ArticleNature metabolism2025
Metabolic variation reflects dietary exposure in a multi-ethnic Asian population.
Article in Nature metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Validating a Multibiomarker Panel for the Assessment of Quantity and Quality of Plant Foods in the Diet (PLAENTI): Protocol for a Parallel Group-Designed Randomized Controlled Trial.JMIR research protocols · 2026Trial
- Adversity, adiposity, nutrition and metabolic well-being in multi-ethnic Asia.Nature metabolism · 2026Review
- The Health for Life in Singapore (HELIOS) Study: delivering precision medicine research for Asian populations.Nature communications · 2025Article
- Plasma Metabolite Profiles of Children with Autism Spectrum Disorder.Metabolites · 2025Article
- Metabolomics and nutrient intake reveal metabolite-nutrient interactions in metabolic syndrome: insights from the Korean Genome and Epidemiology Study.Nutrition journal · 2025Article
- Nuclear regulatory disturbances precede and predict the development of Type-2 diabetes in Asian populations.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
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Authors and funding
24 authors.
Funding
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.
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Registered trials
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