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Han X, Huang S, Zhuang Z, Zhang X, Xie M, Lou N, Hua M, Zhuang X, Yu S, Chen S. Phosphatidate phosphatase Lipin1 involves in diabetic encephalopathy pathogenesis via regulating synaptic mitochondrial dynamics. Redox Biol 2024; 69:102996. [PMID: 38103341 PMCID: PMC10770635 DOI: 10.1016/j.redox.2023.102996] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 12/11/2023] [Indexed: 12/19/2023] Open
Abstract
Diabetic encephalopathy (DE) is a common central nervous system complication of diabetes mellitus without effective therapy currently. Recent studies have highlighted synaptic mitochondrial damages as a possible pathological basis for DE, but the underlying mechanisms remain unclear. Our previous work has revealed that phosphatidate phosphatase Lipin1, a critical enzyme involved with phospholipid synthesis, is closely related to the pathogenesis of DE. Here, we demonstrate that Lipin1 is significantly down-regulated in rat hippocampus of DE. Knock-down of Lipin1 within hippocampus of normal rats induces dysregulation of homeostasis in synaptic mitochondrial dynamics with an increase of mitochondrial fission and a decrease of fusion, then causes synaptic mitochondrial dysfunction, synaptic plasticity deficits as well as cognitive impairments, similar to that observed in response to chronic hyperglycemia exposure. In contrast, an up-regulation of Lipin1 within hippocampus in the DE model ameliorates this cascade of dysfunction. We also find that the effect of Lipin1 that regulating mitochondrial dynamics results from maintaining appropriate phospholipid components in the mitochondrial membrane. In conclusion, alterations in hippocampal Lipin1 contribute to hippocampal synaptic mitochondrial dysfunction and cognitive deficits observed in DE. Targeting Lipin1 might be a potential therapeutic strategy for the clinical treatment of DE.
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Affiliation(s)
- Xiaolin Han
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Shan Huang
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Ziyun Zhuang
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China; Department of Endocrinology and Metabolism, First People's Hospital of Jinan, Jinan, 250011, China
| | - Xiaochen Zhang
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China; Department of Clinical Medicine, Heze Medical College, Heze, 274009, China
| | - Min Xie
- Department of Endocrinology and Metabolism, Binzhou Medical University Hospital, Binzhou, 256603, China
| | - Nengjun Lou
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China; Multidisciplinary Innovation Center for Nephrology of the Second Hospital of Shandong University, Jinan, 250033, China
| | - Mengyu Hua
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Xianghua Zhuang
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China; Multidisciplinary Innovation Center for Nephrology of the Second Hospital of Shandong University, Jinan, 250033, China.
| | - Shuyan Yu
- Department of Physiology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
| | - Shihong Chen
- Depratment of Endocrinology and Metabolism, The Second Hospital of Shandong University, Jinan, 250033, China; Multidisciplinary Innovation Center for Nephrology of the Second Hospital of Shandong University, Jinan, 250033, China.
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Huang Y, Zhang X, Cheng M, Yang Z, Liu W, Ai K, Tang M, Zhang X, Lei X, Zhang D. Altered cortical thickness-based structural covariance networks in type 2 diabetes mellitus. Front Neurosci 2024; 18:1327061. [PMID: 38332862 PMCID: PMC10851426 DOI: 10.3389/fnins.2024.1327061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/11/2024] [Indexed: 02/10/2024] Open
Abstract
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.
