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Fall AB, Preti MG, Eshmawey M, Kagerer SM, Van De Ville D, Unschuld PG. Functional network centrality indicates interactions between APOE4 and age across the clinical spectrum of AD. Neuroimage Clin 2024; 43:103635. [PMID: 38941766 DOI: 10.1016/j.nicl.2024.103635] [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: 04/11/2024] [Revised: 06/07/2024] [Accepted: 06/18/2024] [Indexed: 06/30/2024]
Abstract
Advanced age is the most important risk factor for Alzheimer's disease (AD), and carrier-status of the Apolipoprotein E4 (APOE4) allele is the strongest known genetic risk factor. Many studies have consistently shown a link between APOE4 and synaptic dysfunction, possibly reflecting pathologically accelerated biological aging in persons at risk for AD. To test the hypothesis that distinct functional connectivity patterns characterize APOE4 carriers across the clinical spectrum of AD, we investigated 128 resting state functional Magnetic Resonance Imaging (fMRI) datasets from the Alzheimer's Disease Neuroimaging Initiative database (ADNI), representing all disease stages from cognitive normal to clinical dementia. Brain region centralities within functional networks, computed as eigenvector centrality, were tested for multivariate associations with chronological age, APOE4 carrier status and clinical stage (as well as their interactions) by partial least square analysis (PLSC). By PLSC analysis two distinct brain activity patterns could be identified, which reflected interactive effects of age, APOE4 and clinical disease stage. A first component including sensorimotor regions and parietal regions correlated with age and AD clinical stage (p < 0.001). A second component focused on medial-frontal regions and was specifically related to the interaction between age and APOE4 (p = 0.032). Our findings are consistent with earlier reports on altered network connectivity in APOE4 carriers. Results of our study highlight promise of graph-theory based network centrality to identify brain connectivity linked to genetic risk, clinical stage and age. Our data suggest the existence of brain network activity patterns that characterize APOE4 carriers across clinical stages of AD.
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Affiliation(s)
- Aïda B Fall
- Faculty of Medicine, University of Geneva (UNIGE), Geneva, Switzerland; Geriatric Psychiatry Service, University Hospitals of Geneva (HUG), Thônex, Switzerland; CIBM Center for Biomedical Imaging, Switzerland.
| | - Maria Giulia Preti
- Faculty of Medicine, University of Geneva (UNIGE), Geneva, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Mohamed Eshmawey
- Geriatric Psychiatry Service, University Hospitals of Geneva (HUG), Thônex, Switzerland
| | - Sonja M Kagerer
- Faculty of Medicine, University of Geneva (UNIGE), Geneva, Switzerland; Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Psychogeriatric Medicine, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland
| | - Dimitri Van De Ville
- Faculty of Medicine, University of Geneva (UNIGE), Geneva, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Paul G Unschuld
- Faculty of Medicine, University of Geneva (UNIGE), Geneva, Switzerland; Geriatric Psychiatry Service, University Hospitals of Geneva (HUG), Thônex, Switzerland
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De Marco M, Wright LM, Valera Bermejo JM, Ferguson CE. APOE ε4 positivity predicts centrality of episodic memory nodes in patients with mild cognitive impairment: A cohort-based, graph theory-informed study of cognitive networks. Neuropsychologia 2024; 192:108741. [PMID: 38040087 DOI: 10.1016/j.neuropsychologia.2023.108741] [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: 06/01/2023] [Revised: 11/12/2023] [Accepted: 11/23/2023] [Indexed: 12/03/2023]
Abstract
As network neuroscience can capture the systemic impact of APOE variability at a neuroimaging level, this study investigated the network-based cognitive endophenotypes of ε4-carriers and non-carriers across the continuum between normal ageing and Alzheimer's dementia (AD). We hypothesised that the impact of APOE-ε4 on cognitive functioning can be reliably captured by the measurement of graph-theory centrality. Cognitive networks were calculated in 8118 controls, 3482 MCI patients and 4573 AD patients, recruited in the National Alzheimer's Coordinating Center (NACC) database. Nodal centrality was selected as the neurofunctional readout of interest. ε4-carrier-vs.-non-carrier differences were tested in two independent NACC sub-cohorts assessed with either Version 1 or Version 2 of the Uniform Data Set neuropsychological battery. A significant APOE-dependent effect emerged from the analysis of the Logical-Memory nodes in MCI patients in both sub-cohorts. While non-carriers showed equal centrality in immediate and delayed recall, the latter was significantly less central among carriers (v1: bootstrapped confidence interval 0.107-0.667, p < 0.001; v2: bootstrapped confidence interval 0.018-0.432, p < 0.001). This indicates that, in carriers, delayed recall was, overall, significantly more weakly correlated with the other cognitive scores. These findings were replicated in the sub-groups of sole amnestic-MCI patients (n = 2971), were independent of differences in network communities, clinical severity or other demographic factors. No effects were found in the other two diagnostic groups. APOE-ε4 influences nodal properties of cognitive networks when patients are clinically classified as MCI. This highlights the importance of characterising the impact of risk factors on the wider cognitive network via network-neuroscience methodologies.
