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Ge L, Cao Z, Sun Z, Yue X, Rao Y, Zhao K, Qiu W, Li Y, Lu W, Qiu S. Functional connectivity density aberrance in type 2 diabetes mellitus with and without mild cognitive impairment. Front Neurol 2024; 15:1418714. [PMID: 38915801 PMCID: PMC11194391 DOI: 10.3389/fneur.2024.1418714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 05/29/2024] [Indexed: 06/26/2024] Open
Abstract
Purpose The objective of this study was to investigate alterations in functional connectivity density (FCD) mapping and their impact on functional connectivity (FC) among individuals diagnosed with Type 2 diabetes mellitus (T2DM) across different cognitive states. Moreover, the study sought to explore the potential association between aberrant FCD/FC patterns and clinical or cognitive variables. Methods A total of 211 participants were recruited for this study, consisting of 75 healthy controls (HCs), 89 T2DM patients with normal cognitive function (DMCN), and 47 T2DM patients with mild cognitive impairment (DMCI). The study employed FCD analysis to pinpoint brain regions exhibiting significant FCD alterations. Subsequently, these regions showing abnormal FCD served as seeds for FC analysis. Exploratory partial correlations were conducted to explore the relationship between clinical biochemical indicators, neuropsychological test scores, and altered FCD or FC. Results The FCD analysis revealed an increased trend in global FCD (gFCD), local FCD (lFCD), and long-range FCD (lrFCD) within the bilateral supramarginal gyrus (SMG) among individuals with DMCN. Additionally, significant lFCD alterations were observed in the right inferior frontal gyrus and left precuneus when comparing DMCN to HCs and DMCI. Conclusion When comparing individuals with T2DM and healthy controls (HCs), it was revealed that DMCN exhibited significant improvements in FCD. This suggests that the brain may employ specific compensatory mechanisms to maintain normal cognitive function at this stage. Our findings provide a novel perspective on the neural mechanisms involved in cognitive decline associated with T2DM.
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Affiliation(s)
- Limin Ge
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zidong Cao
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhizhong Sun
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaomei Yue
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yawen Rao
- Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Kui Zhao
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wenbin Qiu
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yifan Li
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Weiye Lu
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou, China
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Lu Y, Liu T, Sheng Q, Zhang Y, Shi H, Jiao Z. Predicting the cognitive function status in end-stage renal disease patients at a functional subnetwork scale. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2024; 21:3838-3859. [PMID: 38549310 DOI: 10.3934/mbe.2024171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Brain functional networks derived from functional magnetic resonance imaging (fMRI) provide a promising approach to understanding cognitive processes and predicting cognitive abilities. The topological attribute parameters of global networks are taken as the features from the overall perspective. It is constrained to comprehend the subtleties and variances of brain functional networks, which fell short of thoroughly examining the complex relationships and information transfer mechanisms among various regions. To address this issue, we proposed a framework to predict the cognitive function status in the patients with end-stage renal disease (ESRD) at a functional subnetwork scale (CFSFSS). The nodes from different network indicators were combined to form the functional subnetworks. The area under the curve (AUC) of the topological attribute parameters of functional subnetworks were extracted as features, which were selected by the minimal Redundancy Maximum Relevance (mRMR). The parameter combination with improved fitness was searched by the enhanced whale optimization algorithm (E-WOA), so as to optimize the parameters of support vector regression (SVR) and solve the global optimization problem of the predictive model. Experimental results indicated that CFSFSS achieved superior predictive performance compared to other methods, by which the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were up to 0.5951, 0.0281 and 0.9994, respectively. The functional subnetwork effectively identified the active brain regions associated with the cognitive function status, which offered more precise features. It not only helps to more accurately predict the cognitive function status, but also provides more references for clinical decision-making and intervention of cognitive impairment in ESRD patients.
