A significant percentage of Black men found to have normal lung function after race-based adjustments to spirometry were actually found to have emphysema on their computed tomography (CT) scans, according to research published at the ATS 2022 international conference.

Black adults in the U.S. are more likely to have unrecognized emphysema than white adults. This is due in part to the normalization of lower lung function in people of color through race-specific interpretations of spirometry. We found in this observational sample of middle-aged adults in the United States that 14.6 percent of Black men (vs. 1.7 percent of white men) with 'above-normal' spirometry based on race-specific equations were found to have emphysema on CT imaging. Our traditional measures of lung health based on race-specific spirometry may be considerably under-recognizing impaired respiratory health in Black individuals."

Gabrielle Liu, MD, study's presenting author, pulmonary and critical care fellow, Northwestern University Feinberg School of Medicine, Chicago

It is standard practice to interpret results from spirometry using race-specific norms, which leads to a decrease in the predicted lower limit of "normal" for FEV1 and FVC for Black patients. FEV1 is the maximum amount of air a person can forcibly exhale in one second and FVC is the forced vital capacity-;maximum amount exhaled forcefully after breathing in deeply. The practice of race correction has no biological basis and is based on the mistaken belief, first proposed during colonial times, that Black individuals have smaller lungs.

Spirometry is a commonly used test of lung function in which a patient forcefully exhales into a mouthpiece that is connected to a spirometry machine. The machine measures how much air the person is able to exhale and inhale and helps determine whether he or she has lung disease. Emphysema, which involves the gradual destruction of lung tissue, is often associated with COPD and can lead to extremely poor health outcomes.

Dr. Liu and colleagues evaluated the association between self-identified race and visually identified emphysema on CT scans in participants with normal spirometry who participated in the multicenter Coronary Artery Risk Development in Young Adults (CARDIA) study, which followed Black and white participants starting in 1985. This study examined 2,674 participants' CT scans when they were the average age of 50, and spirometry results when they were average age 55.

"We found that significant racial disparities in emphysema prevalence occur predominantly among those with FEV1 between 80 and 120 percent of that predicted," said Dr. Liu. "This suggests that the greatest potential for misclassification using race-specific equations occurs among Black adults who are at risk for disease and who could potentially benefit from risk factor modification."

The research team also wanted to see whether individual socioeconomic status (SES) and smoking might contribute to higher rates of emphysema in Black participants, and whether the association between race and emphysema among those with similar lung function would be reduced or eliminated when adjusted for smoking and SES. They found that there was still a racial disparity in emphysema among those with similar predicted race-specific FEV1 . However, after adjusting for SES and smoking, the disparity in emphysema prevalence between Black and white men was reduced.

"We feel these findings support reconsidering the use of race-specific spirometry reference equations in favor of race-neutral reference equations and support further research into the utility and implications of incorporating CT imaging into the evaluation of those with suspected impaired respiratory health and normal spirometry," stated Dr. Liu.

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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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Respiratory trainer is commonly known as breathe exerciser is a device that aims to improve function of the respiratory muscles through specific exercises.

This device increases the amount one can breathe in and delivers a high mixture of oxygen and air.

Respiratory trainer strengthen the muscles of those who suffer from asthma, bronchitis, emphysema and Chronic Obstructive Pulmonary Disease.

There are variety of respiratory trainers are available in the market which include Ultrabreathe, Powerbreathe, PowerLung, and Expand-A-Lung.

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Respiratory trainer- Usage

To give daily workout to the lung, one should inhale through respiratory trainer for a few minutes twice a day in a simple breathing pattern. Respiratory trainer works on the principle of resistance.

As patient inhale, the resistance created which makes the muscles work harder and the harder they work the stronger and more durable they become.

As the breathing power improves, lung exerciser can be gradually adjusted to provide more resistance with just the twist of a knob.

These days’ doctors are also prescribing respiratory trainer for post-surgery patients to increase their lung power. Respiratory trainers are now also used to increase sports performance.

Respiratory trainer- Benefits

Respiratory trainers are compact, convenient and safe. They improve cardio-pulmonary status of the patient, enhancing the overall fitness and wellbeing.

Respiratory trainers are best lung exercisers that improve oxygenation of blood and reduce fat levels by burning calories.

These trainers are good for athletes which boost their performance. Respiratory trainers also help in achieving optimum lung capacity and restoring disrupted breathing patterns.

It also increases circulation of hormones in the blood which increase the blood blow to the heart, brain and lungs.

Now-a-day doctors prescribed respiratory trainer post-surgery, especially after bypass surgery to restore and maintains lung capacity.

The most important advantage of respiratory trainer is it can be used by anyone. Considering the ever increasing pollution, even healthy person can use respiratory trainer to strengthen the lungs.

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Respiratory trainer- Trends

Presently, respiratory trainer market is driven by rising incidence of respiratory disorder. The World Health Organisation (WHO) estimates 235 million people worldwide suffer from asthma.

Besides, technological advancement such as low perfusion and motion tolerant in pulse oximeter, increasing government expenditure, growing patient awareness about various respiratory diseases and rise in demand for better healthcare services is also driven the growth of respiratory trainer market.

Some of the common factors that affect the rate of respiration are age, internal temperature, disease such as Chronic Obstructive Pulmonary Disease and angina is creating robust development in respiratory trainers’ market.

However, critical regulatory compliance procedures inhibit the growth of the respiratory trainer market.

Respiratory trainer- Region

North America dominates the global respiratory trainer market due to technological advancement and increasing incidence of respiratory cases, rising popularity of portable devices and growing demand for home health care devices such as respiratory trainer.

For instance, The American Lung Association states that Chronic Obstructive Pulmonary Disease is the third leading cause of death in the US. While, according to the American Academy of Allergy Asthma and Immunology, asthma is estimated to grow by more than 100 million by 2025.

Asia-Pacific is the fastest emerging market for global respiratory trainer market because of rising number of patients with respiratory diseases.

Respiratory trainer- Forecast

The respiratory trainer market in Asia Pacific offers large opportunities and is projected to expand at the highest CAGR in the next few years.

This growth is mainly due to factors such as untapped opportunities, improving health care infrastructure, and increasing awareness about the available diagnostic procedure.

Improving health care scenario, rising prevalence of respiratory diseases, and growing investments by market players are the major factors fuelling the growth of global respiratory trainer market.

The research report presents a comprehensive assessment of the market and contains thoughtful insights, facts, historical data, and statistically supported and industry-validated market data.

It also contains projections using a suitable set of assumptions and methodologies. The research report provides analysis and information according to market segments such as geographies, types and applications.

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Regional analysis includes

  • North America (U.S., Canada)
  • Latin America (Mexico. Brazil)
  • Western Europe (Germany, Italy, France, U.K, Spain)
  • Eastern Europe (Poland, Russia)
  • Asia Pacific (China, India, ASEAN, Australia & New Zealand)
  • Japan
  • Middle East and Africa (GCC, S. Africa, N. 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.

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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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The lungs are an essential part of the respiratory system. The respiratory system facilitates breathing and has two parts: the upper respiratory tract, which includes the airways like the nose, mouth, sinuses, and windpipe (trachea), and the lower respiratory tract, which consists of the lungs and bronchial tubes. 

The lungs’ main role is to deliver oxygen to the blood and remove carbon dioxide from the blood. Air enters the nose or mouth and passes through your windpipe and into the bronchial tubes when you breathe in. The bronchial tubes lead into the lungs and branch out into smaller tubes known as bronchioles, which end in small air sacs known as alveoli.

The alveoli are surrounded by capillaries (small blood vessels) that carry oxygen-low blood through them. Oxygen from the air in the alveoli flows into the blood, and carbon dioxide moves out of the blood and into the alveoli.

The carbon dioxide flows from the alveoli and back up through the respiratory system, where it is exhaled out of the mouth or nose.

In this article, you will learn about lung anatomy, how lungs function, and how to keep them healthy.

Igor Alecsander / Getty Images

Lung Anatomy

Though both lungs are similar in makeup, they are asymmetrical. The left lung is slightly smaller than the right lung to accommodate the heart. The right lung has three lobes—the right upper lobe, the right middle lobe, and the right lower lobe. The left lung has an upper and lower lobe.

The lungs are wrapped in pleura, a two-layer membrane. Fluid between the layers helps reduce friction when breathing.

Both lungs have a pulmonary artery, bronchial arteries, and pulmonary veins that carry blood in and out of the lungs.

The alveoli inside the lungs are small thin sacs that allow for an exchange of gases, bringing oxygen into the blood and carbon dioxide out of the blood.

Muscles around the lungs aid in breathing. These muscles include the diaphragm, a disk-shaped muscle that sits under the lungs, and the intercostal muscles that run between the ribs. Muscles in the neck and mouth also help with breathing.

Lung Function

Though it is possible to control your breathing—you can take a deep breath, a shallow breath, or even hold your breath for a short period—most breathing happens without thought.

The autonomic nervous system controls breath and works involuntarily. The system senses when you need more oxygen, such as when exercising, and makes adjustments.

The autonomic nervous system has two divisions that have different functions in breathing, which are:

  • The parasympathetic system narrows the bronchial tubes and widens the pulmonary blood vessels.
  • The sympathetic system widens the bronchial tubes to allow more air in and narrows the pulmonary blood vessels. 

To help these systems, there are various sensors throughout the body to signal the body to adjust breathing rate:

  • Sensors in the joints and muscles detect movement, which can signal to the body that you are exercising and an increase in breathing rate is necessary.
  • Sensors in the brain and blood vessels measure oxygen and carbon dioxide levels in the blood, which signals the type of breathing rate adjustment needed.
  • Sensors in the airways themselves can detect substances that may irritate the lungs, such as smoke or allergens, which may cause coughing or sneezing.

Lung Function Tests

A lung function test can determine the health of the lungs. These tests show how well the lungs work and can include:

  • Spirometry: Spirometry is the most common lung function test. The test consists of breathing in and blowing into a tube that records the volume of air inhaled and exhaled. A healthcare provider walks you through the test and has you inhale and exhale in different manners—sometimes forcefully and others at a normal rate.
  • Diffusion capacity test: During this test, a gas mixture is inhaled and then exhaled to determine how well the alveoli function at moving gases into and out of the lungs and blood.
  • Overnight pulse oximetry (OPO): Overnight pulse oximetry can detect the amount of oxygen in the blood over an extended period, mainly at night during sleep. A sensor is placed over the tip of your finger during the test, and the oxygen saturation levels (the amount of oxygen in the blood) are recorded.
  • Six-minute walk test: This test can measure how well your heart and lungs work during exercise or movement. You will walk for six minutes during the test while your heart rate, oxygen levels, and blood pressure are measured.

Respiratory Diseases Affecting the Lungs

There are various respiratory diseases that can affect the lungs and reduce their ability to function. These diseases include:

  • Asthma: Asthma can obstruct the airways, causing wheezing or difficulty breathing. While the cause of asthma is not fully understood, certain pollutants can make it worse such as tobacco smoke and air pollution.
  • Chronic obstructive pulmonary disease (COPD): "COPD" is a term used to describe a group of progressive diseases that causes damage to the tissues of the lungs. This results in a variety of symptoms from shortness of breath to chest pain, a chronic cough, and tiredness.
  • Cystic fibrosis (CF). Cystic fibrosis is a genetic condition that causes the mucus in the lungs to become sticky and disrupt normal breathing patterns.
  • Lung cancer: Cancer of the lungs is a major cause of cancer-related deaths. Cancer of the lungs can affect any part of the lung structures.
  • Pneumonia: Pneumonia is often caused by infection. It results in inflammation in the alveoli of the lungs and can cause difficulty breathing. 
  • Tuberculosis: Tuberculosis is a highly contagious bacterial infection that can damage the lungs if not treated.

Maintaining Lung Health

Taking good care of your overall health, such as by doing the following, can help maintain lung health as well:

  • Regular exercise can keep your lungs healthy and strong.
  • Seeing your healthcare provider regularly for checkups can help detect problems with the lungs early, even if you have no symptoms.
  • Quitting smoking can prevent many lung issues since smoking is the leading cause of lung cancer and COPD issues like emphysema.
  • Taking good care of yourself to minimize exposure to infections can also help prevent lung issues, including washing your hands often, getting recommended vaccinations, and avoiding being around others who are sick.
  • Avoid air pollutants by paying attention to the air quality in your area and staying indoors when air quality is bad, avoiding secondhand smoke, and limiting your exposure to chemicals in your house and at work.


The lungs play an important part in the respiratory system. Their main function is to provide oxygen to the blood and remove carbon dioxide from the blood. Various diseases can affect the lungs, including asthma, infections, COPD, and cancer. Keep the lungs healthy by avoiding pollutants, getting regular exercise, and ceasing smoking.

A Word From Verywell

The lungs are a vital part of your health. When they are working as they should they will provide the oxygen you need to enjoy life with energy and vigor. If you have difficulty breathing or any symptoms related to lung disease, it’s important to talk to your healthcare provider right away.

Frequently Asked Questions

  • What are the first signs of lung problems?

    Some of the first signs of lung problems are shortness of breath, difficulty breathing, and tiredness.

  • What role do the lungs play in the respiratory system?

    The lungs provide oxygen to the blood and remove carbon dioxide from the blood.

  • How can you take care of your lungs?

    Taking care of your overall health can help you take care of your lungs. Exercise regularly, get routine checkups and avoid inhaling pollutants that can damage your lungs.

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DUBLIN, May 12, 2022--(BUSINESS WIRE)--The "Pneumatic Nebulizer Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)" report has been added to ResearchAndMarkets.com's offering.

