Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastroenterol. Dec 21, 2026; 32(47): 124207
Published online Dec 21, 2026. doi: 10.3748/wjg.124207
Published online Dec 21, 2026. doi: 10.3748/wjg.124207
Integrating metabolomics, clinical factors, and genetic risk for colorectal cancer risk prediction: Model development and internal-external cross-validation
Liang-Tang Zeng, Jun-Nan Hu, Feng Liu, Digestive Endoscopy Center, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200072, China
Ming-Hui Pang, Qin-Xing Cao, Neng-Yi Hou, Department of Geriatric General Surgery, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, Sichuan Province, China
Co-first authors: Liang-Tang Zeng and Jun-Nan Hu.
Co-corresponding authors: Neng-Yi Hou and Feng Liu.
Author contributions: Zeng LT and Hu JN contributed equally to this article, they are the co-first authors of this manuscript; Zeng LT drafted the manuscript; Zeng LT, Hu JN, Cao QX, and Hou NY performed data processing, statistical analyses and result interpretation; Zeng LT and Liu F designed the research study; Hou NY and Liu F supervised the study and critically revised the manuscript, study supervision, methodological oversight and critical revision, they contributed equally to this article, they are the co-corresponding authors of this manuscript; and all authors read and approved the final manuscript.
AI contribution statement: Not applicable.
Supported by the Special Project for Clinical Research in Health Industry of Shanghai Municipal Health Commission, No. 202540026; and the Cultivation Grant for Clinical and Basic Integration Research of Shanghai Tenth People’s Hospital, No. SYYYRH2025006.
Institutional review board statement: The UK Biobank received ethical approval from the North West–Haydock Research Ethics Committee and operates as a Research Tissue Bank, approval No. 21/NW/0157.
Clinical trial registration statement: This was a prospective observational cohort study, and no health-related intervention was assigned.
Informed consent statement: All UK Biobank participants provided written informed consent before enrollment and data collection.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
CONSORT 2010 statement: The authors have read the CONSORT 2010 Statement, and the manuscript was prepared and revised according to the CONSORT 2010 Statement.
Data sharing statement: UK Biobank participant-level data are available to approved researchers through the UK Biobank data-access process and cannot be redistributed by the authors. Analytic code is available from the corresponding author upon reasonable request.
Corresponding author: Feng Liu, Chief Physician, Full Professor, Digestive Endoscopy Center, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, No. 301 Yanchang Road, Shanghai 200072, China. 1905041@tongji.edu.cn
Received: June 9, 2026
Revised: July 14, 2026
Accepted: July 27, 2026
Published online: December 21, 2026
Processing time: 140 Days and 15.7 Hours
Revised: July 14, 2026
Accepted: July 27, 2026
Published online: December 21, 2026
Processing time: 140 Days and 15.7 Hours
Core Tip
Core Tip: Using data from 468095 UK Biobank participants, we evaluated 325 nuclear magnetic resonance-based plasma metabolic markers and developed a seven-feature metabolomic risk score for incident colorectal cancer. The score stratified long-term risk and modestly improved prediction when added to an adapted QCancer clinical model and a polygenic risk score. Internal-external cross-validation across 10 geographical clusters supported consistency and geographical transportability within the UK Biobank. These findings suggest that metabolomics may complement, rather than replace, established clinical and genetic risk assessment. Independent external validation and cost-effectiveness evaluation are required before clinical implementation.