Metabolic variation reflects dietary exposure in a multi-ethnic Asian population
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Understanding how diet shapes metabolism across diverse populations is essential to improving nutrition and health. Biomarkers reflecting diet are explored largely in European and American populations, but the food metabolome is highly complex and varies across region and culture. We assessed 1,055 plasma metabolites and 169 foods/beverages in 8,391 multi-ethnic Asian individuals and carried out diet–metabolite association analyses. Using machine learning, we developed multi-biomarker panels and composite scores for key foods, beverages and overall diet quality. Here we show these biomarker panels can be used to objectively assess dietary intakes in the Asian multi-ethnic population and can explain variances in intake prediction models better than single biomarkers. The identified diet–metabolite relationships are reproducible over time and improve prediction of clinical outcomes (insulin resistance, diabetes, body mass index, carotid intima-media thickness and hypertension), compared to self-reports. Our findings show insights into multi-ethnic diet-related metabolic variations and an opportunity to link exposure to population health outcomes.
Date Issued
2025-09-01
Date Acceptance
2025-07-25
Citation
Nature Metabolism, 2025, 7, pp.1939-1954
ISSN
2522-5812
Publisher
Nature Research
Start Page
1939
End Page
1954
Journal / Book Title
Nature Metabolism
Volume
7
Copyright Statement
Copyright © 2025, The Author(s), under exclusive licence to Springer Nature Limited. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40962943
PII: 10.1038/s42255-025-01359-x
Subjects
BIOMARKERS
CITRUS-FRUIT
CONSUMPTION
CORONARY-HEART-DISEASE
Endocrinology & Metabolism
ERGOTHIONEINE
IDENTIFICATION
Life Sciences & Biomedicine
MARKERS
PATTERNS
PLATFORM
RISK
Science & Technology
Publication Status
Published
Coverage Spatial
Germany
Date Publish Online
2025-09-17