The pneumatic nebulizer market is expected to register a 5.3% of CAGR over the forecast period. The increasing number of cases of respiratory diseases and increasing geriatric population is expected to drive the market growth.

According to the Global Burden of Disease Study, the prevalence of chronic pulmonary respiratory diseases (COPD) was found to be around 251 million and more than 90% of the COPD deaths occur in low- and middle-income countries. Hence, with the rising adoption of homecare devices by the patients it is expected to fuel the pneumatic nebulizer market growth.

Key Market Trends

Portable Pneumatic Nebulizer is Expected to Exhibit a Significant Market Growth Over the Forecast Period

Portable pneumatic nebulizer is expected to show a robust growth owing to the rising prevalence of respiratory diseases such as asthma and COPD and increasing geriatric population. The rising adoption of portable nebulizer due to its convenience and effectiveness is expected to influence positively on the growth. According to the study of Analytica Chimica Acta, 2020, pneumatic nebulizer was used for introducing metallic ionic meta callibrant solutions and nanoparticles. Furthermore, according to the World Health Organization, currently there are approximately 339 million people in the world living with asthma and over 80% of these reside in low- and middle- income countries. Hence, these factors are expected to impact positively on the market growth.

North America is Expected to Hold a Significant Share in the Market and Expected to do Same in the Forecast Period

North America is expected to be a dominant region in the Pneumatic Nebulizer market owing to higher prevalence of respiratory diseases and increasing geriatric population. According to the Centre for Disease Control and Prevention, in 2017, prevalence of asthma in male was found to be approximately 6.4% and 9.3% in female in the United States. Moreover, according to the U.S. Department of Health and Human Services, around 33,401 Americans suffered from emphysema in 2018. This is expected to increase the demand for pneumatic nebulizers and thereby propelling the market growth.

Key Topics Covered:





4.1 Market Overview

4.2 Market Drivers

4.2.1 Growing Burden of Respiratory Diseases

4.2.2 Increasing Demand for Home Healthcare Devices

4.2.3 Increasing Geriatric Population

4.3 Market Restraints

4.3.1 Drug Loss during Drug Delivery

4.4 Porter's Five Force Analysis


5.1 By Portability

5.1.1 Tabletop

5.1.2 Portable

5.2 By Sales Channel

5.2.1 Direct Purchase

5.2.2 Online Purchase

5.3 Geography


6.1 Company Profiles

6.1.1 Aerogen

6.1.2 Heyer Medical AG

6.1.3 GE Healthcare

6.1.4 Abbvie Inc. (Agilent Technologies)

6.1.5 Salter Labs

6.1.6 Medline Industries Inc.

6.1.7 Briggs Healthcare

6.1.8 PARI Pharma

6.1.9 Omron Healthcare


For more information about this report visit www.researchandmarkets.com/r/w7hmpp

View source version on businesswire.com: www.businesswire.com/news/home/20220512005562/en/


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Hyperinflation of the lungs is a common complication of chronic obstructive pulmonary disease (COPD). It happens when too much air gets trapped inside your lungs. When you can’t exhale properly, breathing can become difficult.

Chronic obstructive pulmonary disease (COPD) is a group of lung diseases caused by long-term exposure to gases or irritants, including those found in cigarette smoke. These substances cause chronic inflammation and damage lung tissue.

Over time, inflammation can narrow your airways, limit airflow, and make it harder to breathe. Without proper airflow, air can get trapped in your lungs. This can happen no matter how mild or severe your COPD symptoms are.

Read on to learn more about lung hyperinflation with COPD. We’ll cover the specific causes of hyperinflation as well as options for diagnosis and treatment.

If you have hyperinflated lungs, this means that they’re holding too much air. This can contribute to shortness of breath (dyspnea), which is the primary symptom of COPD.

There are two types of hyperinflation:

  • Static hyperinflation. Static hyperinflation occurs when you’re at rest. It’s characterized by air getting trapped in your lungs while you exhale.
  • Dynamic hyperinflation. In dynamic hyperinflation, air gets trapped in your lungs when you inhale before fully exhaling. Dynamic hyperinflation typically happens during physical activity, but it can also happen at rest.

Hyperinflation of the lungs can lead to:

  • difficulty exercising
  • reduced quality of life
  • increased illness

The main symptom of hyperinflated lungs is shortness of breath and difficulty breathing, even when doing light activities like walking upstairs.

Hyperinflation can occur along with other symptoms of COPD, too. Some common COPD symptoms include:

Hyperinflation is not directly related to the underlying causes of COPD. Instead, it’s due to the inflammation triggered by these causes.

The inflammation damages your airways and makes them narrow. This reduces the elastic recoil of your lungs, which is their ability to push out air when you exhale. In turn, you’re unable to fully exhale. This can trap air in your lungs and result in hyperinflation.

If air is trapped in your lungs, it can be difficult to breathe in fresh air. This also increases carbon dioxide levels.

COPD is a progressive disease. This means that it gets worse over time. If you’ve received a diagnosis of COPD, healthcare professionals will continuously monitor your lung function.

If they think you have hyperinflation, they’ll likely use the following tests to examine your lungs:

  • X-ray. A chest X-ray can show if your lungs are filled with too much air. Hyperinflated lungs can also flatten your diaphragm. This can also be seen on an X-ray.
  • CT scan. A CT scan, or CAT scan, creates a more detailed view of the structures in your body. This can help the doctor further examine your lungs or determine the best treatment.

With hyperinflation, treatment is intended to reduce inflammation and improve your lungs’ ability to deflate.

Supplemental oxygen

Supplemental oxygen, or oxygen therapy, uses a device to supply your body with extra oxygen. It can be used in a hospital or at home.

Pulmonary rehabilitation

During pulmonary rehabilitation, a medical professional will teach you strategies to improve your lung function. This involves components like:

  • education
  • exercise training
  • nutrition advice
  • counseling
  • lifestyle changes


Some medications can help reduce inflammation and relax your airways, including:

  • bronchodilators
  • beta-2 agonists
  • anticholinergics


In some cases, the following procedures might help manage COPD:

  • Lung volume reduction surgery. This procedure reduces hyperinflation caused by severe emphysema. This involves removing damaged parts of the lungs so that healthy tissue can function better.
  • Bullectomy. During a bullectomy, doctors remove large air pockets from the lungs.
  • Lung transplantation. A lung transplant for COPD involves replacing one or both lungs with healthy lung tissue from an organ donor.

A doctor might recommend surgery if oxygen therapy, medication, and rehabilitation are unable to help you manage your symptoms.

It’s possible to have hyperinflated lungs without COPD. That’s because other types of lung problems can also cause hyperinflation, including:

Smoking cannabis is also associated with lung hyperinflation.

Hyperinflation of the lungs is a common complication of COPD. It’s caused by the lungs’ inability to properly push out air when you exhale. As a result, too much air gets stuck in your lungs, making it hard to breathe.

A doctor can diagnose lung hyperinflation using an X-ray or CT scan. Treatment may involve supplemental oxygen, pulmonary rehabilitation, and medication. If these therapies do not work, a doctor may recommend surgery.

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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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COPD stands for chronic obstructive pulmonary disease.

It is also called emphysema or chronic bronchitis. It is a type of damage to the lungs caused mostly by smoking cigarettes.

COPD and other conditions can have the same symptoms.

COPD usually starts after age 40 and can make you feel short of breath. Sometimes even with simple chores, you may wheeze when you exert yourself.

You may also have a chronic cough, often with phlegm. When you get a cold, you may notice that it lasts longer than other people’s colds.

COPD is a chronic disease which slowly gets worse (progresses) over time. Quitting smoking slows down its progression.

COPD inhalers help you to:

  • Breathe better
  • Be more active
  • Stay out of hospital

It is important to know if the symptoms you are having are caused by COPD, so that you get the right treatment.

COPD symptoms can feel the same as symptoms of other health conditions, such as asthma, heart disease, or less common lung conditions such as lung “fibrosis” (scarring).

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Spontaneous pneumomediastinum (SPM) is a rare and self-limiting condition characterized by the presence of air in the mediastinum not related to trauma or surgical procedures [1]. Described by Laennec in 1819 as a complication of trauma, Hamman 120 years later published his case series of SPM. This condition typically affects young adults aged 20-30 years, with a male preponderance of 8:1. SPM is associated with other medical conditions, including asthma, connective tissue disease, interstitial lung disease, diabetic ketoacidosis, chronic obstructive airway disease, and influenza-like syndrome. [1] SPM is reported to develop in 10% of cases of intubated COVID-19 with acute respiratory distress syndrome (ARDS) even with low tidal volume strategies [2,3]. One unmatched case control study of 271 patients showed the incidence of SPM among non-intubated acute COVID-19 patients at 3.3%, similar to our patient [4]. The case we described would fit into this group. 

The cause of COVID-19, SARS-CoV 2, is a novel coronavirus associated with wide heterogeneity in clinical presentation ranging from asymptomatic to critical illness. The first infection was detected in late 2019 in Wuhan, China, after which it rapidly spread worldwide. Mortality was high among those with advanced age and significant comorbidities. The acute phase of COVID-19 infection lasts approximately three to four weeks. After four weeks of infection, SARS-CoV 2 no longer has the capability to replicate, and residual illness in this stage is called the post-acute COVID-19 syndrome [5]. Symptoms associated with the infection may persist, such as lethargy, easy fatigability, and shortness of breath, with some requiring prolonged supplemental oxygenation. To our knowledge, the incidence and risk factors of SPM among patients who have recovered from COVID-19 infection, i.e., patients in the post-acute phase, is yet to be studied.

We present a case of SPM in a patient with post-acute COVID-19 syndrome who received high flow nasal oxygen therapy in the acute stages of the disease.

The patient was a 58-year-old Chinese gentleman who never smoked. He had a BMI of 29.4kg/m2 and was fully vaccinated for COVID-19 (last dose was given three months prior to admission). He was admitted to the emergency room complaining of a productive cough accompanied by shortness of breath. A nasal pharyngeal swab for polymerase chain reaction (PCR) detecting SARS‐CoV‐2 ribonucleic acid (RNA) resulted in a positive. His significant medical history included hypertension and hyperlipidemia. He had no prior trauma, asthma history, diabetes, pulmonary tuberculosis, or connective tissue disease.

On admission, physical examination showed decreased breath sounds on both lungs and diffuse systolic murmur. He was febrile at 38 degrees Celsius, with a blood pressure of 114/77mmHg, heart rate of 143 per minute, and respiratory rate of 35 per minute. Oxygen saturation was at 89% on 100% non-rebreather mask. Arterial blood gas showed type 1 respiratory failure with a P/F ratio of 46. Therefore, we decided to start oxygen therapy with a high-flow nasal cannula (HFNC) (FiO2: 100%, flow: 60 L/min with SpO2: 96%). Initial chest X-ray (CXR) revealed right middle and lower zone patchy airspace opacities without pleural effusion or pneumothorax (Figure 1).

The full blood count showed a white blood cell count (WBC) of 6.95x10^9/L, hemoglobin 15.2g/dL, platelets 191x10^9/L, C-Reactive protein (CRP) 151.1mg/L (N=1.0-5.0mg/L), procalcitonin 1.2ng/mL (N=0.5 to 2.0ng/mL), serum lactate 1.9mmol/L (N=0.6-1.4mmol/L), serum urea 6.8mmol/L (N=2.4 to 6.6mmol/L) and beta-hydroxybutyrate 0.35mmol/L (N=0.02-0.27). His International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) 4C score was nine, signifying high risk and an in-hospital mortality of 31.4 to 34.9%. The patient was prescribed intravenous dexamethasone before transferring to medical intensive care unit (MICU).

In the medical intensive care unit, he received empiric intravenous amoxicillin-clavulanic acid and oral doxycycline. Blood cultures and sputum cultures, which were taken from endotracheal tube (ETT), were all reported as no bacterial growths. Fever persisted, and a repeat chest X-ray showed worsening bilateral airspace opacities. Antibiotics were escalated to intravenous piperacillin-tazobactam while on intravenous dexamethasone therapy. Blood cultures and sputum cultures were repeated and were negative. On day six of illness, he received the first dose of a five-day course of intravenous remdesivir. Due to persistent hypoxia, he received two doses of intravenous tocilizumab on day six and day 26 of illness.

He also developed starvation ketosis and revealed newly diagnosed diabetes mellitus with HbA1c of 8.1%. Subcutaneous (SC) intermediate-acting insulin (Insulatard) was prescribed. Thromboprophylaxis with subcutaneous enoxaparin was given during the pulmonary phase of the illness. The HFNC setting for the first 15 days was on maximum flow of 60L/min, with a taper to 40L/min on the remaining seven days. Initial FiO2 on HFNC was at 100%, with subsequent gradual weaning to 40% on day 28 of illness. On day 10 of illness, he received a trial of continuous positive airway pressure ventilation (CPAP), but HFNC was resumed as no significant improvement was seen on oxygenation. CRP levels improved from 151mg/L to 72.8mg/L, and by day 28 of illness, the CRP was at 4.4mg/L. The patient performed awake prone positioning to improve oxygenation.

On day 30 of illness, he was weaned off to a non-rebreather mask and managed to sustain adequate oxygen saturation on nasal cannula oxygenation at 5-liter oxygen. He was transferred to the general ward for rehabilitation. He remained afebrile and normotensive with a resting tachycardia at 100-110/min. Despite mild dyspnea and easy fatigability, oxygen saturations were at 98% on 4-liter oxygen nasal cannula. Intravenous dexamethasone was gradually tapered down.

