Metabolite Predictors of Breast and Colorectal Cancer Risk in the Women’s Health Initiative
Metabolomics has been used extensively to capture the exposome. We investigated whether prospectively measured metabolites provided predictive power beyond well-established risk factors among 758 women with adjudicated cancers [<i>n</i> = 577 breast (BC) and <i>n</i> = 181 colorectal (CRC)] and <i>n</i> = 758 controls with available specimens (collected mean 7.2 years prior to diagnosis) in the Women's Health Initiative Bone Mineral Density subcohort. Fasting samples were analyzed by LC-MS/MS and lipidomics in serum, plus GC-MS and NMR in 24 h urine. For feature selection, we applied LASSO regression and Super Learner algorithms. Prediction models were subsequently derived using logistic regression and Super Learner procedures, with performance assessed using cross-validation (CV). For BC, metabolites did not increase predictive performance over established risk factors (CV-AUCs~0.57). For CRC, prediction increased with the addition of metabolites (median CV-AUC across platforms increased from ~0.54 to ~0.60). Metabolites related to energy metabolism: adenosine, 2-hydroxyglutarate, <i>N</i>-acetyl-glycine, taurine, threonine, LPC (FA20:3), acetate, and glycerate; protein metabolism: histidine, leucic acid, isoleucine, <i>N</i>-acetyl-glutamate, allantoin, <i>N</i>-acetyl-neuraminate, hydroxyproline, and uracil; and dietary/microbial metabolites: myo-inositol, trimethylamine-<i>N</i>-oxide, and 7-methylguanine, consistently contributed to CRC prediction. Energy metabolism may play a key role in the development of CRC and may be evident prior to disease development.
Authors
- Hayley Purcell
- Haiwei Gu (ORCID: https://orcid.org/0000-0002-7598-5022)
- Johanna W. Lampe (ORCID: https://orcid.org/0000-0003-2717-3780)
- Ying Huang (ORCID: https://orcid.org/0000-0002-9655-7502)
- Daniel Raftery (ORCID: https://orcid.org/0000-0003-2467-8118)
- Marian L. Neuhouser (ORCID: https://orcid.org/0000-0002-3876-0000)
- Howard D. Strickler (ORCID: https://orcid.org/0000-0001-6397-7466)
- Cheng Zheng (ORCID: https://orcid.org/0000-0002-6562-870X)
- Lesley F. Tinker (ORCID: https://orcid.org/0000-0003-2469-1929)
- Ross L. Prentice (ORCID: https://orcid.org/0000-0003-2849-5757)
- Fred K. Tabung (ORCID: https://orcid.org/0000-0001-8193-7150)
- Shirley A.A. Beresford (ORCID: https://orcid.org/0000-0002-1631-3541)
- G. A. Nagana Gowda (ORCID: https://orcid.org/0000-0002-0544-7464)
- Sandi L. Navarro (ORCID: https://orcid.org/0000-0002-4260-2486)
- Danijel Djukovic (ORCID: https://orcid.org/0000-0001-5954-8810)
- Brian D. Williamson (ORCID: https://orcid.org/0000-0002-7024-548X)
Institutions
- Albert Einstein College of Medicine (US)
- Kaiser Permanente Washington Health Research Institute (US)
- University of Washington (US)
- Fred Hutch Cancer Center (US)
- The Ohio State University (US)
- Arizona State University (US)
- University of Nebraska Medical Center (US)
Publication Details
- Journal
- Metabolites
- Published
- 2024-08-20
- DOI
- https://doi.org/10.3390/metabo14080463
- Citations
- 6
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- U.S. Department of Health and Human Services
- Brigham and Women's Hospital
- Ohio State University
- Wake Forest University
- University of Pittsburgh
- National Computational Infrastructure
- University of Nevada, Reno
- MedStar Health Research Institute
- National Institutes of Health
- University at Buffalo
- National Heart, Lung, and Blood Institute
- National Cancer Institute
- National Institute of Diabetes and Digestive and Kidney Diseases
- Office of Research Infrastructure Programs, National Institutes of Health