’ assumption using MR-Egger regression,27 the weighted median estimator28 and MR-PRESSO29 (see online supplemental file 1 for details on assumptions relied on for validity by each method). Further sensitivity analyses: (1) investigated robustness of findings to heterogeneity using MR-PRESSO (for traits with some evidence of causation by eosinophils), (2) restricted to non-UKB FEV1/FVC GWAS data, to assess sensitivity to sample overlap and (3) restricted to FEV1/FVC GWAS data in UKB, stratifying by asthma status.

Multivariable MR analyses of multiple blood cell types and respiratory outcomes

Since SNPs affecting eosinophils also affect other blood cell types,13 we used multivariable MR to estimate the influence of multiple cell types on respiratory outcomes, after conditioning on the effects of the SNPs on other cell types. Multivariable MR analyses were performed for respiratory outcomes with evidence of eosinophil causation in the IVW MR analyses above, and with broadly consistent effect estimates in the weighted median and MR-Egger analyses. We also performed an analysis of FEV1/FVC in UKB (stratifying by asthma status).

There were 1166 SNPs associated with at least one of eight blood traits reported by Astle and colleagues13 at a genome-wide threshold. These SNPs were LD clumped, and effect sizes extracted from each blood cell GWAS, and each outcome GWAS. Effects for 318 clumped SNPs were harmonised, that is, so effect sizes for SNP-exposure and SNP-outcome effects corresponded to the same allele (online supplemental table 3, online supplemental file 1). Conditional F-statistics were estimated using the strength_mvmr() function of the ‘MVMR’ R package.30

For IVW multivariable MR analyses, we used the mv_multiple() function of the ‘TwoSampleMR’ R package.31–33 This analysis aimed to further investigate the possibility of horizontal pleiotropy affecting the results of the univariable eosinophil MR; and to establish whether other blood cell types besides eosinophils could affect the respiratory outcomes studied.

Sensitivity MVMR methods (online supplemental file 1) included: (1) use of an MVMR method more robust to pleiotropy in the presence of weak instruments (using the qhet_mvmr() function of the ‘MVMR’ R package,30—standard errors calculated by a jack-knife approach) and (2) recalculation of IVW MVMR estimates after removal of SNPs contributing most to heterogeneity (SNPs identified using the pleiotropy_mvmr() function).


Univariable MR analyses of eosinophils and respiratory outcomes

There were 151 SNPs available for the univariable MR analyses of three quantitative traits (FEV1, FVC and FEV1/FVC), and four respiratory disease phenotypes (moderate-to-severe asthma, AECOPD, ACO and respiratory infections). Details of SNP selection are described in figure 2.

Figure 2
Figure 2

Selection of SNPs for univariable MR analyses of eosinophils and respiratory outcomes flow chart describing the analysis workflow for initial MR analyses of eosinophils. Of 209 SNPs associated with eosinophil count, 167 were available in lung function GWASs (missingness is due to some SpiroMeta studies not being imputed to the HRC panel).18 LD proxies at R2 >0.8 were retrieved for 24/42 missing variants. Of the resulting 191 SNPs, 188 were successfully harmonised between the SNP-eosinophil and SNP-lung function data sets, and 151* remained after LD clumping at an R2 threshold of 0.01. These 151 SNPs were used in analyses. *One SNP, rs9974367, was missing in the moderate-severe asthma GWAS. AECOPD, acute exacerbation of COPD; ACO, asthma COPD overlap; COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume in 1 s, FVC, forced vital capacity; GWAS, genome-wide association study; MR, Mendelian randomisation; SNPs, single-nucleotide polymorphisms.

Results are presented in figure 2. Among the quantitative traits, there was evidence for an effect of eosinophils on FEV1/FVC (SD change in FEV1/FVC per SD eosinophils, IVW estimate=−0.049 (95% CI −0.079 to–0.020)), with a smaller effect on FEV1 (IVW estimate=−0.028 (95% CI −0.054 to –0.003)). However, there was substantial heterogeneity of SNP-specific causal estimates, as evidenced by the large values of Cochran’s Q statistic, suggesting that core MR assumptions were violated for at least some SNPs. Scatterplots of SNP-outcome against SNP-exposure effects are given in online supplemental figure 1).

Among the respiratory disease phenotypes (figure 3), there was evidence for an effect of eosinophils on asthma (OR per SD eosinophil count, IVW method=2.46 (95% CI 1.98 to 3.06)), and ACO (IVW OR=1.86 (95% CI 1.52 to 2.27)). There was substantial heterogeneity of SNP-specific causal estimates for these two traits, and weighted median estimates were of smaller magnitude than IVW estimates (weighted median OR: 1.50 (95% CI 1.23 to 1.83) for asthma, and 1.44 (95% CI 1.19 to 1.74) for ACO). While confidence intervals for the MR Egger estimates were still broad, estimates were generally similar to weighted median estimates. The asthma estimates in particular may have been inflated by overlap between the SNP-exposure and SNP-outcome datasets (see online supplemental file 1). Scatterplots of SNP-outcome against SNP-exposure effects for these outcomes are given in online supplemental figure 2.

Figure 3
Figure 3

MR analyses of eosinophils (exposure) on three quantitative lung function traits (top) and four respiratory disease phenotypes (bottom), using 151 eosinophil-associated SNPs top: results of MR analyses of eosinophil counts (exposure) on three quantitative lung function traits (outcome), FEV1, FVC and FEV1/FVC. A forest plot of three estimates for each traits is shown (IVW, MR Egger, weighted median), along with the maximum sample size in the outcome GWAS (N), the effect size in SD change in outcome trait per SD increase eosinophil count, and 95% CI, values for Cochran’s Q statistic (Q) and the associated df (Q_df), and the p value for the MR Egger intercept (Intercept_P). Boxes of the forest plot represent effect sizes, whiskers are 95% CIs. Bottom: results of MR analyses of eosinophil counts (exposure) on four respiratory disease phenotypes (outcome), moderate-to-severe asthma, acute exacerbations of COPD (AECOPD), asthma-COPD overlap (ACO), and respiratory infection (Resp. IX). A forest plot of three estimates for each traits is shown (IVW, MR Egger, weighted median), along with sample size in the outcome GWAS for cases and controls, respectively (N), the effect size as OR per SD eosinophil count, and 95% CI, values for Cochran’s Q statistic (Q) and the associated df (Q_df), and the p value for the Mr Egger intercept (Intercept_P). Boxes of the forest plot represent ORs, whiskers are 95% CIs. Nb only 150/151 of the eosinophil SNPs were available in the moderate-to-severe asthma GWAS. COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume in 1 s, FVC, forced vital capacity; GWAS, genome-wide association study; IVW, inverse-variance weighted; MR, Mendelian randomisation; SNPs, single-nucleotide polymorphisms.

There was no evidence of association of eosinophils with AECOPD or respiratory infections. CIs for all three MR methods included the null, and point estimates approached the null. See online supplemental table 4 for results for all models and all traits.

Sensitivity analysis to assess further the robustness of findings to heterogeneity, using MR-PRESSO

For FEV1, FEV1/FVC, ACO and asthma (traits showing strongest evidence of causation), we used MR-PRESSO to identify possible pleiotropic outliers (online supplemental table 5). Results were qualitatively similar to IVW estimates (higher eosinophils consistent with respiratory morbidity), but ACO and asthma effect estimates attenuated after MR-PRESSO outlier correction; MR-PRESSO estimates were most similar to weighted median causal estimates.

Sensitivity analysis to assess the effects of sample overlap for quantitative lung function traits

UK Biobank featured in all GWAS datasets used, although the blood cell count GWAS and asthma GWAS included only approximately one third of the UK Biobank genotype data.13 We conducted sensitivity analyses to assess for the effect of sample overlap, since we had access to quantitative lung function GWAS data without UK Biobank participants (see online supplemental file 1). Results were generally consistent (SD change in FEV1/FVC per SD eosinophil count, IVW estimate=−0.041 (95% CI −0.072 to –0.009); SD change FEV1 per SD eosinophil count=−0.043 (95% CI −0.077 to –0.010)) (online supplemental table 6).

Sensitivity analysis to assess the effect on FEV1/FVC in individuals with and without asthma

The causal effect of eosinophils on FEV1/FVC was recalculated using data from UK Biobank, stratifying by asthma status (37 868 cases, 283 179 controls). The effect size was larger in individuals with asthma (IVW −0.083 (95% CI −0.139 to –0.028)) than in those without asthma, in whom there was no effect (IVW −0.013 (95% CI −0.041 to 0.015)). However, confidence intervals for both subgroups overlapped one another (see online supplemental table 7).

Multivariable MR analyses of blood cell counts and respiratory outcomes

To further explore causality between blood cell parameters and FEV1, FEV1/FVC, moderate-to-severe asthma and ACO, and to see if other exposures could have accounted for the heterogeneity observed in the previous analyses, we carried out multivariable MR analyses, using eight cell type exposures (eosinophils, basophils, neutrophils, monocytes, lymphocytes, platelets, red blood cells and reticulocytes).

Selection of 318 SNP IVs for multivariable MR is described in online supplemental file 1, online supplemental table 3. SNPs used in the univariable and multivariable MR are listed in online supplemental tables 8 and 9. Briefly, 1166 unique SNPs were associated with at least one of the eight cell types at a genome-wide level in the cell type GWAS, and were available in outcome GWAS. After LD-clumping, 329 SNPs remained, and after harmonising SNP-exposure and SNP-outcome effects, 318 remained (see online supplemental table 3) for conditional F statistics, which were all F>10, except for basophils (Fconditional=8).

Multivariable MR results for FEV1 and FEV1/FVC are presented in figure 4. Even after conditioning on the effects of the SNPs on other cell types, the average effect of the eosinophil-lowering IVs was to reduce lung function as measured by FEV1/FVC (multivariable estimate, SD change in FEV1/FVC per SD eosinophils adjusted for other cell types: −0.065 (95% CI −0.104 to –0.026)). The eosinophil point estimate for FEV1 (−0.032 (95% CI −0.068 to 0.005)) was consistent with the univariable estimate (figure 3), but CIs for all cell types were consistent with the null. When asthma cases were excluded from SNP-FEV1/FVC results, the eosinophil estimate attenuated, and confidence intervals overlapped the null (−0.028 (95% CI −0.069 to 0.013)), consistent with the causal effect of eosinophils on lung function being of greater magnitude in people with a history of asthma (online supplemental figure 3).

Figure 4
Figure 4

Multivariable MR analyses of eight cell types and forced expiratory volume in 1 s (FEV1) and FEV1/forced vital capacity (FVC) forest plot showing multivariable MR estimating the causal effect of multiple cell types on quantitative lung function outcomes, after conditioning on the effects of the SNPs on other cell types. Models were run for each of FEV1 and the ratio of FEV1 to FVC separately, but effect sizes are shown next to one another for comparison. Effect sizes (beta, 95% CI) are in SD change in lung function outcome per SD cell count (adjusted for the effects of other cell types). Points of the forest plot represent effect size estimate; whiskers are 95% CIs. MR, Mendelian randomisation.

Results of the multivariable MR analysis for ACO and asthma are presented in figure 5. There was an association of eosinophil count with both ACO (OR 1.95 (95% CI 1.57 to 2.42)) and asthma (OR 2.90 (95% CI 2.31 to 3.65)), after adjusting for the effects of the SNPs on other cell types. Confidence intervals for other cell type estimates were consistent with the null, with the exception of neutrophils for ACO. None of the additional seven cell types showed strong evidence of causality.

Figure 5
Figure 5

Multivariable MR analyses of eight cell types and two respiratory disease outcomes, ACO and asthma forest plot showing multivariable MR estimating the causal effect of multiple cell types on respiratory disease outcomes, after conditioning on the effects of the SNPs on other cell types. Models were run for each of ACO and asthma separately, but effect sizes are shown next to one another for comparison. ORs (95% CI) are per SD cell count (adjusted for the effects of other cell types). Points of the forest plot represent ORs; whiskers are 95% CIs. ACO, asthma-COPD overlap; MR, Mendelian randomisation; SNP, single-nucleotide polymorphisms.

Sensitivity multivariable MR analyses

Sensitivity MVMR analyses (1) used an estimation technique more robust to balanced pleiotropy and (2) repeated IVW MVMR, omitting SNP IVs with the most evidence of heterogeneity. Effect directions of sensitivity analyses and the main MVMR analyses were concordant for FEV1, FEV1/FVC, ACO, and asthma. However, CIs for FEV1 and FEV1/FVC were broad, and overlapped the null. For ACO and asthma estimates, there was still evidence of an effect, although attenuated in both analyses (estimates from analysis more robust to pleiotropy; ACO OR 1.57 (95% CI 1.07 to 2.30); asthma OR 2.66 (95% CI 1.65 to 4.33); estimates after omitting the most heterogeneous SNPs: ACO OR 1.51 (95% CI 1.23 to 1.85); asthma OR 2.29 (95% CI 1.84 to 2.86)).


