Genome-wide association study of biochemical traits based on eQTL-SNPs in Korean

Most of genome-wide association studies consider genes that are located closest to single nucleotide polymorphisms (SNPs) that are highly significant association loci; however, the significance of the associations between SNPs and candidate genes has not been fully determined. Fortunately, recent achievements of ENCODE project provide the information of genomewide functional variants (i.e. RegulomeDB websites) such as expression quantitative trait loci (eQTL-SNPs). In this study, we propose an approach that uses eQTL SNPs to support the functional relationships between an SNP and a candidate gene in a genome-wide association study. The study subjects (n=8,842) were previously reported in the KARE consortium and were tested the associations between eQTL-SNPs (n=24,235) and 10 biochemical measures (fasting glucose levels, BUN, serum albumin levels, AST, ALT, gamma GTP, total cholesterol, HDL cholesterol, triglycerides, and LDL cholesterol) by linear regression analysis. As results, we identified that a total of 17 eQTL-SNPs were significantly associated with the biochemical traits after the multiple comparison p-values adjusted by Bonferroni correction. The each alternative allele of the 17 eQTL-SNPs is likely to correlate with one of the following gene expression changes in more than one tissue or cell lines: B3GALT4, CPSF7, NRG3, MYL2, FAM169A. Conclusively, we could identify the functionally linked genes in expression levels the biochemical traits, and those eQTL-SNPs discovered from GWAS analysis might be applied to other genome-wide association studies.