Researchers have developed a new genetic tool for predicting the risk of chronic obstructive pulmonary disease (COPD) in individuals of non-European ancestry.
It was found to more effectively determine COPD risk for both African Americans and heavy smokers than existing models that are primarily built on genetic information from people of European ancestry.
The new tool is expected to work better at identifying risk factors and predicting COPD among individuals of diverse backgrounds both in the U.S. and worldwide, the researchers said.
“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,” Ani W. Manichaikul, PhD, a professor at the University of Virginia and the study’s senior author, said in a press release.
“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,” added Manichaikul, of Virginia’s School of Medicine.
The study, “Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program,” was published in the American Journal of Human Genetics.
A polygenic risk score, or PRS, is a method of predicting a person’s genetic predisposition to develop a particular disease. It is based on the number of genetic variants, or mutations, that people carry in their genome that is associated with a specific disease.
Studies demonstrate that PRS can provide early identification of genetic risk factors for COPD — an inflammatory condition of the lungs characterized by cough with mucus and shortness of breath.
However, PRS is derived from genetic information primarily collected from people of European ancestry. As a result, this limits the predictive ability of PRS for COPD in other ethnic groups, such as African Americans, other Black people, and Hispanics.
To make prediction tools more effective, Manichaikul and her colleagues developed the PrediXcan-derived polygenic transcriptome risk score, or PTRS. It combines genomic data with gene expression information collected from those of European ancestry, as well as African American and Hispanic individuals in the U.S.
PrediXcan in recent years has become a widely used gene-based method for testing associations between disease and gene expression (activity), prioritizing the genes that are more likely to cause a disease characteristic.
For COPD, the PTRS was constructed on large-scale genomic studies related to lung function. Such function was measured by FEV1, which indicates the amount of air a person can exhale in one second, and the ratio of FEV1 to FVC, which measures the total amount of air exhaled during the FEV test.
The resulting model “bears a more direct connection to underlying disease biology than standard PRS approaches,” the team wrote.
Researchers then examined the ability of PTRS to predict COPD in people who participated in studies conducted by the Trans-Omics for Precision Medicine (TOPMed) program. This included 29,381 multi-ethnic participants from TOPMed population/family-based groups, and 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Participants were categorized based on smoking status, a major contributor to COPD.
Compared with PRS, PTRS showed a stronger association with COPD for African Americans. PTRS also was better at predicting moderate to severe COPD among heavy smokers — those with 40 or more pack-years of smoking. Of note, pack-years is a way of determining how much a person has smoked in their lifetime; it is calculated by multiplying the number of cigarette packs smoked in a day by the number of years a person has smoked.
In contrast, and not unexpectedly, PRS was better than PTRS at predicting COPD in people of European ancestry.
Across different ethnic groups, PTRS was significantly higher than PRS for FEV1 and FEV1/FVC and in different smoking status groups.
“Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk,” the authors wrote.
“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. “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.”