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Khalilullah KMI, Agcaoglu O, Sui J, Duda M, Adali T, Calhoun VD. Parallel Multilink Group Joint ICA: Fusion of 3D Structural and 4D Functional Data Across Multiple Resting fMRI Networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.21.586091. [PMID: 38585901 PMCID: PMC10996497 DOI: 10.1101/2024.03.21.586091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Multimodal neuroimaging research plays a pivotal role in understanding the complexities of the human brain and its disorders. Independent component analysis (ICA) has emerged as a widely used and powerful tool for disentangling mixed independent sources, particularly in the analysis of functional magnetic resonance imaging (fMRI) data. This paper extends the use of ICA as a unifying framework for multimodal fusion, introducing a novel approach termed parallel multilink group joint ICA (pmg-jICA). The method allows for the fusion of gray matter maps from structural MRI (sMRI) data to multiple fMRI intrinsic networks, addressing the limitations of previous models. The effectiveness of pmg-jICA is demonstrated through its application to an Alzheimer's dataset, yielding linked structure-function outputs for 53 brain networks. Our approach leverages the complementary information from various imaging modalities, providing a unique perspective on brain alterations in Alzheimer's disease. The pmg-jICA identifies several components with significant differences between HC and AD groups including thalamus, caudate, putamen with in the subcortical (SC) domain, insula, parahippocampal gyrus within the cognitive control (CC) domain, and the lingual gyrus within the visual (VS) domain, providing localized insights into the links between AD and specific brain regions. In addition, because we link across multiple brain networks, we can also compute functional network connectivity (FNC) from spatial maps and subject loadings, providing a detailed exploration of the relationships between different brain regions and allowing us to visualize spatial patterns and loading parameters in sMRI along with intrinsic networks and FNC from the fMRI data. In essence, developed approach combines concepts from joint ICA and group ICA to provide a rich set of output characterizing data-driven links between covarying gray matter networks, and a (potentially large number of) resting fMRI networks allowing further study in the context of structure/function links. We demonstrate the utility of the approach by highlighting key structure/function disruptions in Alzheimer's individuals.
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Affiliation(s)
- K M Ibrahim Khalilullah
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Oktay Agcaoglu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Jing Sui
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Marlena Duda
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Tülay Adali
- Department of Electrical and Computer Engineering, University of Maryland, Baltimore, Maryland, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
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Feng Y, Laraib A, Lin X, Li Q, Zhan J, Li X. Associations of tau, Aβ, and brain volume of the Papez circuit with cognition in Alzheimer's disease. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01827-7. [PMID: 38824476 DOI: 10.1007/s00406-024-01827-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 05/10/2024] [Indexed: 06/03/2024]
Abstract
This study aimed to investigate the cross-sectional associations between regional Alzheimer's disease (AD) biomarkers, including tau, β-amyloid (Aβ), and brain volume, within the Papez circuit, and neuropsychological functioning across the preclinical and clinical spectrum of AD. We utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including 251 Aβ-positive participants. Participants were categorized into three groups based on the Clinical Dementia Rating (CDR): 73 individuals with preclinical AD (CDR = 0), 114 with prodromal AD (CDR = 0.5), and 64 with clinical AD dementia (CDR ≥ 1). Linear regression analyses, adjusted for age, gender, and education years, were employed to evaluate the associations between five regions of interest (the hippocampus, para-hippocampus, entorhinal cortex, posterior cingulate cortex, and thalamus) and five neuropsychological tests across the three imaging modalities. In the preclinical stage of AD, flortaucipir PET was associated with impaired global cognition and episodic memory (range standardized β = 0.255-0.498, p < 0.05 corrected for multiple comparisons), while florbetapir PET and brain volume were marginally related to global cognition (range standardized β = 0.221-0.231, p < 0.05). In the clinical stages of AD (prodromal and dementia), both increased flortaucipir uptake and decreased brain volume were significantly associated with poorer global neuropsychological and episodic memory performance (range standardized β = 0.222-0.621, p < 0.05, most regions of interest survived correction for multiple comparisions). However, a slight relationship was observed between florbetapir uptake and poorer global cognitive function. The regions most affected by flortaucipir PET were the hippocampus, para-hippocampus, and posterior cingulate cortex. During the clinical stages, the hippocampus and entorhinal cortex exhibited the most significant volumetric changes. Tau PET and brain volume measurements within the Papez circuit are more sensitive indicators of early cognitive deficits in AD than Aβ PET. Furthermore, during the clinical stages of AD, both flortaucipir PET and brain volume of the Papez circuit are closely correlated with cognitive decline. These findings underscore the importance of integrating multiple biomarkers for the comprehensive evaluation of AD pathology and its impact on cognition.