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Affiliation(s)
- Matteo De Marco
- Department of Life Sciences, Brunel University London, Uxbridge, United Kingdom.
| | - Laura M Wright
- Translational and Clinical Research Institute, Newcastle University, Newcastle-Upon-Tyne, United Kingdom
| | - Jose Manuel Valera Bermejo
- Institute of Psychiatry, Psychology & Neuroscience; Department of Neuroimaging; King's College London; London, United Kingdom.
| | - Cameron E Ferguson
- School of Psychological Science, University of Bristol, Bristol, United Kingdom
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Ficek-Tani B, Horien C, Ju S, Xu W, Li N, Lacadie C, Shen X, Scheinost D, Constable T, Fredericks C. Sex differences in default mode network connectivity in healthy aging adults. Cereb Cortex 2023; 33:6139-6151. [PMID: 36563018 PMCID: PMC10183749 DOI: 10.1093/cercor/bhac491] [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: 07/20/2022] [Revised: 11/18/2022] [Accepted: 11/20/2022] [Indexed: 12/24/2022] Open
Abstract
Women show an increased lifetime risk of Alzheimer's disease (AD) compared with men. Characteristic brain connectivity changes, particularly within the default mode network (DMN), have been associated with both symptomatic and preclinical AD, but the impact of sex on DMN function throughout aging is poorly understood. We investigated sex differences in DMN connectivity over the lifespan in 595 cognitively healthy participants from the Human Connectome Project-Aging cohort. We used the intrinsic connectivity distribution (a robust voxel-based metric of functional connectivity) and a seed connectivity approach to determine sex differences within the DMN and between the DMN and whole brain. Compared with men, women demonstrated higher connectivity with age in posterior DMN nodes and lower connectivity in the medial prefrontal cortex. Differences were most prominent in the decades surrounding menopause. Seed-based analysis revealed higher connectivity in women from the posterior cingulate to angular gyrus, which correlated with neuropsychological measures of declarative memory, and hippocampus. Taken together, we show significant sex differences in DMN subnetworks over the lifespan, including patterns in aging women that resemble changes previously seen in preclinical AD. These findings highlight the importance of considering sex in neuroimaging studies of aging and neurodegeneration.
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Affiliation(s)
- Bronte Ficek-Tani
- Department of Neurology, Yale School of Medicine, New Haven, CT 06520, United States
| | - Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, United States
| | - Suyeon Ju
- Department of Neurology, Yale School of Medicine, New Haven, CT 06520, United States
| | - Wanwan Xu
- Department of Biostatistics, Yale School of Medicine, New Haven, CT 06520, United States
| | - Nancy Li
- Department of Neurology, Yale School of Medicine, New Haven, CT 06520, United States
| | - Cheryl Lacadie
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, United States
| | - Carolyn Fredericks
- Department of Neurology, Yale School of Medicine, New Haven, CT 06520, United States
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Yang Z, Chen Y, Hou X, Xu Y, Bai F. Topologically convergent and divergent large scale complex networks among Alzheimer's disease spectrum patients: A systematic review. Heliyon 2023; 9:e15389. [PMID: 37101638 PMCID: PMC10123263 DOI: 10.1016/j.heliyon.2023.e15389] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 03/16/2023] [Accepted: 04/05/2023] [Indexed: 04/28/2023] Open
Abstract
Alzheimer's disease (AD) is associated with disruption at the level of a large-scale complex network. To explore the underlying mechanisms in the progression of AD, graph theory was used to quantitatively analyze the topological properties of structural and functional connections. Although an increasing number of studies have shown altered global and nodal network properties, little is known about the topologically convergent and divergent patterns between structural and functional networks among AD-spectrum patients. In this review, we summarized the topological patterns of the large-scale complex networks using multimodal neuroimaging graph theory analysis in AD spectrum patients. Convergent deficits in the connectivity characteristics were primarily in the default mode network (DMN) itself both in the structural and functional networks, while a divergent changes in the neighboring regions of the DMN were also observed between the patient groups. Together, the application of graph theory to large-scale complex brain networks provides quantitative insights into topological principles of brain network organization, which may lead to increasing attention in identifying the underlying neuroimaging pathological changes and predicting the progression of AD.
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Affiliation(s)
- Zhiyuan Yang
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Ya Chen
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing 210008, China
| | - Xinle Hou
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
- Department of Neurology, Nanjing Drum Tower Hospital, State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing 210008, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
- Geriatric Medicine Center, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
- Correspondence to: 321 Zhongshan Road, Nanjing, 210008, China.
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Ma J, Zheng MX, Wu JJ, Xing XX, Xiang YT, Wei D, Xue X, Zhang H, Hua XY, Guo QH, Xu JG. Mapping the long-term delayed recall-based cortex-hippocampus network constrained by the structural and functional connectome: a case-control multimodal MRI study. Alzheimers Res Ther 2023; 15:61. [PMID: 36964589 PMCID: PMC10037827 DOI: 10.1186/s13195-023-01197-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 02/23/2023] [Indexed: 03/26/2023]
Abstract
Background Connectome mapping may reveal new treatment targets for patients with neurological and psychiatric diseases. However, the long-term delayed recall based-network with structural and functional connectome is still largely unknown. Our objectives were to (1) identify the long-term delayed recall-based cortex-hippocampus network with structural and functional connectome and (2) investigate its relationships with various cognitive functions, age, and activities of daily living. Methods This case-control study enrolled 131 subjects (73 amnestic mild cognitive impairment [aMCI] patients and 58 age- and education-matched healthy controls [HCs]). All subjects completed a neuropsychological battery, activities of daily living assessment, and multimodal magnetic resonance imaging. Nodes of the cortical-hippocampal network related to long-term delayed recall were identified by probabilistic fiber tracking and functional connectivity (FC) analysis. Then, the main and interaction effects of the network on cognitive functions were assessed by a generalized linear model. Finally, the moderating effects of the network on the relationships between long-term delayed recall and clinical features were analyzed by multiple regression and Hayes’ bootstrap method. All the effects of cortex-hippocampus network were analyzed at the connectivity and network levels. Results The result of a generalized linear model showed that the bilateral hippocampus, left dorsolateral superior frontal gyrus, right supplementary motor area, left lingual gyrus, left superior occipital gyrus, left superior parietal gyrus, left precuneus, and right temporal pole (superior temporal gyrus) are the left and right cortex-hippocampus network nodes related to long-term delayed recall (P < 0.05). Significant interaction effects were found between the Auditory Verbal Learning Test Part 5 (AVLT 5) scores and global properties of the left cortex-hippocampus network [hierarchy, clustering coefficient, characteristic path length, global efficiency, local efficiency, Sigma and synchronization (P < 0.05 Bonferroni corrected)]. Significant interaction effects were found between the general cognitive function/executive function/language and global properties of the left cortex-hippocampus network [Sigma and synchronization (P < 0.05 Bonferroni corrected)]. Conclusion This study introduces a novel symptom-based network and describes relationships among cognitive functions, brain function, and age. The cortex–hippocampus network constrained by the structural and functional connectome is closely related to long-term delayed recall. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-023-01197-7.
