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Wheeler DW, Banduri S, Sankararaman S, Vinay S, Ascoli GA. Unsupervised classification of brain-wide axons reveals the presubiculum neuronal projection blueprint. Nat Commun 2024; 15:1555. [PMID: 38378961 PMCID: PMC10879163 DOI: 10.1038/s41467-024-45741-x] [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: 06/22/2023] [Accepted: 02/01/2024] [Indexed: 02/22/2024] Open
Abstract
We present a quantitative strategy to identify all projection neuron types from a given region with statistically different patterns of anatomical targeting. We first validate the technique with mouse primary motor cortex layer 6 data, yielding two clusters consistent with cortico-thalamic and intra-telencephalic neurons. We next analyze the presubiculum, a less-explored region, identifying five classes of projecting neurons with unique patterns of divergence, convergence, and specificity. We report several findings: individual classes target multiple subregions along defined functions; all hypothalamic regions are exclusively targeted by the same class also invading midbrain and agranular retrosplenial cortex; Cornu Ammonis receives input from a single class of presubicular axons also projecting to granular retrosplenial cortex; path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes; the identified classes have highly non-uniform abundances; and presubicular somata are topographically segregated among classes. This study thus demonstrates that statistically distinct projections shed light on the functional organization of their circuit.
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Affiliation(s)
- Diek W Wheeler
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax, VA, USA.
| | - Shaina Banduri
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax, VA, USA
| | - Sruthi Sankararaman
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax, VA, USA
| | - Samhita Vinay
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax, VA, USA
| | - Giorgio A Ascoli
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax, VA, USA.
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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Wheeler DW, Banduri S, Sankararaman S, Vinay S, Ascoli GA. Unsupervised classification of brain-wide axons reveals neuronal projection blueprint. RESEARCH SQUARE 2023:rs.3.rs-3044664. [PMID: 37461601 PMCID: PMC10350180 DOI: 10.21203/rs.3.rs-3044664/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
Long-range axonal projections are quintessential determinants of network connectivity, linking cellular organization and circuit architecture. Here we introduce a quantitative strategy to identify, from a given source region, all "projection neuron types" with statistically different patterns of anatomical targeting. We first validate the proposed technique with well-characterized data from layer 6 of the mouse primary motor cortex. The results yield two clusters, consistent with previously discovered cortico-thalamic and intra-telencephalic neuron classes. We next analyze neurons from the presubiculum, a less-explored region. Extending sparse knowledge from earlier retrograde tracing studies, we identify five classes of presubicular projecting neurons, revealing unique patterns of divergence, convergence, and specificity. We thus report several findings: (1) individual classes target multiple subregions along defined functions, such as spatial representation vs. sensory integration and visual vs. auditory input; (2) all hypothalamic regions are exclusively targeted by the same class also invading midbrain, a sharp subset of thalamic nuclei, and agranular retrosplenial cortex; (3) Cornu Ammonis, in contrast, receives input from the same presubicular axons projecting to granular retrosplenial cortex, also the purview of a single class; (4) path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes, suggesting fine temporal coordination in activating distant areas; (5) the identified classes have highly non-uniform abundances, with substantially more neurons projecting to midbrain and hypothalamus than to medial and lateral entorhinal cortex; (6) lastly, presubicular soma locations are segregated among classes, indicating topographic organization of projections. This study thus demonstrates that classifying neurons based on statistically distinct axonal projection patterns sheds light on the functional organizational of their circuit.