In MR analyses, we found that the average effect of raising eosinophils was to decrease FEV1/FVC and FEV1, and to increase ACO and asthma risk, and there was broad consistency across MR methods. However, causal estimates of individual variants were highly heterogeneous, suggesting that caution is needed in concluding causal inference: some IVs may have violated MR assumptions, and other important genetically correlated mechanisms could be responsible for the effect on lung health and disease by the eosinophil-raising variants studied.

To our knowledge, this is the largest MR of eosinophils and lung function, and the first to investigate eosinophils and AECOPD, ACO and respiratory infections. Terminology of ACO has changed over time, yet recognition that asthma and COPD coexist in some patients has not changed,34 and this is what our analysis aimed to capture.

A previous two-sample MR of eosinophils and asthma was undertaken by the authors of the GWAS that discovered the eosinophil IVs used; this MR analysis used asthma GWAS data from the GABRIEL study.13 We are aware of one other small MR of eosinophils and asthma, COPD, FEV1 and FEV1/FVC, conducted in the LifeLines cohort (N=13 301, 5 SNPs IVs).15 In that study, CIs for causal estimates of eosinophils overlapped the null, although point estimates were consistent with a harmful effect for FEV1/FVC, asthma and COPD. We used a larger eosinophil GWAS (N=172 275)13 to derive IVs, and found that the average effect of eosinophil-raising IVs was to reduce FEV1/FVC, the trait used in COPD diagnosis and FEV1, used to grade COPD airflow limitation. However, sensitivity analyses highlighted a larger causal estimate of eosinophils on FEV1/FVC among those with asthma, with effect estimates attenuating when excluding this group. These findings may highlight the importance of eosinophils as a marker of impaired lung function and airflow obstruction in people with a history of asthma.

We highlight a need for caution in inferring simple causation between eosinophils and these phenotypes, since high degrees of heterogeneity in our results may arise from pleiotropy. To investigate, we compared MR methods relying on differing assumptions for validity (Methods section). Attenuation of some results when using the MR-Egger, weighted median, and MR-PRESSO approaches suggests that some SNP IVs are associated with asthma and ACO via pathways other than eosinophils, which is a known challenge in MR studies (see also Methods section).

Since many of the eosinophil SNP IVs are also associated with other cell counts,13 we performed multivariable MR to estimate the influence of multiple cell types simultaneously, after conditioning on the effects of the SNPs on other cell types. While we did not find substantial evidence for a harmful effect of neutrophils on asthma, nor a protective effect of monocytes and lymphocytes, as reported previously,13 effect directions in our IVW multivariable MR were consistent with the previous study for neutrophils, monocytes and lymphocytes. We observed a larger effect of eosinophils on asthma than reported previously: this could be because our SNP-outcome dataset was of moderate-to-severe asthma (which has a higher point estimate of genetic correlation with eosinophils), but also, around half of the cases and the majority of controls were also included in the exposure GWAS, which may make this analysis closer to a one-sample MR, and inflate causal effect estimates. Notably, effect sizes partly attenuated in sensitivity analyses which may be more robust to heterogeneity. The MR estimates from multivariable analyses, and the MR-Egger regression and weighted median univariable analyses were consistent with the previous estimate reported for asthma in multivariable analysis by Astle et al.13 Nevertheless, these limitations may preclude precise estimation of effect sizes, and our results may be more useful in terms of assessing whether there is causality between eosinophils and the phenotypes studied, as opposed to providing estimates of the magnitude of any causal effect between phenotypes.

While we did not find strong evidence for causality of eosinophils on AECOPD and respiratory infections, point estimates were consistent with a harmful effect on AECOPD, and may have been limited by power. The effects of anti-IL5 drugs that have been attributed to the reduction of eosinophils have been noted to be smaller in AECOPD compared with asthma.2 35

Key strengths are that we used MR methods with differing sensitivities to underlying assumptions. We a large GWAS of eosinophil counts, to provide a comprehensive assessment of the role of blood eosinophils in relation to multiple respiratory health and disease outcomes. Another strength is that we undertook multivariable MR to investigate causality between multiple cell types and the outcomes studied, while controlling for the effects of IVs that may have had pleiotropic effects via other cell types.

We acknowledge several limitations. We did not have post-bronchodilator measures of spirometry. We used GOLD Stage 2–4 COPD (prebronchodilator FEV1 <80% predicted) when defining ACO; using the same prebronchodilator spirometry definition of COPD, a positive predictive value of 98% for diagnosis of postbronchodilation-defined COPD has been shown.36 Sample overlap between the SNP-eosinophil and SNP-outcome datasets (all included participants from UK Biobank) could bias estimates towards the observational eosinophil-outcome association21; we repeated the univariable MR analysis of eosinophils using SNP-lung function results excluding UK Biobank participants, and observed a consistent IVW estimate. Nevertheless, our other analyses (particularly the asthma analysis) could be vulnerable to some non-conservative bias.19 21 GWAS analyses of cell counts have, since analysis, been extended to a larger sample across UKB, and future work deriving IVs from this study would be valuable.37 UK BiLEVE participants (a subset of UK Biobank selected for extremes of respiratory traits), were overrepresented in Astle et al, which used the interim release of UKB data. While correlation between effect sizes from the two GWAS for the 151 IVs used in this analyses were high, the possibility of selection effects remains. Our MR analyses also use genome-wide results adjusted for covariates, and therefore may be susceptible to collider bias.19 38 There is also potential bias in the causal estimates for binary outcomes due to non-collapsibility of the OR,22 and we did not consider the possibility of non-linear effects. The multivariable analyses may still be vulnerable to pleiotropy via pathways other than the eight cell types studied, so while we cannot strongly assert causality of eosinophils on lung function, neither do we rule it out, as our results are consistent with a causal effect.

At present, treatment with anti-IL5/anti-IL5Rα agents in asthma is initiated according to eosinophil counts and other factors,8 yet it is possible that a more proximal factor may be an even better predictor of drug response. Future work could seek therefore to identify whether particular pathways upstream of eosinophil counts might help design better methods for deciding on treatment initiation. In addition, use of suitable IVs for IL5 levels would permit two-step MR analyses, assessing for a mediating effect of eosinophils on the action of anti-IL5 agents in reducing respiratory morbidity.

To conclude, using MR, we found that the average effect of raising eosinophils was to increase risk of ACO and asthma, and to reduce FEV1/FVC (the latter association was only prominent in individuals with asthma). Broad consistency across MR methods is suggestive of a causal effect of eosinophils on asthma overall, and in individuals with features of both asthma and fixed airflow obstruction, although of uncertain magnitude. However, given heterogeneity in results derived from individual IVs, which may indicate violation of MR assumptions, we highlight a need for caution, since alternative mechanisms may be responsible for the impairment of respiratory health by these eosinophil-raising variants. These results could suggest that anti-IL5 agents (designed to lower eosinophils) may be of value in a wider range of respiratory traits, including people with features of both asthma and COPD. Future work should seek to explore other potential mechanisms besides eosinophils by which anti-IL5 agents may improve respiratory health.

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Asthma is a heterogeneous chronic inflammatory disease of the airways characterized by airway hyper-responsiveness, bronchoconstriction, and airway remodeling. Asthma affects over 260 million people worldwide and was responsible for over 21 million Disability-adjusted Life Years (DALYs) in 2019,1 representing significant morbidity and economic burden. The prevalence of asthma is highest in countries with the highest socio-demographic index (SDI); however, death rates are highest in countries with low–middle SDI.1

Table 1 Overview of Integrins Involved in Asthmatic Airway Remodeling

The symptoms of asthma include wheezing, shortness of breath, chest tightness, and cough that fluctuate in frequency and intensity, as well as variable expiratory airflow restriction.2 Treatment includes targeting bronchoconstriction through the use of β2 adrenergic agonists, or some cases muscarinic receptor antagonists, and reducing airway inflammation via inhaled or oral corticosteroids. Such an approach is sufficient to control symptoms in most patients, however, some patients suffer from difficult-to-treat asthma, with uncontrolled symptoms despite good adherence to treatment. Severe asthma, defined as uncontrolled symptoms despite treatment with highest doses of inhaled corticosteroids in combination with an additional controller medication (eg, long-acting β2 agonist), affects approximately 5–10% of patients and is associated with frequent and uncontrolled exacerbations, and a long-term decrease in lung function.3–5

Remodeling of the airways contributes to airway wall thickening and has a detrimental effect on asthma. It is associated with accelerated decline in lung function, an increased rate of exacerbation in asthmatic patients, and irreversible airflow obstruction.6–8 Thickening of the airways is not limited to patients suffering from the severest forms of the disease and can be evident even in mild forms of asthma; however, the degree of thickening is associated with increased disease severity and degree of airflow obstruction.9,10 Airway remodeling is thought to play a vital role in the uncontrolled symptoms and disease burden observed in severe asthmatics. Over recent years many studies have implicated a family of cell surface receptors known as integrins in the development and progression of airway remodeling. This review aims to bring together our current knowledge of how integrins may either drive or inhibit airway remodeling in asthma, and discuss the potential utility of targeting integrins as a therapeutic strategy in severe asthma.

Airway Remodeling in Asthma

Airway remodeling is the collective term given to the structural changes that occur within the asthmatic airway. These changes include sub-epithelial fibrosis, thickening of the airway smooth muscle (ASM) layer, mucous gland hyperplasia, angiogenesis, and loss of epithelial layer integrity, all of which contribute to a thickened and stiffened airway wall. The development of airway remodeling begins early in the disease course, with structural changes being evident in preschool children with clinically confirmed wheeze, even prior to an asthma diagnosis.11–13

The underlying mechanisms driving the development of airway remodeling are largely unclear and likely to be extremely complex and multifaceted. While for many years airway remodeling was thought to result from the presence of chronic inflammation within the asthmatic airway, this has more recently been questioned. Structural changes in the airways of preschool wheezers do not correlate with inflammatory cell counts in bronchoalveolar lavage fluid.11 It is possible that different features of airway remodeling differ in the underlying mechanisms driving them. The following section will discuss the potential mechanisms responsible for the development and progression of airway remodeling in asthma.

Potential Mechanisms Driving Airway Remodeling

Airway inflammation has long been thought to drive the development of asthmatic airway remodeling. Asthma is largely driven by TH2 inflammation associated with interleukin-4 (IL4), interleukin-5 (IL5), and interleukin-13 (IL13), and TH2 inflammation remains a crucial target in asthma therapy development. However, a cluster analysis of asthmatic patients has suggested that patients with fixed airflow obstruction and evident airway remodeling have predominantly TH17 rather than TH2 driven inflammation.14

Further evidence of a link between inflammation and airway remodeling comes from in vivo and in silico models of asthma. A theoretical model of airway remodeling demonstrates that inflammation is sufficient to promote thickening of the airway wall towards the lumen, although increased thickening occurs when biomechanical contractile forces and inflammation are modeled simultaneously,15 suggesting interplay of multiple pathways. Additionally, numerous mouse models have highlighted a potential link between inflammation and remodeling. For example, Interleukin-33 (IL33) can exacerbate allergen-induced inflammation and remodeling in a mouse model,16 and M2 macrophages, which IL33 promotes polarization towards,17,18 has been associated with allergen-induced remodeling in mice.19

From the studies described above it is clear that the mechanistic link between airway inflammation and airway remodeling is still ambiguous. The fact that remodeling occurs very early in the disease course, including in young children with wheeze prior to a diagnosis of asthma,11–13 suggests that chronic inflammation may not be the sole driver of airway remodeling.

An alternative possibility is that the mechanical environment of the asthmatic airway drives remodeling changes. This was initially suggested in 2011 when Grainge et al20 demonstrated remodeling changes in response to bronchoconstriction in the absence of additional inflammation. Mechanistically, contraction of ASM cells and airways causes activation of the pro-remodeling cytokine TGFβ and downstream remodeling changes.21–23 Moreover, pharmacological inhibition of transient receptor potential vanilloid-1 (TRPV1), which can modulate ASM tone, reduces airway remodeling in vivo.24,25 Mathematical modeling has also suggested that airway contraction contributes to remodeling.15

In addition to contractile mechanical forces promoting airway remodeling it is also possible that non-contractile biomechanical forces contribute.26 ECM proteins within the asthmatic airway wall can promote proliferation of ASM cells27 and drive remodeling changes in vivo.28 Additionally, altered mechanics due to a stiffer airway wall may drive remodeling changes. Increased matrix stiffness promotes epithelial–mesenchymal transition,29 collagen production by fibroblasts,30 and ASM cell proliferation,31 all of which may contribute to airway remodelling. Recently, a link between matrix crosslinking, which stiffens ECM, and the development of asthmatic airway remodeling has been described whereby the matrix crosslinking enzyme lysyl oxidase-like-2 (LOXL2) has been implicated.32 Crucially, LOXL2 levels were increased in asthmatic ASM cells and pharmacological inhibition of LOXL2 in vivo reduced allergen-induced airway remodeling.32


Integrins are heterodimeric transmembrane receptors that facilitate cell–cell and cell–matrix interactions. They provide a direct link between the environment outside of the cell and the cytoskeleton within the cell, and involved in the transmission of biomechanical signals. The family is composed of 24 mammalian members, made up by a variety of combinations of alpha (α) and a beta (β) subunit; there are eight distinct β subunits and 18 distinct α subunits.33 The α subunit is responsible for the ligand binding properties of integrins, while the downstream intracellular signaling events are co-ordinated by the β subunit. Some integrins can bind to only one type of ligand, while other integrins are able to recognize several ECM proteins.