On day 34 of illness, COVID-19 PCR with cycle threshold (CT) ratio was 33.34/33.37. Despite this, his saturations dropped to 77% while on 4-liter oxygen nasal cannula. He was put on 100% non-rebreather mask, and oxygen saturations increased to 96-99%. Repeat CXR showed stable bilateral diffuse airspace opacities with no evidence of pneumothorax. Repeat arterial blood gas revealed type 1 respiratory failure with a P/F ratio of 119 and CRP of 0.7mg/L. An electrocardiogram showed normal sinus rhythm at 73/min. A computed tomography pulmonary angiogram (CTPA) was arranged to rule out acute pulmonary embolism. SC enoxaparin was restarted at a therapeutic dose. The scan was negative for pulmonary embolism but detected a pneumomediastinum (PM), pneumopericardium (PP), and subcutaneous emphysema (Figure 2, 3). Respiratory medicine service recommended keeping him on non-rebreather mask oxygenation, and he was deemed a poor candidate for positive pressure ventilation in the event of current deterioration. On examination, he was alert tachypneic with bilateral scattered crackles in the middle and lower zones on auscultation. He developed subcutaneous emphysema at the neck but no change in the quality of his voice. After discussion with the patient and his family, he opted for maximum ward management in the event of further deterioration. The family was hopeful for his full recovery. On day 36 of illness, he developed atrial flutter with a pulse rate of 160bpm on 12-lead electrocardiography (ECG) with a blood pressure of 109/79mmHg. He received rate control measures, including intravenous amiodarone, oral bisoprolol, and digoxin, and his heart rate improved to sinus rhythm at 76bpm on 12-lead ECG.

On day 40 of illness, the patient was found unresponsive with pulseless electrical activity on the cardiac monitor. Cardiopulmonary resuscitation (CPR) was initiated and he was intubated by the on-call airway team. Despite the resuscitation team’s best efforts, no return of spontaneous circulation was achieved, and the patient was pronounced demised.

There are a number of mechanisms that lead to the development of spontaneous pneumomediastinum. First is the alveolar rupture secondary to inflammation and diffuse alveolar pressures due to coughing. The escaping air from the ruptured alveoli tracks along the bronchovascular sheaths, dissecting into the pulmonary hila and escaping into the mediastinal space. This is seen on thoracic computed tomography scans demonstrating the Macklin effect, described as linear collections of air continuous to the bronchovascular sheaths dissecting into the pulmonary hilum [6]. Second is the direct viral invasion of the lung parenchyma, visceral and parietal pleura causing disruption of the parenchymal and pleural integrity or ruptured alveoli leading to subsequent air leak [7]. Third is the prothrombotic effect of COVID-19 infection-causing pulmonary vascular thrombosis and subsequent necrosis in the alveolar membranes. Fourth is cytokine storm-induced diffuse alveolar injury or direct viral infection of type 1 and type 2 pneumocytes increasing the risk of alveolar rupture [3].

COVID-19 related SPM affects an older population aged 38-72 years of age versus 5-34 years for non-COVID SPM [8]. COVID-19 related SPM has been associated with a more severe course of the disease and a mortality rate of 28.5% versus non-COVID SPM, which has an estimated mortality rate of 5.6% [1].

We highlight the risk of SPM, PP, and subcutaneous emphysema developing in COVID-19 patients without the usually associated conditions who did not receive invasive positive pressure ventilation at the post-acute phase of the disease. We also hope this launches further investigations comparing the non-invasive and invasive modalities of oxygen supplementation and the respective settings for severe COVID-19 to achieve the optimal oxygenation profile while minimizing the risk of barotrauma and PP and PM. We also anticipate more studies that look into developing multidisciplinary treatment protocols for patients who develop COVID-19 related PP and PM. The question is: which modality achieves optimal oxygenation while minimizing the risk of barotrauma and SPM? 

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Chronic obstructive pulmonary disease (COPD) is characterized as nonreversible airflow limitation abnormality, which is currently diagnosed based on spirometric results and respiratory symptoms.1,2 Nevertheless, there are several limitations for the evaluation of lung ventilatory function with spirometry. First, spirometric results reflect a global changes of lung function without regional information.3 In other words, it is hard to discriminate the different patterns of underlying pathologic abnormalities, including emphysema, bronchial inflammation, and small airway disease, as well as their distribution in lung.4–6 Second, spirometric results did not significantly reflect the morphological disorders (eg, emphysema and air trapping) observed on CT images.7–12 Additional limitation of spirometry is related to the infective risk under current new coronavirus pandemic. As we all know, it is difficult to carry out spirometry without close contact with potential infected patients.

CT can provide in vivo anatomical information to assess the severity of COPD and make up for the limitations aforementioned to some degree. More recently, quantitative CT analysis have been used for monitoring the progression of diseases such as emphysema and air trapping over time in large longitudinal studies (eg, COPDGene, SPIROMICS, MESA).13–15 Strain analysis based on 4D dynamic-ventilation CT has emerged as a new quantitative measurement to record lung deformation during ventilation, opening a new era for monitoring pathophysiological changes in COPD.16–18 Mathematically speaking, strain on a point of a deformable body is determined from the derivatives of the displacement field that deforms the body.19–23 Xu et al17 have firstly introduced strain analysis in COPD to monitor pulmonary motion during ventilation. Although that study demonstrated the potential of strain measurement for evaluating pulmonary mechanics, only the “middle” field of the lung were analyzed with single strain-related parameter (maximum principal strain).17 Despite the significant correlations were observed between the strain-related parameter and spirometry, evidence that strain measurement can reflect lung function changes was insufficiently presented. Considering the regional heterogeneity of emphysema in COPD, especially in the upper-lower direction,3–5 substantial improvements in the method of strain analysis, particularly analyze scope covering the whole lung and multi-dimensional parameters setting, are needed.

Consequently, the strain analysis performed by a computational fluid dynamic analysis software covering the whole lung was introduced to monitor lung motion during ventilation. The purpose of our study was to quantitatively identify abnormal lung motion in patients at high-risk for COPD, and further clarify the potential differences of deformation in COPD with different severity of airflow limitation. In addition, we also intended to explore the possibility of monitoring lung function using strain analysis in the future.

Materials and Methods

The retrospective study protocol complied with the Declaration of Helsinki for medical studies, and it was approved by the Institutional Review Board at China-Japan Friendship Hospital (approval No. 2020–53-K31), and all participants provided written informed consent.


Totally, 70 subjects at high-risk for COPD were recruited in this study between August 2020 and June 2021. The inclusion criteria were: 1) ≥18 years old; 2) ex-/current smoking or long-term (at least one year) passive smoke exposure accompanied with respiratory symptoms (eg, cough, sputum production, or dyspnea); 3) no acute respiratory infection or other severe pulmonary distortion such as interstitial lung diseases or tuberculosis that could affect the quantitative CT measurement; 4) no previous thoracic operation; 5) the interval between CT examinations and spirometry within 2 weeks.

However, subjects who met any of the following criteria were excluded from the late analysis: 1) poor cooperation with voice guidance during dynamic-ventilation CT (n=11); 2) poor image quality that unable to carry out strain analysis (n=3); 3) measurement items of spirometry were incomplete (n=3). Finally, 53 subjects (36 men and 17 women; mean age, 57.87 years; age range, 30–85 years) were enrolled in the study. Detailed clinical characteristics of the subjects enrolled in were summarized in Table 1.

Table 1 Basic Clinical Characteristics and Imaging Measurements of Study Groups

CT Scans Protocol

All patients underwent both conventional low-dose chest CT and dynamic-ventilation CT scans on a 320-row MDCT scanner (Aquilion ONE, Canon Medical Systems, Japan). Subjects underwent conventional low-dose chest CT at full inspiration in the supine position.

Parameters for the conventional low-dose chest CT were as follows: tube currents = automatic exposure control (AEC); tube voltage =120 kVp; scanning method = helical scanning; rotation time =0.35 s; beam pitch =0.828; imaging FOV =320 mm; collimation = 0.5 mm ×80 rows; slice thickness =1 mm; reconstruction kernel = FC17 (for mediastinum); iterative reconstruction = adaptive iterative dose reduction using three-dimensional processing (AIDR3D; mild setting); slice thickness/interval=0.5mm/0.5mm.

All participants were coached on continuous deep breathing before dynamic-ventilation CT scans. Dynamic-ventilation CT was performed using dynamic volume scan mode (Zmax=16cm) without bed movement. Two volumes of dynamic-ventilation CT with 1cm overlap were set to cover the entire thorax. Scanning and reconstruction parameters for dynamic-ventilation CT were as follows: tube current =60 mA; tube voltage =80 kV; rotation time =0.35 s; total scanning time =8.4 s; imaging FOV =320 mm; collimation =0.5 mm; slice thickness =1 mm; reconstruction kernel = FC15 (for mediastinum); reconstruction interval =0.2 s/frame (total 41 frames); iterative reconstruction = AIDR3D (mild setting); slice thickness/interval=0.5mm/0.5mm.

Radiation exposure was calculated using dose-length product (DLP), which was based on CT dose index volumes (CTDIvol). The effective dose (ED) was calculated by multiplying DLP values by a conversion factor of k=0.014mSv•mGy−1•cm−1.24 For conventional low-dose chest CT, the average DLP was 144.64 mGy•cm and average ED 2.02 mSv. For dynamic-ventilation CT, the average DLP was 521.6 mGy•cm and average ED 7.30 mSv.

Image Analysis – Low Density Index (LD Index), Total Lung Volume (TLV) by Static CT

Using commercially embedded software (Lung density analysis, Canon Medical Systems, Japan), the low attenuation (threshold, <-950 Hounsfield units [HU]) on images was automatically identified, and the percent low attenuation (<-950 Hounsfield units) volume of the whole lung (LD index), as well as TLV, was automatically measured.

Image Analysis – Lung Volume-Time Curve by Dynamic-Ventilation CT

Using the same commercial software (Lung density analysis, Canon Medical Systems, Japan), the lung volume of the scanned lung was automatically measured in each frame, then a lung volume-frame curve (Figure 1) was obtained. On the volume-frame curve, the frame with the maximum lung volume was defined as the peak inspiratory frame (=first expiratory frame), and the expiratory phase defined as the process from the peak inspiratory frame (=first expiratory frame; maximum lung volume frame) to the peak expiratory frame (minimum lung volume frame) on lung volume-frame curve.

Figure 1 Lung volume-frame curve.

Image Analysis – Strain Analysis

Strain analysis was performed on dynamic-ventilation CT using a computational fluid dynamics analysis software (Micro Vec V3.6.2, Micorvec Pte Ltd, Beijing, China) as follows (Figure 2):

  1. Image matching and fusion. Using the motion coherence algorithm, the upper and lower volume date were matched and joined together. The overlapped cross sections in the dataset were deleted;
  2. Data abstraction. Script codes are used to extract all-frame data of different slices, respectively. The image format is converted from Dicom to Tiff.bmp, and the frequency of data acquisition is 10Hz;
  3. The displacement field calculation. All-frame data of the same slice was imported into MicroVec software, and the irrelevant areas that was not included in the calculation were concealed by “Mask” function. Then cross-correlation algorithm was used to calculate the cross-correlation of lung image data and derive the maximum displacement time of those data;
  4. The strain-related parameters calculation using Tecplot macro-command. The values of strain-related parameters (maximum Principal Strain [PSmax], mean Principal Strain [PSmean] and maximum Displacement Speed [Speedmax]) were calculated and normalized using the following formula. PSmax and PSmean referred to the maximum and average strain in the pixel displacement field (velocity field) based on pixel displacement, respectively. And Speedmax was defined as the maximum displacement of pixel in the same velocity field.

Figure 2 Schematic diagram of strain analysis.

where Exx is transverse strain; Eyy is longitudinal strain; Exy and Eyx are shearing strains.

  • 5. The final parameter diagram generation. The pseudo-color fusion image was generated by superimposing the values of different strain-related parameters on the original CT image.
  • Briefly, in the series of data obtained from dynamic-ventilation CT, only the expiration phase on lung volume-frame curve was included in the analysis. The strain-related parameters (PSmax, PSmean, Speedmax) derived from the whole expiration phase, the first 2s of expiration phase were included in final analysis, respectively. The strain-related parameters’ values of the 1st expiratory frame, as well as the lung volume, were selected as the basic reference values. From the 2nd expiration frame, all strain-related parameters’ values were divided by the volume changes of corresponding frame to adjust potential influence of expiration degree. Then, adjusted values of all strain-related parameters from 2nd to 10th expiration frame, from 2nd expiration frame to peak expiration frame were summed to express the total strain measurement for different period of expiration phase (PSmax2s, PSmean2s, Speedmax2s; PSmax-all, PSmean-all, Speedmax-all), respectively.


    All subjects underwent spirometry (MasterScreen PFT, Vyaire Medical GmbH, Germany) under the guidance of qualified pulmonary function technicians following the standards published by the American Thoracic Society (ATS) and the European Respiratory Society (ERS).2 COPD was diagnosed clinically with post-bronchodilator FEV1/FVC <0.70, and severity was categorized according to Global initiative for Chronic obstructive Lung Disease (GOLD) recommendations.2 The spirometric parameters included forced vital capacity (FVC), forced expiratory volume at 1 second (FEV1); PEF, peak expiratory flow (PEF), maximum mid-expiratory flow 75% (MMEF 75%), MMEF50%, MMEF25%, and MMEF25–75%. The interval between spirometry and CT examination was within 2 weeks.

