Evidence map›Paper›PMID 40348015›Full record

ArticleMolecular metabolism2025

Abundance of a metabolically active subpopulation in dedifferentiated adipocytes inversely correlates with body mass index.

Jonathan Trujillo-Viera, Mona C Wittmann, Daniel Lam, Yang Shen, Adhideb Ghosh, Falko Noé, Anne Hoffmann, Coralie Viollet, Alec Dick, Matthias Blüher and 6 more

Abstract read
In one paragraph

Article in Molecular metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Jonathan Trujillo-VieraCardio Metabolic Diseases Research, Boehringer Ingelheim Pharma GmbH & Co KG, Biberach an der Riß, Germany.
Mona C WittmannCardio Metabolic Diseases Research, Boehringer Ingelheim Pharma GmbH & Co KG, Biberach an der Riß, Germany.
Daniel LamGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach an der Riß, Germany.
Yang ShenGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach an der Riß, Germany.
Adhideb GhoshInstitute of Food, Nutrition and Health, ETH Zürich, 8603, Schwerzenbach, Switzerland.
Falko NoéInstitute of Food, Nutrition and Health, ETH Zürich, 8603, Schwerzenbach, Switzerland.
Anne HoffmannHelmholtz Institute for Metabolic, Obesity and Vascular Research of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany.
Coralie ViolletGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach an der Riß, Germany.
Alec DickGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach an der Riß, Germany.
Matthias BlüherHelmholtz Institute for Metabolic, Obesity and Vascular Research of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany; Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany.
Jiawei ZhongDepartment of Medicine Huddinge (H7), Karolinska Institutet, Karolinska University Hospital Huddinge, SE-141 83, Huddinge, Sweden.
Lucas MassierHelmholtz Institute for Metabolic, Obesity and Vascular Research of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany; Department of Medicine Huddinge (H7), Karolinska Institutet, Karolinska University Hospital Huddinge, SE-141 83, Huddinge, Sweden.
Christian WolfrumInstitute of Food, Nutrition and Health, ETH Zürich, 8603, Schwerzenbach, Switzerland.
Holger KleinGlobal Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach an der Riß, Germany.
Heike NeubauerCardio Metabolic Diseases Research, Boehringer Ingelheim Pharma GmbH & Co KG, Biberach an der Riß, Germany.
Bradford HamiltonCardio Metabolic Diseases Research, Boehringer Ingelheim Pharma GmbH & Co KG, Biberach an der Riß, Germany. Electronic address: bradford.hamilton@boehringer-ingelheim.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe cellular composition and functionality of adipose tissue are key determinants of metabolic diseases associated with adipose tissue dysregulation, such as obesity. We hypothesized that distinct subpopulations with unique gene expression profiles and functional characteristics exist within human adipocytes.

methodsDedifferentiated adipocytes (DFAT), obtained by ceiling culture of human adipocytes, were analyzed using single-cell RNA sequencing (10x Genomics). Clustering analysis identified one subpopulation with a particular gene signature containing muscle cell genes which was further characterized by bulk-sequencing and analyzed alongside different cohorts of human adipose tissue.

resultsThis subpopulation, named cluster 7 (C7), was isolated by FACS using two specific surface markers: cluster of differentiation 36 (CD36) and melanoma cell adhesion molecule (MCAM/CD146). Upon differentiation into adipocytes, the FACS-isolated CD36+/CD146+ cells (C7∗) showed an increased oxygen consumption rate compared to CD36-/CD146-cells (control cells) and non-sorted cells. Bulk RNA-sequencing revealed important pathways regulated in the differentiated C7∗ subpopulation that may contribute to its increased metabolic activity. Furthermore, the relative abundance of this specific cluster varied across eleven different human donors, demonstrating an inverse correlation between the proportion of C7∗ cells and the body mass index (BMI) of the respective donor. Importantly, a subset of genes regulated within this subpopulation also correlates with clinically relevant metabolic parameters, including weight, BMI, glycated hemoglobin, and plasma insulin, when analyzed alongside the gene expression of a large cohort of human subcutaneous adipose tissue (1759 donors).

conclusionOur results not only characterize DFAT cells derived from human adipose tissue, but also identify a specific subpopulation with increased energy expenditure that may play a role in body weight control. Future efforts to identify possible therapeutic targets or to promote the enrichment or activation of these energy-burning cells in adipose tissue might be useful in the field of cardiometabolic diseases.

Indexed as

AdipocytesAdipose TissueAdultBody Mass IndexCD146 AntigenCD36 AntigensCell DedifferentiationCell DifferentiationCells, CulturedFemaleHumansMaleMiddle AgedObesityCD146 AntigenCD36 AntigensAdipocytesCD146CD36DFATEnergy expenditureObesity

Identifiers

PMID40348015
PMCPMC12145827

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.