Integrins can mediate bi-directional signals through the cell membrane; inside-out signalling regulates extracellular binding activity of integrins and thereby switching into active conformation. On the other hand, binding of ECM proteins on integrins activate signals that are transmitted into the cells known as outside-in signaling.33 These signaling events modulate roles in cell attachment, survival, proliferation, leukocyte trafficking, cell differentiation, cytoskeleton organization, cell migration, gene expression, tumorigenicity, and intracellular pH.

Integrins combine with multiple proteins to form integrin adhesion complexes (IAC), also known as the integrin adhesome, to activate downstream signaling pathways. To date the literature suggests such complexes involve at least 232 distinct integrin-associated proteins (IAP),34 including talin, paxillin, kindlins, filamin, vinculin, integrin-linked kinase (ILK), focal adhesion kinase (FAK), Src family protein tyrosine kinases (SFK), and GTPases of the Rho family. Such complexes can be split into four compartments: the ECM, the integrin, IAPs, and the actin cytoskeleton.34 The wide-ranging and diverse functions of just 24 distinct integrins are largely dependent on the complexity and diversity of IACs.

Several integrins are expressed within the lung and have roles in lung development, including branching morphogenesis, epithelial cell polarization, and differentiation.35,36 Expression of integrins varies across lung cell types and at varying times of development. Within the airway epithelium eight integrins are expressed, namely α2β1, α3β1, α5β1, α6β4, α9β1, αvβ5, αvβ6, and αvβ8.36–38 In some cases, integrin subunit expression in the epithelium is dramatically increased during inflammation or repair, most notably for the epithelially-restricted integrin αvβ6.37,39–41 Within the lung mesenchymal cells expression of α5β1, αvβ3, α2β1, α4β1, α5β1, αvβ5, and α7β5 have all been reported.22,42,43 Lung inflammatory cells also express integrin receptors; macrophages express β2 integrins, α4β1 and α5β1,44,45 and T lymphocytes are known to express α4β1, α5β1, αEβ7 and β2 integrins.42 Eosinophils, which have an important role in the pathophysiology of asthma, have a distinctive combination of eight integrins, α4β1, α6β1, αLβ2, αDβ2, αMβ2, αXβ2, and α4β7.46,47

The known function of integrins and integrin adhesomes make them attractive candidates for understanding how mechanical cues, including contractile forces and matrix stiffening, might influence airway remodeling processes. Furthermore, integrins are well-known for regulating leukocyte and inflammatory cell trafficking, which could also have important implications for asthma development and progression and for airway remodeling. The following section will discuss the role of integrin superfamily members in mediating specific airway remodeling processes in a variety of lung cells important to asthma pathogenesis. We have summarised how specific integrin heterodimers might be involved in asthmatic airway remodeling process in Table 1 and Figure 1.

Epithelial Changes in Airway Remodeling

The epithelial layer serves as a physical barrier to the exterior environment. As a result, it is the lungs’ first line of defence against foreign bodies inhaled during breathing. In addition, the healthy airway epithelium modulates immune responses and promotes the expulsion of inhaled particles through mucous production and cilia movement. The asthmatic airway epithelium undergoes dramatic phenotypic changes resulting in loss of epithelial integrity through epithelial shedding and increased mucous production via mucous gland hyperplasia.

Loss of airway epithelium is a well-documented phenomenon in asthma48–51 and is linked with airway hyper-reactivity.48,50 Loss of epithelial integrity occurs early in the disease course,49 and is thought to result from cellular apoptosis, senescence, and ineffective repair mechanisms.52,53 The asthmatic airway epithelium expresses markers of cellular injury/repair including increased epidermal growth factor receptor (EGFR),54,55 transforming growth factor β (TGFβ),56,57 and decreased E-cadherin.58 Furthermore, apoptosis and proliferative pathways are altered.59

Senescence of the epithelium occurs in asthma53 and may promote asthma development by compromising epithelial integrity and barrier function. Moreover, epithelial cell senescence drives thymic stromal lymphopoietin (TSLP)-induced airway remodeling.53 Crucially, airway epithelial senescence can be driven by a deficiency in integrin β4 expression in a P53 dependent manner,60 and the asthmatic human bronchial airway epithelium has reduced integrin β4 expression.61 In the ovalbumin mouse model of asthma, integrin β4 expression is reduced on the airway epithelium and is associated with structural disruption of the epithelial layer.62 Together, these studies in human asthmatic patients and animal models of asthma suggest a crucial role for β4 integrins in maintaining epithelial integrity in the airway.

In addition to loss of epithelial integrity, the asthmatic airway produces excessive quantities of mucous. MUC5AC and MUC5B are polymeric mucins that are significantly increased in the asthmatic airway and MUC5AC levels correlate with clinical measures of asthma including fractional exhaled nitric oxide (FeNO), sputum eosinophils, and airway hyper-responsiveness.63 A key driver of increased mucous production is goblet cell hyperplasia, which is evident in mild through to severe asthma.64,65 Additionally, mucous over-production can be driven by paracrine interactions with underlying airway smooth muscle cells.66 Overall, mucous gland hyperplasia and excessive mucus production can lead to mucous plugging of the airway, reduced airway lumen area, and airflow obstruction.67 Integrins have been implicated in mucous overproduction and goblet cell hyperplasia. β1 integrins have recently been shown to regulate cellular and secreted MUC5AC and MUC5B production in lung epithelial cells.68,69 Conversely, interactions between Mfge8 and integrin β3 subunits protect against allergen induced airway remodeling changes, including goblet cell hyperplasia.70

Increased Airway Smooth Muscle Mass (ASM)

Thickening of the airway smooth muscle (ASM) layer is a common and prominent feature of asthmatic airway remodeling. In the healthy airway, ASM cells are thought to play an important role in modulating respiratory airway tone. During disease processes, however, they have an important role in inflammatory and remodeling processes, releasing chemokines, pro-inflammatory and/or pro-fibrotic cytokines, and ECM proteins,22,26,71–73 which contributes to asthma pathogenesis.

In the asthmatic airway increased ASM mass appears to be driven by both increased myocyte size (hypertrophy) and increased myocyte number (hyperplasia), which are in turn associated with disease duration and severity.74 Some studies have suggested that the increase is due to hyperplasia rather than hypertrophy75 and others have suggested that hyperplasia only occurs in cases of fatal asthma.76 The causes of increased ASM mass in asthma are likely to be multifaceted. Interactions between ASM cells and airway epithelial cells can promote increased ASM cell proliferation and production of inflammatory cytokines and chemokines,77 suggesting a role for paracrine signaling between the two cell types. Furthermore, interactions between ASM cells and CD4+ T lymphocytes, known to be crucial to the pathogenesis of asthma, can increase ASM cell proliferation.78 Numerous ASM cell mitogens have been implicated in asthma, including Platelet derived growth factor (PDGF),79 TGFβ80 epidermal growth factor (EGF),78 heparin-binding EGF,81 and vascular endothelial growth factor (VEGF).82 In certain cases, such as PDGF,83 these mitogens can also promote ASM cell migration, which may contribute to the thickening of the ASM layer and expansion of the airway wall. Regardless of the underlying mechanism, during an asthma exacerbation, the thickened ASM bundle contributes to the airway-constricting capacity of the muscle84 and is thought to contribute to fixed airflow obstruction in severe asthma.

Several integrins have been linked with the contractile function of ASM cells. The fibronectin binding α5β1 integrins are involved in ASM cell contraction; functional blockade of α5β1 interrupts the function of focal adhesions, reduces interleukin-13 (IL13)-induced contraction of tracheal rings and inhibits airway hyper-responsiveness in vivo.85 Crucially, pharmacological inhibition of α5β1 had no effect on baseline tone of the smooth muscle rings and only reduced contraction in response to asthma-relevant contractile agonists, making it a potentially attractive approach for therapeutic targeting in asthma as the homeostatic functions of ASM could be preserved.85 A similar role has recently been identified for α2β1 integrins in regulating IL13-induced contraction, in this case through interrupting ASM cell tethering to collagen I and laminin-111.86

Contraction of ASM cells occurs via force transmission through polymerization and reorganization of the actin cytoskeleton. The cytoplasmic tail of β integrins binds to actin filaments through “linker” proteins such as vinculin, talin, and α-actinin, whereas the extracellular component of integrins interacts with the extracellular matrix to tether the cell.87 Force transmission between the cell and the extracellular matrix is therefore delivered by the actin–integrin–matrix complex. Actin filament polymerization and myosin activation are two concurrent biochemical mechanisms that are critical for smooth muscle contraction homeostasis, however, inhibiting actin polymerization limits smooth muscle force generation with minimal impact on myosin light chain phosphorylation.88–90 Crucially, actin-regulatory proteins are involved in regulating proliferation of smooth muscle cells,91 demonstrating how force transmission through integrins may influence cell proliferation and remodeling. Finally, TGFβ, which can be activated by ASM cells via integrins in response to reorganization of the actin cytoskeleton,22 augments ASM cell contraction in a RhoA-independent manner.92 This suggests a perpetual feedback loop whereby bronchoconstriction causes integrin-mediated TGFβ activation to promote airway remodeling, which in turn increases the contractility of the ASM cells and contributes to fixed airflow obstruction by increasing the baseline tone of the ASM layer.

In addition to promoting cell contractility through interactions with actin, integrin superfamily members are also involved in negative regulation of ASM contraction. Ligation of α8β1 integrins on ASM cells by milk fat globule-EGF factor-8 (Mfge8) proteins prevents IL13-induced ASM contraction.93 α9β1 integrins are also capable of negatively regulating ASM contraction. Loss of, or inhibition of, α9β1 integrins in mice increases airway contraction.94 These studies all highlight the importance of ASM cell interactions with matrix proteins through cell surface integrins to regulate ASM contraction and airway narrowing. As discussed previously, uncontrolled bronchoconstriction can promote airway remodeling via integrin-mediated activation of the pro-remodeling cytokine TGFβ.21–23 Taken together, it is clear that integrins have a potentially crucial role in regulating both pathological ASM contraction and downstream pro-remodeling effects, representing a direct link between uncontrolled asthma symptoms and the development of airway remodeling through a mechanobiological mechanism.

In addition to effects on ASM contraction, integrins expressed by ASM cells may also promote migration and proliferation of ASM cells, which is thought to contribute to thickening of the ASM layer and airway lumen narrowing in airway remodeling.95 Global blockade of RGD-binding integrins with a synthetic RGDS peptide attenuates allergen-induced ASM hyperplasia and hypercontractility, suggesting a crucial role for this subset of integrins in ASM remodeling.96 β1 integrins are highly expressed in ASM cells plus other mesenchymal cells in the lung, including myofibroblasts, and have recently been shown to localize key adaptor proteins at the leading edge of migrating ASM cells.97 Additionally, β1 integrins have been implicated in pro-proliferative responses of ASM cells to increasing matrix stiffness.31 α2β1, α4β1, and α5β1 have all been shown to regulate ASM cell proliferation.98 The matrix protein fibulin-5 has been implicated in this process through binding to β1 integrins to promote ASM cell proliferation via the mechanosensing YAP/TAZ pathway.99 Furthermore, laminin binding to α7β1 integrins promotes ASM cell survival and differentiation to a contractile phenotype.100 All together these studies support an important role of β1 integrins in regulating increased ASM mass in asthmatic airway remodeling.