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Affiliation(s)
- Jie Ma
- grid.412540.60000 0001 2372 7462Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437 China
- grid.412540.60000 0001 2372 7462School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China
| | - Mou-Xiong Zheng
- grid.412540.60000 0001 2372 7462Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437 China
| | - Jia-Jia Wu
- grid.412540.60000 0001 2372 7462Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437 China
| | - Xiang-Xin Xing
- grid.412540.60000 0001 2372 7462Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437 China
| | - Yun-Ting Xiang
- grid.412540.60000 0001 2372 7462School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China
| | - Dong Wei
- grid.412540.60000 0001 2372 7462School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China
| | - Xin Xue
- grid.412540.60000 0001 2372 7462School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China
| | - Han Zhang
- grid.440637.20000 0004 4657 8879School of Biomedical Engineering, ShanghaiTech University, Shanghai, 201210 China
| | - Xu-Yun Hua
- grid.412540.60000 0001 2372 7462Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437 China
| | - Qi-Hao Guo
- grid.412528.80000 0004 1798 5117Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, 200233 China
| | - Jian-Guang Xu
- grid.412540.60000 0001 2372 7462Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200437 China
- grid.412540.60000 0001 2372 7462School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203 China
- grid.419897.a0000 0004 0369 313XEngineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, 201203 China
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Wang M, Zhao G, Jiang Y, Lu T, Wang Y, Zhu Y, Zhang Z, Xie C, Wang Z, Ren Q. Disconnection of Network Hubs Underlying the Executive Function Deficit in Patients with Ischemic Leukoaraiosis. J Alzheimers Dis 2023; 94:1577-1586. [PMID: 37458032 DOI: 10.3233/jad-230048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
BACKGROUND Cognitive impairment is the most common clinical manifestation of ischemic leukoaraiosis (ILA), but the underlying neurobiological pathways have not been well elucidated. Recently, it was thought that ILA is a "disconnection syndrome". Disorganized brain connectome were considered the key neuropathology underlying cognitive deficits in ILA patients. OBJECTIVE We aimed to detect the disruption of network hubs in ILA patients using a new analytical method called voxel-based eigenvector centrality (EC) mapping. METHODS Subjects with moderate to severe white matters hyperintensities (Fazekas score ≥3) and healthy controls (HCs) (Fazekas score = 0) were included in the study. The resting-state functional magnetic resonance imaging and the EC mapping approach were performed to explore the alteration of whole-brain network connectivity in ILA patients. RESULTS Relative to the HCs, the ILA patients exhibited poorer cognitive performance in episodic memory, information processing speed, and executive function (all ps < 0.0125). Additionally, compared with HCs, the ILA patients had lower functional connectivity (i.e., EC values) in the medial parts of default-mode network (i.e., bilateral posterior cingulate gyrus and ventral medial prefrontal cortex [vMPFC]). Intriguingly, the functional connectivity strength at the right vMPFC was positively correlated with executive function deficit in the ILA patients. CONCLUSION The findings suggested disorganization of the hierarchy of the default-mode regions within the whole-brain network in patients with ILA and advanced our understanding of the neurobiological mechanism underlying executive function deficit in ILA.
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Affiliation(s)
- Mengxue Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Guofeng Zhao
- Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| | - Ying Jiang
- Department of Neurology, The 962nd Hospital of the PLA Joint Logistic Support Force, Harbin, China
| | - Tong Lu
- Department of Radiology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yanjuan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yixin Zhu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhengsheng Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Qingguo Ren
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
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Effects of apolipoprotein E4 genotype on cerebro-cerebellar connectivity, brain atrophy, and cognition in patients with Alzheimer's disease. J Neurol Sci 2022; 442:120435. [PMID: 36201963 DOI: 10.1016/j.jns.2022.120435] [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: 02/26/2022] [Revised: 08/28/2022] [Accepted: 09/18/2022] [Indexed: 11/20/2022]
Abstract
INTRODUCTION While several studies have substantially revealed the influence of the apolipoprotein E4 genotype (APOE4) on the vulnerability of Alzheimer's disease (AD), there are still far fewer studies investigating whether and how APOE4, in the absence of the amyloid-β (Aβ), alters regional brain atrophy, cerebro-cerebellar connectivity and cognitive performance in AD patients. METHODS We employed MRI and neuropsychological data from 234 old adults with AD dementia, including 143 APOE4-positive (with ε2/ε4, ε3/ε4, or ε4/ε4 alleles) and 91 APOE4-negative (with ε2/ε2, ε2/ε3 or ε3/ε3), to investigate the cerebro-cerebellar connectivity in three cerebro-cerebellar brain networks: default mode network, motor network and affective-limbic network. Amyloid PET images were used to evaluate individual Aβ burdens, later used as covariates. Regional volumetric and cortical thickness measures were quantified in both the cerebellum and the cerebrum using the cerebellum segmentation algorithm and Freesurfer5.3, respectively. RESULTS Our corrected functional connectivity (FC) results showed that APOE4 carriers (APOE4+) had lower FC within the cerebro-cerebellar motor network. In addition, significant group differences in regional cortical thickness were observed in the left Crus I, the right VIIB, left superior frontal, and right middle temporal gyri. Group differences in regional brain volumes were observed in the left lobule V and right parstriangularis. Furthermore, multiple linear regression analysis indicated that APOE4+ AD patients show greater episodic memory impairment. CONCLUSION Since amyloid-β, age, education, and gender were included as confounds in the statistical models, our findings suggest that APOE4 independently contributes to brain atrophy, disrupted FC, and associated memory declines in AD patients.