    Statistical Analysis

    Statistical analysis was performed using SPSS software (SPSS 17.0 for Windows, SPSS, Chicago, IL). The Kolmogorov–Smirnov test for normality was performed on continuous variables and the graphical spread of the data was visually inspected. Descriptive statistics were shown as means ± standard deviation (SD) or medians ± interquartile range (IQR) for continuous variables, and as frequency and percentage for categorical variables. Spearman rank correlation analysis was used to evaluate associations between the adjusted strain measurements and various spirometric values. Comparisons of the strain-related parameters between COPD and non-COPD patients, between GOLD I (mild airflow restriction) and GOLD II–IV (moderate to severe airflow restriction) were made using the Mann–Whitney U-test. Then, receiver-operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of the adjusted strain parameters for COPD. The areas under the ROC curve (AUC) were calculated: an AUC value < 0.50 indicated poor diagnostic accuracy; an AUC value of 0.51~0.70, fair diagnostic accuracy; an AUC value of 0.71~0.90, moderate diagnostic accuracy; an AUC value > 0.91, high diagnostic accuracy. The cut-off values with the largest Youden index [(sensitivity + specificity) - 1] were calculated from the ROC curves. For all the analyses mentioned above, P<0.05 was considered statistically significant.


    A total of 53 subjects were enrolled, including 18 non-COPD and 35 COPD patients. The latter group included 19 GOLD I, 12 GOLDII, and 4 GOLD IV. Basic clinical characteristics and imaging measurements of all subjects were summarized in Table 1.

    All subjects underwent spirometry and CT scans, including conventional low-dose chest CT and dynamic-ventilation CT. The average interval time between the two kinds of examinations was (7.8±3.4) days.

    Correlation Between CT Measurements and Spirometry

    The adjusted strain-related parameters, especially the ones derived from the first 2s of expiration (PSmax2s, PSmean2s, Speedmax2s), were significantly correlated with FEV1/FVC (ρ=0.450~0.687, P<0.001), serial parameters of MMEF (ρ=0.364~0.643, P<0.05), and PEF (ρ=0.275~0.456, P<0.05), suggesting that heterogeneity in lung motion associated with impaired lung function (Table 2).

    Table 2 Correlations Between CT Measurements and Spirometry

    Comparison of CT Measurements Between Study Groups

    Male, ex- or current smoker, and lower BMI subjects were more frequently observed in COPD group. According to static CT data, TLV in COPD group was significantly larger than that in non-COPD group (P=0.004), whereas the values of spirometric parameters showed the opposite trend, suggesting that more invalid aerated lung tissue may be in COPD patients.

    By comparison of COPD group and non-COPD group, all the values of strain-related parameters in COPD group were significantly lower than those in non-COPD group (P<0.001). In addition, compared to GOLD I patients, even though lower values of strain-related parameters were observed in GOLD II–IV, only parameters of the whole expiration phase (PSmax-all, Speedmax-all) demonstrated statistically significant difference (z=−2.782, P=0.005; z=−2.053, P=0.04; Table 3).

    Table 3 Strain-Related Parameters in COPD Patients with Different Severity of Airflow Restriction

    Predictive Significance of Strain-Related Parameters for COPD

    According to the ROC curve, the adjusted strain-related parameters showed moderate diagnostic significance with the AUC values range from 0.821 to 0.894. The PSmax2s value for the COPD patients was lower than 65.48 and that for non-COPD patients was greater than 65.48, with the maximal accuracy rate of 86.79% and the maximal sensitivity of 94.29% (Table 4, Figure 3).

    Table 4 Cut-off Values and Corresponding Diagnostic Rate for Strain-Related Parameters

    Figure 3 Receiver-operating characteristic curve for strain-related parameters in distinguishing COPD patients from non-COPD ones.


    In this study, strain analysis based on dynamic-ventilation CT data was introduced to quantitatively measure lung deformation during expiration in COPD using a computational fluid dynamics analysis software. Here we reported that strain-related parameters demonstrated positive correlations with spirometric parameters (ρ=0.275~0.687, P<0.05). And strain-related parameters can quantitatively distinguish COPD from non-COPD patients with moderate diagnostic significance. Furthermore, parameters of the whole expiration phase (PSmax-all, Speedmax-all) demonstrated significant differences (P=0.005; P=0.04) between COPD patients with mild and moderate to severe airflow limitation. These findings suggest that strain measurements for lung deformation during expiration can reflect lung function impairment to some degree, and it also provides promising imaging biomarkers to assess severity of airflow limitation. Our study added to the growing body of evidence supporting the utility of strain measurement in quantitative analysis of COPD.17

    Strain measurements is closely related structural changes in lung. Even though COPD has been classified into several phenotype basing on morphologic appearance on CT,3–6 the extent of structure destruction does not always correlate with the severity of expiratory airflow limitation, which is a set of comprehensive physical phenomenon involving the elastic recoil pressure and the expiratory flow-volume curve.1,2,4,7,25,26 To complicate matters further, multiple patterns of morphologic changes such as emphysema, bronchial wall thickening, or expiratory air trapping always coexist,3–6,11 and it is exceedingly difficult to quantify their contributions to airflow limitation separately. Hence, it was no wonder that correlation coefficients were variable between strain-related parameters and different spirometric items.

    Theoretically, PSmax and PSmean represent the maximum and average degree of deformation in the displacement field, respectively. And Speedmax represents the maximum displacement speed in the same field. Thus, lower values of strain-related parameters observed in COPD patients in the present study indicated that either motion extent or speed was decreased during expiration in COPD patients, then reflecting impairment of lung function. Interestingly, emphysematous destruction with decreased values of strain-related parameters was observed in the upper lobes of some non-COPD patients, whereas no abnormalities have been shown yet by spirometry. This phenomenon indirectly confirmed that the extent of structure destruction was not linear correlation with the change of lung function,7–11,27 meanwhile, identify that strain analysis is sensitive enough to detect the regional functional abnormalities prior to the functional parameters given by spirometry.

    In this study, we excluded obvious disorders (eg, respiratory infection, interstitial lung diseases) in pulmonary that could affect quantitative measurement. Actually, GOLD III/IV patients often accompanied with the aforementioned abnormalities. This was also one of the reasons for the limited cases of GOLD III/IV (only 4 cases) in the study population. According to severity of airflow limitation, COPD patients were divided into two subgroups: mild (GOLD I) and moderate to severe (GOLD II–IV) groups, only parameters derived from the whole expiration phase (PSmax-all, Speedmax-all) demonstrated statistical difference between the two groups. Even though decreased trend was observed in parameters derived from the first 2s of expiration phase in GOLD II–IV group. This finding may indicate that parameters of the whole expiration phase may be more sensitive to subtle differences that occur as airflow limitation progresses. However, considering the limited sample size and non-linear correlation between strain measurements and lung function discussed above, further analysis needs to be performed with much larger cohort.

    The present study has a number of limitations. First, a limited number of patients were enrolled, and considering the burden of second-hand smoke exposure among non-smokers in China,28 those subjects with long-term passive smoke exposure were also enrolled, which was different from the inclusion criteria used in other COPD-related studies,5,17 thus our study results need to be verified in further study. Second, COPD patients with severe airflow limitation (GOLD III–IV) were underrepresented and aggregated with GOLD II patients into a single group for analysis, so our results cannot be generalized to more severe COPD population. Third, since the airflow obstruction of COPD is more severe in expiration phase during ventilation, we focused on strain analysis for the expiration phase only in this study. Fourth, various breathing patterns (eg, chest breathing, abdominal breathing) in patients were not assessed, which may have influenced the final results.18 Fifth, due to limited scan length in the Z-axis (Zmax=16cm), currently, a whole-lung dynamic-ventilation CT scan needs two volume scans to complete. Even though a low-dose CT scan protocol combined with an advanced iterative reconstruction method (AIDR3D) was adopted,29 increased radiation exposure was unavoidable. In the further study, AiCE (advanced intelligent clear-IQ engine) technology, which is a novel reconstruction method involving deep learning and AI technologies,30,31 would be actively conducted to reduce radiation dose as far as possible. In addition, since data from two CT volume packages needed to match and joint together for pro-processing, even though the motion coherence algorithm can be selected, subject cooperation was quite important to acquire high-quality images. In this study, 11 subjects have been excluded for poor cooperation with voice guidance during CT scans.

    In conclusion, strain-related parameters derived from dynamic-ventilation CT data covering the whole lung associated with lung function changes in COPD, reflecting the severity of airflow limitation in some degree, even though its utility in severe COPD patients remains to be investigated. Our results would also be an evidence for the feasibility of monitoring lung function using strain analysis in the future.


    Yanyan Xu received a research grant from China-Japan Friendship Hospital (2019-1-QN-60).


    Yanyan Xu received a research grant from China-Japan Friendship Hospital (2019-1-QN-60). The authors report no other conflicts of interest in this work.


    1. Celli BR, Wedzicha JA. Update on clinical aspects of chronic obstructive pulmonary disease. N Engl J Med. 2019;381(13):1257–1266. doi:10.1056/NEJMra1900500

    2. Celli BR, MacNee W; ATS/ERS Task Force. Standards for the diagnosis and treatment of patients with COPD: a summary of the ATS/ERS position paper. Eur Respir J. 2006;27(1):242.

    3. Matsuoka S, Yamashiro T, Washko GR, Kurihara Y, Nakajima Y, Hatabu H. Quantitative CT assessment of chronic obstructive pulmonary disease. Radiographics. 2010;30(1):55–66. doi:10.1148/rg.301095110

    4. Kang HS, Bak SH, Oh HY, et al. Computed tomography-based visual assessment of chronic obstructive pulmonary disease: comparison with pulmonary function test and quantitative computed tomography. J Thorac Dis. 2021;13(3):1495–1506. doi:10.21037/jtd-20-3041

    5. MacNeil JL, Capaldi DPI, Westcott AR, et al. Pulmonary imaging phenotypes of chronic obstructive pulmonary disease using multiparametric response maps. Radiology. 2020;295(1):227–236. doi:10.1148/radiol.2020191735

    6. Park J, Hobbs BD, Crapo JD, et al. Subtyping COPD by using visual and quantitative CT imaging features. Chest. 2020;157(1):47–60. doi:10.1016/j.chest.2019.06.015

    7. Feldhaus FW, Theilig DC, Hubner RH, Kuhnigk JM, Neumann K, Doellinger F. Quantitative CT analysis in patients with pulmonary emphysema: is lung function influenced by concomitant unspecific pulmonary fibrosis? Int J Chron Obstruct Pulmon Dis. 2019;14:1583–1593. doi:10.2147/COPD.S204007

    8. Oh AS, Strand M, Pratte K, et al. Visual emphysema at chest CT in GOLD Stage 0 cigarette smokers predicts disease progression: results from the COPDGene study. Radiology. 2020;296(3):641–649. doi:10.1148/radiol.2020192429

    9. Cosío BG, Pascual-Guardia S, Borras-Santos A, et al. Phenotypic characterisation of early COPD: a prospective case-control study. ERJ Open Res. 2020;6(4):00047–2020. doi:10.1183/23120541.00047-2020

    10. El Kaddouri B, Strand MJ, Baraghoshi D, et al. Fleischner society visual emphysema CT patterns help predict progression of emphysema in current and former smokers: results from the COPDGene study. Radiology. 2021;298(2):441–449. doi:10.1148/radiol.2020200563

    11. Virdee S, Tan WC, Hogg JC, et al. Spatial dependence of CT emphysema in chronic obstructive pulmonary disease quantified by using join-count statistics. Radiology. 2021;301(3):702–709. doi:10.1148/radiol.2021210198

    12. Lange P, Halpin DM, O’Donnell DE, MacNee W. Diagnosis, assessment, and phenotyping of COPD: beyond FEV₁. Int J Chron Obstruct Pulmon Dis. 2016;11:3–12.

    13. Regan EA, Hokanson JE, Murphy JR, et al. Genetic epidemiology of COPD (COPDGene) study design. COPD. 2010;7(1):32–43. doi:10.3109/15412550903499522

    14. Couper D, LaVange LM, Han M, et al.; SPIROMICS Research Group. Design of the subpopulations and intermediate outcomes in COPD study (SPIROMICS). Thorax. 2014;69(5):491–494. doi:10.1136/thoraxjnl-2013-203897.