Subepithelial Fibrosis

Subepithelial fibrosis in the asthmatic airway occurs in the lamina reticularis, just below the basement membrane, where ECM proteins such as interstitial collagens, fibronectin, tenascin, and proteoglycan accumulate.101 Subepithelial fibrosis is linked to asthma severity; collagen expression in the airway wall is higher in patients with moderate or severe asthma compared with those with mild disease,57 and the degree of subepithelial fibrosis is inversely correlated with FEV1.102 Increased deposition and decreased degradation of extracellular matrix (ECM) proteins is one of the major hallmarks of fibrosis regardless of organ or tissue type, and is primarily controlled by fibroblasts and myofibroblasts. Within the asthmatic airway, the number of myofibroblasts present correlates with the amount of collagens and tenascin detected in the subepithelial region.102 Furthermore, fibrocytes, which can differentiate into myofibroblasts, are increased in asthma and may contribute to subepithelial fibrosis.103

Information relating to a direct role for integrins in regulating matrix deposition in asthma is limited. In vitro studies have shown that treatment of ASM cells with the pro-remodeling cytokine TGFβ leads to increased fibronectin deposition via an α5β1 mediated mechanism involving ERK signaling.104 Additionally, in murine models it has been reported that interleukin-32 (IL32) reduces allergen-induced fibrosis via suppression of the integrin-FAK-paxillin signaling axis.105

Transforming growth factor-β (TGFβ) is thought to be a key driver of subepithelial fibrosis in asthma. TGFB1 mRNA is increased in bronchial biopsies from asthmatic individuals and levels correlate with the degree of subepithelial fibrosis.106 Furthermore, all three isoforms of TGFβ are increased in the asthmatic airway.56,57,107–109 TGFβ causes transdifferentiation of airway fibroblasts into highly synthetic, matrix producing myofibroblasts110,111 and increases production of matrix proteins by fibroblasts/myofibroblasts.112,113 Crucial evidence from murine animal models shows that inhibition of both TGFβ1 and 2 with isoform-specific function blocking antibodies reduced allergen-induced subepithelial collagen deposition,114 and intra-tracheal instillation of TGFβ1 is sufficient to cause subepithelial fibrosis.115 Finally, there is recent evidence suggesting that human bronchial fibroblast responses to TGFβ are altered in asthma, with pro-fibrotic responses being increased while anti-fibrotic responses are decreased.116 Together, these studies highlight a crucial role for TGFβ in regulating subepithelial fibrosis in asthma.

αvβ8 integrins are capable of activating TGFβ via recruitment of matrix metalloproteinases, which proteolytically cleave the latent TGFβ complex on the cell surface.117 Proteolytic cleavage of TGFβ has been previously reported,71,118 however, αvβ8 is the only integrin described thus far that mediates TGFβ activation via proteolysis. Importantly, expression of αvβ8 integrins is increased in asthma119 and expression of MMP-9 and MMP-8 in the airway inversely correlate with FEV1.120,121 Other cell types are capable of activating TGFβ via integrins including myofibroblasts, lung epithelial cells, and ASM cells.22,122–124 This raises the possibility that integrin-mediated TGFβ contributes to matrix deposition in the asthmatic airway, although this remains to be definitively proved.

Integrins have been implicated in inflammatory cell-mediated mechanisms of airway remodeling. Inhibiting RGD-binding integrins peptide on eosinophils using an RGDS blocks their ability to bind to ASM cells and interrupts the eosinophil-induced increased in ECM gene expression.125,126 Despite these studies it has been shown that a blockade of RGD-binding integrins, again using a synthetic RGDS peptide, reduces markers of ASM remodeling in vivo but has no effect on airway fibrosis, suggesting that this subset of integrins does not mediate subepithelial fibrosis.96 Finally a limited study has shown that collagen deposition in the asthmatic airway is inversely correlated with expression of α2 subunits on blood and CD4+ cells.


Angiogenesis refers to the process of forming new blood vessels. Increased vascularity of the asthmatic airway is a common observation and is evident in newly diagnosed asthma patients.127–129 The implications of increased vascularity on the pathogenesis of asthma and airway remodeling are still somewhat unclear. Correlations between increased vascularity and decreased lung function in asthma are inconsistent, with some reports finding a correlation128 and others reporting no link.127 Furthermore, animal models have shown that reducing angiogenesis experimentally using the inhibitor of angiogenesis, tumstatin, does not improve lung function.130 Although a link between increased vascularity and decreased lung function in asthma is still unclear, angiogenesis within the asthmatic airway wall enhances inflammatory cell recruitment and can cause edema, which may contribute to asthma pathogenesis.129

VEGF is one of the most potent activators of endothelial cell growth and promotes vascular permeability. VEGF levels in bronchial biopsies, serum, and bronchoalveolar lavage fluid are increased in asthma,131–133 and VEGF expression within airway cells correlates with the number of vessels.134 ASM cells isolated from asthmatics can drive angiogenesis via increased VEGF secretion.135 Crucially, pharmacological inhibition of VEGF signaling has shown promise in experimental models of asthma by reducing expression of growth factors, improving epithelial barrier function,136,137 and reducing markers of airway remodeling.138

Integrins have long been implicated in angiogenic processes, with the earliest descriptions demonstrating links between αvβ3 and αvβ5 and angiogenesis.139,140 Single nucleotide polymorphisms (SNPs) within the ITGB3 gene are associated with asthma pathogenesis.141 Additionally, pharmacological inhibition of αvβ3 prevents blood vessel maturation.142 However, genetic knockout of either β3 or β5 subunits does not alter vascular development.143,144

Genetic knockdown of integrin subunits has highlighted some potentially important roles in angiogenesis during development, which may also be important in disease. For example, genetic loss of integrin α5, which binds to fibronectin, leads to vascular defects and mice that are embryonic lethal, similar to the fibronectin knockout animals.145 This suggests a crucial role of α5 integrins and fibronectin in early angiogenesis. However a separate study found that inhibiting α5β1 with a small molecule inhibitor alpha5beta1 Integrin blockade inhibits lymphangiogenesis in airway inflammation and interrupts lymphatic vessel development without affecting blood vessel development.146 Finally, an important role for endothelial cell α2β1 integrin in promoting lumen formation in new capillaries has been described.147

Integrins in Airway Remodeling: Inflammation

Chronic airway inflammation is a hallmark of asthma and, as has been discussed previously in this article, has the potential to influence pro-remodeling pathways. Several integrins including α2β1, α5β1, αvβ3, and αvβ1 have been linked with increased cytokine release when ASM cells are cultured on collagen and fibronectin, suggesting that an altered mechanical environment may influence the inflammatory environment within the airway wall.148

Eosinophils are thought to be important to the pathogenesis of asthma and they express numerous integrins. Integrins have a key role in mediating migration of eosinophils from the blood into the lung, where they accumulate in asthma.149 Integrins, particularly β2 integrins such as αmβ2 and α4 integrins, have been implicated in eosinophil degranulation and inflammatory mediator release.150–152 In addition, α4 integrin binding to its ligand fibronectin via Fas antigen signaling increases the eosinophil survival, which may contribute to airway eosinophilia in asthma.153

Airway neutrophilia is associated with increased asthma severity and asthma that is refractory to corticosteroids, the backbone of asthma treatment.154 There is a paucity of research focused directly upon a potential role for integrins in driving airway neutrophilia in asthma; however, integrins, particularly β2 integrins, are well known to regulate neutrophil recruitment to sites of inflammation.155,156 Furthermore, neutrophils and their products have been implicated in lung fibrogenesis in other chronic lung diseases such as interstitial lung disease (ILD). For example αMβ2 integrins can regulate neutrophil extracellular trap (NET) formation in ILD,157 and secretory leukocyte protease inhibitor (SLPI), which inhibits neutrophil elastase, has differential effects on collagen expression in mouse lung tissue.158 Previous work has shown that integrin expression by sputum neutrophils in asthmatic patients is aberrant compared with healthy controls,159 however, whether such changes in integrin expression affect the overall activity of neutrophils in asthma and the impact this has on airway remodeling is yet to be elucidated.

Exposure to allergens causes an increase in TH2 cell infiltration and TH2 cytokine expression in asthmatic patients. TH2 cells co-ordinate allergy-induced asthmatic inflammatory responses through Th2 cytokines (IL-4 and IL-5), causing eosinophil infiltration and hyper-responsiveness of the airways.160 Airway epithelial cells, by acting as antigen presentation cells (APCs), can cause T-cell activation and proliferation, and silencing β4 integrins in asthmatic airway epithelial cells impairs their antigen presentation capacity and decreases T-cell proliferation.161 This is one possible integrin-dependent mechanism that may contribute to TH2 inflammation bias in asthmatic airways.

Therapeutic Targeting of Integrins to Impact Airway Remodeling

To date no drug has been developed that specifically targets the development and progression of airway remodeling. Corticosteroids, which are the mainstay of asthma treatment and primarily target airway inflammation, can reduce several markers of airway remodeling, including ASM proliferation,162 TGFβ expression in fibroblasts,163 and VEGF expression by epithelial cells,164 and can reconstitute epithelial structure.165 Despite these effects, airway remodeling persists in asthmatic patients despite long-term treatment with inhaled or oral corticosteroids, suggesting there is no overwhelming impact of corticosteroids on airway remodeling in asthmatic patients.

In recent years several new biological therapies have been developed and approved, particularly for the treatment of severe asthma, some of which have shown some effects on airway remodeling. Mepolizumab, a clinically approved anti-IL5 monoclonal antibody, has been shown to reduce airway wall thickness in CT scans166 and reduce matrix protein deposition in bronchial biopsies.167 Benralizumab is another monoclonal antibody that targets IL5 signaling, which computational modeling has suggested reduces ASM mass and the number of tissue myofibroblasts present in the airway wall.168 Omalizumab targets IgE for the treatment of allergic asthma and has been shown to reduce airway wall thickness when measured by computed tomography.169 Research into the effects of other new monoclonal antibody therapies such as dupilumab (anti-Il4 receptor) and reslizumab (anti-Il5) are yet to be published, however, the former studies suggest that inhibiting TH2 inflammation may reduce asthmatic airway remodeling in severe asthma patients. Whether such treatments can sufficiently reduce airway remodeling to lead to long-term positive effects on fixed airflow obstruction or slow the decline in lung function seen in asthmatics, which is thought to be driven by airway remodeling, is likely to be the focus of ongoing studies into the utility of biological therapies. Another key question that remains to be answered is whether therapeutic treatment of airway remodeling will be sufficient or whether prophylactic treatment much earlier in the disease course will be required for the biggest clinical benefit.

Research Dilemmas in Airway Remodeling

As discussed above, airway remodeling is a complex and diverse collection of structural changes involving many tissues and cell types. Despite the introduction of various new therapies for asthma in recent years including various biological treatments targeting airway inflammation, there has yet to be an effective treatment for airway remodeling. This is potentially a result of the many specific challenges associated with researching the underlying mechanisms driving airway remodeling, which were highlighted in detail in an American Thoracic Society statement in 2017,170 and which will be discussed briefly here.

Lack of Appropriate Animal Models

A major hindrance to research investigating airway remodeling and asthma pathogenesis more widely is the lack of an appropriate animal model. Mice are the most commonly used species for in vivo models of asthma and airway remodeling, however, rats, guinea pigs, and larger species including pigs, sheep, and horses are also used.171

A significant drawback to animal models of asthma is that asthma is a human disease that does not spontaneously occur within the animal kingdom, with the exception of eosinophilic bronchitis in cats and heaves in horses, both of which are obstructive airway diseases with some similarities to asthma. Animal models are therefore largely dependent upon sensitizing animals experimentally to an allergen and then delivering that allergen to the airways to elicit an allergic inflammatory response.171 Such models are advantageous when studying how allergy and/or inflammation drive features of asthma; however, as discussed above, the relative roles of these processes in driving airway remodeling is still largely unclear and so using such models to drive airway remodeling in animals may not accurately reflect the pathogenesis driving remodeling in man.

Size and anatomical differences between human lungs and the species used for models of asthma and airway remodeling also have the potential to negatively impact the utility of findings from such models. For example the human lung has a vastly greater number of branching airways compared with mouse lungs, the effect of which on the development of remodeling is unclear with our insufficient understanding of the mechanisms driving remodeling.170 Recent methodological advances in assessing airway remodeling in airways of various sizes in murine models of asthma172 may aid our understanding of the heterogeneic nature of remodeling, albeit within the confines of a rodent disease model discussed above.

Lack of Uniformity in Core Experimental and Technological Design

Aside from species differences, the ability to compare results across studies is further complicated by methodologies used to assess airway remodeling. Airway remodeling is often quantified across large- and medium-sized airways by measuring airway wall thickness; however, bronchioles and other smaller bronchi, because of their diverse components and structures, may have different impacts on the evolution of airway remodeling. Even at the cellular level, distinct morphological, synthetic, and epigenetic differences between lung compartments exist, as has been described for fibroblasts isolated from airways compared with distal lung regions.173,174 Existing whole-organ/whole-body imaging modalities do not have enough resolution to distinguish particular cell types and can only assess various degrees of wall thickness.170

Quantifying airway remodeling in human airways largely depends upon measuring indices within airway biopsy samples, or imaging modalities such as high-resolution computed tomography (HR-CT), both of which can predict fixed airflow obstruction in asthmatic patients.7,175 These techniques present challenges when attempting to study the longitudinal development and slow progression of airway remodeling in asthma patients due to either their invasive nature (biopsy) or high radiation exposure and cost (HR-CT). Several studies have suggested potential biomarkers of airway remodeling including TGFβ and periostin,176 galectin-3,177 hyaluronan,178 however, they have yet to be widely validated, which restricts their utility in clinical research. It is clear that both mechanistic studies of airway remodeling and clinical trials testing potential interventions that target airway remodeling remain incredibly difficult due to a lack of consensus on which AR index to use, cost effectiveness, safety, ability to make repeated measurements, plus sensitivity and specificity of measurement.

