| Title: | Genetic subtypes of type 2 diabetes are distinguished through the lens of abdominal MRI |
| Journal: | Frontiers in Genetics |
| Published: | 16 Jul 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40741412/ |
| DOI: | https://doi.org/10.3389/fgene.2025.1605721 |
| URL: | https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2025.1605721/pdf |
Publication 16158
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Abstract
Objective: This study seeks to understand type 2 diabetes (T2D) heterogeneity through detailed phenotypic characterization of various T2D genetic subtypes using advanced magnetic resonance imaging (MRI) techniques.</p>
Study design and method: MRI data from over 44,000 UK Biobank participants was used to characterize distinct T2D genetic subtypes based on a compendium of imaging-derived phenotypes (IDPs) quantifying body fat distribution, organ volumes, and muscle quality. Partitioned polygenic risk scores (pPS) representing genetic T2D subtypes were associated with adipose tissue distribution across ten compartments, liver and pancreas volume, three muscle mass indices, and fatty acid composition in subcutaneous and visceral fat.</p>
Results: Subtype pPS marked by insulin deficiency were associated with lower subcutaneous fat, while insulin resistance subtypes were associated with higher adiposity with evidence of fat excess in multiple organs, including the pancreas, paraspinal muscle, thigh muscle, iliopsoas muscle, and other organs not routinely quantified at scale in human cohorts. Distinct patterns of muscle mass and fatty acid composition further differentiated subtype pPS, underscoring variation in metabolic profiles linked to specific genetic pathways.</p>
Conclusion: The use of non-invasive MRI to phenotype T2D at a granular level has provided unique insights into the disease's heterogeneity, confirming and expanding upon known genetic associations. These findings highlight the potential of using MRI for pathophysiological insights into T2D.</p>
9 Authors
- Elena P. Sorokin
- Madeleine Cule
- Marjola Thanaj
- Nicolas Basty
- Brandon Whitcher
- Naveed Sattar
- E. Louise Thomas
- Jimmy D. Bell
- Hanieh Yaghootkar
1 Application
| Application ID | Title |
|---|---|
| 44584 | Enriched Image Based Phenotypes for Health Exploration and Discovery |
Enabling scientific discoveries that improve human health