Human genomics · 2025
Association between hot spring residency and dry eye disease: a crossover gene-environment interaction (GxE) study in Taiwan.
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Wu Hsin-Yu, Chang Kao-Jung, Chiu Wei, Wang Ching-Yun, Lin Yi-Chen, Hsu Yu-Tien, Wen Yuan-Chih, Chiang Pin-Hsuan, Chen Yu-Hsiang, Dai He-Jhen, Lu Chia-Hsin, Chen Yi-Cheng, Tsai Han-Ying, Chen Yu-Chun, Hsu Chih-Hung, Chiou Shih-Hwa, Yang Yi-Ping, Hsieh Ai-Ru, Hsu Chih-Chien
Аннотация
BACKGROUND/AIMS: 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). After 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 with their genetic predisposition.
RESULTS: After socioeconomic covariate adjustment, prevalence of dry eye disease (DED) was significantly associated with hot spring distribution. Through single nucleotide polymorphisms (SNPs) discovery and subsequent PPI pathway aggregation, CDKL2 kinase pathways were significantly enriched in hot-spring specific DED functional SNPs. Notably, PRS predicted disease well in hot spring regions (AUC = 0.9168). Hot spring and discovered SNPs contributed to crossover GxE effect on DED (relative risk (RR)G+E-= 0.99; RRG-E+ = 0.35; RRG+E+ = 2.04).
CONCLUSION: We identified hot-spring exposure as a modifiable risk in the PRS-predicted GxE context of DED.
METHODS: A complete genetic and demographic registry comprising 129,451 individuals was obtained from Taiwan Biobank (TWB). After 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 with their genetic predisposition.
RESULTS: After socioeconomic covariate adjustment, prevalence of dry eye disease (DED) was significantly associated with hot spring distribution. Through single nucleotide polymorphisms (SNPs) discovery and subsequent PPI pathway aggregation, CDKL2 kinase pathways were significantly enriched in hot-spring specific DED functional SNPs. Notably, PRS predicted disease well in hot spring regions (AUC = 0.9168). Hot spring and discovered SNPs contributed to crossover GxE effect on DED (relative risk (RR)G+E-= 0.99; RRG-E+ = 0.35; RRG+E+ = 2.04).
CONCLUSION: We identified hot-spring exposure as a modifiable risk in the PRS-predicted GxE context of DED.