Concluding Remarks

As our understanding of the underlying mechanisms driving airway remodeling in asthma improves, so does our knowledge of how cell surface integrins play a critical role in the development and progression of airway remodeling. There is still much that we do not fully understand including the relative importance of mechanical and inflammatory cues to the development of airway remodeling. However, what is clear from research in recent years is that integrins may be involved in multiple aspects of airway remodeling across all lung cells types (see Figure 1). In the years to come, therapeutic targeting of airway remodeling may improve morbidity and lung function in patients with severe, uncontrolled asthma. With the advent of biological therapies in recent years we have begun to observe some positive effects on features of airway remodeling in the most severe asthmatics. Questions remain, however, about whether these effects are sufficient to produce long-term and long lasting impacts on airway remodeling that would improve fixed airflow obstruction and slow the decline in lung function that is observed in asthma. While the effects of some biologics on airway remodeling are encouraging we believe targeting airway remodeling specifically, rather than as a bi-product of targeting inflammatory pathways, will lead to the biggest clinical improvement in airway remodeling in the years to come. Such targeting could include approaches to target integrin mediated pathways since we have hopefully demonstrated in this review that integrins are integral to many pathways involved in airway remodeling pathogenesis. Targeting integrins directly to impact airway remodeling could be a useful adjunct to existing therapies that target airway inflammation to enable both fundamental features of asthma to be treated simultaneously.

Figure 1 Schematic diagram giving an overview of how different integrin heterodimers expressed by a variety of lung cell types may contribute to the development and/or progression of airway remodeling in asthma. Both environmental and cellular stimuli converge upon integrin signaling pathways in a variety of cell types to contribute to airway hyper-responsiveness and ASM thickening, mucous over-production, subepithelial fibrosis, new blood vessel formation, and airway inflammation.


Amanda Tatler reports grants from Medical research foundation, Asthma UK, and Biogen during the conduct of the study and personal fees from Pliant therapeutics outside the submitted work. The authors report no other potential conflicts of interest for this work.


1. Vos T, Lim SS, Abbafati C, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1204–1222. doi:10.1016/S0140-6736(20)30925-9

2. Hough KP, Curtiss ML, Blain TJ, et al. Airway remodeling in asthma. Front Med. 2020;7:191. doi:10.3389/fmed.2020.00191

3. O’Byrne PM, Pedersen S, Lamm CJ, et al. Severe exacerbations and decline in lung function in asthma. Am J Respir Crit Care Med. 2009;179:19–24. doi:10.1164/rccm.200807-1126OC

4. Sorkness RL, Bleecker ER, Busse WW, et al. Lung function in adults with stable but severe asthma: air trapping and incomplete reversal of obstruction with bronchodilation. J Appl Physiol. 2008;104:394–403. doi:10.1152/japplphysiol.00329.2007

5. Ortega H, Yancey SW, Keene ON, et al. Asthma exacerbations associated with lung function decline in patients with severe eosinophilic asthma. J Allergy Clin Immunol Pract. 2018;6:980–986 e981. doi:10.1016/j.jaip.2017.12.019

6. Krings JG, Goss CW, Lew D, et al. Quantitative CT metrics are associated with longitudinal lung function decline and future asthma exacerbations: results from SARP-3. J Allergy Clin Immunol. 2021;148:752–762. doi:10.1016/j.jaci.2021.01.029

7. Kasahara K, Shiba K, Ozawa T, Okuda K, Adachi M. Correlation between the bronchial subepithelial layer and whole airway wall thickness in patients with asthma. Thorax. 2002;57:242–246. doi:10.1136/thorax.57.3.242

8. Kozlik P, Zuk J, Bartyzel S, et al. The relationship of airway structural changes to blood and bronchoalveolar lavage biomarkers, and lung function abnormalities in asthma. Clin Exp Allergy. 2020;50:15–28. doi:10.1111/cea.13501

9. Niimi A, Matsumoto H, Amitani R, et al. Airway wall thickness in asthma assessed by computed tomography. Relation to clinical indices. Am J Respir Crit Care Med. 2000;162:1518–1523. doi:10.1164/ajrccm.162.4.9909044

10. Aysola RS, Hoffman EA, Gierada D, et al. Airway remodeling measured by multidetector CT is increased in severe asthma and correlates with pathology. Chest. 2008;134:1183–1191. doi:10.1378/chest.07-2779

11. Lezmi G, Gosset P, Deschildre A, et al. Airway remodeling in preschool children with severe recurrent wheeze. Am J Respir Crit Care Med. 2015;192:164–171. doi:10.1164/rccm.201411-1958OC

12. Saglani S, Payne DN, Zhu J, et al. Early detection of airway wall remodeling and eosinophilic inflammation in preschool wheezers. Am J Respir Crit Care Med. 2007;176:858–864. doi:10.1164/rccm.200702-212OC

13. O’Reilly R, Ullmann N, Irving S, et al. Increased airway smooth muscle in preschool wheezers who have asthma at school age. J Allergy Clin Immunol. 2013;131:1024–1032, 1032 e1021-1016. doi:10.1016/j.jaci.2012.08.044

14. Ye WJ, Xu W-G, Guo X-J, et al. Differences in airway remodeling and airway inflammation among moderate-severe asthma clinical phenotypes. J Thorac Dis. 2017;9:2904–2914. doi:10.21037/jtd.2017.08.01

15. Hill MR, Philp CJ, Billington CK, et al. A theoretical model of inflammation- and mechanotransduction-driven asthmatic airway remodelling. Biomech Model Mechanobiol. 2018;17:1451–1470. doi:10.1007/s10237-018-1037-4

16. Sjoberg LC, Nilsson AZ, Lei Y, et al. Interleukin 33 exacerbates antigen driven airway hyperresponsiveness, inflammation and remodeling in a mouse model of asthma. Sci Rep. 2017;7:4219. doi:10.1038/s41598-017-03674-0

17. John AE, Wilson MR, Habgood A, et al. Loss of epithelial G q and G 11 signaling inhibits TGFβ production but promotes IL-33–mediated macrophage polarization and emphysema. Sci Signal. 2016;9:ra104. doi:10.1126/scisignal.aad5568

18. Kurowska-Stolarska M, Stolarski B, Kewin P, et al. IL-33 amplifies the polarization of alternatively activated macrophages that contribute to airway inflammation. J Immunol. 2009;183:6469–6477. doi:10.4049/jimmunol.0901575

19. Wang Q, Hong L, Chen M, et al. Targeting M2 macrophages alleviates airway inflammation and remodeling in asthmatic mice via miR-378a-3p/GRB2 pathway. Front Mol Biosci. 2021;8:717969. doi:10.3389/fmolb.2021.717969

20. Grainge CL, Lau LCK, Ward JA, et al. Effect of bronchoconstriction on airway remodeling in asthma. N Engl J Med. 2011;364:2006–2015. doi:10.1056/NEJMoa1014350

21. Oenema TA, Smit M, Smedinga L, et al. Muscarinic receptor stimulation augments TGF-beta1-induced contractile protein expression by airway smooth muscle cells. Am J Physiol. 2012;303:L589–597. doi:10.1152/ajplung.00400.2011

22. Tatler AL, John AE, Jolly L, et al. Integrin alphavbeta5-mediated TGF-beta activation by airway smooth muscle cells in asthma. J Immunol. 2011;187:6094–6107. doi:10.4049/jimmunol.1003507

23. Oenema TA, Maarsingh H, Smit M, et al. Bronchoconstriction induces TGF-beta release and airway remodelling in guinea pig lung slices. PLoS One. 2013;8:e65580. doi:10.1371/journal.pone.0065580

24. Yocum GT, Chen J, Choi CH, et al. Role of transient receptor potential vanilloid 1 in the modulation of airway smooth muscle tone and calcium handling. Am J Physiol. 2017;312:L812–L821. doi:10.1152/ajplung.00064.2017

25. Choi JY, Lee HY, Hur J, et al. TRPV1 blocking alleviates airway inflammation and remodeling in a chronic asthma murine model. Allergy Asthma Immunol Res. 2018;10:216–224. doi:10.4168/aair.2018.10.3.216

26. Noble PB, Pascoe CD, Lan B, et al. Airway smooth muscle in asthma: linking contraction and mechanotransduction to disease pathogenesis and remodelling. Pulm Pharmacol Ther. 2014;29:96–107. doi:10.1016/j.pupt.2014.07.005

27. Johnson PR, Burgess JK, Underwood PA, et al. Extracellular matrix proteins modulate asthmatic airway smooth muscle cell proliferation via an autocrine mechanism. J Allergy Clin Immunol. 2004;113:690–696. doi:10.1016/j.jaci.2003.12.312

28. Zhang C, Wang W, Liu C, Lu J, Sun K. Role of NF-kappaB/GATA3 in the inhibition of lysyl oxidase by IL-1beta in human amnion fibroblasts. Immunol Cell Biol. 2017;95:943–952. doi:10.1038/icb.2017.73

29. Brown AC, Fiore VF, Sulchek TA, Barker TH. Physical and chemical microenvironmental cues orthogonally control the degree and duration of fibrosis-associated epithelial-to-mesenchymal transitions. J Pathol. 2013;229:25–35. doi:10.1002/path.4114

30. Humphrey JD, Dufresne ER, Schwartz MA. Mechanotransduction and extracellular matrix homeostasis. Nat Rev Mol Cell Biol. 2014;15:802–812. doi:10.1038/nrm3896

31. Shkumatov A, Thompson M, Choi KM, et al. Matrix stiffness-modulated proliferation and secretory function of the airway smooth muscle cells. Am J Physiol. 2015;308:L1125–1135. doi:10.1152/ajplung.00154.2014

32. Jopeth Ramis RM, Pappalardo F, Cairns J, et al. LOXL2 mediates airway smooth muscle cell matrix stiffness and drives asthmatic airway remodelling. BioRxivs. 2020. doi:10.1101/2020.11.16.384792

33. Cox D, Brennan M, Moran N. Integrins as therapeutic targets: lessons and opportunities. Nat Rev Drug Discov. 2010;9:804–820. doi:10.1038/nrd3266

34. Green HJ, Brown NH. Integrin intracellular machinery in action. Exp Cell Res. 2019;378:226–231. doi:10.1016/j.yexcr.2019.03.011

35. Coraux C, Delplanque A, Hinnrasky J, et al. Distribution of integrins during human fetal lung development. J Histochem Cytochem. 1998;46:803–810. doi:10.1177/002215549804600703

36. Wu JE, Santoro SA. Differential expression of integrin alpha subunits supports distinct roles during lung branching morphogenesis. Dev Dyn. 1996;206:169–181. doi:10.1002/(SICI)1097-0177(199606)206:2<169::AID-AJA6>3.0.CO;2-G

37. Pilewski JM, Latoche JD, Arcasoy SM, Albelda SM. Expression of integrin cell adhesion receptors during human airway epithelial repair in vivo. Am J Physiol. 1997;273:L256–263. doi:10.1152/ajplung.1997.273.1.L256

38. Mette SA, Pilewski J, Buck CA, Albelda SM. Distribution of integrin cell adhesion receptors on normal bronchial epithelial cells and lung cancer cells in vitro and in vivo. Am J Respir Cell Mol Biol. 1993;8:562–572. doi:10.1165/ajrcmb/8.5.562

39. Tatler AL, Habgood A, Porte J, et al. Reduced Ets domain-containing protein Elk1 promotes pulmonary fibrosis via increased integrin alphavbeta6 expression. J Biol Chem. 2016;291:9540–9553. doi:10.1074/jbc.M115.692368

40. Tatler AL, Goodwin AT, Gbolahan O, et al. Amplification of TGFbeta induced ITGB6 gene transcription may promote pulmonary fibrosis. PLoS One. 2016;11:e0158047. doi:10.1371/journal.pone.0158047

41. Sheppard D, Cohen DS, Wang A, Busk M. Transforming growth factor beta differentially regulates expression of integrin subunits in Guinea pig airway epithelial cells. J Biol Chem. 1992;267:17409–17414. doi:10.1016/S0021-9258(18)41941-2

42. Teoh CM, Tan S, Tran T, et al. Integrins as therapeutic targets for respiratory diseases. Curr Mol Med. 2016;15:714–734. doi:10.2174/1566524015666150921105339

43. Roman J, Little CW, McDonald JA. Potential role of RGD-binding integrins in mammalian lung branching morphogenesis. Development. 1991;112:551–558. doi:10.1242/dev.112.2.551

44. Albert RK, Embree LJ, McFeely JE, Hickstein DD. Expression and function of beta 2 integrins on alveolar macrophages from human and nonhuman primates. Am J Respir Cell Mol Biol. 1992;7:182–189. doi:10.1165/ajrcmb/7.2.182