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Affiliation(s)
- Yang Huang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Xin Zhang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Miao Cheng
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Zhen Yang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Wanting Liu
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Kai Ai
- Department of Clinical and Technical Support, Philips Healthcare, Xi’an, China
| | - Min Tang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Xiaoling Zhang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Xiaoyan Lei
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Dongsheng Zhang
- Department of MRI, Shaanxi Provincial People’s Hospital, Xi’an, China
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Wang YX, Liang JX, Lin R, Yan YJ, Li H, Chen MF. Stratified support pattern-based internet-assisted self-management therapy for diabetes mellitus -mild cognitive impairment: a randomized controlled trial protocol. BMC Endocr Disord 2023; 23:240. [PMID: 37919711 PMCID: PMC10621157 DOI: 10.1186/s12902-023-01485-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 10/11/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Mild cognitive impairment (MCI) associated with diabetes mellitus (DM) is common among older adults, and self-management is critical to controlling disease progression. However, both MCI and DM are heterogeneous diseases, and existing integrated self-management interventions do not consider patient differences. Grouping patients by disease characteristics could help to individualize disease management and improve the use of available resources. The current study sought to explore the feasibility and effectiveness of a stratified support model for DM-MCI patients. METHODS Eighty-four DM-MCI patients will be randomly divided into an intervention group and a control group in a 1:1 ratio. The intervention group will receive a self-management intervention using the stratified support pattern-based internet-assisted therapy (SISMT), while the control group will receive the health manual intervention (HMI). The study recruiter will be blinded to the group allocation and unable to foresee which group the next participant will be assigned to. At the same time, the allocation will be also hidden from the research evaluators and participants. After 12 weeks and 24 weeks, cognitive function, blood glucose, self-management ability, psychological status, health literacy, and self-management behavior of patients in both groups will be measured and compared. DISCUSSION This study developed a stratified support pattern-based internet-assisted to provide self-management intervention for patients with DM-MCI. The impact of different models and forms of self-management intervention on cognitive function, blood glucose management, and psychological status health literacy and self-management behavior of patients will be assessed. The results of this study will inform related intervention research on the stratified support pattern-based internet-assisted self-management therapy, and help to slow the decline of cognitive function in patients with DM-MCI. TRIAL REGISTRATION ChiCTR2200061991. Registered 16 July 2022.
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Affiliation(s)
- Yun-Xian Wang
- The School of Nursing, Fujian Medical University, No. 88 Jiaotong Road, Fuzhou City, 350004, Fujian Province, China
- Nursing Department, The First People's Hospital of Yunnan Province, No 157 Jinbi Road, Kunming City, 650032, Yunnan Province, China
| | - Ji-Xing Liang
- Endocrinology Department, Fujian Provincial Hospital & Shengli Clinical Medical College, No. 134 East Street, Fuzhou City, 350122, Fujian Province, China
| | - Rong Lin
- The School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Fuzhou City, 350122, Fujian Province, China
| | - Yuan-Jiao Yan
- Research Center for Nursing Theory and Practice, Fujian Provincial Hospital & Shengli Clinical Medical College, No. 134 East Street, Fuzhou City, 350122, Fujian Province, China
| | - Hong Li
- The School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Fuzhou City, 350122, Fujian Province, China.
| | - Ming-Feng Chen
- Neurology Department, Fujian Provincial Hospital & Shengli Clinical Medical College, No. 134 East Street, Fuzhou City, 350122, Fujian Province, China.
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Madole JW, Buchanan CR, Rhemtulla M, Ritchie SJ, Bastin ME, Deary IJ, Cox SR, Tucker-Drob EM. Strong intercorrelations among global graph-theoretic indices of structural connectivity in the human brain. Neuroimage 2023; 275:120160. [PMID: 37169117 DOI: 10.1016/j.neuroimage.2023.120160] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/06/2023] [Accepted: 05/08/2023] [Indexed: 05/13/2023] Open
Abstract
Graph-theoretic metrics derived from neuroimaging data have been heralded as powerful tools for uncovering neural mechanisms of psychological traits, psychiatric disorders, and neurodegenerative diseases. In N = 8,185 human structural connectomes from UK Biobank, we examined the extent to which 11 commonly-used global graph-theoretic metrics index distinct versus overlapping information with respect to interindividual differences in brain organization. Using unthresholded, FA-weighted networks we found that all metrics other than Participation Coefficient were highly intercorrelated, both with each other (mean |r| = 0.788) and with a topologically-naïve summary index of brain structure (mean edge weight; mean |r| = 0.873). In a series of sensitivity analyses, we found that overlap between metrics is influenced by the sparseness of the network and the magnitude of variation in edge weights. Simulation analyses representing a range of population network structures indicated that individual differences in global graph metrics may be intrinsically difficult to separate from mean edge weight. In particular, Closeness, Characteristic Path Length, Global Efficiency, Clustering Coefficient, and Small Worldness were nearly perfectly collinear with one another (mean |r| = 0.939) and with mean edge weight (mean |r| = 0.952) across all observed and simulated conditions. Global graph-theoretic measures are valuable for their ability to distill a high-dimensional system of neural connections into summary indices of brain organization, but they may be of more limited utility when the goal is to index separable components of interindividual variation in specific properties of the human structural connectome.
