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Liu Z, Shu K, Geng Y, Cai C, Kang H. Deep brain stimulation of fornix in Alzheimer's disease: From basic research to clinical practice. Eur J Clin Invest 2023; 53:e13995. [PMID: 37004153 DOI: 10.1111/eci.13995] [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: 12/15/2022] [Revised: 03/13/2023] [Accepted: 03/23/2023] [Indexed: 04/03/2023]
Abstract
Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases associated with the degradation of memory and cognitive ability. Current pharmacotherapies show little therapeutic effect in AD treatment and still cannot prevent the pathological progression of AD. Deep brain stimulation (DBS) has shown to enhance memory in morbid obese, epilepsy and traumatic brain injury patients, and cognition in Parkinson's disease (PD) patients deteriorates during DBS off. Some relevant animal studies and clinical trials have been carried out to discuss the DBS treatment for AD. Reviewing the fornix trials, no unified conclusion has been reached about the clinical benefits of DBS in AD, and the dementia ratings scale has not been effectively improved in the long term. However, some patients have presented promising results, such as improved glucose metabolism, increased connectivity in cognition-related brain regions and even elevated cognitive function rating scale scores. The fornix plays an important regulatory role in memory, attention, and emotion through its complex fibre projection to cognition-related structures, making it a promising target for DBS for AD treatment. Moreover, the current stereotaxic technique and various evaluation methods have provided references for the operator to select accurate stimulation points. Related adverse events and relatively higher costs in DBS have been emphasized. In this article, we summarize and update the research progression on fornix DBS in AD and seek to provide a reliable reference for subsequent experimental studies on DBS treatment of AD.
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Affiliation(s)
- Zhikun Liu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Kai Shu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Yumei Geng
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Chang Cai
- National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, Hubei Province, China
| | - Huicong Kang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
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2
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López-Cáceres A, Cruz-Sanabria F, Mayorga P, Sanchez AI, Gonzalez-Nieves S, Ayala-Ramírez P, Zarante I, Matallana D. Association between risk polymorphisms for neurodegenerative diseases and cognition in colombian patients with frontotemporal dementia. Front Neurol 2022; 13:675301. [PMID: 36071893 PMCID: PMC9443520 DOI: 10.3389/fneur.2022.675301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disease of presenile onset. A better characterization of neurodegenerative disorders has been sought by using tools such as genome-wide association studies (GWAS), where associations between single nucleotide polymorphisms (SNPs) and cognitive profiles could constitute predictive biomarkers for these diseases. However, in FTD, associations between genotypes and cognitive phenotypes are yet to be explored. Here, we evaluate a possible relationship between genetic variants and some cognitive functions in an FTD population.MethodologyA total of 47 SNPs in genes associated with neurodegenerative diseases were evaluated using the Sequenom MassARRAY platform along with their possible relationship with performance in neuropsychological tests in 105 Colombian patients diagnosed with FTD.Results and discussionThe SNPs rs429358 (APOE), rs1768208 (MOBP), and rs1411478 (STX6), were identified as risk factors for having a low cognitive performance in inhibitory control and phonological verbal fluency. Although the significance level was not enough to reach the corrected alpha for multiple comparison correction, our exploratory data may constitute a starting point for future studies of these SNPs and their relationship with cognitive performance in patients with a probable diagnosis of FTD. Further studies with an expansion of the sample size and a long-term design could help to explore the predictive nature of the potential associations we identified.
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Affiliation(s)
- Andrea López-Cáceres
- Faculty of Medicine, Institute of Human Genetics, Pontificia Universidad Javeriana, Bogotá, Colombia
- Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
- *Correspondence: Andrea López-Cáceres
| | - Francy Cruz-Sanabria
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
- Neuroscience Group, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Pilar Mayorga
- Mental Health Department, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - Ana Isabel Sanchez
- Faculty of Health Sciences, Pontificia Universidad Javeriana, Cali, Colombia
- Imbanaco Medical Center, Cali, Colombia
| | | | - Paola Ayala-Ramírez
- Faculty of Medicine, Institute of Human Genetics, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Ignacio Zarante
- Faculty of Medicine, Institute of Human Genetics, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Diana Matallana
- Mental Health Department, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
- Department of Psychiatry, School of Medicine, Instituto de Envejecimiento, Pontificia Universidad Javeriana, Bogotá, Colombia
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3
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Yeung MK, Chau AKY, Chiu JYC, Shek JTL, Leung JPY, Wong TCH. Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis. Ageing Res Rev 2022; 80:101675. [PMID: 35724862 DOI: 10.1016/j.arr.2022.101675] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 06/09/2022] [Accepted: 06/14/2022] [Indexed: 11/25/2022]
Abstract
While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.
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Affiliation(s)
- Michael K Yeung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China; University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
| | - Anson Kwok-Yun Chau
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Jason Yin-Chuen Chiu
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Jay Tsz-Lok Shek
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Jody Po-Yi Leung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Toby Chun-Ho Wong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
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4
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Feng F, Huang W, Meng Q, Hao W, Yao H, Zhou B, Guo Y, Zhao C, An N, Wang L, Huang X, Zhang X, Shu N. Altered Volume and Structural Connectivity of the Hippocampus in Alzheimer's Disease and Amnestic Mild Cognitive Impairment. Front Aging Neurosci 2021; 13:705030. [PMID: 34675796 PMCID: PMC8524052 DOI: 10.3389/fnagi.2021.705030] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 09/10/2021] [Indexed: 01/08/2023] Open
Abstract
Background: Hippocampal atrophy is a characteristic of Alzheimer’s disease (AD). However, alterations in structural connectivity (number of connecting fibers) between the hippocampus and whole brain regions due to hippocampal atrophy remain largely unknown in AD and its prodromal stage, amnestic mild cognitive impairment (aMCI). Methods: We collected high-resolution structural MRI (sMRI) and diffusion tensor imaging (DTI) data from 36 AD patients, 30 aMCI patients, and 41 normal control (NC) subjects. First, the volume and structural connectivity of the bilateral hippocampi were compared among the three groups. Second, correlations between volume and structural connectivity in the ipsilateral hippocampus were further analyzed. Finally, classification ability by hippocampal volume, its structural connectivity, and their combination were evaluated. Results: Although the volume and structural connectivity of the bilateral hippocampi were decreased in patients with AD and aMCI, only hippocampal volume correlated with neuropsychological test scores. However, positive correlations between hippocampal volume and ipsilateral structural connectivity were displayed in patients with AD and aMCI. Furthermore, classification accuracy (ACC) was higher in AD vs. aMCI and aMCI vs. NC by the combination of hippocampal volume and structural connectivity than by a single parameter. The highest values of the area under the receiver operating characteristic (ROC) curve (AUC) in every two groups were all obtained by combining hippocampal volume and structural connectivity. Conclusions: Our results showed that the combination of hippocampal volume and structural connectivity (number of connecting fibers) is a new perspective for the discrimination of AD and aMCI.