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Wang Z, Zhang Z, Xie C, Shu H, Liu D, Zhang Z. Identification of the Neural Circuit Underlying Episodic Memory Deficit in Amnestic Mild Cognitive Impairment via Machine Learning on Gray Matter Volume. J Alzheimers Dis 2021; 84:959-964. [PMID: 34602473 DOI: 10.3233/jad-210579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Based on whole-brain gray matter volume (GMV), we used relevance vector regression to predict the Rey's Auditory Verbal Learning Test Delayed Recall (AVLT-DR) scores of individual amnestic mild cognitive impairment (aMCI) patient. The whole-brain GMV pattern could significantly predict the AVLT-DR scores (r = 0.54, p < 0.001). The most important GMV features mainly involved default-mode (e.g., posterior cingulate gyrus, angular gyrus, and middle temporal gyrus) and limbic systems (e.g., hippocampus and parahippocampal gyrus). Therefore, our results provide evidence supporting the idea that the episodic memory deficit in aMCI patients is associated with disruption of the default-mode and limbic systems.
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Affiliation(s)
- Zan Wang
- School of Medicine, Southeast University, Nanjing, China.,Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Zhengsheng Zhang
- School of Medicine, Southeast University, Nanjing, China.,Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Chunming Xie
- School of Medicine, Southeast University, Nanjing, China.,Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Hao Shu
- School of Medicine, Southeast University, Nanjing, China.,Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Duan Liu
- School of Medicine, Southeast University, Nanjing, China
| | - Zhijun Zhang
- School of Medicine, Southeast University, Nanjing, China.,Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
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Saito S, Shinmyozu K, Kawakami D, Yamauchi M, Ikeda S, Hattori Y, Yamamoto R, Hayakawa N, Ihara M. Conversion from cilostazol to OPC-13015 linked to mitigation of cognitive impairment. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 7:e12182. [PMID: 34095441 PMCID: PMC8158162 DOI: 10.1002/trc2.12182] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 03/03/2021] [Accepted: 04/20/2021] [Indexed: 01/30/2023]
Abstract
INTRODUCTION Cilostazol may be a novel therapeutic agent for Alzheimer's disease. Its metabolite, OPC-13015, has a stronger inhibitory effect on type 3 phosphodiesterase than cilostazol. METHODS We prospectively enrolled patients with mild cognitive impairment to whom cilostazol was newly prescribed. Patients underwent the Montreal Cognitive Assessment (MoCA) twice, at a 6-month interval. Plasma cilostazol, OPC-13015, OPC-13213, and OPC-13217 concentrations were determined using liquid chromatography-tandem mass spectrometry. RESULTS MoCA score changes from baseline to the 6-month visit were positively correlated with ratios of OPC-13015 to cilostazol and total metabolites (n = 19, P = .005). Patients with higher ratios of OPC-13015 (≥0.18, median value; n = 10) had significantly higher MoCA scores (P = .036) than patients with lower ratios (the ratio <0.18, n = 9). The absolute value of OPC-13015 concentration in blood was also higher in patients with preserved cognitive function (P = .033). DISCUSSION Blood OPC-13015 levels may be a predictive biomarker of cilostazol treatment for Alzheimer's disease.
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Affiliation(s)
- Satoshi Saito
- Department of NeurologyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
- Department of Pediatric DentistryOsaka University Graduate School of DentistrySuitaOsakaJapan
| | - Kaori Shinmyozu
- Department of PharmacyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
| | - Daisuke Kawakami
- Division of Analytical & Measuring InstrumentsShimadzu CorporationNakagyo‐kuKyotoJapan
| | - Miho Yamauchi
- Department of NeurologyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
| | - Shuhei Ikeda
- Department of NeurologyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
| | - Yorito Hattori
- Department of NeurologyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
| | - Rintaro Yamamoto
- Division of Analytical & Measuring InstrumentsShimadzu CorporationNakagyo‐kuKyotoJapan
| | - Naoki Hayakawa
- Department of PharmacyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
| | - Masafumi Ihara
- Department of NeurologyNational Cerebral and Cardiovascular CenterSuitaOsakaJapan
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10
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Sanabria-Diaz G, Melie-Garcia L, Draganski B, Demonet JF, Kherif F. Apolipoprotein E4 effects on topological brain network organization in mild cognitive impairment. Sci Rep 2021; 11:845. [PMID: 33436948 PMCID: PMC7804004 DOI: 10.1038/s41598-020-80909-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 12/30/2020] [Indexed: 01/29/2023] Open
Abstract
The Apolipoprotein E isoform E4 (ApoE4) is consistently associated with an elevated risk of developing late-onset Alzheimer's Disease (AD); however, less is known about the potential genetic modulation of the brain networks organization during prodromal stages like Mild Cognitive Impairment (MCI). To investigate this issue during this critical stage, we used a dataset with a cross-sectional sample of 253 MCI patients divided into ApoE4-positive (‛Carriers') and ApoE4-negative ('non-Carriers'). We estimated the cortical thickness (CT) from high-resolution T1-weighted structural magnetic images to calculate the correlation among anatomical regions across subjects and build the CT covariance networks (CT-Nets). The topological properties of CT-Nets were described through the graph theory approach. Specifically, our results showed a significant decrease in characteristic path length, clustering-index, local efficiency, global connectivity, modularity, and increased global efficiency for Carriers compared to non-Carriers. Overall, we found that ApoE4 in MCI shaped the topological organization of CT-Nets. Our results suggest that in the MCI stage, the ApoE4 disrupting the CT correlation between regions may be due to adaptive mechanisms to sustain the information transmission across distant brain regions to maintain the cognitive and behavioral abilities before the occurrence of the most severe symptoms.
