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Srinivasan S, Jablonski KA, Knowler WC, et al. A Polygenic Lipodystrophy Genetic Risk Score Characterizes Risk Independent of BMI in the Diabetes Prevention Program. J Endocr Soc. 2019;3(9):1663-1677doi: 10.1210/js.2019-00069.
Srinivasan, S., Jablonski, K. A., Knowler, W. C., Dagogo-Jack, S., E Kahn, S., Boyko, E. J., Bray, G. A., Horton, E. S., Hivert, M. F., Goldberg, R., Chen, L., Mercader, J., Harden, M., Florez, J. C. (2019). A Polygenic Lipodystrophy Genetic Risk Score Characterizes Risk Independent of BMI in the Diabetes Prevention Program. Journal of the Endocrine Society, 3(9), 1663-1677. https://doi.org/10.1210/js.2019-00069
Srinivasan, Shylaja, et al. "A Polygenic Lipodystrophy Genetic Risk Score Characterizes Risk Independent of BMI in the Diabetes Prevention Program." Journal of the Endocrine Society vol. 3,9 (2019): 1663-1677. doi: https://doi.org/10.1210/js.2019-00069
Srinivasan S, Jablonski KA, Knowler WC, Dagogo-Jack S, E Kahn S, Boyko EJ, Bray GA, Horton ES, Hivert MF, Goldberg R, Chen L, Mercader J, Harden M, Florez JC. A Polygenic Lipodystrophy Genetic Risk Score Characterizes Risk Independent of BMI in the Diabetes Prevention Program. J Endocr Soc. 2019 Jun 24;3(9):1663-1677. doi: 10.1210/js.2019-00069. eCollection 2019 Sep 01. PMID: 31428720; PMCID: PMC6694040.
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J Endocr Soc. 2019 Jun 24;3(9):1663-1677. doi: 10.1210/js.2019-00069. eCollection 2019 Sep 01.

A Polygenic Lipodystrophy Genetic Risk Score Characterizes Risk Independent of BMI in the Diabetes Prevention Program.

Journal of the Endocrine Society

Shylaja Srinivasan, Kathleen A Jablonski, William C Knowler, Samuel Dagogo-Jack, Steven E Kahn, Edward J Boyko, George A Bray, Edward S Horton, Marie-France Hivert, Ronald Goldberg, Ling Chen, Josep Mercader, Maegan Harden, Jose C Florez,

Affiliations

  1. Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, University of California at San Francisco, San Francisco, California.
  2. Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC.
  3. Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona.
  4. Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, Tennessee.
  5. Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington.
  6. Division of General Internal Medicine, University of Washington, Seattle, Washington.
  7. Division of Clinical Obesity and Metabolism, Pennington Biomedical Research Center, Baton Rouge, Louisiana.
  8. Joslin Diabetes Center, Boston, Massachusetts.
  9. Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts.
  10. Department of Medicine, Harvard Medical School, Boston, Massachusetts.
  11. Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
  12. Diabetes Research Institute, University of Miami Health System, Miami, Florida.
  13. Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  14. Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard & Massachusetts Institute of Technology, Cambridge, Massachusetts.

PMID: 31428720 PMCID: PMC6694040 DOI: 10.1210/js.2019-00069

Abstract

CONTEXT: There is substantial heterogeneity in insulin sensitivity, and genetics may suggest possible mechanisms by which common variants influence this trait.

OBJECTIVES: We aimed to evaluate an 11-variant polygenic lipodystrophy genetic risk score (GRS) for association with anthropometric, glycemic and metabolic traits in the Diabetes Prevention Program (DPP). In secondary analyses, we tested the association of the GRS with cardiovascular risk factors in the DPP.

DESIGN: In 2713 DPP participants, we evaluated a validated GRS of 11 common variants associated with fasting insulin-based measures of insulin sensitivity discovered through genome-wide association studies that cluster with a metabolic profile of lipodystrophy, conferring high metabolic risk despite low body mass index (BMI).

RESULTS: At baseline, a higher polygenic lipodystrophy GRS was associated with lower weight, BMI, and waist circumference measurements, but with worse insulin sensitivity index (ISI) values. Despite starting at a lower weight and BMI, a higher GRS was associated with less weight and BMI reduction at one year and less improvement in ISI after adjusting for baseline values but was not associated with diabetes incidence. A higher GRS was also associated with more atherogenic low-density lipoprotein peak-particle-density at baseline but was not associated with coronary artery calcium scores in the Diabetes Prevention Program Outcomes Study.

CONCLUSIONS: In the DPP, a higher polygenic lipodystrophy GRS for insulin resistance with lower BMI was associated with diminished improvement in insulin sensitivity and potential higher cardiovascular disease risk. This GRS helps characterize insulin resistance in a cohort of individuals at high risk for diabetes, independent of adiposity.

Keywords: insulin resistance; lifestyle intervention; metformin; obesity; type 2 diabetes

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