Background:The etiology of Colorectal cancer(CRC) is not fully understood. Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study(n=1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2>0.01(Nmetabolite=58) were applied to predict levels of metabolites in two large consortia with a combined sample size of ~46,300 cases and 59,200 controls of European and ~21,700 cases and 47,400 controls of East Asian(EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with CRC risk in logistic regressions within each racial group, after which the results were combined by meta-analysis. Results:Of the 58 metabolites tested, 24 metabolites were significantly associated with CRC risk(BH-FDR<0.05) in the European population(odds ratios [ORs] ranged from 0.91 to 1.06;P-values ranged from 0.02 to 6.4x10-8). Twenty one of the twenty-four associations were replicated in the EA population(ORs ranged from 0.26 to 1.69,BH-FDR<0.05). Additionally, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with CRC risk in the EA population only(OREA:1.94,1.60-2.36,P=2.6x10-11;OREUR:1.01,0.99-1.04,P=0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols(TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups(PEUR-EA-Het<0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of CRC. Conclusions:This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data. Impact:The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and East Asian populations.

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