Multi-omic definition of metabolic obesity through adipose tissue–microbiome interactionsShow others and affiliations
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
National Category
Endocrinology and Diabetes Public Health, Global Health and Social Medicine Medical Genetics and Genomics
Identifiers
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
Note
QC 20260127
2026-01-212026-01-212026-01-27Bibliographically approved