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Affiliation(s)
- Feng Feng
- Department of Neurology, First Medical Center, Chinese PLA General Hospital, Beijing, China.,Department of Neurology, PLA Rocket Force Characteristic Medical Center, Beijing, China
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Qingqing Meng
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.,Health Care Office of the Service Bureau of Agency for Offices Administration of the Central Military Commission, Beijing, China
| | - Weijun Hao
- Department of Healthcare, Bureau of Guard, General Office of the Communist Party of China, Beijing, China
| | - Hongxiang Yao
- Department of Radiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Bo Zhou
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yan'e Guo
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Cui Zhao
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.,Department of Geriatrics, Affiliated Hospital of Chengde Medical University, Chengde, China
| | - Ningyu An
- Department of Radiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Luning Wang
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Xusheng Huang
- Department of Neurology, First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xi Zhang
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
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5
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Gozdas E, Fingerhut H, Chromik LC, O'Hara R, Reiss AL, Hosseini SMH. Focal white matter disruptions along the cingulum tract explain cognitive decline in amnestic mild cognitive impairment (aMCI). Sci Rep 2020; 10:10213. [PMID: 32576866 PMCID: PMC7311416 DOI: 10.1038/s41598-020-66796-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 05/27/2020] [Indexed: 12/11/2022] Open
Abstract
White matter abnormalities of the human brain are implicated in typical aging and neurodegenerative diseases. However, our understanding of how fine-grained changes in microstructural properties along white matter tracts are associated with memory and cognitive decline in normal aging and mild cognitive impairment remains elusive. We quantified tract profiles with a newer method that can reliably measure fine-grained changes in white matter properties along the tracts using advanced multi-shell diffusion magnetic resonance imaging in 25 patients with amnestic mild cognitive impairment (aMCI) and 23 matched healthy controls (HC). While the changes in tract profiles were parallel across aMCI and HC, we found a significant focal shift in the profile at specific locations along major tracts sub-serving memory in aMCI. Particularly, our findings depict white matter alterations at specific locations on the right cingulum cingulate, the right cingulum hippocampus and anterior corpus callosum (CC) in aMCI compared to HC. Notably, focal changes in white matter tract properties along the cingulum tract predicted memory and cognitive functioning in aMCI. The results suggest that white matter disruptions at specific locations of the cingulum bundle may be a hallmark for the early prediction of Alzheimer’s disease and a predictor of cognitive decline in aMCI.
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Affiliation(s)
- Elveda Gozdas
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Hannah Fingerhut
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Lindsay C Chromik
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Ruth O'Hara
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Allan L Reiss
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - S M Hadi Hosseini
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.
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6
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Dalboni da Rocha JL, Bramati I, Coutinho G, Tovar Moll F, Sitaram R. Fractional Anisotropy changes in Parahippocampal Cingulum due to Alzheimer's Disease. Sci Rep 2020; 10:2660. [PMID: 32060334 PMCID: PMC7021702 DOI: 10.1038/s41598-020-59327-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 01/16/2020] [Indexed: 11/10/2022] Open
Abstract
Current treatments for Alzheimer's disease are only symptomatic and limited to reduce the progression rate of the mental deterioration. Mild Cognitive Impairment, a transitional stage in which the patient is not cognitively normal but do not meet the criteria for specific dementia, is associated with high risk for development of Alzheimer's disease. Thus, non-invasive techniques to predict the individual's risk to develop Alzheimer's disease can be very helpful, considering the possibility of early treatment. Diffusion Tensor Imaging, as an indicator of cerebral white matter integrity, may detect and track earlier evidence of white matter abnormalities in patients developing Alzheimer's disease. Here we performed a voxel-based analysis of fractional anisotropy in three classes of subjects: Alzheimer's disease patients, Mild Cognitive Impairment patients, and healthy controls. We performed Support Vector Machine classification between the three groups, using Fisher Score feature selection and Leave-one-out cross-validation. Bilateral intersection of hippocampal cingulum and parahippocampal gyrus (referred as parahippocampal cingulum) is the region that best discriminates Alzheimer's disease fractional anisotropy values, resulting in an accuracy of 93% for discriminating between Alzheimer's disease and controls, and 90% between Alzheimer's disease and Mild Cognitive Impairment. These results suggest that pattern classification of Diffusion Tensor Imaging can help diagnosis of Alzheimer's disease, specially when focusing on the parahippocampal cingulum.
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Affiliation(s)
| | - Ivanei Bramati
- D'Or Institute for Research and Education, Rio de Janeiro, Brazil
| | - Gabriel Coutinho
- D'Or Institute for Research and Education, Rio de Janeiro, Brazil
| | - Fernanda Tovar Moll
- D'Or Institute for Research and Education, Rio de Janeiro, Brazil
- Federal Univerisity of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Ranganatha Sitaram
- Institute for Biological and Medical Engineering, Department of Psychiatry, and Section of Neuroscience, Pontificia Universidad Católica de Chile, Santiago, Chile.
