Zhang, RuyangZhao, YangChu, MinjieMehta, AWei, YongyueLiu, YaoXun, PengchengBai, JianlingYu, HaoSu, LiZhang, HongxiHu, ZhibinShen, HongbingChen, FengChristiani, David2013-05-072013Zhang, 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): e59035.1932-6203http://nrs.harvard.edu/urn-3:HUL.InstRepos:10611678Background: 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.en-USBiologyComputational BiologyGenomicsGenome Analysis ToolsGenetic ScreensGenome-Wide Association StudiesPopulation GeneticsGenetic PolymorphismGeneticsHuman GeneticsPopulation BiologyEpidemiologyGenetic EpidemiologyMedicineNon-Clinical MedicineEnvironmental HealthPublic HealthOccupational and Industrial HealthPulmonologyChronic Obstructive Pulmonary DiseasesEnvironmental and Occupational Lung DiseasesInterstitial Lung DiseasesJournal Article2013-05-0710.1371/journal.pone.0059035