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Affiliation(s)
- James W Madole
- Department of Psychology, University of Texas at Austin, Austin, TX, USA; VA Puget Sound Health Care System, Seattle Division, Seattle, WA, USA.
| | - Colin R Buchanan
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Mijke Rhemtulla
- Department of Psychology, University of California, Davis, CA, USA
| | - Stuart J Ritchie
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Mark E Bastin
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Elliot M Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA; Population Research Center and Center on Aging and Population Sciences, University of Texas at Austin, Austin, TX, 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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Alterations in regional homogeneity and functional connectivity associated with cognitive impairment in patients with hypertension: a resting-state functional magnetic resonance imaging study. Hypertens Res 2023; 46:1311-1325. [PMID: 36690806 DOI: 10.1038/s41440-023-01168-3] [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: 05/26/2022] [Revised: 11/09/2022] [Accepted: 12/22/2022] [Indexed: 01/24/2023]
Abstract
Our study aims to investigate the alterations and diagnostic efficiency of regional homogeneity (ReHo) and functional connectivity (FC) in hypertension patients with cognitive impairment. A total of 62 hypertension patients with cognitive impairment (HTN-CI), 59 hypertension patients with normal cognition (HTN-NC), and 58 healthy controls (HCs) with rs-fMRI data were enrolled in this study. Univariate analysis (based on whole-brain ReHo and seed-based FC maps) was performed to observe brain regions with significant differences among the three groups. Multiple voxel pattern analysis (MVPA) was applied to evaluate the diagnostic accuracy in classifying HTN-CI from HTN-NC and HCs. Compared with the HCs and HTN-NC, HTN-CI exhibited decreased ReHo in the right caudate, left postcentral gyrus, posterior cingulate gyrus, insula, while increased ReHo in the left superior occipital gyrus and superior parietal gyrus. HTN-CI showed increased FC between seed regions (left posterior cingulate gyrus, insula, postcentral gyrus) with many specific brain regions. MVPA analysis (based on whole-brain ReHo and seed-based FC maps) displayed high classification ability in distinguishing HTN-CI from HTN-NC and HCs. The ReHo values (right caudate) and the FC values (left postcentral gyrus seed to left posterior cingulate gyrus) were positively correlated with the MoCA scores in HTN-CI. HTN-CI was associated with decreased ReHo and increased FC mainly in the left posterior cingulate gyrus, postcentral gyrus, insula compared to HTN-NC and HC. Besides, MVPA analysis yields excellent diagnostic accuracy in classifying HTN-CI from HTN-NC and HCs. The findings may contribute to unveiling the underlying neuropathological mechanism of 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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Zhang G, Liu T, Wei W, Zhang R, Wang H, Wang M. Evaluation of altered brain activity in type 2 diabetes using various indices of brain function: A resting-state functional magnetic resonance imaging study. Front Hum Neurosci 2023; 16:1032264. [PMID: 36699964 PMCID: PMC9870028 DOI: 10.3389/fnhum.2022.1032264] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/05/2022] [Indexed: 01/11/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) has been identified as a risk factor that increases the rate of cognitive decline. Previous studies showed that patients with T2DM had brain function alterations based on a single index of resting-state functional magnetic resonance imaging (rs-fMRI). The present study aimed to explore spontaneous brain activity in patients with T2DM by comparing various rs-fMRI indices, and to determine the relationship between these changes and cognitive dysfunction. Methods A total of 52 patients with T2DM and age- and sex-matched control participants were included in this study. