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Metabolites
Special Issues
Metabolomics-Based Biomarkers for Nutrition and Health
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Metabolomics-Based Biomarkers for Nutrition and Health

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Nutrition and Metabolism".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 3098

Special Issue Editors

Dr. Cheng Zheng

E-Mail Website
Guest Editor
Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA
Interests: causal inference; measurement error modeling; biomarker evaluation; metabolomics; nutritional epidemiology; risk of chronic diseases
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Daniel Raftery

E-Mail Website
Guest Editor
Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA, USA
Interests: metabolite profiling; metabolite method development; disease diagnostics; systems biology; NMR spectroscopy; mass spectrometry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Metabolites focuses on methodology and applied research in the area of metabolomics-based biomarker discovery, evaluation, validation and application for nutrition and health.

With technological advancement, various types of high-dimensional objective measurements such as metabolomics data provide great opportunities to develop biomarkers for nutrition and health outcomes. Recent developments in the area showed the usefulness of metabolomics as biomarkers for dietary intake for various macronutrients and helped study the association between dietary intakes and disease outcomes. Additionally, studies showed that metabolites can be used as biomarkers for an early detection of diseases and predict the risk of developing future diseases. However, there are many remaining gaps to be filled. The high dimensionality of these novel metabolomics data combined with their own measurement uncertainty present noteworthy challenges for statistical analysis in biomarker discovery. The potential heterogeneity in metabolomics platforms and technical variation between labs raised the question of the reliability, reproducibility and generalizability of developed metabolite-based biomarkers. Additional topics to be addressed include incorporating biological metabolomics pathway information and finding interpretable biomarkers, integrating multiple metabolomics data with other measurements and personal characteristics in predicting nutrition and disease status.

We hope that this Special Issue will provide a platform for researchers from various disciplines to share their latest findings, discuss emerging challenges and propose novel solutions. We welcome submissions that cover a wide range of topics, including, but not limited to:

  • Development of a metabolomics-based biomarkers for nutrition and/or health-related outcomes;
  • Validation and/or integration of developed metabolomics-based biomarkers;
  • Utilization of metabolomics-based biomarkers for association studies relating nutrition and health;
  • Early diagnosis of disease and prediction of intervention/treatment response utilizing metabolomics data.

Dr. Cheng Zheng
Prof. Dr. Daniel Raftery
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomarker
  • metabolomics
  • nutritional epidemiology
  • disease diagnostics and prevention
  • risk prediction

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Published Papers (2 papers)

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20 pages, 590 KiB  
Article
Metabolite Predictors of Breast and Colorectal Cancer Risk in the Women’s Health Initiative
by Sandi L. Navarro, Brian D. Williamson, Ying Huang, G. A. Nagana Gowda, Daniel Raftery, Lesley F. Tinker, Cheng Zheng, Shirley A. A. Beresford, Hayley Purcell, Danijel Djukovic, Haiwei Gu, Howard D. Strickler, Fred K. Tabung, Ross L. Prentice, Marian L. Neuhouser and Johanna W. Lampe
Metabolites 2024, 14(8), 463; https://doi.org/10.3390/metabo14080463 - 20 Aug 2024
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Abstract
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 [n = 577 breast (BC) and n = 181 colorectal (CRC)] and n = [...] Read more.
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 [n = 577 breast (BC) and n = 181 colorectal (CRC)] and n = 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, N-acetyl-glycine, taurine, threonine, LPC (FA20:3), acetate, and glycerate; protein metabolism: histidine, leucic acid, isoleucine, N-acetyl-glutamate, allantoin, N-acetyl-neuraminate, hydroxyproline, and uracil; and dietary/microbial metabolites: myo-inositol, trimethylamine-N-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. Full article
(This article belongs to the Special Issue Metabolomics-Based Biomarkers for Nutrition and Health)
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Review

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16 pages, 249 KiB  
Review
Intake Biomarkers for Nutrition and Health: Review and Discussion of Methodology Issues
by Ross L. Prentice
Metabolites 2024, 14(5), 276; https://doi.org/10.3390/metabo14050276 - 10 May 2024
Cited by 1 | Viewed by 1308
Abstract
Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, [...] Read more.
Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group’s recent contributions to the Women’s Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets. Full article
(This article belongs to the Special Issue Metabolomics-Based Biomarkers for Nutrition and Health)
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