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

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 
Citation
 CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, Vol.31(6) : 1216-1226, 2022-06 
Journal Title
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
ISSN
 1055-9965 
Issue Date
2022-06
MeSH
Asians ; Case-Control Studies ; Colorectal Neoplasms* / epidemiology ; Colorectal Neoplasms* / genetics ; Colorectal Neoplasms* / metabolism ; Glycerophospholipids ; Humans ; Lipids ; Metabolomics / methods
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.
Full Text
https://aacrjournals.org/cebp/article/31/6/1216/699221/Large-scale-Integrated-Analysis-of-Genetics-and
DOI
10.1158/1055-9965.EPI-21-1008
Appears in Collections:
4. Graduate School of Public Health (보건대학원) > Graduate School of Public Health (보건대학원) > 1. Journal Papers
Yonsei Authors
Jung, Keum Ji(정금지) ORCID logo https://orcid.org/0000-0003-4993-0666
Jee, Sun Ha(지선하) ORCID logo https://orcid.org/0000-0001-9519-3068
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/189527
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