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Affiliation(s)
- Diek W. Wheeler
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax VA (USA)
| | - Shaina Banduri
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax VA (USA)
| | - Sruthi Sankararaman
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax VA (USA)
| | - Samhita Vinay
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax VA (USA)
| | - Giorgio A. Ascoli
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering & Computing, George Mason University, Fairfax VA (USA)
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Islam A, Saito T, Saido T, Ali AB. Presubiculum principal cells are preserved from degeneration in knock-in APP/TAU mouse models of Alzheimer's disease. Semin Cell Dev Biol 2023; 139:55-72. [PMID: 35292192 PMCID: PMC10439011 DOI: 10.1016/j.semcdb.2022.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 02/25/2022] [Accepted: 03/03/2022] [Indexed: 12/31/2022]
Abstract
The presubiculum (PRS) is an integral component of the perforant pathway that has recently been recognised as a relatively unscathed region in clinical Alzheimer's disease (AD), despite neighbouring components of the perforant pathway, CA1 and the entorhinal cortex, responsible for formation of episodic memory and storage, showing severe hallmarks of AD including, amyloid-beta (Aβ) plaques, tau tangles and marked gliosis. However, the question remains whether this anatomical resilience translates into functional resilience of the PRS neurons. Using neuroanatomy combined with whole-cell electrophysiological recordings, we investigated whether the unique spatial profile of the PRS was replicable in two knock-in mouse models of AD, APPNL-F/NL-F, and APPNL-F/MAPTHTAU and whether the intrinsic properties and morphological integrity of the PRS principal neurons was maintained compared to the lateral entorhinal cortex (LEC) and hippocampal CA1 principal cells. Our data revealed an age-dependent Aβ and tau pathology with neuroinflammation in the LEC and CA1, but a presence of fleece-like Aβ deposits with an absence of tau tangles and cellular markers of gliosis in the PRS of the mouse models at 11-16 and 18-22 months. These observations were consistent in human post-mortem AD tissue. This spatial profile also correlated with functional resilience of strong burst firing PRS pyramidal cells that showed unaltered sub- and suprathreshold intrinsic biophysical membrane properties and gross morphology in the AD models that were similar to the properties of pyramidal cells recorded in age-matched wild-type mice (11-14 months). This was in contrast to the LEC and CA1 principal cells which showed altered subthreshold intrinsic properties such as a higher input resistance, longer membrane time constants and hyperexcitability in response to suprathreshold stimulation that correlated with atrophied dendrites in both AD models. In conclusion, our data show for the first time that the unique anatomical profile of the PRS constitutes a diffuse AD pathology that is correlated with the preservation of principal pyramidal cell intrinsic biophysical and morphological properties despite alteration of LEC and CA1 pyramidal cells in two distinct genetic models of AD. Understanding the underlying mechanisms of this resilience could be beneficial in preventing the spread of disease pathology before cognitive deficits are precipitated in AD.
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Affiliation(s)
- Anam Islam
- UCL School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, UK
| | - Takashi Saito
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, Aichi 467-8601, Japan
| | - Takaomi Saido
- RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Afia B Ali
- UCL School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, UK.
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Adams JN, Márquez F, Larson MS, Janecek JT, Miranda BA, Noche JA, Taylor L, Hollearn MK, McMillan L, Keator DB, Head E, Rissman RA, Yassa MA. Differential involvement of hippocampal subfields in the relationship between Alzheimer's pathology and memory interference in older adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12419. [PMID: 37035460 PMCID: PMC10075195 DOI: 10.1002/dad2.12419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 02/15/2023] [Accepted: 02/28/2023] [Indexed: 04/11/2023]
Abstract
Introduction We tested whether Alzheimer's disease (AD) pathology predicts memory deficits in non-demented older adults through its effects on medial temporal lobe (MTL) subregional volume. Methods Thirty-two, non-demented older adults with cerebrospinal fluid (CSF) (amyloid-beta [Aβ]42/Aβ40, phosphorylated tau [p-tau]181, total tau [t-tau]), positron emission tomography (PET; 18F-florbetapir), high-resolution structural magnetic resonance imaging (MRI), and neuropsychological assessment were analyzed. We examined relationships between biomarkers and a highly granular measure of memory consolidation, retroactive interference (RI). Results Biomarkers of AD pathology were related to RI. Dentate gyrus (DG) and CA3 volume were uniquely associated with RI, whereas CA1 and BA35 volume were related to both RI and overall memory recall. AD pathology was associated with reduced BA35, CA1, and subiculum volume. DG volume and Aβ were independently associated with RI, whereas CA1 volume mediated the relationship between AD pathology and RI. Discussion Integrity of distinct hippocampal subfields demonstrate differential relationships with pathology and memory function, indicating specificity in vulnerability and contribution to different memory processes.