45. McNally AK, Anderson JM. Beta1 and beta2 integrins mediate adhesion during macrophage fusion and multinucleated foreign body giant cell formation. Am J Pathol. 2002;160:621–630. doi:10.1016/s0002-9440(10)64882-1

46. Barthel SR, Johansson MW, McNamee DM, Mosher DF. Roles of integrin activation in eosinophil function and the eosinophilic inflammation of asthma. J Leukoc Biol. 2008;83:1–12. doi:10.1189/jlb.0607344

47. Barthel SR, Annis DS, Mosher DF, Johansson MW. Differential engagement of modules 1 and 4 of vascular cell adhesion molecule-1 (CD106) by integrins alpha4beta1 (CD49d/29) and alphaMbeta2 (CD11b/18) of eosinophils. J Biol Chem. 2006;281:32175–32187. doi:10.1074/jbc.M600943200

48. Jeffery PK, Wardlaw AJ, Nelson FC, Collins JV, Kay AB. Bronchial biopsies in asthma. An ultrastructural, quantitative study and correlation with hyperreactivity. Am Rev Respir Dis. 1989;140:1745–1753. doi:10.1164/ajrccm/140.6.1745

49. Zhou C, Yin G, Liu J, Liu X, Zhao S. Epithelial apoptosis and loss in airways of children with asthma. J Asthma. 2011;48:358–365. doi:10.3109/02770903.2011.565848

50. Laitinen LA, Heino M, Laitinen A, Kava T, Haahtela T. Damage of the airway epithelium and bronchial reactivity in patients with asthma. Am Rev Respir Dis. 1985;131:599–606. doi:10.1164/arrd.1985.131.4.599

51. Faul JL, Tormey VJ, Leonard C, et al. Lung immunopathology in cases of sudden asthma death. Eur Respir J. 1997;10:301–307. doi:10.1183/09031936.97.10020301

52. Heijink IH, Kuchibhotla VN, Roffel MP, et al. Epithelial cell dysfunction, a major driver of asthma development. Allergy. 2020;75:1902–1917. doi:10.1111/all.14421

53. Wu J, Dong F, Wang R-A, et al. Central role of cellular senescence in TSLP-induced airway remodeling in asthma. PLoS One. 2013;8:e77795. doi:10.1371/journal.pone.0077795

54. Hirota N, Risse P-A, Novali M, et al. Histamine may induce airway remodeling through release of epidermal growth factor receptor ligands from bronchial epithelial cells. FASEB J. 2012;26:1704–1716. doi:10.1096/fj.11-197061

55. Puddicombe SM, Polosa R, Richter A, et al. Involvement of the epidermal growth factor receptor in epithelial repair in asthma. FASEB J. 2000;14:1362–1374. doi:10.1096/fasebj.14.10.1362

56. Brown SD, Baxter KM, Stephenson ST, et al. Airway TGF-beta1 and oxidant stress in children with severe asthma: association with airflow limitation. J Allergy Clin Immunol. 2012;129:388–396, 396 e381–388. doi:10.1016/j.jaci.2011.11.037

57. Chakir J, Shannon J, Molet S, et al. Airway remodeling-associated mediators in moderate to severe asthma: effect of steroids on TGF-beta, IL-11, IL-17, and type I and type III collagen expression. J Allergy Clin Immunol. 2003;111:1293–1298. doi:10.1067/mai.2003.1557

58. Trautmann A, Krüger K, Akdis M, et al. Apoptosis and loss of adhesion of bronchial epithelial cells in asthma. Int Arch Allergy Immunol. 2005;138:142–150. doi:10.1159/000088436

59. Cohen L, E X, Tarsi J, et al. Epithelial cell proliferation contributes to airway remodeling in severe asthma. Am J Respir Crit Care Med. 2007;176:138–145. doi:10.1164/rccm.200607-1062OC

60. Yuan L, Du X, Tang S, et al. ITGB 4 deficiency induces senescence of airway epithelial cells through p53 activation. FEBS J. 2019;286:1191–1203. doi:10.1111/febs.14749

61. Liu C, Xiang Y, Liu H, et al. Integrin beta4 was downregulated on the airway epithelia of asthma patients. Acta Biochim Biophys Sin. 2010;42:538–547. doi:10.1093/abbs/gmq058

62. Liu C, Liu H-J, Xiang Y, et al. Wound repair and anti-oxidative capacity is regulated by ITGB4 in airway epithelial cells. Mol Cell Biochem. 2010;341:259–269. doi:10.1007/s11010-010-0457-y

63. Tajiri T, Matsumoto H, Jinnai M, et al. Pathophysiological relevance of sputum MUC5AC and MUC5B levels in patients with mild asthma. Allergol Int. 2021. doi:10.1016/j.alit.2021.09.003

64. Ordonez CL, Khashayar R, Wong H, et al. Mild and moderate asthma is associated with airway goblet cell hyperplasia and abnormalities in mucin gene expression. Am J Respir Crit Care Med. 2001;163:517–523. doi:10.1164/ajrccm.163.2.2004039

65. Aikawa T, Shimura S, Sasaki H, Ebina M, Takishima T. Marked goblet cell hyperplasia with mucus accumulation in the airways of patients who died of severe acute asthma attack. Chest. 1992;101:916–921. doi:10.1378/chest.101.4.916

66. Faiz A, Weckmann M, Tasena H, et al. Profiling of healthy and asthmatic airway smooth muscle cells following interleukin-1beta treatment: a novel role for CCL20 in chronic mucus hypersecretion. Eur Respir J. 2018;52:1800310. doi:10.1183/13993003.00310-2018

67. Yoshida Y, Takaku Y, Nakamoto Y, et al. Changes in airway diameter and mucus plugs in patients with asthma exacerbation. PLoS One. 2020;15:e0229238. doi:10.1371/journal.pone.0229238

68. Iwashita J, Murata J. Integrin beta1 subunit regulates cellular and secreted MUC5AC and MUC5B production in NCI-H292 human lung epithelial cells. Biochem Biophys Rep. 2021;28:101124. doi:10.1016/j.bbrep.2021.101124

69. Iwashita J, Yamamoto T, Sasaki Y, Abe T. MUC5AC production is downregulated in NCI-H292 lung cancer cells cultured on type-IV collagen. Mol Cell Biochem. 2010;337:65–75. doi:10.1007/s11010-009-0286-z

70. Zhi Y, Huang H, Liang L. MFG-E8/integrin beta3 signaling contributes to airway inflammation response and airway remodeling in an ovalbumin-induced murine model of asthma. J Cell Biochem. 2018;119:8887–8896. doi:10.1002/jcb.27142

71. Tatler AL, Porte J, Knox A, Jenkins G, Pang L. Tryptase activates TGFbeta in human airway smooth muscle cells via direct proteolysis. Biochem Biophys Res Commun. 2008;370:239–242. doi:10.1016/j.bbrc.2008.03.064

72. John AE, Zhu YM, Brightling CE, Pang L, Knox AJ. Human airway smooth muscle cells from asthmatic individuals have CXCL8 hypersecretion due to increased NF-kappaB p65, C/ EBPbeta, and RNA polymerase II binding to the CXCL8 promoter. J Immunol. 2009;183:4682–4692. doi:10.4049/jimmunol.0803832

73. Clifford RL, Patel JK, John AE, et al. CXCL8 histone H3 acetylation is dysfunctional in airway smooth muscle in asthma: regulation by BET. Am J Physiol. 2015;308:L962–972. doi:10.1152/ajplung.00021.2015

74. Benayoun L, Druilhe A, Dombret MC, Aubier M, Pretolani M. Airway structural alterations selectively associated with severe asthma. Am J Respir Crit Care Med. 2003;167:1360–1368. doi:10.1164/rccm.200209-1030OC

75. Woodruff PG, Dolganov GM, Ferrando RE, et al. Hyperplasia of smooth muscle in mild to moderate asthma without changes in cell size or gene expression. Am J Respir Crit Care Med. 2004;169:1001–1006. doi:10.1164/rccm.200311-1529OC

76. James AL, Elliot JG, Jones RL, et al. Airway smooth muscle hypertrophy and hyperplasia in asthma. Am J Respir Crit Care Med. 2012;185:1058–1064. doi:10.1164/rccm.201110-1849OC

77. O’Sullivan MJ, Jang JH, Panariti A, et al. Airway epithelial cells drive airway smooth muscle cell phenotype switching to the proliferative and pro-inflammatory phenotype. Front Physiol. 2021;12:687654. doi:10.3389/fphys.2021.687654

78. Al Heialy S, Risse P-A, Zeroual MA, et al. T cell-induced airway smooth muscle cell proliferation via the epidermal growth factor receptor. Am J Respir Cell Mol Biol. 2013;49:563–570. doi:10.1165/rcmb.2012-0356OC

79. Hirota JA, Ask K, Farkas L, et al. In vivo role of platelet-derived growth factor–BB in airway smooth muscle proliferation in mouse lung. Am J Respir Cell Mol Biol. 2011;45:566–572. doi:10.1165/rcmb.2010-0277OC

80. Pan Y, Liu L, Li S, et al. Activation of AMPK inhibits TGF-beta1-induced airway smooth muscle cells proliferation and its potential mechanisms. Sci Rep. 2018;8:3624. doi:10.1038/s41598-018-21812-0

81. Wang Q, Li H, Yao Y, et al. HB-EGF-promoted airway smooth muscle cells and their progenitor migration contribute to airway smooth muscle remodeling in asthmatic mouse. J Immunol. 2016;196:2361–2367. doi:10.4049/jimmunol.1402126

82. Kim SH, Pei Q-M, Jiang P, et al. Effect of active vitamin D3 on VEGF-induced ADAM33 expression and proliferation in human airway smooth muscle cells: implications for asthma treatment. Respir Res. 2017;18:7. doi:10.1186/s12931-016-0490-9

83. Parameswaran K, Cox G, Radford K, et al. Cysteinyl leukotrienes promote human airway smooth muscle migration. Am J Respir Crit Care Med. 2002;166:738–742. doi:10.1164/rccm.200204-291OC

84. Ijpma G, Panariti A, Lauzon AM, Martin JG. Directional preference of airway smooth muscle mass increase in human asthmatic airways. Am J Physiol. 2017;312:L845–L854. doi:10.1152/ajplung.00353.2016

85. Sundaram A, Chen C, Khalifeh-Soltani A, et al. Targeting integrin alpha5beta1 ameliorates severe airway hyperresponsiveness in experimental asthma. J Clin Invest. 2017;127:365–374. doi:10.1172/JCI88555

86. Liu S, Ngo U, Tang X-Z, et al. Integrin alpha2beta1 regulates collagen I tethering to modulate hyperresponsiveness in reactive airway disease models. J Clin Invest. 2021;131. doi:10.1172/JCI138140

87. Gunst SJ, Tang DD. The contractile apparatus and mechanical properties of airway smooth muscle. Eur Respir J. 2000;15:600–616. doi:10.1034/j.1399-3003.2000.15.29.x

88. Wang Y, Liao G, Wang R, Tang DD. Acetylation of Abelson interactor 1 at K416 regulates actin cytoskeleton and smooth muscle contraction. FASEB J. 2021;35:e21811. doi:10.1096/fj.202100415R

89. Wang T, Cleary RA, Wang R, Tang DD. Role of the adapter protein Abi1 in actin-associated signaling and smooth muscle contraction. J Biol Chem. 2013;288:20713–20722. doi:10.1074/jbc.M112.439877

90. Wang R, Cleary RA, Wang T, Li J, Tang DD. The association of cortactin with profilin-1 is critical for smooth muscle contraction. J Biol Chem. 2014;289:14157–14169. doi:10.1074/jbc.M114.548099

91. Jia L, Wang R, Tang DD. Abl regulates smooth muscle cell proliferation by modulating actin dynamics and ERK1/2 activation. Am J Physiol. 2012;302:C1026–1034. doi:10.1152/ajpcell.00373.2011

92. Ojiaku CA, Cao G, Zhu W, et al. TGF-beta1 evokes human airway smooth muscle cell shortening and hyperresponsiveness via Smad3. Am J Respir Cell Mol Biol. 2018;58:575–584. doi:10.1165/rcmb.2017-0247OC

93. Khalifeh-Soltani A, Gupta D, Ha A, Podolsky MJ. The Mfge8-alpha8beta1-PTEN pathway regulates airway smooth muscle contraction in allergic inflammation. FASEB J. 2018;fj201800109R. doi:10.1096/fj.201800109R

94. Chen C, Kudo M, Rutaganira F, et al. Integrin alpha9beta1 in airway smooth muscle suppresses exaggerated airway narrowing. J Clin Invest. 2012;122:2916–2927. doi:10.1172/JCI60387

95. Kaminska M, Foley S, Maghni K, et al. Airway remodeling in subjects with severe asthma with or without chronic persistent airflow obstruction. J Allergy Clin Immunol. 2009;124:45–51 e41–e44. doi:10.1016/j.jaci.2009.03.049

