118-OR: Fat Distribution Patterns Predict Type 2 Diabetes Risk and Provide Insights into Prediabetic Metabolism

Abstract

Objective: Fat accumulation in liver, pancreas, skeletal muscle, and visceral bed relates to type 2 diabetes (T2D) . However, distribution of fat in these compartments is heterogenous and it is unclear if specific distribution patterns indicate high T2D risk. We therefore investigated fat distribution patterns and their link to future T2D. Methods: From 2168 individuals without diabetes undergoing computed tomography in Japan, this case-cohort study included 658 randomly selected individuals and 146 incident cases of T2D with a 6-year follow-up. Data-driven analysis (k-means) was applied to develop clusters based on fat content in liver, pancreas, muscle, and visceral bed. Hazard ratios (HRs) for association of clusters and incident T2D were estimated using weighted Cox regression. In 3 individuals without diabetes with magnetic resonance imaging and metabolic phenotyping in Germany, cluster validation with additional assessment of glycemic traits from OGTTs was conducted. Results: We identified four clusters of fat distribution: cluster 1 (Hepatic steatosis cluster) , cluster 2 (Pancreatic steatosis cluster) , cluster 3 (Myosteatosis dominant cluster) , cluster 4 (Steatopenic cluster) . Compared with Steatopenic cluster, the adjusted-HRs (95%CIs) for incident T2D were 4.02 (2.27-7.12) in Hepatic steatosis cluster, 3.38 (1.65-6.91) in Pancreatic steatosis cluster, and 1.95 (1.07-3.54) in Myosteatosis dominant cluster. The clusters were replicated in the German cohort with similar distribution of AUC-glucose to the diabetes hazard in the Japanese cohort. Insulin sensitivity and insulin secretion were different across clusters with the lowest insulin sensitivity and highest insulin secretion in Hepatic steatosis cluster. Conclusions: Extending evidence about fat accumulation in single compartments, we identified specific patterns of fat distribution with different T2D risk presumably due to differences in insulin sensitivity and insulin secretion. Disclosure H.Yamazaki: None. N.Stefan: Advisory Panel; Gilead Sciences, Inc., GlaxoSmithKline plc., Sanofi, Consultant; AstraZeneca, Intercept Pharmaceuticals, Inc., Novo Nordisk, Pfizer Inc., Speaker's Bureau; AstraZeneca, Boehringer Ingelheim International GmbH, Lilly Diabetes, Merck Sharp & Dohme Corp. A.Fritsche: Advisory Panel; Boehringer Ingelheim International GmbH, Novo Nordisk, Sanofi-Aventis Deutschland GmbH. A.L.Birkenfeld: None. R.Wagner: Advisory Panel; Akcea Therapeutics, Daiichi Sankyo, Sanofi-Aventis Deutschland GmbH, Speaker's Bureau; Lilly, Novo Nordisk, Sanofi-Aventis Deutschland GmbH. M.Heni: Advisory Panel; Boehringer Ingelheim International GmbH, Research Support; Boehringer Ingelheim International GmbH, Sanofi, Speaker's Bureau; Amryt Pharma Plc, Boehringer Ingelheim International GmbH, Novo Nordisk. S.Tauchi: None. J.Machann: None. T.Haueise: None. Y.Yamamoto: None. M.Dohke: None. N.Hanawa: None. Y.Kodama: Other Relationship; Eisai Co., Ltd. A.Katanuma: None. Funding the German Center for Diabetes Research (DZD, 01GI0925) , the state of Baden-Württemberg (32-5400/58/2, Forum Gesundheitsstandort Baden-Württemberg) , and JSPS KAKENHI Grant Number 19K16978