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7
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Pelkmans W, Dicks E, Barkhof F, Vrenken H, Scheltens P, van der Flier WM, Tijms BM. Gray matter T1-w/T2-w ratios are higher in Alzheimer's disease. Hum Brain Mapp 2019; 40:3900-3909. [PMID: 31157938 PMCID: PMC6771703 DOI: 10.1002/hbm.24638] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 05/16/2019] [Accepted: 05/17/2019] [Indexed: 01/18/2023] Open
Abstract
Myelin determines the conduction of neuronal signals along axonal connections in networks of the brain. Loss of myelin integrity in neuronal circuits might result in cognitive decline in Alzheimer's disease (AD). Recently, the ratio of T1-weighted by T2-weighted MRI has been used as a proxy for myelin content in gray matter of the cortex. With this approach, we investigated whether AD dementia patients show lower cortical myelin content (i.e., a lower T1-w/T2-w ratio value). We selected structural T1-w and T2-w MR images of 293 AD patients and 172 participants with normal cognition (NC). T1-w/T2-w ratios were computed for the whole brain and within 90 automated anatomical labeling atlas regions using SPM12, compared between groups and correlated with the neuronal injury marker tau in cerebrospinal fluid (CSF) and Mini Mental State Examination (MMSE). In contrast to our hypothesis, AD patients showed higher whole brain T1-w/T2-w ratios than NC, and regionally in 31 anatomical areas (p < .0005; d = 0.21 to 0.48), predominantly in the inferior parietal lobule, angular gyrus, anterior cingulate, and precuneus. Regional higher T1-w/T2-w values were associated with higher CSF tau concentrations (p < .0005; r = .16 to .22) and worse MMSE scores (p < .0005; r = -.16 to -.21). These higher T1-w/T2-w values in AD seem to contradict previous pathological findings of demyelination and disconnectivity in AD. Future research should further investigate the biological processes reflected by increases in T1-w/T2-w values.
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Affiliation(s)
- Wiesje Pelkmans
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ellen Dicks
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Hugo Vrenken
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Pasquini L, Rahmani F, Maleki-Balajoo S, La Joie R, Zarei M, Sorg C, Drzezga A, Tahmasian M. Medial Temporal Lobe Disconnection and Hyperexcitability Across Alzheimer's Disease Stages. J Alzheimers Dis Rep 2019; 3:103-112. [PMID: 31259307 PMCID: PMC6597961 DOI: 10.3233/adr-190121] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
The posteromedial cortex (PMC) and medial temporal lobes (MTL) are two brain regions particularly vulnerable in Alzheimer’s disease (AD). We have reviewed the spatiotemporal patterns of amyloid-β and tau accumulation, local MTL functional alterations and MTL-PMC network reconfiguration, and propose a model to relate these elements to each other. Functional and structural MTL-PMC disconnection happen concomitant with amyloid-β plaques and neurofibrillary tau accumulation within these same regions. Ongoing disconnection is accompanied by dysfunctional intrinsic local MTL circuit hyperexcitability, which exacerbates across distinct clinical stages of AD. Our overarching model proposes a sequence of events relating the spatiotemporal patterns of amyloid-β and tau accumulation to MTL-PMC disconnection and local MTL hyperexcitability. We hypothesize that cortical PMC amyloid-β pathology induces long-range information processing deficits through functional and structural MTL-PMC dysconnectivity at early disease stages, which in turn drives local MTL circuit hyperexcitability. Intrinsic local MTL circuit hyperexcitability subsequently accelerates local age-related tau deposition, facilitating tau spread from the MTL to the PMC, eventually resulting in extensive structural degeneration of white and grey matter as the disease advances. We hope that the present model may inform future longitudinal studies needed to test the proposed sequence of events.
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Affiliation(s)
- Lorenzo Pasquini
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Farzaneh Rahmani
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Somayeh Maleki-Balajoo
- Department of Biomedical Engineering, Electrical Engineering Faculty, K.N. Toosi University of Technology, Tehran, Iran.,Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Christian Sorg
- Departments of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Departments of Psychiatry, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, Cologne, Germany
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
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9
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Schilling LP, Pascoal TA, Zimmer ER, Mathotaarachchi S, Shin M, de Mello Rieder CR, Gauthier S, Palmini A, Rosa-Neto P. Regional Amyloid-β Load and White Matter Abnormalities Contribute to Hypometabolism in Alzheimer's Dementia. Mol Neurobiol 2018; 56:4916-4924. [PMID: 30414086 DOI: 10.1007/s12035-018-1405-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 10/22/2018] [Indexed: 12/18/2022]
Abstract
We investigated the association between amyloid-β deposition and white matter (WM) integrity as a determinant of brain glucose hypometabolism across the Alzheimer's disease (AD) spectrum. We assessed ninety-six subjects (27 cognitively normal, 49 mild cognitive impairment, and 20 AD dementia) who underwent [18F]FDG and [18F]Florbetapir positron emission tomography (PET) as well as magnetic resonance imaging (MRI) with diffusion tensor imaging. Among the regions with reduced fractional anisotropy (FA) in the AD group, we selected a voxel of interest in the angular bundle bilaterally for subsequent analyses. Using voxel-based interaction models at voxel level, we tested whether the regional hypometabolism is associated with FA in the angular bundle and regional amyloid-β deposition. In the AD patients, [18F]FDG hypometabolism in the striatum, mesiobasal temporal, orbitofrontal, precuneus, and cingulate cortices were associated with the interaction between high levels of [18F]Florbetapir standard uptake value ratios (SUVR) in these regions and low FA in the angular bundle. We found that the interaction between, rather than the independent effects of, high levels of amyloid-β deposition and WM integrity disruption determined limbic hypometabolism in patients with AD. This finding highlights a more integrative model for AD, where the interaction between partially independent processes determines the glucose hypometabolism.