96. Dekkers BG, Bos IS, Gosens R, Halayko AJ, Zaagsma J, Meurs H. The integrin-blocking peptide RGDS inhibits airway smooth muscle remodeling in a Guinea pig model of allergic asthma. Am J Respir Crit Care Med. 2010;181:556–565. doi:10.1164/rccm.200907-1065OC

97. Wang R, Liao G, Wang Y, Tang DD. Distinctive roles of Abi1 in regulating actin-associated proteins during human smooth muscle cell migration. Sci Rep. 2020;10:10667. doi:10.1038/s41598-020-67781-1

98. Nguyen TT, Ward JP, Hirst SJ. beta1-Integrins mediate enhancement of airway smooth muscle proliferation by collagen and fibronectin. Am J Respir Crit Care Med. 2005;171:217–223. doi:10.1164/rccm.200408-1046OC

99. Fu J, Zheng M, Zhang X, et al. Fibulin-5 promotes airway smooth muscle cell proliferation and migration via modulating Hippo-YAP/TAZ pathway. Biochem Biophys Res Commun. 2017;493:985–991. doi:10.1016/j.bbrc.2017.09.105

100. Tran T, Teoh CM, Tam JKC, et al. Laminin drives survival signals to promote a contractile smooth muscle phenotype and airway hyperreactivity. FASEB J. 2013;27:3991–4003. doi:10.1096/fj.12-221341

101. Roche WR, Beasley R, Williams JH, Holgate ST. Subepithelial fibrosis in the bronchi of asthmatics. Lancet. 1989;1:520–524. doi:10.1016/S0140-6736(89)90067-6

102. Hoshino M, Nakamura Y, Sim J, Shimojo J, Isogai S. Bronchial subepithelial fibrosis and expression of matrix metalloproteinase-9 in asthmatic airway inflammation. J Allergy Clin Immunol. 1998;102:783–788. doi:10.1016/s0091-6749(98)70018-1

103. Wang CH, Huang C-D, Lin H-C, et al. Increased circulating fibrocytes in asthma with chronic airflow obstruction. Am J Respir Crit Care Med. 2008;178:583–591. doi:10.1164/rccm.200710-1557OC

104. Moir LM, Burgess JK, Black JL. Transforming growth factor beta 1 increases fibronectin deposition through integrin receptor alpha 5 beta 1 on human airway smooth muscle. J Allergy Clin Immunol. 2008;121:1034–1039 e1034. doi:10.1016/j.jaci.2007.12.1159

105. Hong GH, Park S-Y, Kwon H-S, et al. IL-32gamma attenuates airway fibrosis by modulating the integrin-FAK signaling pathway in fibroblasts. Respir Res. 2018;19:188. doi:10.1186/s12931-018-0863-3

106. Vignola AM, Chanez P, Chiappara G, et al. Transforming growth factor-beta expression in mucosal biopsies in asthma and chronic bronchitis. Am J Respir Crit Care Med. 1997;156:591–599. doi:10.1164/ajrccm.156.2.9609066

107. Redington AE, Madden J, Frew A, et al. Transforming growth factor-beta 1 in asthma. Measurement in bronchoalveolar lavage fluid. Am J Respir Crit Care Med. 1997;156:642–647. doi:10.1164/ajrccm.156.2.9605065

108. Torrego A, Hew M, Oates T, Sukkar M, Fan Chung K. Expression and activation of TGF-beta isoforms in acute allergen-induced remodelling in asthma. Thorax. 2007;62:307–313. doi:10.1136/thx.2006.063487

109. Batra V, Musani AI, Hastie AT, et al. Bronchoalveolar lavage fluid concentrations of transforming growth factor (TGF)-beta1, TGF-beta2, interleukin (IL)-4 and IL-13 after segmental allergen challenge and their effects on alpha-smooth muscle actin and collagen III synthesis by primary human lung fibroblasts. Clin Exp Allergy. 2004;34:437–444. doi:10.1111/j.1365-2222.2004.01885.x

110. Walker EJ, Heydet D, Veldre T, Ghildyal R. Transcriptomic changes during TGF-beta-mediated differentiation of airway fibroblasts to myofibroblasts. Sci Rep. 2019;9:20377. doi:10.1038/s41598-019-56955-1

111. Guo W, Shan B, Klingsberg RC, Qin X, Lasky JA. Abrogation of TGF-beta1-induced fibroblast-myofibroblast differentiation by histone deacetylase inhibition. Am J Physiol. 2009;297:L864–870. doi:10.1152/ajplung.00128.2009

112. Sidhu SS, Yuan S, Innes AL, et al. Roles of epithelial cell-derived periostin in TGF-beta activation, collagen production, and collagen gel elasticity in asthma. Proc Natl Acad Sci U S A. 2010;107:14170–14175. doi:10.1073/pnas.1009426107

113. Frangogiannis N. Transforming growth factor-beta in tissue fibrosis. J Exp Med. 2020;217:e20190103. doi:10.1084/jem.20190103

114. Bottoms SE, Howell JE, Reinhardt AK, Evans IC, McAnulty RJ. Tgf-Beta isoform specific regulation of airway inflammation and remodelling in a murine model of asthma. PLoS One. 2010;5:e9674. doi:10.1371/journal.pone.0009674

115. Kenyon NJ, Ward RW, McGrew G, Last JA. TGF-beta1 causes airway fibrosis and increased collagen I and III mRNA in mice. Thorax. 2003;58:772–777. doi:10.1136/thorax.58.9.772

116. Wnuk D, Paw M, Ryczek K, et al. Enhanced asthma-related fibroblast to myofibroblast transition is the result of profibrotic TGF-beta/Smad2/3 pathway intensification and antifibrotic TGF-beta/Smad1/5/(8)9 pathway impairment. Sci Rep. 2020;10:16492. doi:10.1038/s41598-020-73473-7

117. Mu D, Cambier S, Fjellbirkeland L, et al. The integrin alpha(v)beta8 mediates epithelial homeostasis through MT1-MMP-dependent activation of TGF-beta1. J Cell Biol. 2002;157:493–507. doi:10.1083/jcb.200109100

118. Tatler AL, Jenkins G. TGF-beta activation and lung fibrosis. Proc Am Thorac Soc. 2012;9:130–136. doi:10.1513/pats.201201-003AW

119. Ling KM, Sutanto EN, Iosifidis T, et al. Reduced transforming growth factor beta1 (TGF-beta1) in the repair of airway epithelial cells of children with asthma. Respirology. 2016;21:1219–1226. doi:10.1111/resp.12810

120. Prikk K, Maisi P, Pirilä E, et al. Airway obstruction correlates with collagenase-2 (MMP-8) expression and activation in bronchial asthma. Lab Investig. 2002;82:1535–1545. doi:10.1097/01.lab.0000035023.53893.b6

121. Suzuki R, Kato T, Miyazaki Y, et al. Matrix metalloproteinases and tissue inhibitors of matrix metalloproteinases in sputum from patients with bronchial asthma. J Asthma. 2001;38:477–484. doi:10.1081/jas-100105868

122. Wipff PJ, Rifkin DB, Meister JJ, Hinz B. Myofibroblast contraction activates latent TGF- 1 from the extracellular matrix. J Cell Biol. 2007;179:1311–1323. doi:10.1083/jcb.200704042

123. Xu MY, Porte J, Knox AJ, et al. Lysophosphatidic acid induces {alpha}v{beta}6 integrin-mediated TGF-{beta} activation via the LPA2 receptor and the small G protein G{alpha}q. Am J Pathol. 2009;174:1264–1279. doi:10.2353/ajpath.2009.080160

124. Jenkins RG, Su X, Su G, et al. Ligation of protease-activated receptor 1 enhances alpha(v)beta6 integrin-dependent TGF-beta activation and promotes acute lung injury. J Clin Invest. 2006;116:1606–1614. doi:10.1172/JCI27183

125. Januskevicius A, Gosens R, Sakalauskas R, et al. Suppression of eosinophil integrins prevents remodeling of airway smooth muscle in asthma. Front Physiol. 2016;7:680. doi:10.3389/fphys.2016.00680

126. Janulaityte I, Januskevicius A, Kalinauskaite-Zukauske V, Bajoriuniene I, Malakauskas K. In vivo allergen-activated eosinophils promote collagen I and fibronectin gene expression in airway smooth muscle cells via TGF-beta1 signaling pathway in asthma. Int J Mol Sci. 2020;21:1837. doi:10.3390/ijms21051837

127. Tanaka H, Yamada G, Saikai T, et al. Increased airway vascularity in newly diagnosed asthma using a high-magnification bronchovideoscope. Am J Respir Crit Care Med. 2003;168:1495–1499. doi:10.1164/rccm.200306-727OC

128. Orsida BE, Li X, Hickey B, et al. Vascularity in asthmatic airways: relation to inhaled steroid dose. Thorax. 1999;54:289–295. doi:10.1136/thx.54.4.289

129. Salvato G. Quantitative and morphological analysis of the vascular bed in bronchial biopsy specimens from asthmatic and non-asthmatic subjects. Thorax. 2001;56:902–906. doi:10.1136/thorax.56.12.902

130. Van der Velden J, Harkness LM, Barker DM, et al. The effects of tumstatin on vascularity, airway inflammation and lung function in an experimental sheep model of chronic asthma. Sci Rep. 2016;6:26309. doi:10.1038/srep26309

131. Lee HY, Min KH, Lee SM, Lee JE, Rhee CK. Clinical significance of serum vascular endothelial growth factor in young male asthma patients. Korean J Intern Med. 2017;32:295–301. doi:10.3904/kjim.2014.242

132. Lee SY, Kwon S, Kim KH, et al. Expression of vascular endothelial growth factor and hypoxia-inducible factor in the airway of asthmatic patients. Ann Allergy Asthma Immunol. 2006;97:794–799. doi:10.1016/S1081-1206(10)60971-4

133. Feltis BN, Wignarajah D, Zheng L, et al. Increased vascular endothelial growth factor and receptors: relationship to angiogenesis in asthma. Am J Respir Crit Care Med. 2006;173:1201–1207. doi:10.1164/rccm.200507-1105OC

134. Chetta A, Zanini A, Foresi A, et al. Vascular endothelial growth factor up-regulation and bronchial wall remodelling in asthma. Clin Exp Allergy. 2005;35:1437–1442. doi:10.1111/j.1365-2222.2005.02360.x

135. Simcock DE, Kanabar V, Clarke GW, et al. Induction of angiogenesis by airway smooth muscle from patients with asthma. Am J Respir Crit Care Med. 2008;178:460–468. doi:10.1164/rccm.200707-1046OC

136. Zhang R, Dong H, Zhao H, et al. 1,25-Dihydroxyvitamin D3 targeting VEGF pathway alleviates house dust mite (HDM)-induced airway epithelial barrier dysfunction. Cell Immunol. 2017;312:15–24. doi:10.1016/j.cellimm.2016.11.004

137. Turkeli A, Yilmaz Ö, Karaman M, et al. Anti-VEGF treatment suppresses remodeling factors and restores epithelial barrier function through the E-cadherin/beta-catenin signaling axis in experimental asthma models. Exp Ther Med. 2021;22:689. doi:10.3892/etm.2021.10121

138. Yuksel H, Yilmaz O, Karaman M, et al. Role of vascular endothelial growth factor antagonism on airway remodeling in asthma. Ann Allergy Asthma Immunol. 2013;110:150–155. doi:10.1016/j.anai.2012.12.015

139. Brooks PC, Clark RA, Cheresh DA. Requirement of vascular integrin alpha v beta 3 for angiogenesis. Science. 1994;264:569–571. doi:10.1126/science.7512751

140. Friedlander M, Brooks PC, Shaffer RW, et al. Definition of two angiogenic pathways by distinct α v integrins. Science. 1995;270:1500–1502. doi:10.1126/science.270.5241.1500

141. Thompson EE, Pan L, Ostrovnaya I, et al. Integrin beta 3 genotype influences asthma and allergy phenotypes in the first 6 years of life. J Allergy Clin Immunol. 2007;119:1423–1429. doi:10.1016/j.jaci.2007.03.029

142. Drake CJ, Cheresh DA, Little CD. An antagonist of integrin alpha v beta 3 prevents maturation of blood vessels during embryonic neovascularization. J Cell Sci. 1995;108(Pt 7):2655–2661. doi:10.1242/jcs.108.7.2655

143. Hodivala-Dilke KM, McHugh KP, Tsakiris DA, et al. Beta3-integrin-deficient mice are a model for Glanzmann thrombasthenia showing placental defects and reduced survival. J Clin Invest. 1999;103:229–238. doi:10.1172/JCI5487

144. Huang X, Griffiths M, Wu J, Farese RV, Sheppard D. Normal development, wound healing, and adenovirus susceptibility in beta5-deficient mice. Mol Cell Biol. 2000;20:755–759. doi:10.1128/MCB.20.3.755-759.2000