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC) values were calculated to represent the status of spontaneous neural activity. The Montreal Cognitive Assessment (MoCA) was used for the rapid evaluation of cognition in all subjects. Pearson correlation and mediation analyses were conducted to investigate the relationship between rs-fMRI indices and clinical parameters such as fasting glucose, disease duration, and MoCA. Results Patients with T2DM had alterations of concordant spontaneous brain activity in brain areas including the bilateral cerebellum posterior lobe, the left inferior temporal gyrus (ITG.L), the parahippocampal gyrus, and the left supplementary motor area (SMA.L). The indices were significantly correlated to each other in most of the detected brain areas. Positive correlations were observed between fasting glucose and neural activity in the surrounding areas of the left insula and the inferior frontal gyrus. MoCA scores were negatively correlated with the ReHo values extracted from the left anterior occipital lobe and the superior cerebellar cortex and were positively correlated with VMHC values extracted from the left caudate and the precentral gyrus (PreCG). No significant mediation effect of abnormal brain activity was found in the relationship between clinical parameters and MoCA scores. Conclusion The current study demonstrated the functional concordance of abnormal brain activities in patients with T2DM by comparing ALFF, ReHo, and VMHC measurements. Widespread abnormalities mainly involved in motor and sensory processing functions may provide insight into examining T2DM-related neurological pathophysiology.
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Affiliation(s)
- Ge Zhang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China,Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Taiyuan Liu
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Rui Zhang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Huilin Wang
- Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China,*Correspondence: Huilin Wang ✉
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China,Laboratory of Brian Science and Brain-Like Intelligence Technology, Institute for Integrated Medical Science and Engineering, Henan Academy of Sciences, Zhengzhou, China,Meiyun Wang ✉
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Huang Y, Zhang D, Zhang X, Cheng M, Yang Z, Gao J, Tang M, Ai K, Lei X, Zhang X. Altered functional hubs and connectivity in type 2 diabetes mellitus with and without mild cognitive impairment. Front Neurol 2022; 13:1062816. [PMID: 36578308 PMCID: PMC9792165 DOI: 10.3389/fneur.2022.1062816] [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: 10/06/2022] [Accepted: 11/21/2022] [Indexed: 12/14/2022] Open
Abstract
Cognitive impairment in type 2 diabetes mellitus (T2DM) is associated with functional and structural abnormalities of brain networks, especially the damage to hub nodes in networks. This study explored the abnormal hub nodes of brain functional networks in patients with T2DM under different cognitive states. Sixty-five patients with T2DM and 34 healthy controls (HCs) underwent neuropsychological assessment. Then, degree centrality (DC) analysis and seed-based functional connectivity (FC) analysis were performed to identify the abnormal hub nodes and the FC patterns of these hubs in T2DM patients with mild cognitive impairment (MCI) (DMCI group, N = 31) and without MCI (DMCN group, N = 34). Correlation analyzes examined the relationship between abnormal DC and FC and clinical/cognitive variables. Compared with HCs, both T2DM groups showed decreased DC values in the visual cortex, and the T2DM patients with MCI (DMCI) showed more extensive alterations in the right parahippocampal gyrus (PHG), bilateral posterior cingulate cortex (PCC), and left superior frontal gyrus (SFG) regions than T2DM patients with normal cognitive function. Seed-based FC analysis of PHG and PCC nodes showed that functional disconnection mainly occurred in visual and memory connectivity in patients with DMCI. Multiple abnormal DC values correlated with neuropsychological tests in patients with T2DM. In conclusion, this study found that the DMCI group displayed more extensive alterations in hub nodes and FC in vision and memory-related brain regions, suggesting that visual-related regions dysfunctions and disconnection may be involved in the neuropathology of visuospatial function impairment in patients with DMCI.
