{"title":"Hot Spring Residency and Disease Association: a Crossover Gene-Environment Interaction (GxE) Study in Taiwan","authors":"H.-Y. Wu, K.-J. Chang, W. Chiu, C.-Y. Wang, Y.-T. Hsu, Y.-C. Wen, P.-H. Chiang, Y.-H. Chen, H.-J. Dai, C.-H. Lu, Y.-C. Chen, H.-Y. Tsai, C.-H. Hsu, A.-R. Hsieh, S.-H. Chiou, Y.-P. Yang, C.-C. Hsu","doi":"10.1101/2024.07.29.24311167","DOIUrl":null,"url":null,"abstract":"Background The advent of genetic biobanking has powered gene-environment interaction (GxE) studies in various disease contexts. Therefore, we aimed to discover novel GxE effects that address hot spring residency as a risk to inconspicuous disease association. Methods A complete genetic and demographic registry comprising 129,451 individuals was obtained from Taiwan Biobank (TWB). Geographical disease prevalence was analyzed to identify putative disease association with hot-spring residency, multivariable regression and logistic regression were rechecked to exclude socioeconomic confounders in geographical-disease association. Genome-wide association study (GWAS), gene ontology (GO), and protein-protein interaction (PPI) analysis identified predisposing genetic factors among hotspring-associated diseases. Lastly, a polygenic risk score (PRS) model was formulated to stratify environmental susceptibility in accord to their genetic predisposition. Results After socioeconomic covariate adjustment, prevalence of dry eye disease (DED) and valvular heart disease (VHD) was significantly associated with hot spring distribution. Through single nucleotide polymorphisms (SNPs) discovery and subsequent PPI pathway aggregation, CDKL2 and BMPR2 kinase pathways were significantly enriched in hot-spring specific DED and VHD functional SNPs. Notably, PRS predicted disease well in hot spring regions (PRSDED: AUC=0.9168; PRSVHD AUC=0.8163). Hot spring and discovered SNPs contributed to crossover GxE effect on both DED (relative risk (RR)G+E-=0.99; RRG+E+=0.35; RRG+E+=2.04) and VHD (RRG+E-=0.99; RRG+E+=0.49; RRG+E+=2.01). Conclusion We identified hot-spring exposure as a modifiable risk in the PRS predicted GxE context of DED and VHD.","PeriodicalId":506788,"journal":{"name":"medRxiv","volume":"9 36","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.29.24311167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background The advent of genetic biobanking has powered gene-environment interaction (GxE) studies in various disease contexts. Therefore, we aimed to discover novel GxE effects that address hot spring residency as a risk to inconspicuous disease association. Methods A complete genetic and demographic registry comprising 129,451 individuals was obtained from Taiwan Biobank (TWB). Geographical disease prevalence was analyzed to identify putative disease association with hot-spring residency, multivariable regression and logistic regression were rechecked to exclude socioeconomic confounders in geographical-disease association. Genome-wide association study (GWAS), gene ontology (GO), and protein-protein interaction (PPI) analysis identified predisposing genetic factors among hotspring-associated diseases. Lastly, a polygenic risk score (PRS) model was formulated to stratify environmental susceptibility in accord to their genetic predisposition. Results After socioeconomic covariate adjustment, prevalence of dry eye disease (DED) and valvular heart disease (VHD) was significantly associated with hot spring distribution. Through single nucleotide polymorphisms (SNPs) discovery and subsequent PPI pathway aggregation, CDKL2 and BMPR2 kinase pathways were significantly enriched in hot-spring specific DED and VHD functional SNPs. Notably, PRS predicted disease well in hot spring regions (PRSDED: AUC=0.9168; PRSVHD AUC=0.8163). Hot spring and discovered SNPs contributed to crossover GxE effect on both DED (relative risk (RR)G+E-=0.99; RRG+E+=0.35; RRG+E+=2.04) and VHD (RRG+E-=0.99; RRG+E+=0.49; RRG+E+=2.01). Conclusion We identified hot-spring exposure as a modifiable risk in the PRS predicted GxE context of DED and VHD.