    15. Thomashow MA, Shimbo D, Parikh MA, et al. Endothelial microparticles in mild chronic obstructive pulmonary disease and emphysema. The multi-ethnic study of atherosclerosis chronic obstructive pulmonary disease study. Am J Respir Crit Care Med. 2013;188(1):60–68. doi:10.1164/rccm.201209-1697OC

    16. Yamashiro T, Moriya H, Matsuoka S, et al. Asynchrony in respiratory movements between the pulmonary lobes in patients with COPD: continuous measurement of lung density by 4-dimensional dynamic-ventilation CT. Int J Chron Obstruct Pulmon Dis. 2017;12:2101–2109. doi:10.2147/COPD.S140247

    17. Xu Y, Yamashiro T, Moriya H, et al. Strain measurement on four-dimensional dynamic-ventilation CT: quantitative analysis of abnormal respiratory deformation of the lung in COPD. Int J Chron Obstruct Pulmon Dis. 2018;14:65–72. doi:10.2147/COPD.S183740

    18. Mochizuki E, Kawai Y, Morikawa K, et al. Difference in local lung movement during tidal breathing between COPD patients and asthma patients assessed by four-dimensional dynamic-ventilation CT scan. Int J Chron Obstruct Pulmon Dis. 2020;15:3013–3023. doi:10.2147/COPD.S273425

    19. Cruces P, Erranz B, Lillo F, et al. Mapping regional strain in anesthetised healthy subjects during spontaneous ventilation. BMJ Open Respir Res. 2019;6(1):e000423. doi:10.1136/bmjresp-2019-000423

    20. Tanabe Y, Kido T, Kurata A, et al. Three-dimensional maximum principal strain using cardiac computed tomography for identification of myocardial infarction. Eur Radiol. 2017;27(4):1667–1675. doi:10.1007/s00330-016-4550-9

    21. Joseph S, Moazami N, Cupps BP, et al. Magnetic resonance imaging-based multiparametric systolic strain analysis and regional contractile heterogeneity in patients with dilated cardiomyopathy. J Heart Lung Transplant. 2009;28(4):388–394. doi:10.1016/j.healun.2008.12.018

    22. Haugaa KH, Smedsrud MK, Steen T, et al. Mechanical dispersion assessed by myocardial strain in patients after myocardial infarction for risk prediction of ventricular arrhythmia. JACC Cardiovasc Imaging. 2010;3(3):247–256. doi:10.1016/j.jcmg.2009.11.012

    23. Niu J, Zeng M, Wang Y, et al. Sensitive marker for evaluation of hypertensive heart disease: extracellular volume and myocardial strain. BMC Cardiovasc Disord. 2020;20(1):292. doi:10.1186/s12872-020-01553-7

    24. Huda W, Ogden KM, Khorasani MR. Converting dose-length product to effective dose at CT. Radiology. 2008;248(3):995–1003. doi:10.1148/radiol.2483071964

    25. Jacob J, Bartholmai BJ, Rajagopalan S, et al. Serial automated quantitative CT analysis in idiopathic pulmonary fibrosis: functional correlations and comparison with changes in visual CT scores. Eur Radiol. 2018;28(3):1318–1327. doi:10.1007/s00330-017-5053-z

    26. Bates JH. Systems physiology of the airways in health and obstructive pulmonary disease. Wiley Interdiscip Rev Syst Biol Med. 2016;8(5):423–437. doi:10.1002/wsbm.1347

    27. Bodduluri S, Bhatt SP, Hoffman EA, et al.; COPDGene Investigators. Biomechanical CT metrics are associated with patient outcomes in COPD. Thorax. 2017;72(5):409–414. doi:10.1136/thoraxjnl-2016-209544

    28. Xiao L, Jiang Y, Zhang J, Parascandola M. Secondhand smoke exposure among nonsmokers in China. Asian Pac J Cancer Prev. 2020;21(S1):17–22. doi:10.31557/APJCP.2020.21.1.1

    29. Yamashiro T, Miyara T, Honda O, et al. Iterative reconstruction for quantitative computed tomography analysis of emphysema: consistent results using different tube currents. Int J Chron Obstruct Pulmon Dis. 2015;10:321–327. doi:10.2147/COPD.S74810

    30. Nakamura Y, Higaki T, Tatsugami F, et al. possibility of deep learning in medical imaging focusing improvement of computed tomography image quality. J Comput Assist Tomogr. 2020;44(2):161–167. doi:10.1097/RCT.0000000000000928

    31. Singh R, Digumarthy SR, Muse VV, et al. Image quality and lesion detection on deep learning reconstruction and iterative reconstruction of submillisievert chest and abdominal CT. AJR Am J Roentgenol. 2020;214(3):566–573. doi:10.2214/AJR.19.21809

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    As climate change, air pollution and COVID-19 impact millions worldwide, the Global Wellness Institute (GWI) is uniting physicians, scientists, and health and wellness business leaders to improve the quality of the air we breathe.

    The GWI is bringing these specialists together to form its new Respiratory Wellness Initiative.

    Marking the GWI’s 35th global wellness initiative, the new launch will examine the link between climate change, air quality and respiratory wellness.

    Board members (see full list below) will also seek to mobilise people and communities to reduce the impact that poor indoor and outdoor air quality have on our health and wellbeing.

    The GWI reports that the importance of respiratory wellness can’t be overstated because the origins of many respiratory issues that affect our overall health and wellness come from the air that we breathe.

    Lung and respiratory problems including emphysema, allergies, respiratory infections, asthma and COPD have all been firmly linked to poor air quality.

    The situation is rapidly becoming more dire; after assessing recent research the World Health Organization (WHO) found that air pollution is “the single largest environmental threat to human health and wellbeing”.

    Last month, United Nations scientists also found that 99 per cent of the world’s population breathes polluted air that exceeds internationally-approved limits, with negative health impacts kicking in at much lower levels than previously thought.

    Our changing climate also affects the health of our air. Higher temperatures lead to an increase in allergens and harmful air pollutants, such as ozone.

    Longer warm seasons can also mean longer pollen seasons, which can increase allergic sensitisations and asthma episodes for those susceptible and result in a loss of productive work and school days.

    More wildfires mean more carbon dioxide and greenhouse gas emissions, the injection of soot and other harmful aerosols into the atmosphere, and damage to forests that would otherwise remove CO2 from the air.

    “While the WHO recently found that the burden of disease attributable to air pollution is now on a par with other global health risks such as unhealthy diets and smoking, respiratory wellness has received far too little attention,” said Susie Ellis, GWI chair and CEO.

    “We welcome this initiative dedicated to making a global difference in educating people about the importance of this health issue and supporting innovation in protecting the air that we breathe. It’s a wellness industry first.”

    Founding members

    Leo Tonkin, founder and CEO of SALT Chamber, will serve as the new initiative’s chair.

    A specialist in respiratory health and wellness, Tonkin was among the first to bring halotherapy to North America (in 2012) and is a leading authority on the design, building and installation of halotherapy rooms, concepts, and facilities. His company has completed over 1,300 projects worldwide.

    In 2014, Tonkin worked with global industry leaders, researchers, medical professionals, manufacturers, and facility owners in founding the International Salt Therapy Association, which now has more than 3,500 members in 35 countries.

    The initiative’s vice-chair is Dr John Ryan, chief strategy officer at Allergy Standards (ASL) in Dublin, Ireland.

    ASL is an independent global certification company that focuses on creating the healthiest possible indoor environments through science, certification, and education.

    Its management team, with specialist skills in a variety of medical fields including asthma and allergic diseases, develops independent standards for testing a wide range of products to determine their relative suitability for respiratory wellness.

    The other founding members are:
    • Daniel T. Layish, MD - pulmonologist, Central Florida Pulmonary Group (US).
    • Christine Moghadam - founder, Corc Yoga (US).
    • Deliah Shader, LMT,- founder, Whole Body Healing (US).
    • Brayden D. Whitlock, JD, PhD – partner, Outbreaker Solutions (Canada).

    “Air surrounds us every moment, it gives us life, and the quality of the air that we breathe is the cornerstone of human health,” says Tonkin.

    “Respiratory wellness is the very foundation of human wellbeing and I’m proud to lead this Initiative along with Dr Ryan and our other founding members.”

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    This press release was orginally distributed by ReleaseWire

    Las Vegas, NV — (ReleaseWire) — 05/05/2022 — Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstructed airflow from the lungs, according to experts from Intermountain Healthcare.

    "COPD is a common respiratory condition, that is preventable and treatable, in which a patient has persistent respiratory symptoms due to structural damage to the bronchial tubes, or airways, and the air sacs in the lungs," said Dr. Suresh Tawney, Pulmonary Physician, Intermountain Healthcare COPD Clinic.

    More than 15 million people have COPD in the United States. But an additional 12 million people have COPD and do not know it as it is undiagnosed. The CDC reports that more than 150,000 people die every year from COPD. It is the 4th leading cause of death in the US as well as the 4th leading cause of disability. Approximately 185,000 people in Nevada are diagnosed and suffer from COPD.

    Risk factors include:
    – Exposure to air pollution
    – Breathing secondhand smoke
    – Working with chemicals, dust and fumes
    – A genetic condition called Alpha-1 deficiency
    – A history of childhood respiratory infection
    – COPD is more common in women – about 56 percent of cases
    – COPD includes chronic bronchitis, emphysema, and chronic obstructive asthma

    The symptoms according to the American Lung Association:
    – Chronic cough
    – Shortness of breath while doing everyday activities (dyspnea)
    – Frequent respiratory infections
    – Blueness of the lips or fingernail beds (cyanosis)
    – Fatigue
    – Producing a lot of mucus (also called phlegm or sputum)
    – Wheezing

    "Roughly 80 percent of all COPD cases are attributed to smoking," said Dr. Tawney. "The remaining are environmental factors or genetically from your family."

    The damage to the bronchial tubes and air sacs is usually caused by significant exposure to noxious particles, such as in smoking, or gases.

    The American Lung Association provides five steps to help reduce your risk of COPD:
    – If you smoke, it is a smart and healthy choice to quit. Seek help from family and experts to learn how to quit. It is never too late.
    – If you don't smoke, then don't start.
    – Avoid secondhand smoke around you. This includes making your home smoke-free.
    – Be aware of the dangers with chemicals, dust, and fumes at home and at work.
    – Work with your community to help fight for clean air.

    "The Intermountain COPD Clinic focuses currently on Medicare patients. Intermountain Healthcare uses a team to treat you at the COPD Clinic," said Dr. Tawney. "The team includes the physician, case manager, respiratory therapists, among others."

    The COPD Clinic team helps with the following:
    – Medication management
    – Educate disease process
    – Signs and symptoms and how-to self-monitor and manage their chronic condition
    – Provide symptom management and acute symptom triage via direct access to clinic and/or remote patient monitoring
    – Work with help with self-care success
    – Social determinants of health
    – Transition of care coordination during and after hospitalization

    To learn more about COPD, the COPD Clinic and Intermountain, visit intermountainhealthcare.org/Nevada, call (702) 691-9120, or see your primary care provider.

    About Intermountain
    Based in Utah with locations in seven states and additional operations across the western U.S., Intermountain Healthcare is a nonprofit system of 33 hospitals, 385 clinics, medical groups with some 3,800 employed physicians and advanced practice providers, a health plans division with more than one million members called SelectHealth, and other health services. Helping people live the healthiest lives possible, Intermountain is committed to improving community health and is widely recognized as a leader in transforming healthcare by using evidence-based best practices to consistently deliver high-quality outcomes at sustainable costs. For more information, see Intermountain Healthcare.

    For more information on this press release visit: www.releasewire.com/press-releases/what-is-copd-1357173.htm

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    Cuiqiong Dai,&ast; Zihui Wang,&ast; Zhishan Deng, Fan Wu, Huajing Yang, Shan Xiao, Xiang Wen, Youlan Zheng, Jianwu Xu, Lifei Lu, Ningning Zhao, Peiyu Huang, Yumin Zhou, Pixin Ran

    State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, People’s Republic of China

    Correspondence: Pixin Ran; Yumin Zhou, The State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, No. 195 Dongfeng Xi Road, Guangzhou, 510000, People’s Republic of China, Tel +86-020 83205187, Fax +86-020 81340482, Email [email protected]; [email protected]

    Background: Serum total bilirubin has been reported to have antioxidant properties against chronic respiratory diseases. The objective of our study is to evaluate the association of total bilirubin (TB) with annual lung function decline in COPD patients with different GOLD stages.
    Methods: This study used pooled data from two observational and prospective cohorts of 612 COPD patients whose TB levels were measured at baseline. The associations between TB and postbronchodilator FEV1, FEV1pred, FVC, FVCpred, FEV1/FVC, and the rate of their decline were all determined using linear regression models in the total population and strata of GOLD stages.
    Results: Serum TB was positively related to FEV1 and FVC in the total group (β 0.02, 95% CI 0.001∼ 0.02, P = 0.025 and β 0.02, 95% CI 0.002∼ 0.03, P = 0.022, respectively). Additionally, TB was inversely associated with the annual decline in FEV1 and FEV1pred (β 4.91, 95% CI 1.68∼ 8.14, P = 0.025 and β 0.21, 95% CI 0.06∼ 0.36, P = 0.022, respectively) when adjusted for multivariables. After stratification, the significant associations merely persisted in COPD patients with GOLD 2 and GOLD 3– 4.
    Conclusion: Increased TB level was related to less annual decline in FEV1 as well as FEV1pred in moderate-to-severe COPD but not mild COPD, which indicated the different status of TB in different COPD severity and the possible role as potential biomarker merely in moderate-to-severe COPD. Future researches to determine whether TB could be served as biomarker for COPD and the mechanisms should be focused on some target patients with a certain disease severity.


    Serum total bilirubin (TB), an end product of heme degradation, is demonstrated to scavenge oxidation free radicals and thus suppress oxidative stress.1 Experimental evidence from animal models indicated that TB could protect respiratory tissues against environmental stressors by cytoprotective properties.2,3 Additionally, accumulating clinical studies supported that mild higher bilirubin levels could decrease the risk of cardiovascular disease (CVD) and CVD-related diseases.4–6 An increased total bilirubin level is also associated with a lower risk of chronic respiratory diseases, including lung cancer and chronic obstructive pulmonary disease (COPD), as well as all-cause mortality.7–9 Furthermore, Kirstin E. et al found that elevated bilirubin concentrations would decrease the acute exacerbation of COPD.10

    A few longitudinal cohort studies have explored the relationship between total bilirubin and the rate of lung function decline. For example, Ah YL et al11 showed that serum bilirubin concentration was significantly related to the annual changes in FEV1, FVC, and FEV1 /FVC in general Koreans adjusted for sex, age, body mass index (BMI), and baseline lung function. Similarly, only in mild COPD, serum bilirubin is inversely related to the rate of FEV1 decline over 3 to 9 years.12 In a Swiss general population sample, per interquartile range increase of bilirubin exposure is concomitant with 1.1% increase in FEV1/FVC and 116.2 mL in FEF25-75% in smokers with high BMI.13 Also, David M. et al demonstrated that TB is significantly associated with higher FEV1 and FVC in baseline lung function in AIDS individuals.14 However, all these studies focused on the general or specific target population. And the data between bilirubin concentrations and the annual decline in lung function in all different GOLD stages of COPD have not been reported before. To fill this evidence gap, we hypothesized that higher TB level is associated with less annual lung function decline in COPD patients with different GOLD stages. To test the hypothesis, we pooled data from two observational and prospective cohort studies to assess the relationship between serum TB and lung function decline in the total COPD population and then further in different GOLD stage subgroups.