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Affiliation(s)
- Lucas Porcello Schilling
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada.,Alzheimer's Disease Research Unit, MCSA, Douglas Mental Health Research Institute, Montréal, Canada.,Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Tharick A Pascoal
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada.,Alzheimer's Disease Research Unit, MCSA, Douglas Mental Health Research Institute, Montréal, Canada
| | - Eduardo R Zimmer
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada.,Alzheimer's Disease Research Unit, MCSA, Douglas Mental Health Research Institute, Montréal, Canada.,Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil.,Department of Pharmacology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Graduate Program in Biological Science: Biochemistry, UFRGS, Porto Alegre, Brazil.,Graduate Program in Biological Sciences: Pharmacology and Therapeutics, UFRGS, Porto Alegre, Brazil
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada
| | - Monica Shin
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada
| | - Carlos Roberto de Mello Rieder
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Serge Gauthier
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada.,Alzheimer's Disease Research Unit, MCSA, Douglas Mental Health Research Institute, Montréal, Canada
| | - André Palmini
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health Research Institute, 6825, boul. LaSalle Blvd., Montréal, QC, H4H1R3, Canada. .,Alzheimer's Disease Research Unit, MCSA, Douglas Mental Health Research Institute, Montréal, Canada.
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10
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Praet J, Manyakov NV, Muchene L, Mai Z, Terzopoulos V, de Backer S, Torremans A, Guns PJ, Van De Casteele T, Bottelbergs A, Van Broeck B, Sijbers J, Smeets D, Shkedy Z, Bijnens L, Pemberton DJ, Schmidt ME, Van der Linden A, Verhoye M. Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid-β-induced pathology. ALZHEIMERS RESEARCH & THERAPY 2018; 10:1. [PMID: 29370870 PMCID: PMC6389136 DOI: 10.1186/s13195-017-0329-8] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Accepted: 11/28/2017] [Indexed: 11/10/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly population. In this study, we used the APP/PS1 transgenic mouse model to explore the feasibility of using diffusion kurtosis imaging (DKI) as a tool for the early detection of microstructural changes in the brain due to amyloid-β (Aβ) plaque deposition. METHODS We longitudinally acquired DKI data of wild-type (WT) and APP/PS1 mice at 2, 4, 6 and 8 months of age, after which these mice were sacrificed for histological examination. Three additional cohorts of mice were also included at 2, 4 and 6 months of age to allow voxel-based co-registration between diffusion tensor and diffusion kurtosis metrics and immunohistochemistry. RESULTS Changes were observed in diffusion tensor (DT) and diffusion kurtosis (DK) metrics in many of the 23 regions of interest that were analysed. Mean and axial kurtosis were greatly increased owing to Aβ-induced pathological changes in the motor cortex of APP/PS1 mice at 4, 6 and 8 months of age. Additionally, fractional anisotropy (FA) was decreased in APP/PS1 mice at these respective ages. Linear discriminant analysis of the motor cortex data indicated that combining diffusion tensor and diffusion kurtosis metrics permits improved separation of WT from APP/PS1 mice compared with either diffusion tensor or diffusion kurtosis metrics alone. We observed that mean kurtosis and FA are the critical metrics for a correct genotype classification. Furthermore, using a newly developed platform to co-register the in vivo diffusion-weighted magnetic resonance imaging with multiple 3D histological stacks, we found high correlations between DK metrics and anti-Aβ (clone 4G8) antibody, glial fibrillary acidic protein, ionised calcium-binding adapter molecule 1 and myelin basic protein immunohistochemistry. Finally, we observed reduced FA in the septal nuclei of APP/PS1 mice at all ages investigated. The latter was at least partially also observed by voxel-based statistical parametric mapping, which showed significantly reduced FA in the septal nuclei, as well as in the corpus callosum, of 8-month-old APP/PS1 mice compared with WT mice. CONCLUSIONS Our results indicate that DKI metrics hold tremendous potential for the early detection and longitudinal follow-up of Aβ-induced pathology.
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Affiliation(s)
- Jelle Praet
- Bio-Imaging Lab, University of Antwerp, Campus Drie Eiken (CDE-Uc1.14), Universiteitsplein 1, 2610, Antwerp (Wilrijk), Belgium
| | | | - Leacky Muchene
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| | - Zhenhua Mai
- Bio-Imaging Lab, University of Antwerp, Campus Drie Eiken (CDE-Uc1.14), Universiteitsplein 1, 2610, Antwerp (Wilrijk), Belgium.,Icometrix R&D, Leuven, Belgium
| | - Vasilis Terzopoulos
- Icometrix R&D, Leuven, Belgium.,Institute for Biological and Medical Imaging, Technische Universität München, Munich, Germany
| | | | | | - Pieter-Jan Guns
- Bio-Imaging Lab, University of Antwerp, Campus Drie Eiken (CDE-Uc1.14), Universiteitsplein 1, 2610, Antwerp (Wilrijk), Belgium.,Expert Group Antwerp Molecular Imaging (EGAMI), University of Antwerp, Antwerp, Belgium
| | | | | | | | - Jan Sijbers
- imec-Vision Lab, University of Antwerp, Antwerp, Belgium
| | - Dirk Smeets
- Bio-Imaging Lab, University of Antwerp, Campus Drie Eiken (CDE-Uc1.14), Universiteitsplein 1, 2610, Antwerp (Wilrijk), Belgium.,Icometrix R&D, Leuven, Belgium
| | - Ziv Shkedy
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| | - Luc Bijnens
- Janssen Research and Development, Beerse, Belgium
| | | | | | - Annemie Van der Linden
- Bio-Imaging Lab, University of Antwerp, Campus Drie Eiken (CDE-Uc1.14), Universiteitsplein 1, 2610, Antwerp (Wilrijk), Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, Campus Drie Eiken (CDE-Uc1.14), Universiteitsplein 1, 2610, Antwerp (Wilrijk), Belgium.