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Affiliation(s)
- Yang Huang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Dongsheng Zhang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Xin Zhang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Miao Cheng
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Zhen Yang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Jie Gao
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Min Tang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Kai Ai
- Department of Clinical and Technical Support, Philips Healthcare, Xi'an, China
| | - Xiaoyan Lei
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China,Xiaoyan Lei
| | - Xiaoling Zhang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, China,*Correspondence: Xiaoling Zhang
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Cui Y, Tang TY, Lu CQ, Ju S. Insulin Resistance and Cognitive Impairment: Evidence From Neuroimaging. J Magn Reson Imaging 2022; 56:1621-1649. [PMID: 35852470 DOI: 10.1002/jmri.28358] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/02/2022] [Accepted: 07/05/2022] [Indexed: 01/04/2023] Open
Abstract
Insulin is a peptide well known for its role in regulating glucose metabolism in peripheral tissues. Emerging evidence from human and animal studies indicate the multifactorial role of insulin in the brain, such as neuronal and glial metabolism, glucose regulation, and cognitive processes. Insulin resistance (IR), defined as reduced sensitivity to the action of insulin, has been consistently proposed as an important risk factor for developing neurodegeneration and cognitive impairment. Although the exact mechanism of IR-related cognitive impairment still awaits further elucidation, neuroimaging offers a versatile set of novel contrasts to reveal the subtle cerebral abnormalities in IR. These imaging contrasts, including but not limited to brain volume, white matter (WM) microstructure, neural function and brain metabolism, are expected to unravel the nature of the link between IR, cognitive decline, and brain abnormalities, and their changes over time. This review summarizes the current neuroimaging studies with multiparametric techniques, focusing on the cerebral abnormalities related to IR and therapeutic effects of IR-targeting treatments. According to the results, brain regions associated with IR pathophysiology include the medial temporal lobe, hippocampus, prefrontal lobe, cingulate cortex, precuneus, occipital lobe, and the WM tracts across the globe. Of these, alterations in the temporal lobe are highly reproducible across different imaging modalities. These structures have been known to be vulnerable to Alzheimer's disease (AD) pathology and are critical in cognitive processes such as memory and executive functioning. Comparing to asymptomatic subjects, results are more mixed in patients with metabolic disorders such as type 2 diabetes and obesity, which might be attributed to a multifactorial mechanism. Taken together, neuroimaging, especially MRI, is beneficial to reveal early abnormalities in cerebral structure and function in insulin-resistant brain, providing important evidence to unravel the underlying neuronal substrate that reflects the cognitive decline in IR. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ying Cui
- Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Tian-Yu Tang
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chun-Qiang Lu
- Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Shenghong Ju
- Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
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Huang H, Ma X, Yue X, Kang S, Li Y, Rao Y, Feng Y, Wu J, Long W, Chen Y, Lyu W, Tan X, Qiu S. White Matter Characteristics of Damage Along Fiber Tracts in Patients with Type 2 Diabetes Mellitus. Clin Neuroradiol 2022; 33:327-341. [DOI: 10.1007/s00062-022-01213-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 08/06/2022] [Indexed: 11/03/2022]
Abstract
Abstract
Purpose
The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear.
Methods
In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis.
Results
TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients.
Conclusion
Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.