    Study Subjects

    The data were pooled from two population-based, multi-center, and prospective cohort studies, including the National Key Technology Research and Development Program of the 12th National 5-year Development Plan (2012–2015 Program; Trial registration number ChiCTR-OO-14004264) and the Early COPD (ECOPD; Trial registration number ChiCTR1900024643). The details of these two cohorts have been reported previously.15,16 Briefly, two cohorts recruited participants aged 20 years or older and completed bilirubin measurement, questionnaires, and lung function tests at baseline. Subjects included in this study completed spirometric measurements again for an interval of 7 to 9 years follow-up duration in 2012–2015 Program as well as 1 to 2 years in ECOPD. Only participants defined as COPD (postbronchodilator FEV1/FVC <0.7)17 with reliable data were included in our analysis. Participants were excluded if they had any comorbidity that might significantly influence bilirubin, such as hemolytic disorders, hepatobiliary diseases, or renal insufficiency by self-report. Additionally, TB concentrations >1.75 mg/dL for women and >2.34 mg/dL for men were also excluded for suspicious Gilbert syndrome, a benign hereditary disease caused by UGT1A1 genotypes.18 The original two studies were performed in line with the principles of the Declaration of Helsinki. Besides, the two studies were approved by the Ethics Committee of Scientific research project review of the First Hospital of Guangzhou Medical University (No.2013–37 for 2012–2015 Program and N0.2018–53 for ECOPD) and written informed consent was also attained from all the participants.

    Bilirubin Measurement

    At baseline, venous blood samples were collected from eligible participants required to fast for more than 8 hours by trained and professional staff. The samples will be stored at room temperature for at least 30 min and then quantified by biochemical assays performed by the clinical laboratory to test total bilirubin. Bilirubin concentrations were measured or transformed to the nearest 0.06 mg/dL (1 μmol/L).

    Lung Function Measurement

    Spirometry was performed by well-trained staff using a portable spirometer (CareFusion™ MasterScreen Pneumo, Germany) on the same day of bilirubin detection. Only at least three acceptable curves and two reproducible tests can be considered as acceptable for our study. We also performed postbronchodilator Spirometry (salbutamol sulfate aerosol, 400 μg 20min later) and then recorded and retrieved postbronchodilator FEV1, FVC, FEV1pred, FVCpred, and FEV1/FVC. Annual Lung function decline was calculated as the parameters at follow-up minus corresponding baseline values divided by the number of years for follow-up duration. All spirometric maneuvers and quality control were performed following European Respiratory Society/American Thoracic Society standards.19 The definition of GOLD stages in our study was in line with GOLD criteria for COPD, and we considered GOLD 3–4 COPD as severe COPD.17


    A questionnaire interview was carried out using a standardized questionnaire recommended by Zhong N et al.20 We abstracted information about demographic characteristics, risk factors (smoke, occupational exposure, comorbidities, and family history of respiratory diseases), and respiratory symptoms, including any one of wheeze, cough, sputum production, and dyspnea. We classified smoking status as never smoker, former smoker, and current smoker. Subjects who have smoked less than 100 cigarettes in the past are identified as never smokers. Current smokers are referred to someone who were smoking at baseline, and the others are regarded as former smokers. The definition of the smoking index is multiplying the number of packs of cigarettes smoked per day by the number of years the person smoked. We took subjects whose parents, siblings, or children had any of the listed respiratory diseases (chronic bronchitis, emphysema, asthma, COPD, cor pulmonale, bronchiectasis, lung cancer, interstitial lung disease, obstructive sleep apnea hypopnea syndrome) as having a family history of respiratory diseases.

    Statistical Analysis

    All variables are expressed as mean ± SD or number (%). Characteristics of participants among GOLD 1, GOLD 2, and GOLD 3–4 compared using One-Way analysis of variance (ANOVA) test for continuous variables and the χ2 or Fisher's exact test for categorical variables. The associations of TB with pulmonary function parameters at baseline or annual lung function decline were assessed using univariable and multivariable regression models. All linear regression models were adjusted for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities, and family history of respiratory diseases. To ensure the authenticity of the data, there was no imputation for missing values of interest in our analysis. Data analysis was performed using IBM SPSS Version 25.0 and the statistical software R version 4.0.3. Two-sided p < 0.05 were considered statistically significant.


    Baseline Characteristics

    Of the 1053 patients with COPD, 442 were excluded for various reasons (Figure 1). The remaining 612 subjects were divided into three subgroups by GOLD stages. Characteristics of the total group and three subgroups are presented in Table 1. Compared with patients with mild COPD (GOLD 1), patients with moderate-to-severe COPD (GOLD 2, 3 and 4) were more likely to be old, female, breathless and have lower BMI, heavier smoking exposure, more comorbidities, more family history of respiratory diseases as well as worse lung function. There was no significant difference in TB levels among the three subgroups (P = 0.486). The mean follow-up duration for our patients was about two years.

    Table 1 Baseline Characteristics of the Study Subjects

    Figure 1 Flow chart of participant selection.

    Abbreviation: COPD, chronic obstructive pulmonary disease.

    Note: COPD was diagnosed by postbronchodilator FEV1/FVC <0.7.

    Associations of Total Bilirubin with Baseline Lung Function Parameters

    Univariable and multivariable linear regressions of baseline pulmonary function parameters such as FEV1, FEV1pred, FVC, FVCpred, and FEV1/FVC on TB concentrations are shown in Table 2. After adjustment for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities, and family history of respiratory diseases, TB level (μmol/L) was significantly related to FEV1 and FVC in the total COPD patients (β 0.02, 95% CI 0.001~0.02, P = 0.025 and β 0.02, 95% CI 0.002~0.03, P = 0.022, respectively). Stratified by GOLD stages, the relationship between TB and FEV1 was only present in GOLD 1 stage (β 0.01, 95% CI 0.001~0.02, P = 0.032), whereas FVC became tending to be slightly associated with bilirubin (P = 0.054).

    Table 2 Univariable and Multivariable Linear Regression Analysis for TB and Baseline Lung Function Parameters in the Total Group and Subgroups by GOLD Stages

    Total Bilirubin and Annual Lung Function Decline

    Totally, higher bilirubin concentrations were associated with a reduced rate of decline in lung function, which is consistent in the univariable and multivariable regression analysis approximately (Figure 2). In the total COPD group, we found that per 1 μmol/L increase in TB will reduce 4.91 mL/L decline in FEV1 (P = 0.003), 0.21% decline in FEV1pred (P = 0.005), 6.26 mL/L decline in FVC (P = 0.039), and 0.23% in FVCpred (P = 0.023). However, following stratification according to GOLD stages and multi-adjustments, the similar associations of FEV1 and FEV1pred with TB merely existed in GOLD 2 and GOLD 3–4 patients. Besides, bilirubin only showed a protective effect on the rate of decline in airflow limitation (FEV1/FVC) in severe COPD (GOLD 3–4).

    Figure 2 Linear regression analysis for the relationship between bilirubin and annual lung function decline, by overall COPD population and stratified by GOLD stages.

    Notes: Annual Lung function decline was calculated as the parameters at follow-up minus corresponding baseline values divided by the number of years for follow-up duration. Multivariable linear regression analysis models were adjusted for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities and family history of respiratory diseases. Per unit increase of TB in all these models is 1 μmol/L. Crude β means the unstandardized β estimate from univariable analysis, Crude P values mean the P values from univariable analysis, adj.β means the unstandardized β estimate from the multivariable analysis, adj.P values mean the P values from multivariable analysis. Abbreviations see abbreviation section in Table 1.


    In the pooled data from two prospective and longitudinal cohort studies, we found that TB was positively associated with FEV1 in the total COPD population at baseline. Besides, TB also significantly reduced the rate of FEV1 and FEV1pred decline in the total COPD group at follow-up duration after adjustment for age, sex, BMI, smoking status, smoke index, passive smoker, occupational exposure, comorbidities, as well as family history of respiratory diseases. Surprisingly, when stratifying by disease severity according to GOLD stages, relationships significantly persisted only in patients with moderate-to-severe COPD. To our best knowledge, our study was the first to explore TB and lung function in the target COPD population with different GOLD stages.

    What we found between TB and FEV1 were in line with those of Ah YL et al11 who found that higher TB concentration was associated with higher FEV1 and less annual FEV1 decline in the general Koreans and those of Apperley S et al12 who also showed that consistent associations in mild-to-moderate COPD after adjusting for age, sex, race, BMI and baseline measures of lung function. All these demonstrations indicated the potential protective role of TB played on lung function. We could reasonably speculate about the mechanisms of mild higher TB level protecting lung function. Summarily, the most important heme oxygenase that influences the biochemical production of bilirubin is heme oxygenase-1 (HO-1),21 which would be up-regulated by oxidative stress22 and hypoxia.23,24 HO-1 is expressed in pulmonary cells including type II pneumocytes and alveolar macrophages.25 COPD is a chronic pathological process accompanied by endogenously or exogenously produced oxidative stress and inflammation.26,27 Higher HO-1 levels expressed in COPD would increase TB concentrations. Furthermore, bilirubin has been reported to be an endogenous bioactive substance possessing substantial antioxidant activities by several experiments.28–30 Thus, TB may improve the lung function in COPD in this way.

    Another extended finding was that the significant protection effects merely persisted in moderate-to-severe COPD. It may be implied that only when oxidative stress increased to a certain degree can bilirubin perform a function against oxidation. We can get some evidence from the current studies. A Mendelian Randomization analysis using UK Biobank showed that smokers with genetically raised serum bilirubin levels have lower rates of lung cancer and these relationships are strongest in current heavy smokers (20 or more cigarettes per day),31 whereas Hyun et al found that high serum TB was not significantly associated with the presence of COPD in never-smokers.32 Likewise, our data showed that patients in GOLD 2 and GOLD 3–4 had more smoking exposure (more smoking index, pack-yrs). As we know, heavy cigarettes exposure aggravated inflammation and oxidative damage of COPD, which would be suppressed by bilirubin reduction to attenuate pulmonary injury.33 Differently from previous studies,11,13 we found no significant association between TB and airflow limitation (FEV1/FVC) in the total group. The conflicting results may be attributed to the differences of adjusted covariates in the proportion of sex, distribution of age, BMI, smoking status and index, comorbidities, as well as family history of respiratory diseases.

    Our study also has a few limitations. First, the sample size in moderate-to-severe COPD was small, so we could not respectively evaluate the relationship of TB and GOLD 3 COPD or GOLD 4 COPD, given that the participants were community-based. However, GOLD 3 and GOLD 4 were usually incorporated as severe COPD in clinical epidemiology. Second, we only collected one blood sample, which did not allow for continuous evaluation of intraindividual variability, although bilirubin levels are demonstrated to keep stable after adolescence.34 Besides, we could not exclude the influence of alcohol intake on TB for lacking the related information. However, we have excluded other factors affecting bilirubin as we can by incorporating hepatic disease into comorbidities, which may be caused by heavy alcohol consumption.


    In conclusion, we confirmed again that TB is inversely associated with annual lung function decline in FEV1 and FEV1pred in COPD. And that association persists only in moderate-to-severe COPD adjusted for multi-covariates, which implicated the different functional status of TB being in different degrees of COPD severity. It is also suggested that TB may be a biomarker for only moderate-to-severe COPD but not mild COPD. We should focus more on the specific COPD patients with a certain disease severity when validating bilirubin as a biomarker of COPD potentially in future studies, given the protective effects of TB. Besides, further researches are also needed to investigate the mechanisms of TB action on different severity levels of COPD to explain the different influences on lung function decline.


    TB, total bilirubin; COPD, chronic obstructive pulmonary disease; GOLD, the Global Initiative for Chronic Lung Disease; mMRC, Modified Medical Research Council dyspnea; BMI, body mass index; FVC, forced vital capacity; FVC, %predicted, the ratio of FVC to its predicted value; FEV1, forced expiratory volume in the first second; FEV1,%predicted, the ratio of FEV1 to its predicted value; FEV1/FVC, the ratio of FEV1 to FVC; ANOVA, analysis of variance; SD, standard deviation; CI, confidence interval; CVD, cardiovascular disease; ECOPD, the early COPD; HO-1, oxygenase-1.

    Data Sharing Statement

    The datasets used and analyzed in this study are available from the corresponding author on reasonable request.

    Ethics Approval and Consent to Participate

    The original two studies were performed in line with the principles of the Declaration of Helsinki. All the participants from two studies gave written informed consent and two studies were approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (No.2013-37 and No. 2018-53 respectively).


    The authors thank for the contributions of all the subjects who agreed to donate their information for analysis. Besides, the authors thank Bijia Lin, Shaodan Wei and Xiaopeng Ling (State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Nanshan Medicine Innovation Institute of Guangdong Province) for their help in collecting the data.

    Author Contributions

    All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.


    The study was funded by The Nature Key Research and Development Program (2016YFC1304101), the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01s155), the independent project of the State Key Laboratory of Respiratory Diseases (SKLRD-QN-201913), the National Science Foundation of China (81970045), and Zhong Nanshan Medical Development Foundation of Guangdong Province (ZNSA-202003, ZNSA-2020012, ZNSA-2020013).


    All the authors declare they have no real or potential competing interests in this work.


