Affiliation: | 1. Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU München, Munich, Germany Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany;2. Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU München, Munich, Germany Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany Pettenkofer School of Public Health, Munich, Germany;3. Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Freiburg, Germany;4. Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany German Center for Diabetes Research (DZD), München-Neuherberg, Germany;5. Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU München, Munich, Germany Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany German Center for Diabetes Research (DZD), München-Neuherberg, Germany German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany;6. German Center for Diabetes Research (DZD), München-Neuherberg, Germany Institute for Biometrics and Epidemiology, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany;7. German Center for Diabetes Research (DZD), München-Neuherberg, Germany;8. Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU München, Munich, Germany |
Abstract: | Background Non-alcoholic fatty liver disease (NAFLD) represents a major disease burden in the population. While the bidirectional association between NAFLD and diabetes is established, little is known about the association of hepatic iron content and glycaemia. Moreover, analyses of sex-specific effects and of dynamic changes in glycaemia are scarce. Methods We investigated 7-year sex-specific trajectories of glycaemia and related traits (HbA1c, fasting glucose, fasting insulin, HOMA-IR, 2-h glucose and cross-sectional 2-h insulin) in a sample from a population-based cohort (N = 365; 41.1% female). Hepatic iron and fat content were assessed by 3T-Magnetic Resonance Imaging (MRI). Two-step multi-level models adjusted for glucose-lowering medication and confounders were applied. Results In women and men, markers of glucose metabolism correlated with hepatic iron and fat content. Deterioration of glycaemia was associated with increased hepatic iron content in men (normoglycaemia to prediabetes: beta = 2.21 s−1, 95% CI [0.47, 3.95]). Additionally, deterioration of glycaemia (e.g. prediabetes to diabetes: 1.27 log(%), [0.84, 1.70]) and trajectories of glucose, insulin and HOMA-IR were significantly associated with hepatic fat content in men. Similarly, deterioration of glycaemia as well as trajectories of glucose, insulin and HOMA-IR was significantly associated with increased hepatic fat content in women (e.g. trajectory of fasting insulin: 0.63 log(%), [0.36, 0.90]). Conclusions Unfavourable 7-year trajectories of markers of glucose metabolism are associated with increased hepatic fat content, particularly in women, whereas the association with hepatic iron content was less clear. Monitoring changes of glycaemia in the sub-diabetic range might enable early identification of hepatic iron overload and steatosis. |