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Affiliation(s)
- Gretel Sanabria-Diaz
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), Mont Paisible 16, 1011, Lausanne, Switzerland.
| | - Lester Melie-Garcia
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), Mont Paisible 16, 1011, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), Mont Paisible 16, 1011, Lausanne, Switzerland
| | | | - Ferath Kherif
- Laboratoire de Recherche en Neuroimagerie (LREN), Département des neurosciences cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), Mont Paisible 16, 1011, Lausanne, Switzerland
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11
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Eyler LT, Elman JA, Hatton SN, Gough S, Mischel AK, Hagler DJ, Franz CE, Docherty A, Fennema-Notestine C, Gillespie N, Gustavson D, Lyons MJ, Neale MC, Panizzon MS, Dale AM, Kremen WS. Resting State Abnormalities of the Default Mode Network in Mild Cognitive Impairment: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2020; 70:107-120. [PMID: 31177210 DOI: 10.3233/jad-180847] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Large-scale brain networks such as the default mode network (DMN) are often disrupted in Alzheimer's disease (AD). Numerous studies have examined DMN functional connectivity in those with mild cognitive impairment (MCI), a presumed AD precursor, to discover a biomarker of AD risk. Prior reviews were qualitative or limited in scope or approach. OBJECTIVE We aimed to systematically and quantitatively review DMN resting state fMRI studies comparing MCI and healthy comparison (HC) groups. METHODS PubMed was searched for relevant articles. Study characteristics were abstracted and the number of studies showing no group difference or hyper- versus hypo-connnectivity in MCI was tallied. A voxel-wise (ES-SDM) meta-analysis was conducted to identify regional group differences. RESULTS Qualitatively, our review of 57 MCI versus HC comparisons suggests substantial inconsistency; 9 showed no group difference, 8 showed MCI > HC and 22 showed HC > MCI across the brain, and 18 showed regionally-mixed directions of effect. The meta-analysis of 31 studies revealed areas of significant hypo- and hyper-connectivity in MCI, including hypoconnectivity in the posterior cingulate cortex/precuneus (z = -3.1, p < 0.0001). Very few individual studies, however, showed patterns resembling the meta-analytic results. Methodological differences did not appear to explain inconsistencies. CONCLUSIONS The pattern of altered resting DMN function or connectivity in MCI is complex and variable across studies. To date, no index of DMN connectivity qualifies as a useful biomarker of MCI or risk for AD. Refinements to MCI diagnosis, including other biological markers, or longitudinal studies of progression to AD, might identify DMN alterations predictive of AD risk.
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Affiliation(s)
- Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Sean N Hatton
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Sarah Gough
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Anna K Mischel
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Anna Docherty
- Departments of Psychiatry & Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Nathan Gillespie
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Daniel Gustavson
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Michael J Lyons
- Department of Psychology, Boston University, Boston, MA, USA
| | - Michael C Neale
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Anders M Dale
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA.,Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
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12
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Kuang L, Jia J, Zhao D, Xiong F, Han X, Wang Y. Default Mode Network Analysis of APOE Genotype in Cognitively Unimpaired Subjects Based on Persistent Homology. Front Aging Neurosci 2020; 12:188. [PMID: 32733231 PMCID: PMC7358981 DOI: 10.3389/fnagi.2020.00188] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 06/02/2020] [Indexed: 12/22/2022] Open
Abstract
Current researches on default mode network (DMN) in normal elderly have mainly focused on finding some dysfunctional areas with decreased or increased connectivity. The global network dynamics of apolipoprotein E (APOE) e4 allele group is rarely studied. In our previous brain network study, we have demonstrated the advantage of persistent homology. It can distinguish robust and noisy topological features over multiscale nested networks, and the derived properties are more stable. In this study, for the first time we applied persistent homology to analyze APOE-related effects on whole-brain functional network. In our experiments, the risk allele group exhibited lower network radius and modularity in whole brain DMN based on graph theory, suggesting the abnormal organization structure. Moreover, two suggested measures from persistent homology detected significant differences between groups within the left hemisphere and in the whole brain in two datasets. They were more statistically sensitive to APOE genotypic differences than standard graph-based measures. In summary, we provide evidence that the e4 genotype leads to distinct DMN functional alterations in the early phases of Alzheimer's disease using persistent homology approach. Our study offers a novel insight to explore potential biomarkers in healthy elderly populations carrying APOE e4 allele.
