ArticleDiabetes2025
Identifying Four Obesity Axes Through Integrative Multiomics and Imaging Analysis.
Article in Diabetes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Genetics of MASLD: a diabetes perspective.Diabetologia · 2026Review
- Review
- Extreme Obesity (BMI ≥ 60 kg/mObesity (Silver Spring, Md.) · 2026Article
- Survodutide for the Treatment of Obesity Disease in Japanese Participants: Rationale, Design and Baseline Characteristics of the Phase 3 SYNCHRONIZE-JP Trial.Diabetes, obesity & metabolism · 2026Article
- Associations between waist-to-height ratio and hormonal-metabolic profiles in midlife women: evidence from a population-based cross-sectional study.Archives of gynecology and obstetrics · 2026Article
- Genetic and molecular signatures highlight diverse pathways linking obesity to type 2 diabetes.Nature communications · 2026Article
- Genetic associations and candidate functional genes linking depression and obesity: a multi-omics integrative study.Frontiers in genetics · 2026Article
- Inflammation-Mediated Causal Effects of MRI-Defined Body-Composition Obesity Axes on Chronic Obstructive Pulmonary Disease, Asthma, and Allergic Rhinitis: A Mendelian Randomization Study.International journal of chronic obstructive pulmonary disease · 2026Article
- Beyond BMI: Rethinking Obesity Metrics and Cardiovascular Risk in the Era of Precision Medicine.Diagnostics (Basel, Switzerland) · 2025Review
- Genetic subtypes of type 2 diabetes are distinguished through the lens of abdominal MRI.Frontiers in genetics · 2025Article
- Mapping the Four Adiposity Axes-Inflammatory Cytokine-Venous Thromboembolism Risk Landscape: A Two-Step Mediation Mendelian Randomization Analysis.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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Authors and funding
10 authors.
Funding
Abstract
We aimed to identify distinct axes of obesity using advanced magnetic resonance imaging (MRI)-derived phenotypes. We used 24 MRI-derived fat distribution and muscle volume measures (UK Biobank; N = 33,122) to construct obesity axes through principal component analysis. Genome-wide association studies were performed for each axis to uncover genetic factors, followed by pathway enrichment, genetic correlation, and Mendelian randomization analyses to investigate disease associations. Four primary obesity axes were identified: 1) general obesity, reflecting higher fat accumulation in all regions (visceral, subcutaneous, and ectopic fat); 2) muscle dominant, indicating greater muscle volume; 3) peripheral fat, associated with higher subcutaneous fat in abdominal and thigh regions; and 4) lower-body fat, characterized by increased lower-body subcutaneous fat and reduced ectopic fat. Each axis was associated with distinct genetic loci and pathways. For instance, the lower-body fat axis was associated with RSPO3 and COBLL1, which are emerging as promising candidates for therapeutic targeting. Disease risks varied across axes; the general obesity axis was correlated with higher risks of metabolic and cardiovascular diseases, whereas the lower-body fat axis seemed to protect against type 2 diabetes and cardiovascular disease. This study highlights the heterogeneity of obesity through the identification of obesity axes and emphasizes the potential to extend beyond BMI in defining and treating obesity for obesity-related disease management. ARTICLE HIGHLIGHTS: This study aimed to address potential limitations of BMI by exploring the heterogeneity of obesity using magnetic resonance imaging-derived fat distribution and muscle volume measures. We sought to identify distinct obesity axes and investigate their genetic, metabolic, and disease associations. Four obesity axes were identified (general obesity, muscle dominant, peripheral fat, and lower-body fat), each linked to unique genetic loci, metabolic traits, and disease risks. These findings emphasize the potential to extend beyond BMI in defining and managing obesity, offering a more nuanced framework for understanding and treating obesity-related diseases.
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