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Affiliation(s)
- Yuxue Feng
- Department of Neurology, The Fifth People's Hospital of Chongqing, Chongqing, China
| | - Azka Laraib
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74-76 Linjiang Road, Yuzhong District, Chongqing, 400000, China
| | - Xiuqi Lin
- Chongqing Medical University, Chongqing, China
| | - Qin Li
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74-76 Linjiang Road, Yuzhong District, Chongqing, 400000, China
| | - Jiehong Zhan
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74-76 Linjiang Road, Yuzhong District, Chongqing, 400000, China
| | - Xiaofeng Li
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74-76 Linjiang Road, Yuzhong District, Chongqing, 400000, China.
- Department of Neurology, People's Hospital of Linshui County, Guangan, China.
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Teipel S, Grazia A, Dyrba M, Grothe MJ, Pomara N. Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease. Sci Rep 2024; 14:11268. [PMID: 38760448 PMCID: PMC11101449 DOI: 10.1038/s41598-024-60799-9] [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: 01/03/2024] [Accepted: 04/26/2024] [Indexed: 05/19/2024] Open
Abstract
We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.
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Affiliation(s)
- Stefan Teipel
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Gehlsheimer Str. 20, 18147, Rostock, Germany.
- Department of Psychosomatic Medicine, University Medicine Rostock, Gehlsheimer Str. 20, 18147, Rostock, Germany.
| | - Alice Grazia
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Martin Dyrba
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Michel J Grothe
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Nunzio Pomara
- Geriatric Psychiatry Division, Nathan Kline Institute/Department of Psychiatry and Pathology, NYU Grossman School of Medicine, Orangeburg, NY, USA
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Chen CD, McCullough A, Gordon B, Joseph-Mathurin N, Flores S, McKay NS, Hobbs DA, Hornbeck R, Fagan AM, Cruchaga C, Goate AM, Perrin RJ, Wang G, Li Y, Shi X, Xiong C, Pontecorvo MJ, Klein G, Su Y, Klunk WE, Jack C, Koeppe R, Snider BJ, Berman SB, Roberson ED, Brosch J, Surti G, Jiménez-Velázquez IZ, Galasko D, Honig LS, Brooks WS, Clarnette R, Wallon D, Dubois B, Pariente J, Pasquier F, Sanchez-Valle R, Shcherbinin S, Higgins I, Tunali I, Masters CL, van Dyck CH, Masellis M, Hsiung R, Gauthier S, Salloway S, Clifford DB, Mills S, Supnet-Bell C, McDade E, Bateman RJ, Benzinger TLS. Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-β monoclonal antibodies in dominantly inherited Alzheimer's disease. Eur J Nucl Med Mol Imaging 2023; 50:2669-2682. [PMID: 37017737 PMCID: PMC10330155 DOI: 10.1007/s00259-023-06209-0] [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: 12/08/2022] [Accepted: 03/18/2023] [Indexed: 04/06/2023]
Abstract