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Affiliation(s)
- Jenna N. Adams
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Freddie Márquez
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Myra S. Larson
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - John T. Janecek
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Blake A. Miranda
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Jessica A. Noche
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Lisa Taylor
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Martina K. Hollearn
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Liv McMillan
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - David B. Keator
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Elizabeth Head
- Department of Pathology and Laboratory MedicineUniversity of CaliforniaIrvineCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaIrvineCaliforniaUSA
- Department of NeurologyUniversity of KentuckyLexingtonKentuckyUSA
| | - Robert A. Rissman
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
- Veterans Affairs San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Michael A. Yassa
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
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Genetic Specificity of Hippocampal Subfield Volumes, Relative to Hippocampal Formation, Identified in 2148 Young Adult Twins and Siblings. Twin Res Hum Genet 2022; 25:129-139. [PMID: 35791873 DOI: 10.1017/thg.2022.20] [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: 11/07/2022]
Abstract
The hippocampus is a complex brain structure with key roles in cognitive and emotional processing and with subregion abnormalities associated with a range of disorders and psychopathologies. Here we combine data from two large independent young adult twin/sibling cohorts to obtain the most accurate estimates to date of genetic covariation between hippocampal subfield volumes and the hippocampus as a single volume. The combined sample included 2148 individuals, comprising 1073 individuals from 627 families (mean age = 22.3 years) from the Queensland Twin IMaging (QTIM) Study, and 1075 individuals from 454 families (mean age = 28.8 years) from the Human Connectome Project (HCP). Hippocampal subfields were segmented using FreeSurfer version 6.0 (CA4 and dentate gyrus were phenotypically and genetically indistinguishable and were summed to a single volume). Multivariate twin modeling was conducted in OpenMx to decompose variance into genetic and environmental sources. Bivariate analyses of hippocampal formation and each subfield volume showed that 10%-72% of subfield genetic variance was independent of the hippocampal formation, with greatest specificity found for the smaller volumes; for example, CA2/3 with 42% of genetic variance being independent of the hippocampus; fissure (63%); fimbria (72%); hippocampus-amygdala transition area (41%); parasubiculum (62%). In terms of genetic influence, whole hippocampal volume is a good proxy for the largest hippocampal subfields, but a poor substitute for the smaller subfields. Additive genetic sources accounted for 49%-77% of total variance for each of the subfields in the combined sample multivariate analysis. In addition, the multivariate analyses were sufficiently powered to identify common environmental influences (replicated in QTIM and HCP for the molecular layer and CA4/dentate gyrus, and accounting for 7%-16% of total variance for 8 of 10 subfields in the combined sample). This provides the clearest indication yet from a twin study that factors such as home environment may influence hippocampal volumes (albeit, with caveats).
