Large-scale Integrated Analysis of Genetics and Metabolomic Data Reveals Potential Links Between Lipids and Colorectal Cancer Risk

Overview

Journal Cancer Epidemiol Biomarkers Prev

Specialties Biochemistry
Oncology
Public Health

Date 2022 Mar 10

PMID 35266989

Authors

Xiang Shu

Zhishan Chen

Jirong Long

Xingyi Guo

Yaohua Yang

Conghui Qu

Yoon-Ok Ahn

Qiuyin Cai

Graham Casey

Stephen B Gruber

Jeroen R Huyghe

Sun Ha Jee

Mark A Jenkins

Wei-Hua Jia

Keum Ji Jung

Yoichiro Kamatani

Dong-Hyun Kim

Jeongseon Kim

Sun-Seog Kweon

Loic Le Marchand

Koichi Matsuda

Keitaro Matsuo

Polly A Newcomb

Jae Hwan Oh

Jennifer Ose

Isao Oze

Rish K Pai

Zhi-Zhong Pan

Paul D P Pharoah

Mary C Playdon

Ze-Fang Ren

Robert E Schoen

Aesun Shin

Min-Ho Shin

Xiao-Ou Shu

Xiaohui Sun

Catherine M Tangen

Chizu Tanikawa

Cornelia M Ulrich

Franzel J B van Duijnhoven

Bethany van Guelpen

Alicja Wolk

Michael O Woods

Anna H Wu

Ulrike Peters

Wei Zheng

Affiliations

Soon will be listed here.

Abstract

Background: The etiology of colorectal cancer 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 approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer 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 colorectal cancer risk [Benjamini-Hochberg FDR (BH-FDR) < 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10-8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR < 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60-2.36, P = 2.6 × 10-11; OREUR: 1.01, 95% CI, 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 colorectal cancer.

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 EA populations.

Citing Articles

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PMID: 37730576 PMC: 10510155. DOI: 10.1186/s12964-023-01271-5.

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