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Affiliation(s)
- Yu Lu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Tongqiang Liu
- Department of Nephrology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213003, China
| | - Quan Sheng
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Yutao Zhang
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
| | - Haifeng Shi
- Department of Radiology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213003, China
| | - Zhuqing Jiao
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
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Sun K, Li Y, Zhai Z, Yin H, Liang S, Zhai F, Cui Y, Zhang G. Effects of transcutaneous auricular vagus nerve stimulation and exploration of brain network mechanisms in children with high-functioning autism spectrum disorder: study protocol for a randomized controlled trial. Front Psychiatry 2024; 15:1337101. [PMID: 38374975 PMCID: PMC10875019 DOI: 10.3389/fpsyt.2024.1337101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Background Autism Spectrum Disorders (ASD) are a collection of neurodevelopmental diseases characterized by poor social interaction and communication, a limited range of interests, and stereotyped behavior. High-functioning autism (HFA) indicates a subgroup of individuals with autism who possess cognitive and/or language skills that are within the average to above-normal range for their age. Transcutaneous auricular vagus nerve stimulation (taVNS) holds promise in children with HFA. However, few studies have used randomized controlled trials to validate the effectiveness of taVNS. Therefore, in this study, we intend to provide a study protocol to examine the therapeutic effects of taVNS in individuals diagnosed with HFA and to investigate the process of brain network remodeling in individuals with ASD using functional imaging techniques to observe alterations in large-scale neural networks. Methods and design We planned to employ a randomized, double-blind experimental design, including 40 children receiving sham stimulation and 40 children receiving real stimulation. We will assess clinical scales and perform functional imaging examinations before and after the stimulation. Additionally, we will include age- and gender-matched healthy children as controls and conduct functional imaging examinations. We plan first to observe the therapeutic effects of taVNS. Furthermore, we will observe the impact of taVNS stimulation on the brain network. Discussion taVNS was a low-risk, easy-to-administer, low-cost, and portable option to modulate the vagus system. taVNS may improve the social performance of HFA. Changes in the network properties of the large-scale brain network may be related to the efficacy of taVNS. Clinical trial registration http://www.chictr.org.cn, identifier ChiCTR2300074035.
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Affiliation(s)
- Ke Sun
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Ying Li
- Department of Psychiatry, Beijing Children’s Hospital, Beijing, China
| | - Zhenhang Zhai
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Heqing Yin
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Shuli Liang
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Feng Zhai
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Yonghua Cui
- Department of Psychiatry, Beijing Children’s Hospital, Beijing, China
| | - Guojun Zhang
- Functional Neurosurgery Department, National Center for Children’s Health, Beijing Children’s Hospital, Capital Medical University, Beijing, China
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Xin H, Fu Y, Wen H, Feng M, Sui C, Gao Y, Guo L, Liang C. Cognition and motion dysfunction-associated brain functional network disruption in diabetic peripheral neuropathy. Hum Brain Mapp 2024; 45:e26563. [PMID: 38224534 PMCID: PMC10785193 DOI: 10.1002/hbm.26563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/31/2023] [Accepted: 11/28/2023] [Indexed: 01/17/2024] Open
Abstract
Neuroimaging studies have demonstrated extensive brain functional alterations in cognitive and motor functional areas in Type 2 diabetes mellitus (T2DM) with diabetic peripheral neuropathy (DPN), suggesting potential alterations in large-scale brain networks related to DPN and associated cognition and motor dysfunction. In this study, using resting-state functional connectivity (FC) and graph theory computational approaches, we investigated the topological disruptions of brain functional networks in 28 DPN, 43 T2DM without DPN (NDPN), and 32 healthy controls (HCs) and examined the correlations between altered network topological metrics and cognitive/motor function parameters in T2DM. For global topology, NDPN exhibited a significantly decreased shortest path length compared with HCs, suggesting increased efficient global integration. For regional topology, DPN and NDPN had separated topological reorganization of functional hubs compared with HCs. In addition, DPN showed significantly decreased nodal efficiency (Enodal ), mainly in the bilateral superior occipital gyrus (SOG), right cuneus, middle temporal gyrus (MTG), and left inferior parietal gyrus (IPL), compared with NDPN, whereas NDPN showed significantly increased Enodal compared with HCs. Intriguingly, in T2DM patients, the Enodal of the right SOG was significantly negatively correlated with Toronto Clinical Scoring System scores, while the Enodal of the right postcentral gyrus (PoCG) and MTG were significantly positively correlated with Montreal Cognitive Assessment scores. Conclusively, DPN and NDPN patients had segregated disruptions in the brain functional network, which were related to cognition and motion dysfunctions. Our findings provide a theoretical basis for understanding the neurophysiological mechanism of DPN and its effective prevention and treatment in T2DM.