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7
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OUP accepted manuscript. Arch Clin Neuropsychol 2022; 37:1502-1514. [DOI: 10.1093/arclin/acac018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
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Jacobs HIL, O'Donnell A, Satizabal CL, Lois C, Kojis D, Hanseeuw BJ, Thibault E, Sanchez JS, Buckley RF, Yang Q, DeCarli C, Killiany R, Sargurupremraj M, Sperling RA, Johnson KA, Beiser AS, Seshadri S. Associations Between Brainstem Volume and Alzheimer's Disease Pathology in Middle-Aged Individuals of the Framingham Heart Study. J Alzheimers Dis 2022; 86:1603-1609. [PMID: 35213372 PMCID: PMC9038711 DOI: 10.3233/jad-215372] [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] [Indexed: 11/15/2022]
Abstract
The brainstem is among the first regions to accumulate Alzheimer's disease (AD)-related hyperphosphorylated tau pathology during aging. We aimed to examine associations between brainstem volume and neocortical amyloid-β or tau pathology in 271 middle-aged clinically normal individuals of the Framingham Heart Study who underwent MRI and PET imaging. Lower volume of the medulla, pons, or midbrain was associated with greater neocortical amyloid burden. No associations were detected between brainstem volumes and tau deposition. Our results support the hypothesis that lower brainstem volumes are associated with initial AD-related processes and may signal preclinical AD pathology.
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Affiliation(s)
- Heidi I L Jacobs
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, Netherlands
- Gordon Center for Medical Imaging, Boston, MA, USA
| | - Adrienne O'Donnell
- Boston University School of Public Health, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Claudia L Satizabal
- The Framingham Heart Study, Framingham, MA, USA
- Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Cristina Lois
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Gordon Center for Medical Imaging, Boston, MA, USA
| | - Daniel Kojis
- Boston University School of Public Health, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Bernard J Hanseeuw
- Massachusetts General Hospital, Boston, MA, USA
- Gordon Center for Medical Imaging, Boston, MA, USA
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Emma Thibault
- Massachusetts General Hospital, Boston, MA, USA
- Gordon Center for Medical Imaging, Boston, MA, USA
| | - Justin S Sanchez
- Massachusetts General Hospital, Boston, MA, USA
- Gordon Center for Medical Imaging, Boston, MA, USA
| | - Rachel F Buckley
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia
| | - Qiong Yang
- Boston University School of Public Health, Boston, MA, USA
| | | | - Ron Killiany
- Boston University School of Medicine, Boston, MA, USA
| | - Muralidharan Sargurupremraj
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Reisa A Sperling
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Keith A Johnson
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Gordon Center for Medical Imaging, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Alexa S Beiser
- Boston University School of Public Health, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
- Boston University School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA
- Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
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Jacobs HI, Becker JA, Kwong K, Engels-Domínguez N, Prokopiou PC, Papp KV, Properzi M, Hampton OL, Uquillas FD, Sanchez JS, Rentz DM, Fakhri GE, Normandin MD, Price JC, Bennett DA, Sperling RA, Johnson KA. In vivo and neuropathology data support locus coeruleus integrity as indicator of Alzheimer's disease pathology and cognitive decline. Sci Transl Med 2021; 13:eabj2511. [PMID: 34550726 PMCID: PMC8641759 DOI: 10.1126/scitranslmed.abj2511] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Several autopsy studies recognize the locus coeruleus (LC) as the initial site of hyperphosphorylated TAU aggregation, and as the number of LC neurons harboring TAU increases, TAU pathology emerges throughout the cortex. By conjointly using dedicated MRI measures of LC integrity and TAU and amyloid PET imaging, we aimed to address the question whether in vivo LC measures relate to initial cortical patterns of Alzheimer’s disease (AD) fibrillar proteinopathies or cognitive dysfunction in 174 cognitively unimpaired and impaired older individuals with longitudinal cognitive measures. To guide our interpretations, we verified these associations in autopsy data from 1524 Religious Orders Study and Rush Memory and Aging Project and 2145 National Alzheimer’s Coordinating Center cases providing three different LC measures (pigmentation, tangle density, and neuronal density), Braak staging, β-amyloid, and longitudinal cognitive measures. Lower LC integrity was associated with elevated TAU deposition in the entorhinal cortex among unimpaired individuals consistent with postmortem correlations between LC tangle density and successive Braak staging. LC pigmentation ratings correlated with LC neuronal density but not with LC tangle density and were particularly worse at advanced Braak stages. In the context of elevated β-amyloid, lower LC integrity and greater cortical tangle density were associated with greater TAU burden beyond the medial temporal lobe and retrospective memory decline. These findings support neuropathologic data in which early LC TAU accumulation relates to disease progression and identify LC integrity as a promising indicator of initial AD-related processes and subtle changes in cognitive trajectories of preclinical AD.
