title: Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
abstract: Previous research has shown that the brain is an important target of diabetic complications. Since brain regions are interconnected to form a large-scale neural network, we investigated whether severe hyperglycemia affects the topology of the brain network in people with type 2 diabetes. Twenty middle-aged (average age: 54 years) individuals with poorly controlled diabetes (HbA1c: 8.9-14.6%, 74-136 mmol/mol) and 20 age-, sex-, and education-matched healthy volunteers were recruited. Graph theoretic network analysis was performed with axonal fiber tractography and tract-based spatial statistics (TBSS) using diffusion tensor imaging. Associations between the blood glucose level and white matter network characteristics were investigated. Individuals with diabetes had lower white matter network efficiency (P<0.001) and longer white matter path length (P<0.05) compared to healthy individuals. Higher HbA1c was associated with lower network efficiency (r = -0.53, P = 0.001) and longer network path length (r = 0.40, P<0.05). A disruption in local microstructural integrity was found in the multiple white matter regions and associated with higher HbA1c and fasting plasma glucose levels (corrected P<0.05). Poorer glycemic control is associated with lower efficiency and longer connection paths of the global brain network in individuals with diabetes. Chronic hyperglycemia in people with diabetes may disrupt the brain's topological integration, and lead to mental slowing and cognitive impairment.
authors.affiliation: Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.
authors.forename: Dae-Jin
authors.initials: DJ
authors.lastname: Kim
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Ansan, Korea.
authors.forename: Ji Hee
authors.initials: JH
authors.lastname: Yu
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, KEPCO Medical Center, Seoul, Korea.
authors.forename: Mi-Seon
authors.initials: MS
authors.lastname: Shin
authors.affiliation: Department of Psychiatry, Ulsan University School of Medicine, ASAN Medical Center, Seoul, Korea.
authors.forename: Yong-Wook
authors.initials: YW
authors.lastname: Shin
authors.affiliation: Division of Endocrinology and Metabolism, Ulsan University College of Medicine, Seoul, Korea.|Diabetes Center, ASAN Medical Center, Seoul, Korea.
authors.forename: Min-Seon
authors.initials: MS
authors.lastname: Kim
mesh_terms: D000328:Adult; D000368:Aged; D001921:Brain / Q000473:pathology / Q000503:physiopathology*; D016022:Case-Control Studies; D003072:Cognition Disorders / Q000209:etiology / Q000503:physiopathology; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000150:complications / Q000503:physiopathology*; D005260:Female; D006801:Humans; D006943:Hyperglycemia / Q000150:complications / Q000503:physiopathology*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009434:Neural Pathways / Q000503:physiopathology*; D066127:White Matter