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Whole Genome Sequencing to Identify Novel Genetic Variation and Gene-By-Air Pollution Interactions that Influence Lung Function in Minority Children
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A5820 - Whole Genome Sequencing to Identify Novel Genetic Variation and Gene-By-Air Pollution Interactions that Influence Lung Function in Minority Children
Author Block: A. C. Mak1, M. J. White1, K. L. Keys1, J. R. Liberto1, S. Huntsman1, D. Hu1, C. Eng1, S. S. Oh1, M. A. Seibold2, E. G. Burchard1; 1University of California San Francisco, San Francisco, CA, United States, 2Integrated Center for Genes, Enviroment and Health, National Jewish Health, Denver, CO, United States.
Introduction Baseline lung function, quantified as forced expiratory volume per second (FEV1), is one of the standard diagnostic criterion used by pulmonary clinicians to identify and categorize lung diseases. FEV1 is strongly influenced by genetics with heritability estimates as high as 55%. Specifically, numerous genetic loci associated with FEV1 have been identified, and there is also evidence that genetic ancestry plays a role in FEV1 variation. Several epidemiological studies have identified early life exposure to air pollution as a significant predictor of baseline lung function. Although there have been numerous genetic and epidemiological studies aimed at identifying the genetic and environmental factors responsible for variation in FEV1, the majority of the heritability in this phenotype remains undefined. FEV1 is a complex phenotype that has been shown to be heavily influenced by both environmental and genetic factors. We hypothesize that a portion of the “hidden heritability” for FEV1 may be explained by gene-by-environment (GxE) interactions.
Methods We performed whole genome sequencing on 1,133 Puerto Rican children with asthma and available early-life exposure to air pollution data. We then constructed multiplicative interaction models (single nucleotide polymorphism [SNP] x air pollution). We then performed a GWIS (genome-wide interaction study) to test the effect of each interaction model on variation in FEV1. All regression models were adjusted for age, sex, global ancestry, and the main effects of the specified SNP and air pollution.
Results and Conclusions We identified several GxE interactions associated with FEV1 in Puerto Rican children with asthma. Our preliminary results indicate that GxE interactions play an important role in FEV1 variation in this population.
Author Block: A. C. Mak1, M. J. White1, K. L. Keys1, J. R. Liberto1, S. Huntsman1, D. Hu1, C. Eng1, S. S. Oh1, M. A. Seibold2, E. G. Burchard1; 1University of California San Francisco, San Francisco, CA, United States, 2Integrated Center for Genes, Enviroment and Health, National Jewish Health, Denver, CO, United States.
Introduction Baseline lung function, quantified as forced expiratory volume per second (FEV1), is one of the standard diagnostic criterion used by pulmonary clinicians to identify and categorize lung diseases. FEV1 is strongly influenced by genetics with heritability estimates as high as 55%. Specifically, numerous genetic loci associated with FEV1 have been identified, and there is also evidence that genetic ancestry plays a role in FEV1 variation. Several epidemiological studies have identified early life exposure to air pollution as a significant predictor of baseline lung function. Although there have been numerous genetic and epidemiological studies aimed at identifying the genetic and environmental factors responsible for variation in FEV1, the majority of the heritability in this phenotype remains undefined. FEV1 is a complex phenotype that has been shown to be heavily influenced by both environmental and genetic factors. We hypothesize that a portion of the “hidden heritability” for FEV1 may be explained by gene-by-environment (GxE) interactions.
Methods We performed whole genome sequencing on 1,133 Puerto Rican children with asthma and available early-life exposure to air pollution data. We then constructed multiplicative interaction models (single nucleotide polymorphism [SNP] x air pollution). We then performed a GWIS (genome-wide interaction study) to test the effect of each interaction model on variation in FEV1. All regression models were adjusted for age, sex, global ancestry, and the main effects of the specified SNP and air pollution.
Results and Conclusions We identified several GxE interactions associated with FEV1 in Puerto Rican children with asthma. Our preliminary results indicate that GxE interactions play an important role in FEV1 variation in this population.
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