PURPOSE Pittsburgh Compound-B (11C-PiB) and 18F-florbetapir are amyloid-β (Aβ) positron emission tomography (PET) radiotracers that have been used as endpoints in Alzheimer's disease (AD) clinical trials to evaluate the efficacy of anti-Aβ monoclonal antibodies. However, comparing drug effects between and within trials may become complicated if different Aβ radiotracers were used. To study the consequences of using different Aβ radiotracers to measure Aβ clearance, we performed a head-to-head comparison of 11C-PiB and 18F-florbetapir in a Phase 2/3 clinical trial of anti-Aβ monoclonal antibodies. METHODS Sixty-six mutation-positive participants enrolled in the gantenerumab and placebo arms of the first Dominantly Inherited Alzheimer Network Trials Unit clinical trial (DIAN-TU-001) underwent both 11C-PiB and 18F-florbetapir PET imaging at baseline and during at least one follow-up visit. For each PET scan, regional standardized uptake value ratios (SUVRs), regional Centiloids, a global cortical SUVR, and a global cortical Centiloid value were calculated. Longitudinal changes in SUVRs and Centiloids were estimated using linear mixed models. Differences in longitudinal change between PET radiotracers and between drug arms were estimated using paired and Welch two sample t-tests, respectively. Simulated clinical trials were conducted to evaluate the consequences of some research sites using 11C-PiB while other sites use 18F-florbetapir for Aβ PET imaging. RESULTS In the placebo arm, the absolute rate of longitudinal change measured by global cortical 11C-PiB SUVRs did not differ from that of global cortical 18F-florbetapir SUVRs. In the gantenerumab arm, global cortical 11C-PiB SUVRs decreased more rapidly than global cortical 18F-florbetapir SUVRs. Drug effects were statistically significant across both Aβ radiotracers. In contrast, the rates of longitudinal change measured in global cortical Centiloids did not differ between Aβ radiotracers in either the placebo or gantenerumab arms, and drug effects remained statistically significant. Regional analyses largely recapitulated these global cortical analyses. Across simulated clinical trials, type I error was higher in trials where both Aβ radiotracers were used versus trials where only one Aβ radiotracer was used. Power was lower in trials where 18F-florbetapir was primarily used versus trials where 11C-PiB was primarily used. CONCLUSION Gantenerumab treatment induces longitudinal changes in Aβ PET, and the absolute rates of these longitudinal changes differ significantly between Aβ radiotracers. These differences were not seen in the placebo arm, suggesting that Aβ-clearing treatments may pose unique challenges when attempting to compare longitudinal results across different Aβ radiotracers. Our results suggest converting Aβ PET SUVR measurements to Centiloids (both globally and regionally) can harmonize these differences without losing sensitivity to drug effects. Nonetheless, until consensus is achieved on how to harmonize drug effects across radiotracers, and since using multiple radiotracers in the same trial may increase type I error, multisite studies should consider potential variability due to different radiotracers when interpreting Aβ PET biomarker data and, if feasible, use a single radiotracer for the best results. TRIAL REGISTRATION ClinicalTrials.gov NCT01760005. Registered 31 December 2012. Retrospectively registered.
