A Multiomic Approach Integrating Genomic and Metabolomic Data Highlights Colorectal Cancer Pathways

Numerous genetic variants have been identified by genome-wide association studies as being associated with colorectal cancer (CRC) risk. Metabolome-wide association analysis was performed for 187 CRC-associated genetic variants using genomic data and untargeted 1H nuclear magnetic resonance urine metabolomics from 1951 Airwave Health Monitoring Study participants. We identified statistically significant associations between seven CRC single-nucleotide polymorphisms (SNPs) and urinary metabolites. This included SNPs within or close to RHPN2 with sucrose (P = 1.2 × 10-7), SLC6A18 with amino acids (P = 6.9 × 10-5 with tyrosine, P = 9.9 × 10-5 with leucine), and MAP2K5 and BMP2 with gut microbial metabolites (P = 1.6 × 10-4 and P = 4.4 × 10-4). The most significant correlation was followed by functional experiments in Caco-2 colon cancer cells. CRISPR-mediated knockout of a 48-nt RHPN2 intronic region containing rs10411210 in colon cancer cells compromised cell growth. RNA sequencing was performed in the two sets of clones (3 edited and 3 unedited) followed by pathway enrichment, and gene ontology analysis depicted extensive deregulation of genes (448 up- and 195 downregulated) involved in cell division and several metabolic processes. Overall, these findings demonstrate that integrating genetic and metabolomic data highlights the importance of the RHPN2 intronic locus in CRC potentially through metabolic processes affecting excretion of dietary and other metabolites.