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Multi-omic definition of metabolic obesity through adipose tissue–microbiome interactions
Wallenberg Laboratory, Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden; Medical Department III – Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany; Department of Clinical Physiology Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden.ORCID iD: 0000-0001-9901-1815
Wallenberg Laboratory, Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
Wallenberg Laboratory, Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
Center for Health and Performance, Department of Food and Nutrition and Sport Science, University of Gothenburg, Gothenburg, Sweden.
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2026 (English)In: Nature Medicine, ISSN 1078-8956, E-ISSN 1546-170X, Vol. 32, no 1, p. 113-125Article in journal (Refereed) Published
Abstract [en]

Obesity’s metabolic heterogeneity is not fully captured by body mass index (BMI). Here we show that deep multi-omics phenotyping of 1,408 individuals defines a metabolome-informed obesity metric (metBMI) that captures adipose tissue-related dysfunction across organ systems. In an external cohort (n = 466), metBMI explained 52% of BMI variance and more accurately reflected adiposity than other omics models. Individuals with higher-than-expected metBMI had 2–5-fold higher odds of fatty liver disease, diabetes, severe visceral fat accumulation and attenuation, insulin resistance, hyperinsulinemia and inflammation and, in bariatric surgery (n = 75), achieved 30% less weight loss. This obesogenic signature aligned with reduced microbiome richness, altered ecology and functional potential. A 66-metabolite panel retained 38.6% explanatory power, with 90% covarying with the microbiome. Mediation analysis revealed a bidirectional, metabolite-centered host–microbiome axis, mediated by lipids, amino acids and diet-derived metabolites. These findings define an adipose-linked, microbiome-connected metabolic signature that outperforms BMI in stratifying cardiometabolic risk and guiding precision interventions.

Place, publisher, year, edition, pages
Springer Nature , 2026. Vol. 32, no 1, p. 113-125
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Endocrinology and Diabetes Public Health, Global Health and Social Medicine Medical Genetics and Genomics
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URN: urn:nbn:se:kth:diva-375758DOI: 10.1038/s41591-025-04009-7ISI: 001652371100001PubMedID: 41482560Scopus ID: 2-s2.0-105026349968OAI: oai:DiVA.org:kth-375758DiVA, id: diva2:2030833
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QC 20260127

Available from: 2026-01-21 Created: 2026-01-21 Last updated: 2026-01-27Bibliographically approved

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Uhlén, Mathias

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