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Fat-distribution patterns and future type-2 diabetes

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posted on 20.06.2022, 17:54 authored by Hajime Yamazaki, Shinichi Tauchi, Jürgen Machann, Tobias Haueise, Yosuke Yamamoto, Mitsuru Dohke, Nagisa Hanawa, Yoshihisa Kodama, Akio Katanuma, Norbert Stefan, Andreas Fritsche, Andreas L. Birkenfeld, Róbert Wagner, Martin Heni

  

Fat accumulation in the liver, pancreas, skeletal muscle, and visceral bed relates to type-2 diabetes (T2D). However, the distribution of fat among these compartments is heterogenous and it is unclear whether specific distribution patterns indicate high T2D risk. We therefore investigated fat-distribution patterns and their link to future T2D. From 2168 individuals without diabetes who underwent computed tomography in Japan, this case-cohort study included 658 randomly selected individuals and 146 incident cases of T2D over 6 years of follow-up. Using data-driven analysis (k-means) based on fat content in the liver, pancreas, muscle, and visceral bed, we identified four fat-distribution clusters: Hepatic steatosis, Pancreatic steatosis, Trunk myosteatosis, and Steatopenia. Compared with the Steatopenia cluster, the adjusted hazard ratios (95% CIs) for incident T2D were 4.02 (2.27-7.12) for the Hepatic steatosis cluster, 3.38 (1.65-6.91) for the Pancreatic steatosis cluster, and 1.95 (1.07-3.54) for the Trunk myosteatosis cluster. The clusters were replicated in 319 German individuals without diabetes who underwent magnetic resonance imaging and metabolic phenotyping. The distribution of AUC-glucose across the four clusters found in Germany was similar to the distribution of T2D risk across the four clusters in Japan. Insulin sensitivity and insulin secretion differed across the four clusters. Thus, we identified patterns of fat distribution with different T2D risks presumably due to differences in insulin sensitivity and insulin secretion.

Funding

This work was funded in part by the German Center for Diabetes Research (DZD, 01GI0925), by the state of Baden-Württemberg (32-5400/58/2, Forum Gesundheitsstandort Baden-Württemberg), and by JSPS KAKENHI Grant Number JP19K16978 and JP22K15685.

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