Chronic Respiratory Disease Genetics

Asthma is a chronic lung disease characterized by variable airflow limitation that is influenced by genetic and environmental factors. Well-known disparities by race/ethnicity and socioeconomic status in asthma prevalence and severity have been noted in the U.S. for decades. Via genome-wide association studies (GWAS), several genetic loci have been linked with asthma risk and response to drugs used for its treatment. Although most of these genetics studies have been conducted in populations of European ancestry, genetic variants that may contribute to racial/ethnic differences in asthma risk and drug response have also been identified. Two important asthma pharmacogenetic traits we study are bronchodilator drug response and glucocorticoid drug response. In ongoing work, we participate in whole genome sequencing (WGS) studies that are part of the National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program. The results of asthma genetics studies have been valuable to identify genes that are associated with asthma-related traits, and several candidates are the subject of ongoing functional validation studies. Two examples of asthma gene association studies are:

In addition to performing GWAS of specific traits, we are interested in what we can learn about phenotype definitions by contrasting results from association analyses. Biobanks enable this work because large-scale genomics data is available for people along with a variety of demographic and clinical data. Selecting appropriate phenotypes for studies with biobanks is challenged by the difficulty of validating them. For example, the guideline definition of COPD that is based on objective spirometry measures has been preferred in GWAS conducted with epidemiologic cohorts, but spirometry measures are seldom available for biobank participants. Defining COPD based on International Classification of Disease (ICD) codes or self-reported measures is highly feasible in biobanks, but it remains unclear whether the misclassification inherent in these definitions prevents the discovery of genetic variants that contribute to COPD. Using the UK Biobank resource, we found that there was poor agreement in classification of participants as having COPD based on these three definitions. Contrasting GWAS results for these definitions, however, provided insights into what patient characteristics each trait may capture, as described in this paper:

Precision medicine, which refers to understanding how differences in a person’s biology, exposures and lifestyle can help determine approaches to prevent and treat disease, includes the development of biomarkers that allow the tailoring of treatments to individuals. Genetics studies are one aspect of precision medicine, as loci identified may, in addition to providing biological insights into genes that contribute to conditions, lead to improvements in population health via the identification of select groups of individuals whose clinical manifestation of symptoms is based on a specific underlying alteration of a common biological pathway. Several complex conditions, including asthma and COPD, are known to consist of heterogenous forms termed endotypes, each of which has an ideal treatment strategy that matches the underlying pathophysiological disruption. In ongoing work, we (and many other groups!) seek to use genetics to identify specific disease endotypes that may have clinical utility. Two reports that expound on these issues are:

Asthma and COPD are prototypical complex diseases for which studying genetic and environmental factors simultaneously may lead to greater breakthroughs in understanding of pathophysiology than studying genetics or the environment in isolation. However, there have been few attempts to simultaneously and comprehensively address the influence of genetics and the environment on asthma and COPD. While gene-by-environment studies have been performed, most are statistically underpowered to detect associations, and the heterogeneity of environmental and phenotype measures obtained across studies has limited the potential to conduct meta-analyses. We seek to identify environmental factors that are associated with asthma and COPD in specific geographic locations, understanding the relationship among these factors and demographic variables, and subsequently, conducting gene expression and variation studies that consider environmental factors in greater detail. A natural extension of these efforts will be to conduct expansive environmental genomics studies that take advantage of the increasing availability of health information technologies, including smartphone and inhaler medication sensors, to collect large amounts of real-time environmental and medication use data that can inform genomics studies.