Publication: A Large Scale Gene-Centric Association Study of Lung Function in Newly-Hired Female Cotton Textile Workers with Endotoxin Exposure
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Date
2013
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Public Library of Science
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Zhang, Ruyang, Yang Zhao, Minjie Chu, Amar Mehta, Yongyue Wei, Yao Liu, Pengcheng Xun, et al. 2013. A large scale gene-centric association study of lung function in newly-hired female cotton textile workers with endotoxin exposure. PLoS ONE 8(3): e59035.
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Abstract
Background: Occupational exposure to endotoxin is associated with decrements in pulmonary function, but how much variation in this association is explained by genetic variants is not well understood. Objective: We aimed to identify single nucleotide polymorphisms (SNPs) that are associated with the rate of forced expiratory volume in one second (FEV1) decline by a large scale genetic association study in newly-hired healthy young female cotton textile workers. Methods: DNA samples were genotyped using the Illumina Human CVD BeadChip. Change rate in FEV1 was modeled as a function of each SNP genotype in linear regression model with covariate adjustment. We controlled the type 1 error in study-wide level by permutation method. The false discovery rate (FDR) and the family-wise error rate (FWER) were set to be 0.10 and 0.15 respectively. Results: Two SNPs were found to be significant (P<6.29×\(10^{−5}\)), including rs1910047 (P = 3.07×\(10^{−5}\), FDR = 0.0778) and rs9469089 (P = 6.19×\(10^{−5}\), FDR = 0.0967), as well as other eight suggestive (P<5×\(10^{−4}\)) associated SNPs. Gene-gene and gene-environment interactions were also observed, such as rs1910047 and rs1049970 (P = 0.0418, FDR = 0.0895); rs9469089 and age (P = 0.0161, FDR = 0.0264). Genetic risk score analysis showed that the more risk loci the subjects carried, the larger the rate of FEV1 decline occurred (Ptrend = 3.01×\(10^{−18}\)). However, the association was different among age subgroups (P = 7.11×\(10^{−6}\)) and endotoxin subgroups (P = 1.08×\(10^{−2}\)). Functional network analysis illustrates potential biological connections of all interacted genes. Conclusions: Genetic variants together with environmental factors interact to affect the rate of FEV1 decline in cotton textile workers.
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Keywords
Biology, Computational Biology, Genomics, Genome Analysis Tools, Genetic Screens, Genome-Wide Association Studies, Population Genetics, Genetic Polymorphism, Genetics, Human Genetics, Population Biology, Epidemiology, Genetic Epidemiology, Medicine, Non-Clinical Medicine, Environmental Health, Public Health, Occupational and Industrial Health, Pulmonology, Chronic Obstructive Pulmonary Diseases, Environmental and Occupational Lung Diseases, Interstitial Lung Diseases
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