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Affiliation(s)
- Liqun Kuang
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Jiaying Jia
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Deyu Zhao
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Fengguang Xiong
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Xie Han
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
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13
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Moore EE, Liu D, Pechman KR, Acosta LMY, Bell SP, Davis LT, Blennow K, Zetterberg H, Landman BA, Schrag MS, Hohman TJ, Gifford KA, Jefferson AL. Mild Cognitive Impairment Staging Yields Genetic Susceptibility, Biomarker, and Neuroimaging Differences. Front Aging Neurosci 2020; 12:139. [PMID: 32581762 PMCID: PMC7289958 DOI: 10.3389/fnagi.2020.00139] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 04/27/2020] [Indexed: 01/22/2023] Open
Abstract
Introduction While Alzheimer’s disease (AD) is divided into severity stages, mild cognitive impairment (MCI) remains a solitary construct despite clinical and prognostic heterogeneity. This study aimed to characterize differences in genetic, cerebrospinal fluid (CSF), neuroimaging, and neuropsychological markers across clinician-derived MCI stages. Methods Vanderbilt Memory & Aging Project participants with MCI were categorized into 3 severity subtypes at screening based on neuropsychological assessment, functional assessment, and Clinical Dementia Rating interview, including mild (n = 18, 75 ± 8 years), moderate (n = 89 72 ± 7 years), and severe subtypes (n = 18, 78 ± 8 years). At enrollment, participants underwent neuropsychological testing, 3T brain magnetic resonance imaging (MRI), and optional fasting lumbar puncture to obtain CSF. Neuropsychological testing and MRI were repeated at 18-months, 3-years, and 5-years with a mean follow-up time of 3.3 years. Ordinary least square regressions examined cross-sectional associations between MCI severity and apolipoprotein E (APOE)-ε4 status, CSF biomarkers of amyloid beta (Aβ), phosphorylated tau, total tau, and synaptic dysfunction (neurogranin), baseline neuroimaging biomarkers, and baseline neuropsychological performance. Longitudinal associations between baseline MCI severity and neuroimaging and neuropsychological trajectory were assessed using linear mixed effects models with random intercepts and slopes and a follow-up time interaction. Analyses adjusted for baseline age, sex, race/ethnicity, education, and intracranial volume for MRI models. Results Stages differed at baseline on APOE-ε4 status (early < middle = late; p-values < 0.03) and CSF Aβ (early > middle = late), phosphorylated and total tau (early = middle < late; p-values < 0.05), and neurogranin concentrations (early = middle < late; p-values < 0.05). MCI stage related to greater longitudinal cognitive decline, hippocampal atrophy, and inferior lateral ventricle dilation (early < late; p-values < 0.03). Discussion Clinician staging of MCI severity yielded longitudinal cognitive trajectory and structural neuroimaging differences in regions susceptible to AD neuropathology and neurodegeneration. As expected, participants with more severe MCI symptoms at study entry had greater cognitive decline and gray matter atrophy over time. Differences are likely attributable to baseline differences in amyloidosis, tau, and synaptic dysfunction. MCI staging may provide insight into underlying pathology, prognosis, and therapeutic targets.
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Affiliation(s)
- Elizabeth E Moore
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Dandan Liu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kimberly R Pechman
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lealani Mae Y Acosta
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Susan P Bell
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - L Taylor Davis
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom.,UK Dementia Research Institute at UCL, London, United Kingdom
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Matthew S Schrag
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Katherine A Gifford
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Angela L Jefferson
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
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14
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Shi JY, Wang P, Wang BH, Xu Y, Chen X, Li HJ. Brain Homotopic Connectivity in Mild Cognitive Impairment APOE-ε4 Carriers. Neuroscience 2020; 436:74-81. [PMID: 32304722 DOI: 10.1016/j.neuroscience.2020.04.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 04/04/2020] [Accepted: 04/08/2020] [Indexed: 11/15/2022]
Abstract
Individuals with mild cognitive impairment (MCI) are regarded as being at high risk of developing Alzheimer's disease (AD). The apolipoprotein E (APOE) ε4 allele is a well-established genetic risk factor for developing AD. In the present study, by using voxel-mirrored homotopic connectivity (VMHC), we aimed to explore the potential functional disruptions in MCI APOE-ε4 carriers. Resting-state functional magnetic resonance imaging was performed in 35 MCI APOE-ε4 carriers (27 APOE-ε3ε4, 8 APOE-ε4ε4) and 42 MCI APOE-ε4 noncarriers (APOE-ε3ε3). VMHC was employed to investigate the alterations in functional connectivity in MCI APOE-ε4 carriers. We further investigated the seed-based functional connectivity between the VMHC values of altered regions and other brain regions in the two groups. The results showed that MCI APOE-ε4 carriers presented increased VMHC in the inferior frontal gyrus/insula and middle frontal gyrus/superior frontal gyrus in comparison with noncarriers. We found that MCI APOE-ε4 carriers showed increased functional connectivity between the seed regions (bilateral inferior frontal gyri/insula and bilateral middle frontal gyri/superior frontal gyri) and broad brain areas, including the frontal, temporal, parietal, and cerebellar regions. Our findings provide neuroimaging evidence for the modulation of the APOE genotype on the neurodegenerative disease phenotype and may be potentially important for monitoring disease progression in double-high-risk populations of AD.
