Genetic evidence for distinct biological mechanisms that link adiposity to type 2 diabetes: towards precision medicine.


Journal

Diabetes
ISSN: 1939-327X
Titre abrégé: Diabetes
Pays: United States
ID NLM: 0372763

Informations de publication

Date de publication:
26 Mar 2024
Historique:
received: 19 03 2024
accepted: 22 03 2024
medline: 26 3 2024
pubmed: 26 3 2024
entrez: 26 3 2024
Statut: aheadofprint

Résumé

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We employed MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity). We then characterized each cluster based on various biomarkers, metabolites and Magnetic Resonance Imaging-based measures of fat distribution and muscle quality. Analyzing the metabolic signatures of these clusters revealed two primary mechanisms connecting higher adiposity to reduced type 2 diabetes risk. The first involves higher adiposity in subcutaneous tissues (abdomen and thigh), lower liver fat, improved insulin sensitivity, and decreased risk of cardiometabolic diseases and diabetes complications. The second mechanism is characterized by increased body size, enhanced muscle quality, with no impact on cardiometabolic outcomes. Furthermore, our findings unveil diverse mechanisms linking higher adiposity to higher disease risk, such as cholesterol pathways or inflammation. These results reinforce the existence of adiposity-related mechanisms that may act as protective factors against type 2 diabetes and its complications, especially when accompanied by reduced ectopic liver fat.

Identifiants

pubmed: 38530928
pii: 154397
doi: 10.2337/db23-1005
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 by the American Diabetes Association.

Auteurs

Angela Abraham (A)

College of Health and Science, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, UK.

Madeleine Cule (M)

Calico Life Sciences LLC, South San Francisco, CA.

Marjola Thanaj (M)

Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.

Nicolas Basty (N)

Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.

M Amin Hashemloo (MA)

Department of Life Sciences, Brunel University London, Uxbridge, United Kingdom.

Elena P Sorokin (EP)

Calico Life Sciences LLC, South San Francisco, CA.

Brandon Whitcher (B)

Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Department of Radiology, MRI Unit, The Royal Marsden NHS Foundation Trust, London, UK.

Stephen Burgess (S)

MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.

Jimmy D Bell (JD)

Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.

Naveed Sattar (N)

School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK.

E Louise Thomas (EL)

Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.

Hanieh Yaghootkar (H)

College of Health and Science, University of Lincoln, Joseph Banks Laboratories, Green Lane, Lincoln, UK.

Classifications MeSH