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Mechanistic insights into the heterogeneity of glucose response classes in youths with obesity: a latent class trajectory approach

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posted on 2022-06-29, 14:32 authored by Domenico Tricò, Sarah McCollum, Stephanie Samuels, Nicola Santoro, Alfonso Galderisi, Leif Groop, Sonia Caprio, Veronika Shabanova

  

Objective. In a large multiethnic cohort of youths with obesity, we analyzed pathophysiological and genetic mechanisms underlying variations in plasma glucose responses to an oral glucose tolerance test (180min-OGTT).

Research Design and Methods. Latent class trajectory analysis was used to identify different glucose response profiles to 9-point, 180min-OGTT in 2,378 participants in the “Yale Pathogenesis of youth-onset T2D” study, of whom 1,190 had available TCF7L2 genotyping and 358 had multiple OGTTs over a 5-year follow-up. Insulin sensitivity, clearance and β-cell function were estimated by C-peptide modeling. 

Results. Four latent classes were identified and numbered from 1 to 4 based on increasing areas under the glucose curves. Subjects in class 3 and 4 had the worst metabolic and genetic risk profiles, featuring impaired insulin sensitivity, clearance, and β-cell function. Model-predicted probability to be classified as class 1 and 4 increased across ages, while insulin sensitivity and clearance showed transient reductions and β-cell function progressively declined. Insulin sensitivity was the strongest determinant of class assignment at enrolment and of the longitudinal change from class 1 and 2 to higher classes. Transitions between class 3 and 4 were explained only by changes in β-cell glucose sensitivity. 

Conclusions. We identified four glucose response classes in youths with obesity with different genetic risk profiles and progressive impairment in insulin kinetics and action. Insulin sensitivity was the main determinant in the transition between lower and higher glucose classes across ages. In contrast, transitions between the two worst glucose classes were only driven by β-cell glucose sensitivity.  


Funding

S.C. is funded by the National Institutes of Health (NIH) (grants R01-HD-40787, R01-HD-28016, R01DK111038 and K24-HD01464). S.S. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the NIH (grant K12DK094714). This work was also made possible by DK-045735 to the Yale Diabetes Endocrinology Research Center and by Clinical and Translational Science Awards Grant UL1-RR-024139 from the National Center for Advancing Translational Sciences, a component of the NIH, and NIH Roadmap for Medical Research. The contents of this scientific contribution are solely the responsibility of the authors and do not necessarily represent the official view of the NIH.

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