Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.

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 midd...

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Main Authors: Dae-Jin Kim, Ji Hee Yu, Mi-Seon Shin, Yong-Wook Shin, Min-Seon Kim
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4918925?pdf=render
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spelling doaj-4d6645fcdc9c4fdc86ab7367a96e71932020-11-25T02:48:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01116e015726810.1371/journal.pone.0157268Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.Dae-Jin KimJi Hee YuMi-Seon ShinYong-Wook ShinMin-Seon KimPrevious 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.http://europepmc.org/articles/PMC4918925?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Dae-Jin Kim
Ji Hee Yu
Mi-Seon Shin
Yong-Wook Shin
Min-Seon Kim
spellingShingle Dae-Jin Kim
Ji Hee Yu
Mi-Seon Shin
Yong-Wook Shin
Min-Seon Kim
Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
PLoS ONE
author_facet Dae-Jin Kim
Ji Hee Yu
Mi-Seon Shin
Yong-Wook Shin
Min-Seon Kim
author_sort Dae-Jin Kim
title Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
title_short Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
title_full Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
title_fullStr Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
title_full_unstemmed Hyperglycemia Reduces Efficiency of Brain Networks in Subjects with Type 2 Diabetes.
title_sort hyperglycemia reduces efficiency of brain networks in subjects with type 2 diabetes.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description 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.
url http://europepmc.org/articles/PMC4918925?pdf=render
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