    1. Stocker R, Yamamoto Y, Mcdonagh A, Glazer A, Ames B. Bilirubin Is an Antioxidant of Possible Physiological Importance. Science. 1987;235:43.

    2. Wang H-D, Yamaya M, Okinaga S, et al. Bilirubin Ameliorates Bleomycin-Induced Pulmonary Fibrosis in Rats. Am J Respir Crit Care Med. 2002;165(2):406–411.

    3. Ryter SW, Morse D, Choi AM. Carbon monoxide and bilirubin: potential therapies for pulmonary/vascular injury and disease. Am J Respir Cell Mol Biol. 2007;36(2):175–182.

    4. McCarty MF. “Iatrogenic Gilbert syndrome”–a strategy for reducing vascular and cancer risk by increasing plasma unconjugated bilirubin. Med Hypotheses. 2007;69(5):974–994.

    5. Vitek L, Jirsa M, Brodanova M, et al. Gilbert syndrome and ischemic heart disease a protective effect of elevated bilirubin levels. Atherosclerosis. 2008;198:1–11.

    6. Schwertner HA, Vitek L, Schwertner HA. Gilbert syndrome, UGT1A1*28 allele, and cardiovascular disease risk: possible protective effects and therapeutic applications of bilirubin. Atherosclerosis. 2008;198(1):1–11.

    7. Horsfall LJ, Rait G, Walters K, et al. Serum Bilirubin and Risk of Respiratory Disease and Death. JAMA. 2011;305:691–697.

    8. Monroy-Iglesias MJ, Moss C, Beckmann K, et al. Serum Total Bilirubin and Risk of Cancer: a Swedish Cohort Study and Meta-Analysis. Cancers. 2021;13:21.

    9. Lim JE, Kimm H, Jee SH. Combined effects of smoking and bilirubin levels on the risk of lung cancer in Korea: the severance cohort study. PLoS One. 2014;9(8):e103972.

    10. Brown KE, Sin DD, Voelker H, et al. Serum bilirubin and the risk of chronic obstructive pulmonary disease exacerbations. Respir Res. 2017;18(1):179.

    11. Leem AY, Kim HY, Kim YS, Park MS, Chang J, Jung JY. Association of serum bilirubin level with lung function decline: a Korean community-based cohort study. Respir Res. 2018;19(1):99.

    12. Apperley S, Park HY, Holmes DT, et al. Serum Bilirubin and Disease Progression in Mild COPD. Chest. 2015;148(1):169–175.

    13. Curjuric I, Imboden M, Adam M, et al. Serum bilirubin is associated with lung function in a Swiss general population sample. Eur Respir J. 2014;43(5):1278–1288.

    14. MacDonald DM, Zanotto AD, Collins G, et al. Associations between baseline biomarkers and lung function in HIV-positive individuals. AIDS. 2019;33(4):655–664.

    15. Liu S, Zhou Y, Liu S, et al. Association between exposure to ambient particulate matter and chronic obstructive pulmonary disease: results from a cross-sectional study in China. Thorax. 2017;72(9):788–795.

    16. Wu F, Zhou YM, Peng JQ, et al. Rationale and design of the Early Chronic Obstructive Pulmonary Disease (ECOPD) study in Guangdong, China: a prospective observational cohort study. J Thorac Dis. 2021;12:87.

    17. Agusti A, Vogelmeier C, Papi A, et al. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: 2021 report. Available from: goldcopd.org/2021-gold-reports/. Accessed July 1, 2021.

    18. Duzenli T, Maden O, Tanoglu A, Kaplan M, Yazgan Y. Associations between Gilbert’s syndrome and personality characteristics. Trends Psychiatry Psychother. 2021;43(2):151–158.

    19. Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J. 2005;26(2):319–338.

    20. Zhong N, Wang C, Yao W, et al. Prevalence of chronic obstructive pulmonary disease in China: a large, population-based survey. Am J Respir Crit Care Med. 2007;176(8):753–760.

    21. Tenhunen R, Marver HS, Schmid R. Microsomal Heme Oxygenase. Biol Chem. 1969;244(23):6388–6394.

    22. Carter EP, Garat C, Imamura M. Continual emerging roles of HO-1: protection against airway inflammation. Am J Physiol Lung Cell Mol Physiol. 2004;287:L24–L25.

    23. Christou H, Morita T, Hsieh C-M, et al. Prevention of Hypoxia-Induced Pulmonary Hypertension by Enhancement of Endogenous Heme Oxygenase-1 in the Rat. Circ Res. 2000;86:1224–1229.

    24. Minamino T, Christou H, Hsieh C-M, et al. Targeted expression of heme oxygenase-1 prevents the pulmonary inflammatory and vascular responses to hypoxia. PNAS. 2001;98(15):8798–8803.

    25. Fredenburgh LE, Perrella MA, Mitsialis SA. The role of heme oxygenase-1 in pulmonary disease. Am J Respir Cell Mol Biol. 2007;36(2):158–165.

    26. Kirkham PA, Barnes PJ. Oxidative stress in COPD. Chest. 2013;144(1):266–273.

    27. Harijith A, Natarajan V, Fu P. The Role of Nicotinamide Adenine Dinucleotide Phosphate Oxidases in Lung Architecture Remodeling. Antioxidants(Basel). 2017;6(4):87.

    28. Huang H, Guo M, Liu N, et al. Bilirubin neurotoxicity is associated with proteasome inhibition. Cell Death Dis. 2017;8(6):e2877.

    29. Vitek L. Bilirubin as a signaling molecule. Med Res Rev. 2020;40(4):1335–1351.

    30. Stocker R, Glazert AN, Ames BN. Antioxidant activity of albumin-bound bilirubin. Medical Sciences. 1987;84(2):5918–5922.

    31. Horsfall LJ, Burgess S, Hall I, Nazareth I. Genetically raised serum bilirubin levels and lung cancer: a cohort study and Mendelian randomisation using UK Biobank. Thorax. 2020;75(11):955–964.

    32. Lee H, Hong Y, Lim MN, et al. Inflammatory biomarkers and radiologic measurements in never-smokers with COPD: a cross-sectional study from the CODA cohort. Chron Respir Dis. 2018;15(2):138–145.

    33. Wei J, Zhao H, Fan G, Li J. Bilirubin treatment suppresses pulmonary inflammation in a rat model of smoke-induced emphysema. Biochem Biophys Res Commun. 2015;465(2):180–187.

    34. Wilding P, Rollasox JG, Robinson D. Patterns of change for various biochemical constituents detected in well population screening. Clin chim Acta. 1972;1:375–387.

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    As per recent research published in the international Radiology, CT-detected emphysema is associated with an increased risk of lung cancer, with the risk increasing with the severity of the emphysema.

    Lung cancer is the leading cause of cancer-related death globally, accounting for more than one million fatalities each year since 2000. Lung cancer risk, on the other hand, is maybe powered by identifying treatable risk factors such as chronic lung inflammation, as well as smoking, genetics, food, and environmental exposures.

    Lung cancer severity due to emphysema


    (Photo : JOAO PAULO GUIMARAES/AFP via Getty Images)

    Emphysema is a severe lung condition that causes damage to the alveoli, which are the small air sacs inside the lungs.

    Shortness of breath, mucous coughing, wheezing, and chest tightness are all symptoms. There is no cure, but there are several therapies available to assist control symptoms.

    Emphysema and lung cancer, the main cause of cancer-related deaths globally, have several risk factors.

    Cigarette smoking is a major risk factor for both emphysema and lung cancer, as it causes inflammation, DNA damage, and premature aging.

    According to research co-author Marleen Vonder, Ph.D., of the Department of Epidemiology at University Medical Center Groningen in Groningen, the Netherlands, patients with emphysema who may have never smoked have an elevated risk of lung cancer.

    Dr. Vonder and colleagues gathered publications on the link between emphysema and lung cancer from three big databases for the current study.

    A review of 21 studies involving over 107,000 individuals discovered a link between visual and quantitative, or quantifiable, CT evaluations of emphysema and lung cancer.

    "Our meta-analysis found that not just visually judged but also quantitatively assessed emphysema on CT is related with lung cancer and that this risk rises with severity," Dr. Vonder explained.

    While the data show a relationship between the two fatal illnesses, Dr. Vonder believes that further study is needed before any modifications to clinical care are made.

    Read more: ALERT: Sleep Apnea Linked to Increased Risk of Deadly Lung Cancer

    Signs and risk factors of emphysema

    It is possible to develop emphysema for so many years without detecting any indications or symptoms. Shortness of breath is the most common sign of emphysema, and it generally develops gradually.

    You may begin to avoid activities that make you short of breath so that the symptom does not become an issue until it interferes with everyday chores.

    Emphysema eventually causes shortness of breath even when you are not moving.

    Consult your doctor if you've been experiencing inexplicable difficulty breathing for several months, particularly if it's worsening or interfering with your normal activities.

    Don't dismiss it by telling yourself that it's because you're becoming older or out of shape.

    The following factors enhance your chances of acquiring emphysema:

    Smoking- Cigarette smokers are more likely to develop emphysema, although cigar and pipe users are equally at risk.

    The risk increases as the number of years and quantity of tobacco smoked for all types of smokers.

    Age- Although the lung damage caused by emphysema develops gradually, most persons with tobacco-related emphysema report symptoms between the ages of 40 and 60.

    Secondhand smoke exposure- Secondhand smoking is smoke that you mistakenly inhale from someone else's cigarette, pipe, or cigar.

    It is also known as passive or ambient tobacco smoke.

    Being exposed to secondhand smoke raises your chance of developing emphysema.

    Exposure to fumes or dust during work- You are more prone to get emphysema if you breathe fumes from certain chemicals or dust from grain, cotton, wood, or mining materials. This danger is heightened if you smoke.

    Pollution from both indoor and outdoor sources- Breathing interior pollutants, such as heating fuel fumes, as well as outside pollutants, such as automobile emissions, increases your risk of emphysema.

    Related article: Worsening Air Pollution Could be Responsible For Alarming Rise in Lung Cancer Cases

    © 2022 NatureWorldNews.com All rights reserved. Do not reproduce without permission.

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    UVA Health researchers and their collaborators have developed a better way to predict the risk of chronic obstructive pulmonary disease (COPD), a progressive, potentially deadly form of lung inflammation, for people of non-European ancestry.

    Initial tests of the new, more inclusive tool revealed that it is better at predicting COPD risk for both African-Americans and heavy smokers than existing models that were based on genetic information largely collected from people of European ancestry. The tool’s developers say their approach will allow doctors to better predict COPD risk for individuals of diverse ancestry in the United States and around the world.

    “Our study demonstrates the possibility of learning from large-scale genetic studies performed primarily in European ancestry groups, and then developing prediction models that can be used for prediction of genetic risk in other ancestry groups,” said researcher Ani W. Manichaikul, PhD, of the University of Virginia School of Medicine. “While the current study focus on risk prediction for COPD, we are already looking to apply similar approaches to improve prediction of genetic risk for other diseases.”

    About COPD

    While treatable, COPD is a leading cause of death in the United States and around the globe. Approximately 16 million Americans have COPD, which is a group of lung conditions that includes emphysema and chronic bronchitis. The lung damage caused by COPD is irreversible and accumulates over time. That makes early detection and treatment especially important.

    In recent years, doctors have been able to predict patients’ genetic risk of developing COPD and other common diseases using what are called “polygenic risk scores,” or PRS. These look at the total number of naturally occurring gene variations a person has that predispose them to a disease – in this case, COPD. To date, most large-scale genetic studies available for the study of disease risk have limited representation of certain ancestry groups, including African-American and Hispanic, yielding poorer prediction of disease risk for these groups.

    Manichaikul and her collaborators sought to improve the ability to predict COPD by better reflecting the world’s genetic diversity. To do so, they layered genetic measurements with other molecular measures from a diverse ancestry group that included a combination of European ancestry, African-American and Hispanic individuals from the United States. Building on these resources, they developed what they call “PrediXcan-derived polygenic transcriptome risk score,” or PTRS. This new approach incorporates much more information about the cumulative effects of gene variations in different groups of people. The result is a model that “bears a more direct connection to underlying disease biology than standard PRS approaches,” the researchers report in a new scientific paper.

    The scientists put their new tool to the test by analyzing its ability to predict COPD in tens of thousands of participants in studies conducted by the Trans-Omics for Precision Medicine (TOPMed) program sponsored by the National Institutes of Health’s National Heart, Lung and Blood Institute (NHLBI). 

    PTRS, they found, was better at predicting COPD in African-Americans and better at predicting moderate to severe COPD in heavy, longtime smokers. Perhaps unsurprisingly (considering it was developed to better reflect non-European populations), PTRS was less effective than PRS in predicting COPD in people of European ancestry. But the availability of multiple “crystal balls” to predict COPD in different populations moves us an important step closer to true precision medicine – medicine tailored to each individual.

    “So far, we have shown that by building on genomic data combined with gene expression data from diverse ancestry individuals, we can improve prediction of genetic risk for some people,” said Manichaikul, of UVA’s Center for Public Health Genomics and Department of Public Health Sciences. “Looking forward, we are excited to think about how we can build on other collections of molecular data from diverse ancestry individuals and keep working on improved approaches for prediction of genetic risk for other diseases.”

    Findings Published

    The researchers have described their tool in the American Journal of Human Genetics. The research team included Xiaowei Hu, Stephen S. Rich and Manichaikul from UVA. Hu, Rich and Manichaikul declared no conflicts of interest related to the work. A full list of disclosures is included in the paper.

    The work was funded by NHLBI grants R01 HL131565, R01 HL153248, R01 HL135142, R01 HL137927, R01 HL089856, R01 HL147148 and K01-HL129039.