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Affiliation(s)
- Charles D Chen
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Washington University School of Medicine, 660 South Euclid, Campus Box 8225, St. Louis, MO, 63110, USA
| | - Austin McCullough
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Brian Gordon
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Nelly Joseph-Mathurin
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Shaney Flores
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Nicole S McKay
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Diana A Hobbs
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Russ Hornbeck
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | - Yan Li
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Xinyu Shi
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | - Michael J Pontecorvo
- Avid Radiopharmaceuticals, Philadelphia, PA, USA
- Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Yi Su
- Banner Alzheimer's Institute, Banner Health, Phoenix, AZ, USA
- Arizona Alzheimer's Consortium, Phoenix, AZ, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Clifford Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - B Joy Snider
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Erik D Roberson
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jared Brosch
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ghulam Surti
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | | | - Douglas Galasko
- Department of Neurology, University of California San Diego, San Diego, CA, USA
| | | | - William S Brooks
- Prince of Wales Medical Research Institute, University of New South Wales, Sydney, NSW, Australia
| | - Roger Clarnette
- Department of Internal Medicine, University of Western Australia, Crawley, WA, Australia
| | - David Wallon
- Department of Neurology and CNR-MAJ, Normandie Univ, UNIROUEN, INSERM U1245, CHU Rouen, F-76000, Rouen, France
| | - Bruno Dubois
- Sorbonne Université, AP-HP, GRC No. 21, APM, Hôpital de La Pitié-Salpêtrière, Paris, France
- Institut du Cerveau Et de La Moelle Épinière, INSERM U1127, CNRS UMR 7225, Paris, France
- Institut de La Mémoire Et de La Maladie d'Alzheimer, Département de Neurologie, Hôpital de La Pitié-Salpêtrière, Paris, France
| | - Jérémie Pariente
- Department of Neurology, Hôpital Pierre-Paul Riquet, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
- Toulouse NeuroImaging Centre, Université de Toulouse, INSERM, UPS, Toulouse, France
| | - Florence Pasquier
- Univ. Lille, INSERM, CHU Lille, 59000, Lille, France
- CNR-MAJ, Labex DISTALZ, LiCEND, 59000, Lille, France
| | - Raquel Sanchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Fundació Clínic Per a La Recerca Biomèdica, University of Barcelona, Barcelona, Spain
| | | | | | - Ilke Tunali
- Eli Lilly and Company, Indianapolis, IN, USA
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia
| | | | | | - Robin Hsiung
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Serge Gauthier
- Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Steve Salloway
- Alpert Medical School of Brown University, Providence, RI, USA
| | - David B Clifford
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Susan Mills
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Eric McDade
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA.
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Almkvist O, Nordberg A. A biomarker-validated time scale in years of disease progression has identified early- and late-onset subgroups in sporadic Alzheimer's disease. Alzheimers Res Ther 2023; 15:89. [PMID: 37131241 PMCID: PMC10152764 DOI: 10.1186/s13195-023-01231-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/14/2023] [Indexed: 05/04/2023]
Abstract
BACKGROUND It is possible to calculate the number of years to the expected clinical onset (YECO) of autosomal-dominant Alzheimer's disease (adAD). A similar time scale is lacking for sporadic Alzheimer's disease (sAD). The purpose was to design and validate a time scale in YECO for patients with sAD in relation to CSF and PET biomarkers. METHODS Patients diagnosed with Alzheimer's disease (AD, n = 48) or mild cognitive impairment (MCI, n = 46) participated in the study. They underwent a standardized clinical examination at the Memory clinic, Karolinska University Hospital, Stockholm, Sweden, which included present and previous medical history, laboratory screening, cognitive assessment, CSF biomarkers (Aβ42, total-tau, and p-tau), and an MRI of the brain. They were also assessed with two PET tracers, 11C-Pittsburgh compound B and 18F-fluorodeoxyglucose. Assuming concordance of cognitive decline in sAD and adAD, YECO for these patients was calculated using equations for the relationship between cognitive performance, YECO, and years of education in adAD (Almkvist et al. J Int Neuropsychol Soc 23:195-203, 2017). RESULTS The mean current point of disease progression was 3.2 years after the estimated clinical onset in patients with sAD and 3.4 years prior to the estimated clinical onset in patients with MCI, as indicated by the median YECO from five cognitive tests. The associations between YECO and biomarkers were significant, while those between chronological age and biomarkers were nonsignificant. The estimated disease onset (chronological age minus YECO) followed a bimodal distribution with frequency maxima before (early-onset) and after (late-onset) 65 years of age. The early- and late-onset subgroups differed significantly in biomarkers and cognition, but after control for YECO, this difference disappeared for all except the APOE e4 gene (more frequent in early- than in late-onset). CONCLUSIONS A novel time scale in years of disease progression based on cognition was designed and validated in patients with AD using CSF and PET biomarkers. Two early- and late-disease onset subgroups were identified differing with respect to APOE e4.
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Affiliation(s)
- Ove Almkvist
- Division of Clinical Geriatrics, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden.
- Department of Psychology, Stockholm University, Stockholm, Sweden.
