Integration of GWAS and eQTL Analysis to Identify Risk Loci and Susceptibility Genes for Gastric Cancer

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Genome-wide association studies (GWAS) have identified several susceptibility loci for gastric cancer (GC), but the majority of identified single-nucleotide polymorphisms (SNPs) fall within the non-coding region and are likely to exert their biological function by modulating gene expression. To systematically estimate expression-associated SNPs (eSNPs) that confer genetic predisposition to GC, we evaluated the associations of 314,203 stomach tissue-specific eSNPs with GC risk in three GWAS datasets (2,631 cases and 4,373 controls). Subsequently, we conducted a gene-based analysis to calculate the cumulative effect of eSNPs through sequence kernel association combined test and Sherlock integrative analysis. At the SNP-level, we identified two novel variants (rs836545 at 7p22.1 and rs1892252 at 6p22.2) associated with GC risk. The risk allele carriers of rs836545-T and rs1892252-G exhibited higher expression levels of DAGLB (P = 3.70 × 10–18) and BTN3A2 (P = 3.20 × 10–5), respectively. Gene-based analyses identified DAGLB and FBXO43 as novel susceptibility genes for GC. DAGLB and FBXO43 were significantly overexpressed in GC tissues than in their adjacent tissues (P = 5.59 × 10–7 and P = 3.90 × 10–6, respectively), and high expression level of these two genes was associated with an unfavorable prognosis of GC patients (P = 1.30 × 10–7 and P = 7.60 × 10–3, respectively). Co-expression genes with these two novel genes in normal stomach tissues were significantly enriched in several cancer-related pathways, including P53, MAPK and TGF-beta pathways. In summary, our findings confirm the importance of eSNPs in dissecting the genetic basis of GC, and the identified eSNPs and relevant genes will provide new insight into the genetic and biological basis for the mechanism of GC development.
Funding Information
  • National Natural Science Foundation of China (81872702)
  • Jiangsu Provincial Key Research and Development Program (BE2019698)
  • China Postdoctoral Science Foundation (2019TQ0157)

This publication has 42 references indexed in Scilit: