Abstract
Genome-wide association studies have reported 56 independently associated colorectal cancer (CRC) risk variants, most of which are non-coding and believed to exert their effects by modulating gene expression. The computational method PrediXcan uses cis-regulatory variant predictors to impute expression and perform gene-level association tests in GWAS without directly measured transcriptomes. In this study, we used reference datasets from colon (n = 169) and whole blood (n = 922) transcriptomes to test CRC association with genetically determined expression levels in a genome-wide analysis of 12,186 cases and 14,718 controls. Three novel associations were discovered from colon transverse models at FDR ≤ 0.2 and further evaluated in an independent replication including 32,825 cases and 39,933 controls. After adjusting for multiple comparisons, we found statistically significant associations using colon transcriptome models with TRIM4 (discovery P = 2.2 × 10− 4, replication P = 0.01), and PYGL (discovery P = 2.3 × 10− 4, replication P = 6.7 × 10− 4). Interestingly, both genes encode proteins that influence redox homeostasis and are related to cellular metabolic reprogramming in tumors, implicating a novel CRC pathway linked to cell growth and proliferation. Defining CRC risk regions as one megabase up- and downstream of one of the 56 independent risk variants, we defined 44 non-overlapping CRC-risk regions. Among these risk regions, we identified genes associated with CRC (P < 0.05) in 34/44 CRC-risk regions. Importantly, CRC association was found for two genes in the previously reported 2q25 locus, CXCR1 and CXCR2, which are potential cancer therapeutic targets. These findings provide strong candidate genes to prioritize for subsequent laboratory follow-up of GWAS loci. This study is the first to implement PrediXcan in a large colorectal cancer study and findings highlight the utility of integrating transcriptome data in GWAS for discovery of, and biological insight into, risk loci.
Highlights
It is estimated that genetic variants explain 12–35% of the heritability in colorectal cancer (CRC) risk (Lichtenstein et al 2000; Czene et al 2002; Jiao et al 2014)
Genetic variant predictors of gene expression from both colon transverse and whole blood transcriptomes were used to test the association of CRC risk with imputed gene expression
We identified strong gene targets in several known Genome-Wide Association Studies (GWAS) loci, including genes that were previously not reported as putative candidates
Summary
It is estimated that genetic variants explain 12–35% of the heritability in colorectal cancer (CRC) risk (Lichtenstein et al 2000; Czene et al 2002; Jiao et al 2014). Given that most of the associated loci do not include coding variants, a large portion of CRC genetic risk is thought to be explained by regulatory variation that modulates the expression of target genes. This hypothesis is supported by the observation that CRC risk variants are enriched in colon expression quantitative trait loci (eQTLs) (Hulur et al 2015) and active regulatory regions of colorectal enhancers (Bien et al 2017). This evidence highlights the value of studying transcriptional regulation in relation to CRC risk
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