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11
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Su L, Hayes L, Soteriades S, Williams G, Brain SAE, Firbank MJ, Longoni G, Arnold RJ, Rowe JB, O'Brien JT. Hippocampal Stratum Radiatum, Lacunosum, and Moleculare Sparing in Mild Cognitive Impairment. J Alzheimers Dis 2018; 61:415-424. [PMID: 29171994 PMCID: PMC5819729 DOI: 10.3233/jad-170344] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is associated with atrophy in entorhinal cortex (ERC), the hippocampus, and its subfields Cornu Ammonis 1 (CA1) and subiculum, which predict conversion from mild cognitive impairment (MCI) to clinical AD. The stratum radiatum, lacunosum, and moleculare (SRLM) are also important gateways involving ERC and CA1, which are affected by early AD pathology. OBJECTIVE To assess whether the SRLM is affected in MCI and AD. METHODS In this proof-of-concept study, 27 controls, 13 subjects with AD, and 22 with MCI underwent 3T MRI. T1 maps were used for whole-hippocampal volumetry, T2 maps were segmented for hippocampal subfield areas, entorhinal cortex and subiculum thickness, and evaluated for SRLM integrity. RESULTS Significant CA1 atrophy and subiculum thinning were found in both AD and MCI compared to similarly aged controls. However, SRLM integrity was only significantly reduced in AD but not in MCI compared to controls. There were no significant differences in other hippocampal subfields (CA2, CA3/dentate gyrus) or ERC thickness between the groups. Finally, CA1 and CA3/DG areas and SRLM clarity were correlated with clinical and cognitive measurements of disease severity. CONCLUSION Although this study was cross sectional, it suggests a progression of specific subfield changes from MCI to established AD that is associated with the reduced integrity of SRLM, which may reflect more widespread hippocampal involvement as the disease progresses and the relative preservation of SRLM in MCI. These results provide new MRI biomarkers for disease staging and understanding of the neurobiology in AD.
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Affiliation(s)
- Li Su
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SP
- China-UK Centre for Cognition and Ageing Research, Faculty of Psychology, Southwest University, Chongqing, China
| | - Lawrence Hayes
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SP
| | - Soteris Soteriades
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SP
| | - Guy Williams
- Wolfson Brain Imaging Centre, University of Cambridge, School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ
| | - Susannah AE Brain
- Oxford University Hospitals NHS Trust, Windmill Road, Oxford OX3 7LD
| | - Michael J Firbank
- Institute of Neuroscience and Newcastle University Institute for Ageing, Newcastle University Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL
| | - Giulia Longoni
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SP
| | - Robert J Arnold
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SP
| | - James B Rowe
- Department of Clinical Neurosciences, Cambridge University, CB2 0SZ
- MRC Cognition and Brain Sciences Unit, Cambridge, CB2 7EF
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SP
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12
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Powell F, Tosun D, Sadeghi R, Weiner M, Raj A. Preserved Structural Network Organization Mediates Pathology Spread in Alzheimer's Disease Spectrum Despite Loss of White Matter Tract Integrity. J Alzheimers Dis 2018; 65:747-764. [PMID: 29578480 PMCID: PMC6152926 DOI: 10.3233/jad-170798] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Models of Alzheimer's disease (AD) hypothesize stereotyped progression via white matter (WM) fiber connections, most likely via trans-synaptic transmission of toxic proteins along neuronal pathways. An important question in the field is whether and how organization of fiber pathways is affected by disease. It remains unknown whether fibers act as conduits of degenerative pathologies, or if they also degenerate with the gray matter network. This work uses graph theoretic modeling in a longitudinal design to investigate the impact of WM network organization on AD pathology spread. We hypothesize if altered WM network organization mediates disease progression, then a previously published network diffusion model will yield higher prediction accuracy using subject-specific connectomes in place of a healthy template connectome. Neuroimaging data in 124 subjects from ADNI were assessed. Graph topology metrics show preserved network organization in patients compared to controls. Using a published diffusion model, we further probe the effect of network alterations on degeneration spread in AD. We show that choice of connectome does not significantly impact the model's predictive ability. These results suggest that, despite measurable changes in integrity of specific fiber tracts, WM network organization in AD is preserved. Further, there is no difference in the mediation of putative pathology spread between healthy and AD-impaired networks. This conclusion is somewhat at variance with previous results, which report global topological disturbances in AD. Our data indicates the combined effect of edge thresholding, binarization, and inclusion of subcortical regions to network graphs may be responsible for previously reported effects.
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Affiliation(s)
- Fon Powell
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Duygu Tosun
- Department of Radiology, University of California San Francisco, San Francisco, CA, USA
| | - Roksana Sadeghi
- Department of Radiology, University of California San Francisco, San Francisco, CA, USA
| | - Michael Weiner
- Department of Radiology, University of California San Francisco, San Francisco, CA, USA
| | - Ashish Raj
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
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13
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Lee E, Park JE, Iida M, Fujie T, Kaji T, Ichihara G, Weon YC, Kim Y. Magnetic resonance imaging of leukoencephalopathy in amnestic workers exposed to organotin. Neurotoxicology 2016; 57:128-135. [DOI: 10.1016/j.neuro.2016.09.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Revised: 09/08/2016] [Accepted: 09/10/2016] [Indexed: 10/21/2022]
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14
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Knight MJ, McCann B, Tsivos D, Dillon S, Coulthard E, Kauppinen RA. Quantitative T2 mapping of white matter: applications for ageing and cognitive decline. Phys Med Biol 2016; 61:5587-605. [PMID: 27384985 PMCID: PMC5390949 DOI: 10.1088/0031-9155/61/15/5587] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
In MRI, the coherence lifetime T2 is sensitive to the magnetic environment imposed by tissue microstructure and biochemistry in vivo. Here we explore the possibility that the use of T2 relaxometry may provide information complementary to that provided by diffusion tensor imaging (DTI) in ageing of healthy controls (HC), Alzheimer’s disease (AD) and mild cognitive impairment (MCI). T2 and diffusion MRI metrics were quantified in HC and patients with MCI and mild AD using multi-echo MRI and DTI. We used tract-based spatial statistics (TBSS) to evaluate quantitative MRI parameters in white matter (WM). A prolonged T2 in WM was associated with AD, and able to distinguish AD from MCI, and AD from HC. Shorter WM T2 was associated with better cognition and younger age in general. In no case was a reduction in T2 associated with poorer cognition. We also applied principal component analysis, showing that WM volume changes independently of T2, MRI diffusion indices and cognitive performance indices. Our data add to the evidence that age-related and AD-related decline in cognition is in part attributable to WM tissue state, and much less to WM quantity. These observations suggest that WM is involved in AD pathology, and that T2 relaxometry is a potential imaging modality for detecting and characterising WM in cognitive decline and dementia.
