Yu-Chen Chen1, Yun Jiao1, Ying Cui1, Song-An Shang1, Jie Ding1, Yuan Feng1, Wen Song1, Sheng-Hong Ju1, Gao-Jun Teng2. 1. Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China. 2. Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China gjteng@vip.sina.com.
Abstract
OBJECTIVE: Type 2 diabetes is characterized by insulin resistance, which is involved in the development of Alzheimer disease. This study aims to investigate the relationship between abnormal resting-state brain functional connectivity and insulin resistance in type 2 diabetes. RESEARCH DESIGN AND METHODS: A total of 30 patients with type 2 diabetes and 31 healthy well-matched volunteers were prospectively examined. Resting-state brain functional connectivity analysis was used to examine the correlation between the posterior cingulate cortex (PCC) and whole-brain regions. The possible relationships between functional connectivity measures and insulin resistance were evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Compared with healthy controls, we observed significantly decreased functional connectivity of the PCC within some selected regions, including the right middle temporal gyrus (MTG), left lingual gyrus, left middle occipital gyrus, and left precentral gyrus; increased functional connectivity of the PCC was detected in the left cerebellum posterior lobe, right superior frontal gyrus, and right middle frontal gyrus. A significant negative correlation was found between the PCC-right MTG connectivity and HOMA-IR in type 2 diabetic patients (P = 0.014; r = -0.446). CONCLUSIONS: Type 2 diabetic patients develop aberrant functional connectivity of the PCC, which is associated with insulin resistance in selected brain regions. Resting-state connectivity disturbance of PCC-MTG may be a central role for evaluating the cognitive dysfunction in type 2 diabetes.
OBJECTIVE:Type 2 diabetes is characterized by insulin resistance, which is involved in the development of Alzheimer disease. This study aims to investigate the relationship between abnormal resting-state brain functional connectivity and insulin resistance in type 2 diabetes. RESEARCH DESIGN AND METHODS: A total of 30 patients with type 2 diabetes and 31 healthy well-matched volunteers were prospectively examined. Resting-state brain functional connectivity analysis was used to examine the correlation between the posterior cingulate cortex (PCC) and whole-brain regions. The possible relationships between functional connectivity measures and insulin resistance were evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Compared with healthy controls, we observed significantly decreased functional connectivity of the PCC within some selected regions, including the right middle temporal gyrus (MTG), left lingual gyrus, left middle occipital gyrus, and left precentral gyrus; increased functional connectivity of the PCC was detected in the left cerebellum posterior lobe, right superior frontal gyrus, and right middle frontal gyrus. A significant negative correlation was found between the PCC-right MTG connectivity and HOMA-IR in type 2 diabeticpatients (P = 0.014; r = -0.446). CONCLUSIONS: Type 2 diabeticpatients develop aberrant functional connectivity of the PCC, which is associated with insulin resistance in selected brain regions. Resting-state connectivity disturbance of PCC-MTG may be a central role for evaluating the cognitive dysfunction in type 2 diabetes.
Authors: Y Cui; S-F Li; H Gu; Y-Z Hu; X Liang; C-Q Lu; Y Cai; C-X Wang; Y Yang; G-J Teng Journal: AJNR Am J Neuroradiol Date: 2016-06-30 Impact factor: 3.825
Authors: Ramon Casanova; Satoru Hayasaka; Santiago Saldana; Nick R Bryan; Kathryn E Demos; Lisa Desiderio; Kirk I Erickson; Mark A Espeland; Ilya M Nasrallah; Thomas Wadden; Paul J Laurienti Journal: Psychoneuroendocrinology Date: 2016-09-23 Impact factor: 4.905