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Association between Changes in White Matter Microstructure and Cognitive Impairment in White Matter Lesions. Brain Sci 2022; 12:brainsci12040482. [PMID: 35448013 PMCID: PMC9026911 DOI: 10.3390/brainsci12040482] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 03/24/2022] [Accepted: 04/02/2022] [Indexed: 02/05/2023] Open
Abstract
This study investigated the characteristics of cognitive impairment in patients with white matter lesions (WMLs) caused by cerebral small vessel disease and the corresponding changes in WM microstructures. Diffusion tensor imaging (DTI) data of 50 patients with WMLs and 37 healthy controls were collected. Patients were divided into vascular cognitive impairment non-dementia and vascular dementia groups. Tract-based spatial statistics showed that patients with WMLs had significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values throughout the WM areas but predominately in the forceps minor, forceps major (FMA), bilateral corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, inferior longitudinal fasciculus (ILF), and anterior thalamic radiation, compared to the control group. These fiber bundles were selected as regions of interest. There were significant differences in the FA, MD, AD, and RD values (p < 0.05) between groups. The DTI metrics of all fiber bundles significantly correlated with the Montreal Cognitive Assessment (p < 0.05), with the exception of the AD values of the FMA and ILF. Patients with WMLs showed changes in diffusion parameters in the main WM fiber bundles. Quantifiable changes in WM microstructure are the main pathological basis of cognitive impairment, and may serve as a biomarker of WMLs.
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Wang K, Jiang Z, Yu X, Shao Y, Liu H, Wu S, Kong L, Wang Z. Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis. Medicine (Baltimore) 2022; 101:e28946. [PMID: 35451386 PMCID: PMC8913128 DOI: 10.1097/md.0000000000028946] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 02/09/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND More and more studies have shown that cognitive dysfunction is one of the main complications of diabetes. The disorder of glucose and lipid metabolism seriously damages brain function and accelerates the conversion to dementia. At present, there are no drugs that can directly treat diabetic cognitive dysfunction. All drugs for the treatment of this disease achieve the purpose of treatment through strict control of blood sugar levels. This method has great limitations. Traditional Chinese patent medicines (TCPMs) work through multiple targets and multiple pathways, which can not only effectively correct the state of glucose and lipid metabolism disorders, but also significantly improve cognitive ability, but there is a lack of systematic evaluation of their effectiveness and safety. We use the method of network meta-analysis to systematically and comprehensively compare the effectiveness and safety of different Chinese patent medicines. METHODS We will comprehensively search the following databases, including Web of Science, PubMed, The Cochrane Library, EMBASE, China National Knowledge Infrastructure, Chinese Scientific Journals Database, Wanfang database and China BioMedical Literature. We will include all randomized controlled trials that meet the inclusion criteria, starting from the establishment of the database until September 2021. Two researchers will independently screen the literature based on inclusion criteria. While extracting data, we also assess the risk of bias in the included studies. All the data and evidence obtained will be evaluated by the method of Bayesian network meta-analysis. RESULTS This study will evaluate the effectiveness and safety of various TCPMs for diabetic cognitive dysfunction. CONCLUSION The results of this study will provide valuable references for the clinical application of TCPMs, and assist clinicians in formulating more reasonable diagnosis and treatment strategies. ETHICS AND DISSEMINATION This study does not require ethical approval. INTERNATIONAL PLATFORM OF REGISTERED SYSTEMATIC REVIEW AND METAANALYSIS PROTOCOLS REGISTRATION NUMBER INPLASY202190008.
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Affiliation(s)
- Kai Wang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, China
| | - Zhenyuan Jiang
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Xiaowen Yu
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
| | - Yuze Shao
- First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, China
| | - Hailiang Liu
- First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, China
| | - Susu Wu
- First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, China
| | - Linghui Kong
- First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, China
| | - Zhonglin Wang
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
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Paschoal AM. Editorial for "Diffusion Tensor Imaging Reveals Altered Topological Efficiency of Structural Networks in Type-2 Diabetes Patients With and Without Mild Cognitive Impairment". J Magn Reson Imaging 2021; 55:928-929. [PMID: 34424595 DOI: 10.1002/jmri.27899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 11/08/2022] Open
Affiliation(s)
- André M Paschoal
- LIM44, Instituto e Departamento de Radiologia, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
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