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
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Mu T, Wei J, Sun J, Jin J, Zhang T, Wu H, Su B. Association of apolipoprotein E epsilon 4 and cognitive impairment in adults living with human immunodeficiency virus: a meta-analysis. Chin Med J (Engl) 2022; 135:2677-2686. [PMID: 36719356 PMCID: PMC9945176 DOI: 10.1097/cm9.0000000000002480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND It is controversial whether the apolipoprotein E epsilon 4 allele (APOE ε4) is a risk gene for human immunodeficiency virus (HIV)-related neurocognitive impairment. This meta-analysis aimed to summarize evidence of the associations between APOE ε4 and cognitive impairment in people living with HIV (PLWH). METHODS Our study conducted a systematic literature search of PubMed, Web of Science, Embase, Google Scholar, and ProQuest for studies published before April 11, 2022 that evaluated associations between APOE ε4 and cognitive impairment in adult PLWH (aged ≥18 years). We calculated pooled odds ratios (ORs) of global cognitive impairment and 95% confidence intervals (CIs) and standardized mean differences (SMDs) for specific cognitive domains between APOE ε4 carriers and non-carriers. Subgroup meta-analyses were used to evaluate the result profiles across different categorical variables. RESULTS Twenty studies met the inclusion criteria, including 19 that evaluated global cognitive impairment. APOE ε4 was significantly associated with global cognitive impairment in PLWH (OR = 1.36, 95% CI = [1.05, 1.78], number of estimates [k] = 19, P = 0.02, random effects). Subgroup meta-analysis based percentage of females showed evident intergroup differences in global cognitive performance between ε4 carriers and non-carriers (P = 0.015). APOE ε4 carriers had lower cognitive test scores than non-carriers in all seven cognitive domains, including fluency (SMD = -0.51, 95% CI = [-0.76, -0.25], P < 0.001, k = 4, I2 = 0%), learning (SMD = -0.52, 95% CI = [-0.75, -0.28], P < 0.001, k = 5, I2 = 0%), executive function (SMD = -0.41, 95% CI = [-0.59, -0.23], P < 0.001, k = 8, I2 = 0%), memory (SMD = -0.41, 95% CI = [-0.61, -0.20], P < 0.001, k = 10, I2 = 36%), attention/working memory (SMD = -0.34, 95% CI = [-0.54, -0.14], P = 0.001, k = 6, I2 = 0%), speed of information processing (SMD = -0.34, 95% CI = [-0.53, -0.16], P < 0.001, k = 8, I2 = 0%), and motor function (SMD = -0.19, 95% CI = [-0.38, -0.01], P = 0.04, k = 7, I2 = 0%). CONCLUSIONS Our meta-analysis provides significant evidence that APOE ε4 is a risk genotype for HIV-associated cognitive impairment, especially in cognitive domains of fluency, learning, executive function, and memory. Moreover, the impairment is sex specific. META ANALYSIS REGISTRATION PROSPERO, CRD 42021257775.
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Affiliation(s)
- Tingting Mu
- Beijing Key Laboratory for HIV/AIDS Research, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Jiaqi Wei
- Beijing Key Laboratory for HIV/AIDS Research, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Jun Sun
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Junyan Jin
- Beijing Key Laboratory for HIV/AIDS Research, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Tong Zhang
- Beijing Key Laboratory for HIV/AIDS Research, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Hao Wu
- Beijing Key Laboratory for HIV/AIDS Research, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Bin Su
- Beijing Key Laboratory for HIV/AIDS Research, Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
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Strain JF, Brier MR, Tanenbaum A, Gordon BA, McCarthy JE, Dincer A, Marcus DS, Chhatwal JP, Graff-Radford NR, Day GS, la Fougère C, Perrin RJ, Salloway S, Schofield PR, Yakushev I, Ikeuchi T, Vöglein J, Morris JC, Benzinger TLS, Bateman RJ, Ances BM, Snyder AZ. Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease. Neuroimage 2022; 261:119511. [PMID: 35914670 PMCID: PMC9750733 DOI: 10.1016/j.neuroimage.2022.119511] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 07/04/2022] [Accepted: 07/22/2022] [Indexed: 01/05/2023] Open
Abstract
Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.