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Affiliation(s)
- Heidi I.L. Jacobs
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Harvard Medical School; Boston, MA, 02115, USA
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University; 6200MD Maastricht, The Netherlands
| | - John A. Becker
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Harvard Medical School; Boston, MA, 02115, USA
| | - Kenneth Kwong
- Harvard Medical School; Boston, MA, 02115, USA
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02129, USA
| | - Nina Engels-Domínguez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University; 6200MD Maastricht, The Netherlands
| | - Prokopis C. Prokopiou
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Harvard Medical School; Boston, MA, 02115, USA
| | - Kathryn V. Papp
- Harvard Medical School; Boston, MA, 02115, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital; Boston, MA,02115, USA
| | - Michael Properzi
- Harvard Medical School; Boston, MA, 02115, USA
- Department of Neurology, Massachusetts General Hospital; Boston, MA, 02114, USA
| | - Olivia L. Hampton
- Department of Neurology, Massachusetts General Hospital; Boston, MA, 02114, USA
| | | | - Justin S. Sanchez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
| | - Dorene M. Rentz
- Harvard Medical School; Boston, MA, 02115, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital; Boston, MA,02115, USA
- Department of Neurology, Massachusetts General Hospital; Boston, MA, 02114, USA
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Harvard Medical School; Boston, MA, 02115, USA
| | - Marc D. Normandin
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Harvard Medical School; Boston, MA, 02115, USA
| | - Julie C. Price
- Harvard Medical School; Boston, MA, 02115, USA
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02129, USA
| | - David A. Bennett
- Department of Neurological Sciences, Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, Illinois, 60612, USA
| | - Reisa A. Sperling
- Harvard Medical School; Boston, MA, 02115, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital; Boston, MA,02115, USA
- Department of Neurology, Massachusetts General Hospital; Boston, MA, 02114, USA
| | - Keith A. Johnson
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital; Boston, MA, 02114, USA
- Harvard Medical School; Boston, MA, 02115, USA
- Department of Neurology, Massachusetts General Hospital; Boston, MA, 02114, USA
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10
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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Cremona S, Zago L, Mellet E, Petit L, Laurent A, Pepe A, Tsuchida A, Beguedou N, Joliot M, Tzourio C, Mazoyer B, Crivello F. Novel characterization of the relationship between verbal list-learning outcomes and hippocampal subfields in healthy adults. Hum Brain Mapp 2021; 42:5264-5277. [PMID: 34453474 PMCID: PMC8519870 DOI: 10.1002/hbm.25614] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 06/29/2021] [Accepted: 07/20/2021] [Indexed: 11/10/2022] Open
Abstract
The relationship between hippocampal subfield volumetry and verbal list‐learning test outcomes have mostly been studied in clinical and elderly populations, and remain controversial. For the first time, we characterized a relationship between verbal list‐learning test outcomes and hippocampal subfield volumetry on two large separate datasets of 447 and 1,442 healthy young and middle‐aged adults, and explored the processes that could explain this relationship. We observed a replicable positive linear correlation between verbal list‐learning test free recall scores and CA1 volume, specific to verbal list learning as demonstrated by the hippocampal subfield volumetry independence from verbal intelligence. Learning meaningless items was also positively correlated with CA1 volume, pointing to the role of the test design rather than word meaning. Accordingly, we found that association‐based mnemonics mediated the relationship between verbal list‐learning test outcomes and CA1 volume. This mediation suggests that integrating items into associative representations during verbal list‐learning tests explains CA1 volume variations: this new explanation is consistent with the associative functions of the human CA1.