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Affiliation(s)
- Jun-Yan Shi
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Psychiatric Hospital of Taiyuan City, Taiyuan 030000, China; Department of Medical Psychology, Shanxi Mental Health Center, Taiyuan 030000, China
| | - Ping Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bin-Hong Wang
- Psychiatric Hospital of Taiyuan City, Taiyuan 030000, China; Department of Medical Psychology, Shanxi Mental Health Center, Taiyuan 030000, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan 030001, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui-Jie Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
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15
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Williams T, Borchelt DR, Chakrabarty P. Therapeutic approaches targeting Apolipoprotein E function in Alzheimer's disease. Mol Neurodegener 2020; 15:8. [PMID: 32005122 PMCID: PMC6995170 DOI: 10.1186/s13024-020-0358-9] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 01/14/2020] [Indexed: 12/12/2022] Open
Abstract
One of the primary genetic risk factors for Alzheimer’s disease (AD) is the presence of the Ɛ4 allele of apolipoprotein E (APOE). APOE is a polymorphic lipoprotein that is a major cholesterol carrier in the brain. It is also involved in various cellular functions such as neuronal signaling, neuroinflammation and glucose metabolism. Humans predominantly possess three different allelic variants of APOE, termed E2, E3, and E4, with the E3 allele being the most common. The presence of the E4 allele is associated with increased risk of AD whereas E2 reduces the risk. To understand the molecular mechanisms that underlie APOE-related genetic risk, considerable effort has been devoted towards developing cellular and animal models. Data from these models indicate that APOE4 exacerbates amyloid β plaque burden in a dose-dependent manner. and may also enhance tau pathogenesis in an isoform-dependent manner. Other studies have suggested APOE4 increases the risk of AD by mechanisms that are distinct from modulation of Aβ or tau pathology. Further, whether plasma APOE, by influencing systemic metabolic pathways, can also possibly alter CNS function indirectly is not complete;y understood. Collectively, the available studies suggest that APOE may impact multiple signaling pathways and thus investigators have sought therapeutics that would disrupt pathological functions of APOE while preserving or enhancing beneficial functions. This review will highlight some of the therapeutic strategies that are currently being pursued to target APOE4 towards preventing or treating AD and we will discuss additional strategies that holds promise for the future.
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Affiliation(s)
- Tosha Williams
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA.,Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA
| | - David R Borchelt
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA.,Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA.,McKnight Brain Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Paramita Chakrabarty
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA. .,Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA. .,McKnight Brain Institute, University of Florida, Gainesville, FL, 32610, USA.
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16
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Badea A, Wu W, Shuff J, Wang M, Anderson RJ, Qi Y, Johnson GA, Wilson JG, Koudoro S, Garyfallidis E, Colton CA, Dunson DB. Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer's Disease. Front Neuroinform 2019; 13:72. [PMID: 31920610 PMCID: PMC6914731 DOI: 10.3389/fninf.2019.00072] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 11/13/2019] [Indexed: 12/18/2022] Open
Abstract
The major genetic risk for late onset Alzheimer’s disease has been associated with the presence of APOE4 alleles. However, the impact of different APOE alleles on the brain aging trajectory, and how they interact with the brain local environment in a sex specific manner is not entirely clear. We sought to identify vulnerable brain circuits in novel mouse models with homozygous targeted replacement of the mouse ApoE gene with either human APOE3 or APOE4 gene alleles. These genes are expressed in mice that also model the human immune response to age and disease-associated challenges by expressing the human NOS2 gene in place of the mouse mNos2 gene. These mice had impaired learning and memory when assessed with the Morris water maze (MWM) and novel object recognition (NOR) tests. Ex vivo MRI-DTI analyses revealed global and local atrophy, and areas of reduced fractional anisotropy (FA). Using tensor network principal component analyses for structural connectomes, we inferred the pairwise connections which best separate APOE4 from APOE3 carriers. These involved primarily interhemispheric connections among regions of olfactory areas, the hippocampus, and the cerebellum. Our results also suggest that pairwise connections may be subdivided and clustered spatially to reveal local changes on a finer scale. These analyses revealed not just genotype, but also sex specific differences. Identifying vulnerable networks may provide targets for interventions, and a means to stratify patients.
