Body Composition Differentiates Prediabetes Phenotype Clusters in the Diabetes Prevention Program Study
Data-driven clustering of patients with prediabetes allows for identification of prediabetes phenotypes at greater risk for disease progression and responses to risk reduction interventions. Further investigation into phenotypic differences in treatment response could enable better personalization of prediabetes and T2D prevention and treatment choices.
Authors
- Meghana Gadgil (ORCID: https://orcid.org/0000-0001-8638-0048)
- Benjamin Stroebel (ORCID: https://orcid.org/0000-0001-6415-5034)
- Elena Flowers (ORCID: https://orcid.org/0000-0002-7054-7533)
- Kimberly Lewis (ORCID: https://orcid.org/0000-0002-2590-8627)
- Kayla D. Longoria (ORCID: https://orcid.org/0000-0002-3621-388X)
- Li Zhang (ORCID: https://orcid.org/0000-0002-3617-2627)
Institutions
- San Francisco General Hospital (US)
- University of California, San Francisco (US)
- Department of Physiological Sciences (RU)
- Institute of Human Genetics (PL)
Publication Details
- Journal
- The Journal of Clinical Endocrinology & Metabolism
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1210/clinem/dgaf163
- Citations
- 3
- Primary Topic
- Metabolism, Diabetes, and Cancer
- Type
- article
- Field-Weighted Citation Impact
- 2.42