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Affiliation(s)
- Sandrine Cremona
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Laure Zago
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Emmanuel Mellet
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Laurent Petit
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Alexandre Laurent
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Antonietta Pepe
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Ami Tsuchida
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Naka Beguedou
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Marc Joliot
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
| | - Christophe Tzourio
- Université de Bordeaux - Département Santé publique, INSERM, BPH U 1219, Bordeaux, France
| | - Bernard Mazoyer
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France.,Institut des maladies neurodégénératives clinique, CHU de Bordeaux, Bordeaux, France
| | - Fabrice Crivello
- Université de Bordeaux - Neurocampus, CEA, CNRS, IMN UMR 5293, Bordeaux, France
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12
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Hansen N, Singh A, Bartels C, Brosseron F, Buerger K, Cetindag AC, Dobisch L, Dechent P, Ertl-Wagner BB, Fliessbach K, Haynes JD, Heneka MT, Janowitz D, Kilimann I, Laske C, Metzger CD, Munk MH, Peters O, Priller J, Roy N, Scheffler K, Schneider A, Spottke A, Spruth EJ, Teipel S, Tscheuschler M, Vukovich R, Wiltfang J, Duezel E, Jessen F, Goya-Maldonado R. Hippocampal and Hippocampal-Subfield Volumes From Early-Onset Major Depression and Bipolar Disorder to Cognitive Decline. Front Aging Neurosci 2021; 13:626974. [PMID: 33967736 PMCID: PMC8097178 DOI: 10.3389/fnagi.2021.626974] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Accepted: 03/10/2021] [Indexed: 12/04/2022] Open
Abstract
Background: The hippocampus and its subfields (HippSub) are reported to be diminished in patients with Alzheimer's disease (AD), bipolar disorder (BD), and major depressive disorder (MDD). We examined these groups vs healthy controls (HC) to reveal HippSub alterations between diseases. Methods: We segmented 3T-MRI T2-weighted hippocampal images of 67 HC, 58 BD, and MDD patients from the AFFDIS study and 137 patients from the DELCODE study assessing cognitive decline, including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI), and AD, via Free Surfer 6.0 to compare volumes across groups. Results: Groups differed significantly in several HippSub volumes, particularly between patients with AD and mood disorders. In comparison to HC, significant lower volumes appear in aMCI and AD groups in specific subfields. Smaller volumes in the left presubiculum are detected in aMCI and AD patients, differing from the BD group. A significant linear regression is seen between left hippocampus volume and duration since the first depressive episode. Conclusions: HippSub volume alterations were observed in AD, but not in early-onset MDD and BD, reinforcing the notion of different neural mechanisms in hippocampal degeneration. Moreover, duration since the first depressive episode was a relevant factor explaining the lower left hippocampal volumes present in groups.
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Affiliation(s)
- Niels Hansen
- Department of Psychiatry and Psychotherapy, Göttingen, Germany.,Laboratory of Systems Neuroscience and Imaging in Psychiatry, University Medical Center Göttingen, Göttingen, Germany
| | - Aditya Singh
- Department of Psychiatry and Psychotherapy, Göttingen, Germany.,Laboratory of Systems Neuroscience and Imaging in Psychiatry, University Medical Center Göttingen, Göttingen, Germany
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, Göttingen, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Arda C Cetindag
- Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Peter Dechent
- MR-Research in Neurology and Psychiatry, University Medical Center Göttingen, Göttingen, Germany
| | - Birgit B Ertl-Wagner
- Institute for Clinical Radiology, Ludwig-Maximilians-University, Munich, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - John D Haynes
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin, Berlin, Germany
| | - Michael T Heneka
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Coraline D Metzger
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany.,Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, Magdeburg, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Oliver Peters
- Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University of Bonn, Bonn, Germany
| | - Eike J Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Berlin, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Maike Tscheuschler
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
| | - Ruth Vukovich
- Department of Psychiatry and Psychotherapy, Göttingen, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, Göttingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany.,Neurosciences and Signaling Group, Department of Medical Sciences, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
| | - Emrah Duezel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany.,Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Köln, Germany
| | - Roberto Goya-Maldonado
- Department of Psychiatry and Psychotherapy, Göttingen, Germany.,Laboratory of Systems Neuroscience and Imaging in Psychiatry, University Medical Center Göttingen, Göttingen, Germany
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13
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Buckley RF. Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease. Neurotherapeutics 2021; 18:709-727. [PMID: 33782864 PMCID: PMC8423933 DOI: 10.1007/s13311-021-01026-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 12/25/2022] Open
Abstract
Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.