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Affiliation(s)
- Alexandra Badea
- Department of Radiology, Duke University, Durham, NC, United States.,Department of Neurology, Duke University School of Medicine, Durham, NC, United States.,Brain Imaging and Analysis Center, Duke University, Durham, NC, United States
| | - Wenlin Wu
- Pratt School of Engineering, Duke University, Durham, NC, United States
| | - Jordan Shuff
- Department of Biomedical Engineering, University of Delaware, Newark, NJ, United States
| | - Michele Wang
- Department of Psychology and Neuroscience, Trinity College of Arts & Sciences, Duke University, Durham, NC, United States
| | | | - Yi Qi
- Department of Radiology, Duke University, Durham, NC, United States
| | - G Allan Johnson
- Department of Radiology, Duke University, Durham, NC, United States
| | - Joan G Wilson
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States
| | - Serge Koudoro
- School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States
| | - Eleftherios Garyfallidis
- School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States
| | - Carol A Colton
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States
| | - David B Dunson
- Department of Statistical Science, Trinity College of Arts & Sciences, Duke University, Durham, NC, United States
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17
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Xu L, Chen Y, Shen T, Lin C, Zhang B. Genetic Analysis of PICK1 Gene in Alzheimer's Disease: A Study for Finding a New Gene Target. Front Neurol 2019; 9:1169. [PMID: 30687223 PMCID: PMC6333664 DOI: 10.3389/fneur.2018.01169] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 12/17/2018] [Indexed: 01/19/2023] Open
Abstract
Background: Alzheimer's disease (AD) is a neurodegenerative disease with no effective treatment. Researchers have focused on exploring biomarkers for its early diagnosis, especially on finding a new gene target. Recent studies have shown that protein interacting with C-kinase-1(PICK1) is related to AD through regulating hippocampal synaptic plasticity. PICK1 gene polymorphisms have been identified in psychological and other related disorders. Methods: This study included 133 sporadic AD patients and 173 healthy controls. All coding exons and intron-exon boundaries of the PICK1 gene were amplified by polymerase chain reaction (PCR), which were subsequently sequenced and analyzed. Results: This is the first genetic association study to investigate the association between PICK1 gene and AD risk in Chinese Han population. Seven single nucleotide polymorphisms (SNPs) were found in our research (rs397780637, rs713729, rs2076369, rs58230476, rs7289911, rs149474436; and rs146770324 for patient M1659 only). Frequencies of the T allele (p = 0.002; OR, 0.083; 95%CI, 0.011-0.634) and TT/TC genotypes (p = 0.001) of rs149474436 were lower in AD patients than in the controls. The GG homozygotes of rs397780637 were found to be associated with an increased risk of AD (p = 0.018) in APOEε4 allele carriers, while the frequency of the T allele of rs149474436 was significantly lower among AD patients in APOEε4 non-carriers (p = 0.005). Conclusions: Our results suggest that PICK1 gene SNPs are associated with AD susceptibility in East Asian population, T allele of rs149474436 may play as a protective factor while the rs397780637 GG homozygotes may be associated with an increased risk of AD. Further studies should be considered in a larger cohort of patients with diverse demographics.
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Affiliation(s)
- Lingjia Xu
- Department of Neurology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,Department of Neurology, The Second Hospital of Shaoxing, Shaoxing, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Ting Shen
- Department of Neurology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Caixiu Lin
- Department of Neurology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
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18
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Zhu L, Shu H, Liu D, Guo Q, Wang Z, Zhang Z. Apolipoprotein E ε4 Specifically Modulates the Hippocampus Functional Connectivity Network in Patients With Amnestic Mild Cognitive Impairment. Front Aging Neurosci 2018; 10:289. [PMID: 30319395 PMCID: PMC6170627 DOI: 10.3389/fnagi.2018.00289] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 09/03/2018] [Indexed: 11/16/2022] Open
Abstract
The presence of both apolipoprotein E (APOE) ε4 allele and amnestic mild cognitive impairment (aMCI) are considered to be risk factors for Alzheimer’s disease (AD). Numerous neuroimaging studies have suggested that the modulation of APOE ε4 affects intrinsic functional brain networks, both in healthy populations and in AD patients. However, it remains largely unclear whether and how ε4 allele modulates the brain’s functional network architecture in subjects with aMCI. Using resting-state functional magnetic resonance imaging (fMRI) and graph-theory approaches-functional connectivity strength (FCS), we investigate the topological organization of the whole-brain functional network in 28 aMCI ε4 carriers and 38 aMCI ε3ε3 carriers. In the present study, we first observe that ε4-related FCS increases in the right hippocampus/parahippocampal gyrus (HIP/PHG). Subsequent seed-based resting-state functional connectivity (RSFC) analysis revealed that, compared with the ε3ε3 carriers, the ε4 carriers had lower or higher RSFCs between the right HIP/PHG seed and the bilateral medial prefrontal cortex (MPFC) or the occipital cortex, respectively. Further correlation analyses have revealed that the FCS values in the right HIP/PHG and lower HIP/PHG-RSFCs with the bilateral MPFC were significantly correlated with the impairment of episodic memory and executive function in the aMCI ε4 carriers. Importantly, the logistic regression analysis showed that the HIP/PHG-RSFC with the bilateral MPFC predicted aMCI-conversion to AD. These findings suggest that the APOE ε4 allele may modulate the large-scale brain network in aMCI subjects, facilitating our understanding of how the entire assembly of the brain network reorganizes in response to APOE variants in aMCI. Further longitudinal studies need to be conducted, in order to examine whether these network measures could serve as primary predictors of conversion from aMCI ε4 carriers to AD.
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Affiliation(s)
- Lin Zhu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Duan Liu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Qihao Guo
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
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19
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Long H, Liu B, Wang C, Zhang X, Li J, Yu C, Jiang T. Interaction effect between 5-HTTLPR and HTR1A rs6295 polymorphisms on the frontoparietal network. Neuroscience 2017; 362:239-247. [PMID: 28793232 DOI: 10.1016/j.neuroscience.2017.08.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 07/31/2017] [Accepted: 08/01/2017] [Indexed: 10/19/2022]
Abstract
Previous studies have shown a close relationship between the serotonin system and working memory (WM), but the neural mechanism for the role of the serotonin system on the WM is unclear. The frontoparietal network is involved in WM and is associated with the serotonin system. Therefore, this study investigated the interaction effect of the serotonin transporter-linked polymorphic region (5-HTTLPR) and the polymorphism in the serotonin 1A receptor gene (rs6295) on the frontoparietal network obtained from the independent component analysis in a large, young Chinese sample population. The current study found a significant interaction effect of 5-HTTLPR and rs6295 on the connectivity within the right frontoparietal network, specifically in the middle frontal gyrus and inferior parietal lobule. Moreover, the mean connectivity in the right inferior parietal lobule was positively correlated with WM performance. These brain network analysis findings could provide a new perspective on the neural mechanisms of gene-gene interactions and on individual differences in cognitive functions.
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Affiliation(s)
- Haixia Long
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Bing Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Chao Wang
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xiaolong Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia.
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