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Affiliation(s)
- Haotian Xin
- Department of Radiology, Shandong Provincial HospitalShandong UniversityJinanChina
| | - Yajie Fu
- Department of Radiology, Shandong Provincial HospitalShandong UniversityJinanChina
- Department of Medical UltrasoundThe First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Medicine and Health Key Laboratory of Abdominal Medical ImagingJinanChina
| | - Hongwei Wen
- Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of PsychologySouthwest UniversityChongqingChina
| | - Mengmeng Feng
- Department of Radiology, Shandong Provincial HospitalShandong UniversityJinanChina
| | - Chaofan Sui
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain AgingMinistry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
| | - Yian Gao
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain AgingMinistry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
| | - Lingfei Guo
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain AgingMinistry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
| | - Changhu Liang
- Department of Radiology, Shandong Provincial HospitalShandong UniversityJinanChina
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain AgingMinistry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanChina
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Roth R, Busby N, Wilmskoetter J, Schwen Blackett D, Gleichgerrcht E, Johnson L, Rorden C, Newman-Norlund R, Hillis AE, den Ouden DB, Fridriksson J, Bonilha L. Diabetes, brain health, and treatment gains in post-stroke aphasia. Cereb Cortex 2023; 33:8557-8564. [PMID: 37139636 PMCID: PMC10321080 DOI: 10.1093/cercor/bhad140] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 05/05/2023] Open
Abstract
In post-stroke aphasia, language improvements following speech therapy are variable and can only be partially explained by the lesion. Brain tissue integrity beyond the lesion (brain health) may influence language recovery and can be impacted by cardiovascular risk factors, notably diabetes. We examined the impact of diabetes on structural network integrity and language recovery. Seventy-eight participants with chronic post-stroke aphasia underwent six weeks of semantic and phonological language therapy. To quantify structural network integrity, we evaluated the ratio of long-to-short-range white matter fibers within each participant's whole brain connectome, as long-range fibers are more susceptible to vascular injury and have been linked to high level cognitive processing. We found that diabetes moderated the relationship between structural network integrity and naming improvement at 1 month post treatment. For participants without diabetes (n = 59), there was a positive relationship between structural network integrity and naming improvement (t = 2.19, p = 0.032). Among individuals with diabetes (n = 19), there were fewer treatment gains and virtually no association between structural network integrity and naming improvement. Our results indicate that structural network integrity is associated with treatment gains in aphasia for those without diabetes. These results highlight the importance of post-stroke structural white matter architectural integrity in aphasia recovery.
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Affiliation(s)
- Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Janina Wilmskoetter
- Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Deena Schwen Blackett
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Ezequiel Gleichgerrcht
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | | | - Argye E Hillis
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD 21218 USA
| | - Dirk B den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
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Disrupted topological organization of functional brain networks is associated with cognitive impairment in hypertension patients: a resting-state fMRI study. Neuroradiology 2023; 65:323-336. [PMID: 36219250 DOI: 10.1007/s00234-022-03061-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 09/24/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE To investigate the alterations of topological organization of the whole brain functional networks in hypertension patients with cognitive impairment (HTN-CI) and characterize its relationship with cognitive scores. METHODS Fifty-seven hypertension patients with cognitive impairment and 59 hypertension patients with normal cognition (HTN-NC), and 49 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Graph theoretical analysis was used to investigate the altered topological organization of the functional brain networks. The global topological properties and nodal metrics were compared among the three groups. Network-based statistic (NBS) analysis was used to determine the connected subnetwork. The relationships between network metrics and cognitive scores were also characterized. RESULTS HTN-CI patients exhibited significantly decreased global efficiency, lambda, and increased shortest path length when compared with HCs. In addition, both HTN-CI and HTN-NC groups exhibited altered nodal degree centrality and nodal efficiency in the right precentral gyrus. The disruptions of global network metrics (lambda, Lp) and the nodal metrics (degree centrality and nodal efficiency) in the right precentral gyrus were positively correlated with the MoCA scores in HTN-CI. NBS analysis demonstrated that decreased subnetwork connectivity was present both in the HTN-CI and HTN-NC groups, which were mainly involved in the default mode network, frontoparietal network, and cingulo-opercular network. CONCLUSION This study demonstrated the alterations of topographical organization and subnetwork connectivity of functional brain networks in HTN-CI. In addition, the global and nodal network properties were correlated with cognitive scores, which may provide useful insights for the understanding of neuropsychological mechanisms underlying HTN-CI.
