PMID- 38332862 OWN - NLM STAT- PubMed-not-MEDLINE LR - 20240210 IS - 1662-4548 (Print) IS - 1662-453X (Electronic) IS - 1662-453X (Linking) VI - 18 DP - 2024 TI - Altered cortical thickness-based structural covariance networks in type 2 diabetes mellitus. PG - 1327061 LID - 10.3389/fnins.2024.1327061 [doi] LID - 1327061 AB - Cognitive impairment is a common complication of type 2 diabetes mellitus (T2DM), and early cognitive dysfunction may be associated with abnormal changes in the cerebral cortex. This retrospective study aimed to investigate the cortical thickness-based structural topological network changes in T2DM patients without mild cognitive impairment (MCI). Fifty-six T2DM patients and 59 healthy controls underwent neuropsychological assessments and sagittal 3-dimensional T1-weighted structural magnetic resonance imaging. Then, we combined cortical thickness-based assessments with graph theoretical analysis to explore the abnormalities in structural covariance networks in T2DM patients. Correlation analyses were performed to investigate the relationship between the altered topological parameters and cognitive/clinical variables. T2DM patients exhibited significantly lower clustering coefficient (C) and local efficiency (Elocal) values and showed nodal property disorders in the occipital cortical, inferior temporal, and inferior frontal regions, the precuneus, and the precentral and insular gyri. Moreover, the structural topological network changes in multiple nodes were correlated with the findings of neuropsychological tests in T2DM patients. Thus, while T2DM patients without MCI showed a relatively normal global network, the local topological organization of the structural network was disordered. Moreover, the impaired ventral visual pathway may be involved in the neural mechanism of visual cognitive impairment in T2DM patients. This study enriched the characteristics of gray matter structure changes in early cognitive dysfunction in T2DM patients. CI - Copyright (c) 2024 Huang, Zhang, Cheng, Yang, Liu, Ai, Tang, Zhang, Lei and Zhang. FAU - Huang, Yang AU - Huang Y AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Zhang, Xin AU - Zhang X AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Cheng, Miao AU - Cheng M AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Yang, Zhen AU - Yang Z AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Liu, Wanting AU - Liu W AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Ai, Kai AU - Ai K AD - Department of Clinical and Technical Support, Philips Healthcare, Xi'an, China. FAU - Tang, Min AU - Tang M AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Zhang, Xiaoling AU - Zhang X AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Lei, Xiaoyan AU - Lei X AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. FAU - Zhang, Dongsheng AU - Zhang D AD - Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China. LA - eng PT - Journal Article DEP - 20240124 PL - Switzerland TA - Front Neurosci JT - Frontiers in neuroscience JID - 101478481 PMC - PMC10851426 OTO - NOTNLM OT - cortical thickness OT - neuroimaging OT - structural network OT - topological properties OT - type 2 diabetes mellitus COIS- KA was employed by company Philips Healthcare. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. EDAT- 2024/02/09 06:42 MHDA- 2024/02/09 06:43 PMCR- 2024/01/01 CRDT- 2024/02/09 03:45 PHST- 2023/10/24 00:00 [received] PHST- 2024/01/11 00:00 [accepted] PHST- 2024/02/09 06:43 [medline] PHST- 2024/02/09 06:42 [pubmed] PHST- 2024/02/09 03:45 [entrez] PHST- 2024/01/01 00:00 [pmc-release] AID - 10.3389/fnins.2024.1327061 [doi] PST - epublish SO - Front Neurosci. 2024 Jan 24;18:1327061. doi: 10.3389/fnins.2024.1327061. eCollection 2024.