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Affiliation(s)
- Michael J Knight
- School of Experimental Psychology, 12a Priory Road, University of Bristol, Bristol, BS8 1TU, UK
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15
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Nishioka C, Poh C, Sun SW. Diffusion tensor imaging reveals visual pathway damage in patients with mild cognitive impairment and Alzheimer's disease. J Alzheimers Dis 2016; 45:97-107. [PMID: 25537012 DOI: 10.3233/jad-141239] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Visual deficits are commonly seen in patients with Alzheimer's disease (AD), but postmortem histology has not found substantial damage in visual cortex regions, leading to the hypothesis that the visual pathway, from eye to the brain, may be damaged in AD. Diffusion tensor imaging (DTI) has been used to characterize white matter abnormalities. However, there is a lack of data examining the optic nerves and tracts in patients with AD. In this study, we used DTI to analyze the visual pathway in healthy controls, patients with mild cognitive impairment (MCI) and AD using scans provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We found significant increases in the total diffusivity and radial diffusivity and reductions in fractional anisotropy in optic nerves among AD patients. Similar but less extensive changes in these metrics were seen in MCI patients as compared to controls. The differences in DTI metrics between groups mirrored changes in the splenium of the corpus callosum, which has commonly been shown to exhibit white matter damage during AD and MCI. Our findings indicate that white matter damage extends to the visual system, and may help explain the visual deficits experienced by AD patients.
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Affiliation(s)
| | - Christina Poh
- Loma Linda University School of Medicine, Loma Linda, CA, USA
| | - Shu-Wei Sun
- Neuroscience Graduate Program, University of California, Riverside, CA, USA Departments of Basic Sciences and Radiation Medicine, School of Medicine, Loma Linda University, Loma Linda, CA, USA Department of Pharmaceutical Science, School of Pharmacy, Loma Linda University, Loma Linda, CA, USA Department of Bioengineering, University of California, Riverside, CA, USA
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16
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Larvie M, Fischl B. Volumetric and fiber-tracing MRI methods for gray and white matter. HANDBOOK OF CLINICAL NEUROLOGY 2016; 135:39-60. [PMID: 27432659 DOI: 10.1016/b978-0-444-53485-9.00003-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Magnetic resonance imaging (MRI) is capable of generating high-resolution brain images with fine anatomic detail and unique tissue contrasts that reveal structures that are not visible to the eye. Sharply defined gray- and white-matter interfaces allow for quantitative anatomic analysis that can be accurately performed with largely automated segmentation methods. In an analogous fashion, diffusion MRI in the brain provides structural information based on contrasts derived from the diffusivity of water in brain tissue, which can highlight the orientation of neuronal axons. Also using largely automated methods, diffusion MRI can be used to generate models of white-matter tracts throughout the brain, a method known as tractography, as well as characterize the microstructural integrity of neuronal axons. Tractographic analysis has helped to define connectivity in the brain that powerfully informs understanding of brain function, and, together with other diffusion metrics, is useful in evaluation of the normal and diseased brain. The quantitative methods of brain segmentation, tractography, and diffusion MRI extend MRI into a realm beyond visual inspection and provide otherwise unachievable sensitivity and specificity in the analysis of brain structure and function.
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Affiliation(s)
- Mykol Larvie
- Divisions of Neuroradiology and Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, MA, USA.
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
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17
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Daianu M, Jahanshad N, Nir TM, Jack CR, Weiner MW, Bernstein MA, Thompson PM. Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network. Hum Brain Mapp 2015; 36:3087-103. [PMID: 26037224 PMCID: PMC4504816 DOI: 10.1002/hbm.22830] [Citation(s) in RCA: 102] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Revised: 02/04/2015] [Accepted: 04/21/2015] [Indexed: 11/11/2022] Open
Abstract
Diffusion imaging can assess the white matter connections within the brain, revealing how neural pathways break down in Alzheimer's disease (AD). We analyzed 3-Tesla whole-brain diffusion-weighted images from 202 participants scanned by the Alzheimer's Disease Neuroimaging Initiative-50 healthy controls, 110 with mild cognitive impairment (MCI) and 42 AD patients. From whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We tested whether AD disrupts the "rich club" - a network property where high-degree network nodes are more interconnected than expected by chance. We calculated the rich club properties at a range of degree thresholds, as well as other network topology measures including global degree, clustering coefficient, path length, and efficiency. Network disruptions predominated in the low-degree regions of the connectome in patients, relative to controls. The other metrics also showed alterations, suggesting a distinctive pattern of disruption in AD, less pronounced in MCI, targeting global brain connectivity, and focusing on more remotely connected nodes rather than the central core of the network. AD involves severely reduced structural connectivity; our step-wise rich club coefficients analyze points to disruptions predominantly in the peripheral network components; other modalities of data are needed to know if this indicates impaired communication among non rich club regions. The highly connected core was relatively preserved, offering new evidence on the neural basis of progressive risk for cognitive decline.
