Integrating genome‐wide association study summaries and element‐gene interaction datasets identified multiple associations between elements and complex diseases. Issue 2 (18th December 2017)

• Record Type: Journal Article
• Authors: He, Awen; Wang, Wenyu; Prakash, N. Tejo; Tinkov, Alexey A.; Skalny, Anatoly V.; Wen, Yan; Hao, Jingcan; Guo, Xiong; Zhang, Feng
• Is Part Of: Genetic epidemiology. Volume 42:Issue 2(2018)
• Page Start: 168
• Page End: 173
• Publication Date: 2017-12-18
• Subjects: complex diseases -- elements -- gene set enrichment analysis; Genetic epidemiology -- Periodicals; Heredity -- Periodicals; Medical geography -- Periodicals; 614
• DOI: 10.1002/gepi.22106
• Languages: English
• ISSNs: 0741-0395

Abstract

ABSTRACT: Chemical elements are closely related to human health. Extensive genomic profile data of complex diseases offer us a good opportunity to systemically investigate the relationships between elements and complex diseases/traits. In this study, we applied gene set enrichment analysis (GSEA) approach to detect the associations between elements and complex diseases/traits though integrating element‐gene interaction datasets and genome‐wide association study (GWAS) data of complex diseases/traits. To illustrate the performance of GSEA, the element‐gene interaction datasets of 24 elements were extracted from the comparative toxicogenomics database (CTD). GWAS summary datasets of 24 complex diseases or traits were downloaded from the dbGaP or GEFOS websites. We observed significant associations between 7 elements and 13 complex diseases or traits (all false discovery rate (FDR) < 0.05), including reported relationships such as aluminum vs. Alzheimer's disease (FDR = 0.042), calcium vs. bone mineral density (FDR = 0.031), magnesium vs. systemic lupus erythematosus (FDR = 0.012) as well as novel associations, such as nickel vs. hypertriglyceridemia (FDR = 0.002) and bipolar disorder (FDR = 0.027). Our study results are consistent with previous biological studies, supporting the good performance of GSEA. Our analyzing results based on GSEA framework provide novel clues for discovering causal relationships between elements and complex diseases.