    To keep up with the latest medical research news from UVA, subscribe to the Making of Medicine blog at makingofmedicine.virginia.edu.

    Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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    Dublin, May 04, 2022 (GLOBE NEWSWIRE) -- The "Asthma and COPD Drugs Market by Diseases and Medication Class (Combination Drugs, Inhaled Corticosteroids, Short Acting Beta Agonists, Long Acting Beta Agonists, Leukotriene Antagonists, Anticholinergics, and Others.): Global Opportunity Analysis and Industry Forecast, 2021--2030" report has been added to ResearchAndMarkets.com's offering.

    The asthma and COPD drugs market was valued at $32988.7 million in 2020 and is projected to reach $52049.54 million by 2030, registering a CAGR of 4.64%% from 2021 to 2030.

    Asthma is a respiratory disorder, in which there is narrowing of bronchi that leads to difficulty in breathing. Asthma patients may suffer with shortness of breath, chest tightness or pain, and wheezing sound while exhaling. Chronic Obstructive Pulmonary Diseases (COPD) is a group of respiratory disorders, which mainly includes emphysema and chronic bronchitis.

    Asthma and COPD can be diagnosed by performing X-ray imaging, nitric oxide test, and sputum examination test. Asthma and COPD have bronchoconstriction as common symptoms and can be treated with corticosteroids, anticholinergic drugs, and long acting beta agonists. Patients that have asthma may suffer with sudden bronchoconstriction, generally known as asthmatic attack. Asthmatic attack can be treated with bronchodilators. In emergency conditions, broncho dilators are delivered with specially designed pump for quick relief.

    The increase in prevalence of asthma globally drives the growth of asthma and COPD drugs market. For instance, according to report of Global Asthma Network published on 2020, asthma kills around 1000 people every day and affects as many as 339 million people globally. In addition, increase in awareness about the respiratory diseases in people propels the growth of asthma and COPD drugs market. The R&D in the treatment of the asthma by manufacturers and researchers also contributes in the growth of market. Furthermore, initiatives taken by respective governments to treat and improve the lifestyle of asthma & COPD patients boosts market growth. The rise in number of hospitals and well-developed healthcare infrastructure further contributes in market growth.

    In addition, increase in the tobacco smoking habits in people and he rise in air pollution contribute in the growth of the asthma and COPD drugs market. However, the high cost of treatment and lack of awareness in people about asthma & COPD are expected to limit the growth of market.

    The asthma and COPD drugs market is segmented on the basis of diseases, medication class, and region. By diseases, the market is divided into asthma and COPD. By medication class, the market is divided into combination drugs, inhaled corticosteroids (ics), short acting beta agonists (saba), long acting beta agonists (laba), leukotriene antagonists (lta), anticholinergics and others. By Region, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

    The major companies profiled in the report include Abbott Laboratories, AstraZeneca, Boehringer Ingelheim International GmbH, GlaxoSmithKline PLC., Hoffmann-La Roche Ltd, Novartis AG, Organon, Sanofi, Teva Pharmaceutical Industries Ltd., and Vectura Group plc.

    Key Benefits

    • The report provides an in-depth analysis of the global asthma and COPD drugs market size along with the current trends and future estimations to elucidate the imminent investment pockets
    • It offers market analysis from 2021 to 2030, which is expected to enable the stakeholders to capitalize on the prevailing opportunities in the market
    • A comprehensive analysis of the region assists to understand the regional market and facilitate strategic business planning and determine prevailing opportunities
    • The profiles and growth strategies of the key players are thoroughly analyzed to understand the competitive outlook of the global asthma and COPD drugs market growth

    Key Topics Covered:

    Chapter 1: Introduction

    Chapter 2: Executive Summary

    Chapter 3: Market Landscape
    3.1. Market Definition and Scope
    3.2. Key Findings
    3.2.1. Top Investment Pockets
    3.2.2. Top Winning Strategies
    3.3. Porter's Five Forces Analysis
    3.3.1. Bargaining Power of Suppliers
    3.3.2. Threat of New Entrants
    3.3.3. Threat of Substitutes
    3.3.4. Competitive Rivalry
    3.3.5. Bargaining Power Among Buyers
    3.4. Market Share Analysis/Top Player Positioning
    3.4.1. Market Share Analysis/Top Player Positioning 2020
    3.5. Market Dynamics
    3.5.1. Drivers
    3.5.2. Restraints
    3.5.3. Opportunities
    3.6. Covid-19 Impact Analysis

    Chapter 4: Asthma and Copd Drugs Market, by Diseases
    4.1. Market Overview
    4.1.1Market Size and Forecast, by Diseases
    4.2. Asthma
    4.2.1. Key Market Trends, Growth Factors and Opportunities
    4.2.2. Market Size and Forecast, by Region
    4.2.3. Market Share Analysis, by Country
    4.3. Copd
    4.3.1. Key Market Trends, Growth Factors and Opportunities
    4.3.2. Market Size and Forecast, by Region
    4.3.3. Market Share Analysis, by Country

    Chapter 5: Asthma and Copd Drugs Market, by Medication Class
    5.1. Market Overview
    5.1.1Market Size and Forecast, by Medication Class
    5.2. Combination Drugs
    5.2.1. Key Market Trends, Growth Factors and Opportunities
    5.2.2. Market Size and Forecast, by Region
    5.2.3. Market Share Analysis, by Country
    5.3. Short Acting Beta Agonists (Saba)
    5.3.1. Key Market Trends, Growth Factors and Opportunities
    5.3.2. Market Size and Forecast, by Region
    5.3.3. Market Share Analysis, by Country
    5.4. Long Acting Beta Agonists (Laba)
    5.4.1. Key Market Trends, Growth Factors and Opportunities
    5.4.2. Market Size and Forecast, by Region
    5.4.3. Market Share Analysis, by Country
    5.5. Leukotriene Antagonists (Lta)
    5.5.1. Key Market Trends, Growth Factors and Opportunities
    5.5.2. Market Size and Forecast, by Region
    5.5.3. Market Share Analysis, by Country
    5.6. Anticholinergics
    5.6.1. Key Market Trends, Growth Factors and Opportunities
    5.6.2. Market Size and Forecast, by Region
    5.6.3. Market Share Analysis, by Country
    5.7. Others
    5.7.1. Key Market Trends, Growth Factors and Opportunities
    5.7.2. Market Size and Forecast, by Region
    5.7.3. Market Share Analysis, by Country

    Chapter 6: Asthma and Copd Drugs Market, by Region

    Chapter 7: Company Profiles
    7.1. Abbott Laboratories
    7.1.1. Company Overview
    7.1.2. Key Executives
    7.1.3. Company Snapshot
    7.1.4. Operating Business Segments
    7.1.5. Product Portfolio
    7.1.6. Business Performance
    7.1.7. Key Strategic Moves and Developments
    7.2. Astrazeneca plc
    7.2.1. Company Overview
    7.2.2. Key Executives
    7.2.3. Company Snapshot
    7.2.4. Operating Business Segments
    7.2.5. Product Portfolio
    7.2.6. Business Performance
    7.2.7. Key Strategic Moves and Developments
    7.3. Boehringer Ingelheim International GmbH
    7.3.1. Company Overview
    7.3.2. Key Executives
    7.3.3. Company Snapshot
    7.3.4. Operating Business Segments
    7.3.5. Product Portfolio
    7.3.6. Business Performance
    7.3.7. Key Strategic Moves and Developments
    7.4. GlaxoSmithKline plc
    7.4.1. Company Overview
    7.4.2. Key Executives
    7.4.3. Company Snapshot
    7.4.4. Operating Business Segments
    7.4.5. Product Portfolio
    7.4.6. Business Performance
    7.4.7. Key Strategic Moves and Developments
    7.5. Hoffmann-La Roche Ltd
    7.5.1. Company Overview
    7.5.2. Key Executives
    7.5.3. Company Snapshot
    7.5.4. Operating Business Segments
    7.5.5. Product Portfolio
    7.5.6. Business Performance
    7.5.7. Key Strategic Moves and Developments
    7.6. Novartis AG
    7.6.1. Company Overview
    7.6.2. Key Executives
    7.6.3. Company Snapshot
    7.6.4. Operating Business Segments
    7.6.5. Product Portfolio
    7.6.6. Business Performance
    7.6.7. Key Strategic Moves and Developments
    7.7. Organon
    7.7.1. Company Overview
    7.7.2. Key Executives
    7.7.3. Company Snapshot
    7.7.4. Operating Business Segments
    7.7.5. Product Portfolio
    7.7.6. Business Performance
    7.7.7. Key Strategic Moves and Developments
    7.8. Sanofi
    7.8.1. Company Overview
    7.8.2. Key Executives
    7.8.3. Company Snapshot
    7.8.4. Operating Business Segments
    7.8.5. Product Portfolio
    7.8.6. Business Performance
    7.8.7. Key Strategic Moves and Developments
    7.9. Teva Pharmaceutical Industries Ltd
    7.9.1. Company Overview
    7.9.2. Key Executives
    7.9.3. Company Snapshot
    7.9.4. Operating Business Segments
    7.9.5. Product Portfolio
    7.9.6. Business Performance
    7.9.7. Key Strategic Moves and Developments
    7.10. Vectura Group plc
    7.10.1. Company Overview
    7.10.2. Key Executives
    7.10.3. Company Snapshot
    7.10.4. Operating Business Segments
    7.10.5. Product Portfolio
    7.10.6. Business Performance
    7.10.7. Key Strategic Moves and Developments

    For more information about this report visit www.researchandmarkets.com/r/8ebiue


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    Doctors and scientists see a direct link between lung function and quality of life, yet lung health often declines with age. As a caregiver for an older adult, it’s incredibly important to do everything you can to keep your loved one’s lungs healthy, but poor air quality, allergies, existing disease and the general effects of aging can work against us. 

    After all, the lungs can be greatly affected by changes brought about by aging: Thinning bones can change the shape of the ribcage and impact the ability to expand and contract during breathing. Muscles that support breathing may also become weakened, lowering the oxygen level in the body. Changes to lung tissue may also cause airways to close easily, and air sacs can lose their shape, making it hard to breathe. 

    On top of those changes, seasonal allergies can also get worse with age and give rise to a condition known as geriatric rhinitis—mucus and discomfort in the nose due to aging. In fact, mucus buildup (also known as phlegm or sputum) is a common symptom in chronic lung diseases such as COPD (including chronic bronchitis and emphysema), cystic fibrosis, bronchiectasis, nontuberculous mycobacteria (NTM) lung disease or asthma. 

    This mucus buildup is hard to avoid, too: The World Health Organization (WHO) recently reported that 99% of all people in the world breathe air that exceeds WHO quality limits and threatens their health. Nitrogen dioxide, found in higher levels in unhealthy air, is associated with respiratory diseases, particularly asthma, and leads to respiratory symptoms such as coughing, wheezing or difficulty breathing, hospital admissions and visits to emergency rooms.

    All this paints a dire picture for seniors, but the good news is that older adults don’t need to suffer through breathing issues or be forced to turn to potentially dangerous prescription medications. In fact, certain herbs and supplements may help reduce mucus buildup in the lungs and protect against the ill effects of phlegm buildup. 

    Introducing mullein

    A common plant with furry leaves and small yellow flowers, mullein is an herb with a long history of use for many respiratory diseases. The leaves can relieve irritation in the body’s mucus membranes in the nose, mouth and throat and can also work as an expectorant, which thins and loosens phlegm—breaking up congestion associated with a cold or other respiratory problems, just like a modern cough medicine.

    “Leaves from mullein are helpful with lung congestion and mucus production,” writes Suzy Cohen, a registered pharmacist, in the Marco Eagle. “It appears to work by dilating capillaries and therefore increasing circulation. This helps relieve stagnancy and congestion, making it an interesting adjunctive remedy to people with COPD, bronchitis, asthma and dry coughs.”

    While it’s possible to harvest and produce your own mullein leaf teas and tinctures, BetterLungs by Betterbrand thankfully offers a modern-day version of the mullein leaf herbalists have used for decades. Designed to support healthy respiratory and immune systems, preserve stamina and manage mucus, these pills contain mullein leaf, elderberry (used for traditional immune support), vitamin D and other beneficial herbs. No prescription is necessary, and users rave about improvements to breathing and lack of stuffy noses.

    “I can’t believe how this cleared up my breathing on the first day,” Charlene P. commented. “I stopped coughing all the time and feel a whole lot better!”

    The company recommends two capsules each morning for the typical senior looking for complete respiratory and immune support, or four capsules (two in the morning and two in the evening) for those who may need additional support, including smokers, travelers and those who especially suffer from seasonal changes. A 30-day supply (60 capsules) is $34.95, but those who wish to subscribe to a monthly delivery can save 15%.

    The company also offers BetterLungs Immunity with IMMUSE, designed to reduce fatigue from exercise and help with work productivity by supporting the immune system. 

    Learn more about BetterLungs and the other products by Betterbrand at trybetterbrand.com.

    Supporting healthy lungs

    Working with your loved one to support and maintain lung function can be a major component in ensuring they live long, happy, comfortable lives. A combination of supplements, exercise and a healthy environment is a great way to proactively fend off the natural toll aging takes on the lungs. 

    Reduce exposure to triggers

    Decrease exposure to allergy triggers by taking note of your loved one’s environment during flare-ups. Staying indoors with closed windows is the best way to avoid triggers such as pollen, grass and pine trees. Inside, try to eliminate dust and mold buildup. Fans and air purifiers can make a difference in improving circulation and eliminating allergens. Your loved one should also bathe and change clothes after being outdoors in allergy season.

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