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Affiliation(s)
- Madelaine Daianu
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, California
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, California
| | - Talia M Nir
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, California
| | | | - Michael W Weiner
- Department of Radiology, Medicine, and Psychiatry, University of California San Francisco, California
- Department of Veterans Affairs Medical Center, San Francisco, California
| | | | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, California
- Departments of Neurology, Psychiatry, Radiology, Engineering, Pediatrics, and Ophthalmology, University of Southern California, Los Angeles, California
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18
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Cedarbaum J, Green RC, Harvey D, Jack CR, Jagust W, Luthman J, Morris JC, Petersen RC, Saykin AJ, Shaw L, Shen L, Schwarz A, Toga AW, Trojanowski JQ. 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception. Alzheimers Dement 2015; 11:e1-120. [PMID: 26073027 PMCID: PMC5469297 DOI: 10.1016/j.jalz.2014.11.001] [Citation(s) in RCA: 208] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/18/2013] [Indexed: 01/18/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
| | - Paul S Aisen
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jesse Cedarbaum
- Neurology Early Clinical Development, Biogen Idec, Cambridge, MA, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Johan Luthman
- Neuroscience Clinical Development, Neuroscience & General Medicine Product Creation Unit, Eisai Inc., Philadelphia, PA, USA
| | - John C Morris
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li Shen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adam Schwarz
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Lee SH, Coutu JP, Wilkens P, Yendiki A, Rosas HD, Salat DH. Tract-based analysis of white matter degeneration in Alzheimer's disease. Neuroscience 2015; 301:79-89. [PMID: 26026680 DOI: 10.1016/j.neuroscience.2015.05.049] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2015] [Revised: 05/18/2015] [Accepted: 05/20/2015] [Indexed: 12/31/2022]
Abstract
Although much prior work has focused on the known cortical pathology that defines Alzheimer's disease (AD) histologically, recent work has additionally demonstrated substantial damage to the cerebral white matter in this condition. While there is large evidence of diffuse damage to the white matter in AD, it is unclear whether specific white matter tracts exhibit a more accelerated pattern of damage and whether the damage is associated with the classical neurodegenerative changes of AD. In this study, we investigated microstructural differences in the large fascicular bundles of the cerebral white matter of individuals with AD and mild cognitive impairment (MCI), using recently developed automated diffusion tractography procedures in the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset. Eighteen major fiber bundles in a total of 36 individuals with AD, 81 MCI and 60 control participants were examined with the TRActs Constrained by UnderLying Anatomy (TRACULA) procedure available as part of the FreeSurfer image processing software package. For each fiber bundle, the mean fractional anisotropy (FA), and mean, radial and axial diffusivities were calculated. Individuals with AD had increased diffusivities in both left and right cingulum-angular bundles compared to control participants (p<0.001). Individuals with MCI also had increased axial and mean diffusivities and increased FA in both cingulum-angular bundles compared to control participants (p<0.05) and decreased radial diffusivity compared to individuals with AD (p<0.05). We additionally examined how white matter deterioration relates to hippocampal volume, a traditional imaging measure of AD pathology, and found the strongest negative correlations in AD patients between hippocampal volume and the diffusivities of the cingulum-angular and cingulum-cingulate gyrus bundles and of the corticospinal tracts (p<0.05). However, statistically controlling for hippocampal volume did not remove all group differences in white matter measures, suggesting a unique contribution of white matter damage to AD unexplained by this disease biomarker. These results suggest that (1) AD-associated deterioration of white matter fibers is greatest in tracts known to be connected to areas of pathology in AD and (2) lower white matter tract integrity is more diffusely associated with lower hippocampal volume indicating that the pathology in the white matter follows to some degree the neurodegenerative staging and progression of this condition.
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Affiliation(s)
- S-H Lee
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Kangwon National University School of Medicine, Chuncheon, South Korea.
| | - J-P Coutu
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - P Wilkens
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Yendiki
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - H D Rosas
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - D H Salat
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
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Kehoe EG, Farrell D, Metzler-Baddeley C, Lawlor BA, Kenny RA, Lyons D, McNulty JP, Mullins PG, Coyle D, Bokde AL. Fornix White Matter is Correlated with Resting-State Functional Connectivity of the Thalamus and Hippocampus in Healthy Aging but Not in Mild Cognitive Impairment - A Preliminary Study. Front Aging Neurosci 2015; 7:10. [PMID: 25698967 PMCID: PMC4318417 DOI: 10.3389/fnagi.2015.00010] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Accepted: 01/22/2015] [Indexed: 01/31/2023] Open
Abstract
In this study, we wished to examine the relationship between the structural connectivity of the fornix, a white matter (WM) tract in the limbic system, which is affected in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease, and the resting-state functional connectivity (FC) of two key related subcortical structures, the thalamus, and hippocampus. Twenty-two older healthy controls (HC) and 18 older adults with aMCI underwent multi-modal MRI scanning. The fornix was reconstructed using constrained-spherical deconvolution-based tractography. The FC between the thalamus and hippocampus was calculated using a region-of-interest approach from which the mean time series were exacted and correlated. Diffusion tensor imaging measures of the WM microstructure of the fornix were correlated against the Fisher Z correlation values from the FC analysis. There was no difference between the groups in the fornix WM measures, nor in the resting-state FC of the thalamus and hippocampus. We did however find that the relationship between functional and structural connectivity differed significantly between the groups. In the HCs, there was a significant positive association between linear diffusion (CL) in the fornix and the FC of the thalamus and hippocampus, however, there was no relationship between these measures in the aMCI group. These preliminary findings suggest that in aMCI, the relationship between the functional and structural connectivity of regions of the limbic system may be significantly altered compared to healthy ageing. The combined use of diffusion weighted imaging and functional MRI may advance our understanding of neural network changes in aMCI, and elucidate subtle changes in the relationship between structural and functional brain networks.
