Genome-wide interaction study of gene-by-occupational exposures on respiratory symptoms

Abstract: Respiratory symptoms are important indicators of respiratory diseases. Both genetic and environmental factors contribute to respiratory symptoms development but less is known about gene-environment interactions. We aimed to assess interactions between single nucleotide polymorphisms (SNPs) and occupational exposures on respiratory symptoms cough, dyspnea and phlegm. As identification cohort LifeLines I (n = 7976 subjects) was used. Job-specific exposure was estimated using the ALOHA + job exposure matrix. SNP-by-occupational exposure interactions on respiratory symptoms were tested using logistic regression adjusted for gender, age, and current smoking. SNP-by-exposure interactions with a p-value <10−4 were tested for replication in two independent cohorts: LifeLines II (n = 5260) and the Vlagtwedde-Vlaardingen cohort (n = 1529). The interaction estimates of the replication cohorts were meta-analyzed using PLINK. Replication was achieved when the meta-analysis p-value was <0.05 and the interaction effect had the same direction as in the identification cohort. Additionally, we assessed whether replicated SNPs associated with gene expression by analyzing if they were cis-acting expression quantitative trait loci (eQTL) in lung tissue. In the replication meta-analysis, sixteen out of 477 identified SNP-by-occupational exposure interactions had a p-value <0.05 and 9 of these interactions had the same direction as in the identification cohort. Several identified loci were plausible candidates for respiratory symptoms, such as TMPRSS9, SERPINH1, TOX3, and ARHGAP18. Three replicated SNPs were cis-eQTLs for FCER1A, CHN1, and TIMM13 in lung tissue. Taken together, this genome-wide SNP-by-occupational exposure interaction study in relation to cough, dyspnea, and phlegm identified several suggestive susceptibility genes. Further research should determine if these genes are true susceptibility loci for respiratory symptoms in relation to occupational exposures.

Conclusions: This paper presents a GWIS on the risk of respiratory symptoms cough, dyspnea and phlegm, which investigated interactions between SNPs and several types of occupational exposures (i.e. dust, gases and fumes, pesticides, solvents, and metals). We identified some plausible candidate genes that may be involved in biological pathways leading to respiratory symptoms, i.e. FCER1A, CHN1, TMPRSS9, SERPINH1, TOX3, and ARHGAP18. The next step should be to determine if the identified genes are true susceptibility loci for respiratory symptoms. Findings from this study may eventually contribute to the understanding of pathways underlying the development of respiratory symptoms, which may lead to the identification of novel therapeutic targets and provide targeted protection measures to environmental exposures, especially for the genetically susceptible population.