145. Yang JT, Rayburn H, Hynes RO. Embryonic mesodermal defects in alpha 5 integrin-deficient mice. Development. 1993;119:1093–1105. doi:10.1242/dev.119.4.1093

146. Okazaki T, Ni A, Ayeni OA, et al. alpha5beta1 Integrin blockade inhibits lymphangiogenesis in airway inflammation. Am J Pathol. 2009;174:2378–2387. doi:10.2353/ajpath.2009.080942

147. Davis GE, Camarillo CW. An alpha 2 beta 1 integrin-dependent pinocytic mechanism involving intracellular vacuole formation and coalescence regulates capillary lumen and tube formation in three-dimensional collagen matrix. Exp Cell Res. 1996;224:39–51. doi:10.1006/excr.1996.0109

148. Peng Q, Lai D, Nguyen TT-B, et al. Multiple β 1 integrins mediate enhancement of human airway smooth muscle cytokine secretion by fibronectin and type I collagen. J Immunol. 2005;174:2258–2264. doi:10.4049/jimmunol.174.4.2258

149. Weller PF, Rand TH, Goelz SE, Chi-Rosso G, Lobb RR. Human eosinophil adherence to vascular endothelium mediated by binding to vascular cell adhesion molecule 1 and endothelial leukocyte adhesion molecule 1. Proc Natl Acad Sci USA. 1991;88:7430–7433. doi:10.1073/pnas.88.16.7430

150. Nagata M, Sedgwick JB, Kita H, Busse WW. Granulocyte macrophage colony-stimulating factor augments ICAM-1 and VCAM-1 activation of eosinophil function. Am J Respir Cell Mol Biol. 1998;19:158–166. doi:10.1165/ajrcmb.19.1.3001

151. Kato M, Kita H, Tokuyama K, Morikawa A. Cross-linking of the beta2 integrin, CD11b/CD18, on human eosinophils induces protein tyrosine phosphorylation and cellular degranulation. Int Arch Allergy Immunol. 1998;117(Suppl 1):68–71. doi:10.1159/000053576

152. Nagata M, Sedgwick JB, Bates ME, Kita H, Busse WW. Eosinophil adhesion to vascular cell adhesion molecule-1 activates superoxide anion generation. J Immunol. 1995;155:2194–2202.

153. Higashimoto I, Chihara J, Kakazu T, et al. Regulation of eosinophil cell death by adhesion to fibronectin. Int Arch Allergy Immunol. 1996;111(Suppl 1):66–69. doi:10.1159/000237420

154. Ray A, Kolls JK. Neutrophilic inflammation in asthma and association with disease severity. Trends Immunol. 2017;38:942–954. doi:10.1016/j.it.2017.07.003

155. Sekheri M, Othman A, Filep JG. beta2 integrin regulation of neutrophil functional plasticity and fate in the resolution of inflammation. Front Immunol. 2021;12:660760. doi:10.3389/fimmu.2021.660760

156. Fan Z, McArdle S, Marki A, et al. Neutrophil recruitment limited by high-affinity bent beta2 integrin binding ligand in cis. Nat Commun. 2016;7:12658. doi:10.1038/ncomms12658

157. Khawaja AA, Chong DLW, Sahota J, et al. Identification of a novel HIF-1alpha-alphaMbeta2 integrin-NET axis in fibrotic interstitial lung disease. Front Immunol. 2020;11:2190. doi:10.3389/fimmu.2020.02190

158. Habgood AN, Tatler AL, Porte J, et al. Secretory leukocyte protease inhibitor gene deletion alters bleomycin-induced lung injury, but not development of pulmonary fibrosis. Lab Investig. 2016;96:623–631. doi:10.1038/labinvest.2016.40

159. Maestrelli P, De Fina O, Bertin T, et al. Integrin expression on neutrophils and mononuclear cells in blood and induced sputum in stable asthma. Allergy. 1999;54:1303–1308. doi:10.1034/j.1398-9995.1999.00337.x

160. Holgate ST, Davies DE. Rethinking the pathogenesis of asthma. Immunity. 2009;31:362–367. doi:10.1016/j.immuni.2009.08.013

161. Liu C, Qin X, Liu H, Xiang Y. Downregulation of integrin beta4 decreases the ability of airway epithelial cells to present antigens. PLoS One. 2012;7:e32060. doi:10.1371/journal.pone.0032060

162. Fernandes D, Guida E, Koutsoubos V, et al. Glucocorticoids inhibit proliferation, cyclin D1 expression, and retinoblastoma protein phosphorylation, but not activity of the extracellular-regulated kinases in human cultured airway smooth muscle. Am J Respir Cell Mol Biol. 1999;21:77–88. doi:10.1165/ajrcmb.21.1.3396

163. Shull S, Meisler N, Absher M, Phan S, Cutroneo K. Glucocorticoid-induced down regulation of transforming growth factor-beta 1 in adult rat lung fibroblasts. Lung. 1995;173:71–78. doi:10.1007/BF02981467

164. Bandi N, Kompella UB. Budesonide reduces vascular endothelial growth factor secretion and expression in airway (Calu-1) and alveolar (A549) epithelial cells. Eur J Pharmacol. 2001;425:109–116. doi:10.1016/s0014-2999(01)01192-x

165. Laitinen LA, Laitinen A, Haahtela T. A comparative study of the effects of an inhaled corticosteroid, budesonide, and a beta 2-agonist, terbutaline, on airway inflammation in newly diagnosed asthma: a randomized, double-blind, parallel-group controlled trial. J Allergy Clin Immunol. 1992;90:32–42. doi:10.1016/s0091-6749(06)80008-4

166. Haldar P, Brightling CE, Hargadon B, et al. Mepolizumab and exacerbations of refractory eosinophilic asthma. N Engl J Med. 2009;360:973–984. doi:10.1056/NEJMoa0808991

167. Flood-Page P, Menzies-Gow A, Phipps S, et al. Anti-IL-5 treatment reduces deposition of ECM proteins in the bronchial subepithelial basement membrane of mild atopic asthmatics. J Clin Invest. 2003;112:1029–1036. doi:10.1172/JCI17974

168. Chachi L, Diver S, Kaul H, et al. Computational modelling prediction and clinical validation of impact of benralizumab on airway smooth muscle mass in asthma. Eur Respir J. 2019;54:1900930. doi:10.1183/13993003.00930-2019

169. Tajiri T, Niimi A, Matsumoto H, et al. Comprehensive efficacy of omalizumab for severe refractory asthma: a time-series observational study. Ann Allergy Asthma Immunol. 2014;113:470–475 e472. doi:10.1016/j.anai.2014.06.004

170. Prakash YS, Halayko AJ, Gosens R, et al. An Official American Thoracic Society Research Statement: current challenges facing research and therapeutic advances in airway remodeling. Am J Respir Crit Care Med. 2017;195:e4–e19. doi:10.1164/rccm.201611-2248ST

171. Kianmeher M, Ghorani V, Boskabady MH. Animal model of asthma, various methods and measured parameters: a methodological review. Iran J Allergy Asthma Immunol. 2016;15:445–465.

172. Tatler AL, Philp CJ, Hill MR, et al. Differential remodelling in small and large murine airways revealed by novel whole lung airway analysis. BioRxivs. 2022. doi:10.1101/2022.01.15.476324

173. Kotaru C, Schoonover KJ, Trudeau JB, et al. Regional fibroblast heterogeneity in the lung: implications for remodeling. Am J Respir Crit Care Med. 2006;173:1208–1215. doi:10.1164/rccm.200508-1218OC

174. Clifford RL, Yang CX, Fishbane N, et al. TWIST1 DNA methylation is a cell marker of airway and parenchymal lung fibroblasts that are differentially methylated in asthma. Clin Epigenetics. 2020;12:145. doi:10.1186/s13148-020-00931-4

175. Gupta S, Siddiqui S, Haldar P, et al. Qualitative analysis of high-resolution CT scans in severe asthma. Chest. 2009;136:1521–1528. doi:10.1378/chest.09-0174

176. Cianchetti S, Cardini C, Puxeddu I, et al. Distinct profile of inflammatory and remodelling biomarkers in sputum of severe asthmatic patients with or without persistent airway obstruction. World Allergy Organ J. 2019;12:100078. doi:10.1016/j.waojou.2019.100078

177. Riccio AM, Mauri P, De Ferrari L, et al. Galectin-3: an early predictive biomarker of modulation of airway remodeling in patients with severe asthma treated with omalizumab for 36 months. Clin Transl Allergy. 2017;7:6. doi:10.1186/s13601-017-0143-1

178. Ayars AG, Altman LC, Potter-Perigo S, et al. Sputum hyaluronan and versican in severe eosinophilic asthma. Int Arch Allergy Immunol. 2013;161:65–73. doi:10.1159/000343031

179. Kitamura H, Cambier S, Somanath S, et al. Mouse and human lung fibroblasts regulate dendritic cell trafficking, airway inflammation, and fibrosis through integrin alphavbeta8-mediated activation of TGF-beta. J Clin Invest. 2011;121:2863–2875. doi:10.1172/JCI45589

180. Macias-Perez I, Borza C, Chen X, et al. Loss of integrin alpha1beta1 ameliorates Kras-induced lung cancer. Cancer Res. 2008;68:6127–6135. doi:10.1158/0008-5472.CAN-08-1395

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As part of a comprehensive lung exam, a doctor may try to listen for various sounds by tapping your back and chest with their hand, which is a test called percussion.

If the percussion produces a drum-like sound known as hyperresonance, it could indicate air has filled the space around your lungs and is prohibiting them from expanding fully. It may also suggest that air is trapped inside the small airways and alveoli (air sacs) of your lungs.

Hyperresonance can be a sign of chronic obstructive pulmonary disease (COPD) or another respiratory condition. It may also indicate that the condition is worsening and that more aggressive treatment may be necessary.

Although percussion is no longer used to help diagnose COPD, there is older research that suggests it should be.

The sounds your lungs make can help a doctor diagnose COPD, asthma, or other pulmonary conditions. They can also help a doctor determine whether your respiratory health is strong.

You may be more familiar with auscultation, which involves listening to your lungs with a stethoscope. Doctors perform auscultation while you inhale and exhale. The sounds your lungs make can indicate narrowed airways, for example.

But chest percussion aims to determine if there’s too much air or fluid in lung tissue. There are three distinct sounds a physician listens for, and each one suggests a different diagnosis:

  • A resonant or fairly low, hollow noise is often a sign of healthy lungs.
  • A dull or flat sound suggests fluid in your lungs (pneumonia) or in the space between your lungs and chest wall (pleural effusion). It can also be a sign of a lung tumor.
  • Hyperresonance suggests too much air around your lungs or in the lung tissue itself.

Hyperresonance is often a symptom of a type of COPD called emphysema. In emphysema, tiny air sacs in your lungs become damaged and enlarged.

This can lead to hyperinflation, which means there’s an atypical amount of air in your lungs. Hyperinflation, in turn, expands your rib cage, creating a temporary condition known as “barrel chest.”

If COPD or another respiratory problem is suspected, a doctor may perform chest percussion to help reach a diagnosis. If you’ve already received a diagnosis of COPD, chest percussion is one way a doctor can determine how much, if at all, your condition is progressing.

Doctors may do chest percussion a few different ways. Generally, the test starts with a doctor placing a hand flat on your chest or back. They’ll then use their other hand’s index or middle finger to tap the middle finger of the hand that is against your skin.

The doctor may start on your chest or back. But a comprehensive exam should involve tapping or percussing several locations around your torso to understand how both lungs sound, top to bottom.

There are other diagnostic tests for COPD, including a breathing test called spirometry. But in a 2019 study, researchers determined that hyperresonance to chest percussion is a strong indicator of COPD.

Can hyperresonance indicate a condition other than COPD?

While hyperresonance is a common symptom of COPD, it can also indicate another serious respiratory condition known as pneumothorax.

The space between the lungs and chest wall is usually hollow. In the case of pneumothorax, also known as a collapsed lung, air fills that space and puts pressure on one or both lungs.

A person having an asthma attack may also produce hyperresonance with chest percussion. Their lungs become hyperinflated as exhaling becomes more difficult.

Can I perform a chest percussion exam on my own to test for COPD?

Someone may teach you self-percussion but not necessarily as a diagnostic tool.

People with chronic bronchitis, another form of COPD, may use chest percussion to clear mucus from their lungs, but that is a different process.

Are there any other obvious signs of COPD?

Other telltale signs of COPD include:

Hyperresonance can be a significant indicator of COPD. Chest percussion is an advisable test to undergo if a doctor suspects COPD.

A joint 2015 statement by the American Thoracic Society and European Respiratory Society indicates that the combination of hyperresonance and decreased breath sounds likely suggests that someone has COPD.

COPD is a serious respiratory ailment. But if you receive an early diagnosis and stick to your treatment plan, it can be a manageable condition. Learning self-percussion may help clear your lungs of mucus.

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