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Affiliation(s)
- Elizabeth G Kehoe
- Trinity College Institute of Neuroscience and Cognitive Systems Group, Discipline of Psychiatry, School of Medicine, Trinity College Dublin , Dublin , Ireland
| | - Dervla Farrell
- Trinity College Institute of Neuroscience and Cognitive Systems Group, Discipline of Psychiatry, School of Medicine, Trinity College Dublin , Dublin , Ireland
| | - Claudia Metzler-Baddeley
- Cardiff University Brain Research Imaging Centre (CUBRIC), Neuroscience and Mental Health Research Institute (NMHRI), School of Psychology, Cardiff University , Cardiff , UK
| | - Brian A Lawlor
- Department of Psychiatry, Jonathan Swift Clinic, St. James Hospital, Trinity College Institute of Neuroscience, Trinity College Dublin , Dublin , Ireland
| | - Rose Anne Kenny
- Mercer's Institute for Successful Ageing, St. James Hospital, Trinity College Institute of Neuroscience, Trinity College Dublin , Dublin , Ireland
| | | | - Jonathan P McNulty
- School of Medicine and Medical Science, University College Dublin , Dublin , Ireland
| | | | - Damien Coyle
- Intelligent Systems Research Centre, University of Ulster , Derry , UK
| | - Arun L Bokde
- Trinity College Institute of Neuroscience and Cognitive Systems Group, Discipline of Psychiatry, School of Medicine, Trinity College Dublin , Dublin , Ireland
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Agosta F, Dalla Libera D, Spinelli EG, Finardi A, Canu E, Bergami A, Bocchio Chiavetto L, Baronio M, Comi G, Martino G, Matteoli M, Magnani G, Verderio C, Furlan R. Myeloid microvesicles in cerebrospinal fluid are associated with myelin damage and neuronal loss in mild cognitive impairment and Alzheimer disease. Ann Neurol 2014; 76:813-25. [DOI: 10.1002/ana.24235] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Revised: 07/25/2014] [Accepted: 07/25/2014] [Indexed: 12/11/2022]
Affiliation(s)
- Federica Agosta
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Dacia Dalla Libera
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Edoardo Gioele Spinelli
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Annamaria Finardi
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Elisa Canu
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Alessandra Bergami
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | | | | | - Giancarlo Comi
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
- Vita-Salute San Raffaele University; Milan
| | - Gianvito Martino
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Michela Matteoli
- CNR Institute of Neuroscience and Department of Medical Pharmacology; Milan
- Istituto Clinico Humanitas IRCCS; Milan Italy
| | - Giuseppe Magnani
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
| | - Claudia Verderio
- CNR Institute of Neuroscience and Department of Medical Pharmacology; Milan
- Istituto Clinico Humanitas IRCCS; Milan Italy
| | - Roberto Furlan
- Division of Neuroscience, Institute of Experimental Neurology; Scientific Institute San Raffaele; Milan
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Acosta-Cabronero J, Nestor PJ. Diffusion tensor imaging in Alzheimer's disease: insights into the limbic-diencephalic network and methodological considerations. Front Aging Neurosci 2014; 6:266. [PMID: 25324775 PMCID: PMC4183111 DOI: 10.3389/fnagi.2014.00266] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2014] [Accepted: 09/15/2014] [Indexed: 11/25/2022] Open
Abstract
Glucose hypometabolism and gray matter atrophy are well known consequences of Alzheimer's disease (AD). Studies using these measures have shown that the earliest clinical stages, in which memory impairment is a relatively isolated feature, are associated with degeneration in an apparently remote group of areas—mesial temporal lobe (MTL), diencephalic structures such as anterior thalamus and mammillary bodies, and posterior cingulate. These sites are thought to be strongly anatomically inter-connected via a limbic-diencephalic network. Diffusion tensor imaging or DTI—an imaging technique capable of probing white matter tissue microstructure—has recently confirmed degeneration of the white matter connections of the limbic-diencephalic network in AD by way of an unbiased analysis strategy known as tract-based spatial statistics (TBSS). The present review contextualizes the relevance of these findings, in which the fornix is likely to play a fundamental role in linking MTL and diencephalon. An interesting by-product of this work has been in showing that alterations in diffusion behavior are complex in AD—while early studies tended to focus on fractional anisotropy, recent work has highlighted that this measure is not the most sensitive to early changes. Finally, this review will discuss in detail several technical aspects of DTI both in terms of image acquisition and TBSS analysis as both of these factors have important implications to ensure reliable observations are made that inform understanding of neurodegenerative diseases.
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Affiliation(s)
- Julio Acosta-Cabronero
- Brain Plasticity and Neurodegeneration Group, German Center for Neurodegenerative Diseases (DZNE) Magdeburg, Germany
| | - Peter J Nestor
- Brain Plasticity and Neurodegeneration Group, German Center for Neurodegenerative Diseases (DZNE) Magdeburg, Germany
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23
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ten Brinke LF, Bolandzadeh N, Nagamatsu LS, Hsu CL, Davis JC, Miran-Khan K, Liu-Ambrose T. Aerobic exercise increases hippocampal volume in older women with probable mild cognitive impairment: a 6-month randomised controlled trial. Br J Sports Med 2014; 49:248-54. [PMID: 24711660 DOI: 10.1136/bjsports-2013-093184] [Citation(s) in RCA: 237] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BACKGROUND Mild cognitive impairment (MCI) is a well-recognised risk factor for dementia and represents a vital opportunity for intervening. Exercise is a promising strategy for combating cognitive decline by improving brain structure and function. Specifically, aerobic training (AT) improved spatial memory and hippocampal volume in healthy community-dwelling older adults. In older women with probable MCI, we previously demonstrated that resistance training (RT) and AT improved memory. In this secondary analysis, we investigated: (1) the effect of RT and AT on hippocampal volume and (2) the association between change in hippocampal volume and change in memory. METHODS 86 women aged 70-80 years with probable MCI were randomly assigned to a 6-month, twice-weekly programme of: (1) AT, (2) RT or (3) balance and tone training (BAT; ie, control). At baseline and trial completion, participants performed a 3T MRI scan to determine hippocampal volume. Verbal memory and learning were assessed by Rey's Auditory Verbal Learning Test. RESULTS Compared with the BAT group, AT significantly improved left, right and total hippocampal volumes (p≤0.03). After accounting for baseline cognitive function and experimental group, increased left hippocampal volume was independently associated with reduced verbal memory and learning performance as indexed by loss after interference (r=0.42, p=0.03). CONCLUSIONS Aerobic training significantly increased hippocampal volume in older women with probable MCI. More research is needed to ascertain the relevance of exercise-induced changes in hippocampal volume on memory performance in older adults with MCI. TRAIL REGISTRATION NUMBER NCT00958867.
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Affiliation(s)
| | - Niousha Bolandzadeh
- Department of Physical Therapy, UBC, Vancouver, British Columbia, Canada Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
| | | | - Chun Liang Hsu
- Department of Physical Therapy, UBC, Vancouver, British Columbia, Canada Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
| | - Jennifer C Davis
- Centre for Clinical Epidemiology and Evaluation, UBC, Vancouver, British Columbia, Canada
| | - Karim Miran-Khan
- Department of Family Practice, Faculty of Medicine, UBC, Vancouver, British Columbia, Canada
| | - Teresa Liu-Ambrose
- Department of Physical Therapy, UBC, Vancouver, British Columbia, Canada Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada Department of Family Practice, Faculty of Medicine, UBC, Vancouver, British Columbia, Canada Centre for Hip Health and Mobility, Vancouver, British Columbia, Canada
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