Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Multi-omic definition of metabolic obesity through adipose tissue–microbiome interactions

Chakaroun, Rima M. ; Pradhan, Meenakshi ; Björnson, Elias ; Arvidsson, Daniel LU ; Fridolfsson, Jonatan ; Gummesson, Anders ; Schoeler, Marc ; Mitteregger, Matthias ; Smith, Gustav J. LU orcid and Larsson, Ingrid LU orcid , et al. (2026) In Nature Medicine 32(1). p.113-125
Abstract

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... (More)

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.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Medicine
volume
32
issue
1
pages
13 pages
publisher
Nature Publishing Group
external identifiers
  • pmid:41482560
  • scopus:105026349968
ISSN
1078-8956
DOI
10.1038/s41591-025-04009-7
language
English
LU publication?
yes
additional info
Publisher Copyright: © The Author(s) 2026.
id
a44f893d-11e0-469f-8253-12bc7d05a1b6
date added to LUP
2026-03-23 14:13:35
date last changed
2026-05-04 19:09:40
@article{a44f893d-11e0-469f-8253-12bc7d05a1b6,
  abstract     = {{<p>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.</p>}},
  author       = {{Chakaroun, Rima M. and Pradhan, Meenakshi and Björnson, Elias and Arvidsson, Daniel and Fridolfsson, Jonatan and Gummesson, Anders and Schoeler, Marc and Mitteregger, Matthias and Smith, Gustav J. and Larsson, Ingrid and Börjesson, Mats and Blüher, Matthias and Uhlén, Mathias and Stumvoll, Michael and Bergström, Göran and Tremaroli, Valentina and Bäckhed, Fredrik}},
  issn         = {{1078-8956}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{113--125}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Medicine}},
  title        = {{Multi-omic definition of metabolic obesity through adipose tissue–microbiome interactions}},
  url          = {{http://dx.doi.org/10.1038/s41591-025-04009-7}},
  doi          = {{10.1038/s41591-025-04009-7}},
  volume       = {{32}},
  year         = {{2026}},
}