American Diabetes Association
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Evidence That Hypothalamic Gliosis Is Related to Impaired Glucose Homeostasis in Adults With Obesity

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posted on 2021-11-30, 17:21 authored by Jennifer L. Rosenbaum, Susan J. Melhorn, Stefan Schoen, Mary F. Webb, Mary Rosalynn B. De Leon, Madelaine Humphreys, Kristina M. Utzschneider, Ellen A. Schur
Objective: Preclinical research implicates hypothalamic glial cell responses in the pathogenesis of obesity and type 2 diabetes. The current study sought to translate such findings into humans by testing if radiologic markers of gliosis in the mediobasal hypothalamus (MBH) were greater in persons with obesity and impaired glucose homeostasis or type 2 diabetes.

Research Design and Methods: Using cross-sectional and prospective cohort study designs, we applied a validated, quantitative magnetic resonance imaging (MRI) approach to assess gliosis in 67 adults with obesity and normal glucose tolerance, impaired glucose tolerance, or type 2 diabetes. Assessments of glucose homeostasis were conducted via oral glucose tolerance tests (OGTT) and β-cell modeling.

Results: We found significantly greater T2 relaxation times (a marker of gliosis by MRI), that were independent of adiposity, in the impaired glucose tolerance and type 2 diabetes groups as compared to the normal glucose tolerance group. Findings were present in the MBH, but not control regions. Moreover, positive linear associations were present in the MBH but not control regions between T2 relaxation time and glucose area under the curve during an OGTT, fasting glucose concentrations, hemoglobin A1c, and visceral adipose tissue mass, whereas negative linear relationships were present in the MBH for markers of insulin sensitivity and β-cell function. In a prospective cohort study, greater MBH T2 relaxation times predicted declining insulin sensitivity over one year.

Conclusions: Findings support a role for hypothalamic gliosis in the progression of insulin resistance in obesity and, thus, type 2 diabetes pathogenesis in humans.


This work was supported by American Diabetes Association Innovative Clinical or Translational Science award 1-17-ICTS-085 (EAS). Additional support was from National Institutes of Health awards R01DK089036 (EAS), R01DK117623 (EAS), K24HL144917 (EAS), and T32HL007028 (JLR) and the University of Washington Nutrition and Obesity Research Center P30DK035816 and Diabetes Research Center P30DK017047. KMU is supported by the Veterans Affairs Administration. Some study data were collected and managed using REDCap electronic data capture tools hosted at the University of Washington Institute of Translational Health Sciences, which are supported by the NIH National Center for Advancing Translational Sciences award UL1TR002319.