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Affiliation(s)
- Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital & Brigham and Women's, Harvard Medical School, Boston, MA, USA.
- Melbourne School of Psychological Sciences and Florey Institutes, University of Melbourne, Melbourne, VIC, Australia.
- Department of Neurology, Massachusetts General Hospital, 149 13th St, Charlestown, MA, 02129, USA.
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14
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Wan M, Ye Y, Lin H, Xu Y, Liang S, Xia R, He J, Qiu P, Huang C, Tao J, Chen L, Zheng G. Deviations in Hippocampal Subregion in Older Adults With Cognitive Frailty. Front Aging Neurosci 2021; 12:615852. [PMID: 33519422 PMCID: PMC7838368 DOI: 10.3389/fnagi.2020.615852] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 12/15/2020] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Cognitive frailty is a particular state of cognitive vulnerability toward dementia with neuropathological hallmarks. The hippocampus is a complex, heterogeneous structure closely relates to the cognitive impairment in elderly which is composed of 12 subregions. Atrophy of these subregions has been implicated in a variety of neurodegenerative diseases. The aim of this study was to explore the changes in hippocampal subregions in older adults with cognitive frailty and the relationship between subregions and cognitive impairment as well as physical frailty. METHODS Twenty-six older adults with cognitive frailty and 26 matched healthy controls were included in this study. Cognitive function was evaluated by the Montreal Cognitive Assessment (MoCA) scale (Fuzhou version) and Wechsler Memory Scale-Revised Chinese version (WMS-RC), while physical frailty was tested with the Chinese version of the Edmonton Frailty Scale (EFS) and grip strength. The volume of the hippocampal subregions was measured with structural brain magnetic resonance imaging. Partial correlation analysis was carried out between the volumes of hippocampal subregions and MoCA scores, Wechsler's Memory Quotient and physical frailty indexes. RESULTS A significant volume decrease was found in six hippocampal subregions, including the bilateral presubiculum, the left parasubiculum, molecular layer of the hippocampus proper (molecular layer of the HP), and hippocampal amygdala transition area (HATA), and the right cornu ammonis subfield 1 (CA1) area, in older adults with cognitive frailty, while the proportion of brain parenchyma and total number of white matter fibers were lower than those in the healthy controls. Positive correlations were found between Wechsler's Memory Quotient and the size of the left molecular layer of the HP and HATA and the right presubiculum. The sizes of the left presubiculum, molecular of the layer HP, and HATA and right CA1 and presubiculum were found to be positively correlated with MoCA score. The sizes of the left parasubiculum, molecular layer of the HP and HATA were found to be negatively correlated with the physical frailty index. CONCLUSION Significant volume decrease occurs in hippocampal subregions of older adults with cognitive frailty, and these changes are correlated with cognitive impairment and physical frailty. Therefore, the atrophy of hippocampal subregions could participate in the pathological progression of cognitive frailty.
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Affiliation(s)
- Mingyue Wan
- College of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Yu Ye
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Huiying Lin
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Ying Xu
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Shengxiang Liang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Rui Xia
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jianquan He
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Pingting Qiu
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Chengwu Huang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jing Tao
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lidian Chen
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Guohua Zheng
- College of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai, China
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