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Zhang W, Fu L, Bi Y, Liu J, Li X, Zhang X, Zhang Z, Miao Y, Cheng H, Zhang B. Large-scale functional network connectivity mediates the associations between lipids metabolism and cognition in type 2 diabetes. J Cereb Blood Flow Metab 2024; 44:384-396. [PMID: 37795619 PMCID: PMC10870959 DOI: 10.1177/0271678x231204426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/06/2023] [Accepted: 09/04/2023] [Indexed: 10/06/2023]
Abstract
Type 2 diabetes (T2D) is associated with dyslipidemia and mild cognitive impairment. This study investigated the relationships between serum lipids metabolism, cognition, and functional connectivity (FC) within and between brain networks in T2D patients. The study included 102 T2D patients and 45 healthy controls who underwent functional magnetic resonance imaging, lipid profile tests, and cognitive assessments. Thirteen functional networks were identified using independent component analysis. The statistical analyses included multivariate analysis of covariance, partial correlation, canonical correlation, and mediation analyses. We found widely reduced between-network FCs in T2D, especially between the ventral sensorimotor network (SMN) and dorsal attention network (DAN) (p = 0.001) and between the ventral SMN and lateral visual network (VN) (p < 0.001). Moreover, lower between-network FCs were correlated with worse serum lipids metabolism and poorer cognitive performance (all p < 0.05). Importantly, between-network FCs mediated the relationship between lipid metabolism and cognition (β = -0.3136, 95% CI: -0.7660, -0.0186). Within-network analyses revealed altered FCs within the anterior default mode network, DAN, and lateral VN, each positively correlated with global cognition (all p < 0.01). Our results suggest the potential of improving cognitive function by regulating serum lipids in individuals with T2D.
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Affiliation(s)
- Wen Zhang
- Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Linqing Fu
- Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yan Bi
- Department of Endocrinology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Jiani Liu
- Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Xin Li
- Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Xin Zhang
- Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
| | - Zhou Zhang
- Department of Endocrinology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yingwen Miao
- Department of Endocrinology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Haiyan Cheng
- Department of Endocrinology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Bing Zhang
- Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Institute of Brain Science, Nanjing University, Nanjing, China
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Ni MH, Li ZY, Sun Q, Yu Y, Yang Y, Hu B, Ma T, Xie H, Li SN, Tao LQ, Yuan DX, Zhu JL, Yan LF, Cui GB. Neurovascular decoupling measured with quantitative susceptibility mapping is associated with cognitive decline in patients with type 2 diabetes. Cereb Cortex 2022; 33:5336-5346. [PMID: 36310091 DOI: 10.1093/cercor/bhac422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/26/2022] [Accepted: 09/28/2022] [Indexed: 01/10/2023] Open
Abstract
Abstract
Disturbance of neurovascular coupling (NVC) is suggested to be one potential mechanism in type 2 diabetes mellitus (T2DM) associated mild cognitive impairment (MCI). However, NVC evidence derived from functional magnetic resonance imaging ignores the relationship of neuronal activity with vascular injury. Twenty-seven T2DM patients without MCI and thirty healthy controls were prospectively enrolled. Brain regions with changed susceptibility detected by quantitative susceptibility mapping (QSM) were used as seeds for functional connectivity (FC) analysis. NVC coefficients were estimated using combined degree centrality (DC) with susceptibility or cerebral blood flow (CBF). Partial correlations between neuroimaging indicators and cognitive decline were investigated. In T2DM group, higher susceptibility values in right hippocampal gyrus (R.PHG) were found and were negatively correlated with Naming Ability of Montreal Cognitive Assessment. FC increased remarkably between R.PHG and right middle temporal gyrus (R.MTG), right calcarine gyrus (R.CAL). Both NVC coefficients (DC-QSM and DC-CBF) reduced in R.PHG and increased in R.MTG and R.CAL. Both NVC coefficients in R.PHG and R.MTG increased with the improvement of cognitive ability, especially for executive function. These demonstrated that QSM and DC-QSM coefficients can be promising biomarkers for early evaluation of cognitive decline in T2DM patients and help to better understand the mechanism of NVC.
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Affiliation(s)
- Min-Hua Ni
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
- Faculty of Medical Technology, Shaanxi University of Chinese Medicine , 1 Middle Section of Shiji Road, Xian yang, Shaanxi 712046 , China
| | - Ze-Yang Li
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Qian Sun
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Ying Yu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Yang Yang
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Bo Hu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Teng Ma
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Hao Xie
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Si-Ning Li
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
- Faculty of Medical Technology, Xi’an Medical University , 1 Xinwang Road, Xi'an, Shaanxi 710016 , China
| | - Lan-Qiu Tao
- Student Brigade, Fourth Military Medical University , 169 Changle Road, Xi'an, Shaanxi 710032 , China
| | - Ding-Xin Yuan
- Student Brigade, Fourth Military Medical University , 169 Changle Road, Xi'an, Shaanxi 710032 , China
| | - Jun-Ling Zhu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Lin-Feng Yan
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Guang-Bin Cui
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
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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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Canna A, Esposito F, Tedeschi G, Trojsi F, Passaniti C, di Meo I, Polito R, Maiorino MI, Paolisso G, Cirillo M, Rizzo MR. Neurovascular coupling in patients with type 2 diabetes mellitus. Front Aging Neurosci 2022; 14:976340. [PMID: 36118711 PMCID: PMC9476313 DOI: 10.3389/fnagi.2022.976340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 08/15/2022] [Indexed: 11/29/2022] Open
Abstract
Functional and metabolic neural changes in Type 2 diabetes mellitus (T2DM) can be associated with poor cognitive performances. Here we analyzed the functional-metabolic neurovascular coupling (NVC) in the brain of T2DM patients. Thirty-three patients (70 ± 6 years, 15 males) with recent T2DM diagnosis and 18 healthy control (HC) subjects (65 ± 9 years, 9 males) were enrolled in a brain MRI study to identify the potential effects of T2DM on NVC. T2DM patients were either drug-naive (n = 19) or under treatment with metformin (n = 14) since less than 6 months. Arterial spin labeling and blood oxygen level dependent resting-state functional MRI (RS-fMRI) images were combined to derive NVC measures in brain regions and large-scale networks in a standard brain parcelation. Altered NVC values in T2DM patients were correlated with cognitive performances spanning several neurological domains using Spearman correlation coefficients. Compared to HC, T2DM patients had reduced NVC in the default mode network (DMN) and increased NVC in three regions of the dorsal (DAN) and salience-ventral (SVAN) attention networks. NVC abnormalities in DAN and SVAN were associated with reduced visuo-spatial cognitive performances. A spatial pattern of NVC reduction in the DMN, accompanied by isolated regional NVC increases in DAN and SVAN, could reflect the emergence of (defective) compensatory processes in T2DM patients in response to altered neurovascular conditions. Overall, this pattern is reminiscent of neural abnormalities previously observed in Alzheimer’s disease, suggesting that similar neurobiological mechanisms, secondary to insulin resistance and manifesting as NVC alterations, might be developing in T2DM pathology.
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