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Zhang D, Liu S, Huang Y, Gao J, Liu W, Liu W, Ai K, Lei X, Zhang X. Altered Functional Connectivity Density in Type 2 Diabetes Mellitus with and without Mild Cognitive Impairment. Brain Sci 2023; 13:brainsci13010144. [PMID: 36672125 PMCID: PMC9856282 DOI: 10.3390/brainsci13010144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/06/2023] [Accepted: 01/11/2023] [Indexed: 01/18/2023] Open
Abstract
Although disturbed functional connectivity is known to be a factor influencing cognitive impairment, the neuropathological mechanisms underlying the cognitive impairment caused by type 2 diabetes mellitus (T2DM) remain unclear. To characterize the neural mechanisms underlying T2DM-related brain damage, we explored the altered functional architecture patterns in different cognitive states in T2DM patients. Thirty-seven T2DM patients with normal cognitive function (DMCN), 40 T2DM patients with mild cognitive impairment (MCI) (DMCI), and 40 healthy controls underwent neuropsychological assessments and resting-state functional MRI examinations. Functional connectivity density (FCD) analysis was performed, and the relationship between abnormal FCD and clinical/cognitive variables was assessed. The regions showing abnormal FCD in T2DM patients were mainly located in the temporal lobe and cerebellum, but the abnormal functional architecture was more extensive in DMCI patients. Moreover, in comparison with the DMCN group, DMCI patients showed reduced long-range FCD in the left superior temporal gyrus (STG), which was correlated with the Rey auditory verbal learning test score in all T2DM patients. Thus, DMCI patients show functional architecture abnormalities in more brain regions involved in higher-level cognitive function (executive function and auditory memory function), and the left STG may be involved in the neuropathology of auditory memory in T2DM patients. These findings provide some new insights into understanding the neural mechanisms underlying T2DM-related cognitive impairment.
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Affiliation(s)
- Dongsheng Zhang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Shasha Liu
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Yang Huang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Jie Gao
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Weirui Liu
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Wanting Liu
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Kai Ai
- Department of Clinical Science, Philips Healthcare, Xi’an 710000, China
| | - Xiaoyan Lei
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
| | - Xiaoling Zhang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an 710068, China
- Correspondence: ; Tel.: +86-13087581380
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Lin L, Zhang J, Liu Y, Hao X, Shen J, Yu Y, Xu H, Cong F, Li H, Wu J. Aberrant brain functional networks in type 2 diabetes mellitus: A graph theoretical and support-vector machine approach. Front Hum Neurosci 2022; 16:974094. [PMID: 36310847 PMCID: PMC9597867 DOI: 10.3389/fnhum.2022.974094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 08/23/2022] [Indexed: 11/23/2022] Open
Abstract
Objective Type 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities. Methods A total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC. Results In patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model. Conclusion Functional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM.
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Affiliation(s)
- Lin Lin
- Graduate School, Tianjin Medical University, Tianjin, China
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Jindi Zhang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
| | - Yutong Liu
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
| | - Xinyu Hao
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
- Faculty of Information Technology, University of Jyvaskyla, Jyvaskyla, Finland
| | - Jing Shen
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Yang Yu
- Department of Endocrinology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Huashuai Xu
- Faculty of Information Technology, University of Jyvaskyla, Jyvaskyla, Finland
| | - Fengyu Cong
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
| | - Huanjie Li
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
- School of Biomedical Engineering, Dalian University of Technology, Dalian, China
- Huanjie Li,
| | - Jianlin Wu
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
- *Correspondence: Jianlin Wu,
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