This proposal is in response to PAR-13-382, supporting secondary data analyses of existing large genomic datasets for the purpose of identifying gene-by-environment (GxE) interactions. Lung function and its decline in older adulthood is likely the result of genetic and environmental influences. Cigarette smoking is a key environmental context for loss of lung function over time. Genome-wide association studies (GWAS) identified 26 genetic loci associated with cross-sectional spirometric measures of lung function. Recent GWAS of the longitudinal change in lung function have identified additional novel loci. To date, there is only one published genome-wide study of GxE interaction on lung function that considers smoking as the environment of interest. This genome-wide GxE study used common variation and cross-sectional information on lung function and smoking to identify three novel loci not previously associated with lung function. In aggregate, these published studies made important contributions to understanding the etiology of lung function, and were facilitated by the organizational structure and support of the Cohorts for Heart and Aging in Genomic Epidemiology (CHARGE) consortium and the CHARGE Pulmonary Working Group. Additional investigation is warranted to further understand how smoking interacts with genetic factors to influence lung function. The objective of this proposal is to elucidate the complex interplay of genes and environment underlying lung function using state-of-the-art statistical methods and analysis strategies that leverage available data resources. Ongoing work within the CHARGE Pulmonary Working Group includes analysis of data from the Illumina HumanExome BeadChip (the exome chip) for ~33,800 individuals of European ancestry with spirometric measures of lung function, all of whom also have longitudinal measures of smoking history and lung function. An additional ~6,000 individuals of African ancestry have measures of lung function, smoking history, and exome chip data, and ~3,800 also have longitudinal measures. Spirometric measures include forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and their ratio (FEV1/FVC). These measures of lung function are important clinical tools for diagnosing pulmonary disease, classifying its severity, and evaluating its progression over time. The large volume of phenotype and exome chip data available within the CHARGE consortium provides a unique, cost-effective opportunity to apply new analytical approaches and methods. This application has two novel aspects: 1) investigation of rare variation and environmental interactions, and 2) investigation of longitudinal measures of environmental factors. The proposed research represents the next step in the efforts to investigate the interplay of genetic variation and environmental factors influencing lung function. Results from this study may disclose novel genetic susceptibilities to smoking exposure or a greater understanding of the role of smoking in the development, progression, and severity of declining lung function.
Decline in lung function in older adulthood is likely the result of both genetic and environmental influences, such as cigarette smoking. In order to understand how lung function is affected by the interaction between smoking environment and genetic factors, we will use state-of-the-art statistical methods and analysis strategies that leverage available data resources, including rare variation in protein coding regions of the genome and longitudinal measures of lung function and smoking history. Results from this study may disclose novel genetic susceptibilities to smoking exposure or a greater understanding of the role of smoking in the development, progression, and severity of declining lung function.