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Affiliation(s)
- Jeremy F Strain
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Matthew R Brier
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Aaron Tanenbaum
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - John E McCarthy
- Department of Mathematics and Statistics, Washington University, St. Louis, MO 63130, USA
| | - Aylin Dincer
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA
| | - Daniel S Marcus
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jasmeer P Chhatwal
- Martinos Center, Massachusetts General Hospital, 149 13th St Room 2662, Charlestown, MA 02129, USA
| | - Neill R Graff-Radford
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Road, Jacksonville, Fl 32224, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Road, Jacksonville, Fl 32224, USA
| | - Christian la Fougère
- Department of Nuclear Medicine and Clinical Molecular Imaging, Universityhospital Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
| | - Richard J Perrin
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Stephen Salloway
- Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI 02906, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW 2131, Australia; School of Medical Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich 81675, Germany
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Japan
| | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität Munich, Germany
| | - John C Morris
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA.
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8
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Forno G, Lladó A, Hornberger M. Going round in circles-The Papez circuit in Alzheimer's disease. Eur J Neurosci 2021; 54:7668-7687. [PMID: 34656073 DOI: 10.1111/ejn.15494] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 10/01/2021] [Accepted: 10/12/2021] [Indexed: 11/29/2022]
Abstract
The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and increasing evidence suggests that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology. In the current review, we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at-genetic-risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD and autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal-centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches.
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Affiliation(s)
- Gonzalo Forno
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,School of Psychology, Universidad de los Andes, Santiago, Chile.,Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department, ICBM, Neurosciences Department, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
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9
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Qin Q, Fu L, Wang R, Lyu J, Ma H, Zhan M, Zhou A, Wang F, Zuo X, Wei C. Prominent Striatum Amyloid Retention in Early-Onset Familial Alzheimer's Disease With PSEN1 Mutations: A Pilot PET/MR Study. Front Aging Neurosci 2021; 13:732159. [PMID: 34603009 PMCID: PMC8480470 DOI: 10.3389/fnagi.2021.732159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 08/13/2021] [Indexed: 11/17/2022] Open
Abstract
Background: With the advancements of amyloid imaging in recent years, this new imaging diagnostic method has aroused great interest from researchers. Till now, little is known regarding amyloid deposition specialty in patients with early-onset familial Alzheimer's disease (EOFAD), and even less is known about its role in cognitive impairments. Objectives: Our study aimed to evaluate the amyloid deposition in five patients with EOFAD, 15 patients with late-onset sporadic AD, and 12 healthy subjects utilizing 11C-labeled Pittsburgh compound-B (11C-PiB) amyloid PET imaging. Moreover, we figured out the correlation between striatal and cortical standardized uptake value ratios (SUVRs). We also investigated the correlation between 11C-PiB retention and cognitive presentation. Results: All patients with EOFAD showed high amyloid deposition in the striatum, a pattern that is not usually seen in patients with late-onset sporadic AD. The SUVR in the striatum, especially in the amygdala, showed significant correlations with cortex SUVR in EOFAD. However, neither striatal nor cortical 11C-PiB retention was related to cognitive decline. Conclusions: The amyloid distribution in patients with EOFAD differs from late-onset sporadic AD, with higher amyloid deposits in the striatum. Our study also demonstrated positive correlations in 11C-PiB retention between the striatum and other cortical areas. We revealed that the distribution of amyloid in the brain is not random but diffuses following the functional and anatomical connections. However, the degree and pattern of amyloid deposition were not correlated with cognitive deficits.
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Affiliation(s)
- Qi Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Liping Fu
- Department of Nuclear Medicine, China-Japan Friendship Hospital, Beijing, China.,Department of Nuclear Medicine, The First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Ruimin Wang
- Department of Nuclear Medicine, The First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Jihui Lyu
- Center for Cognitive Disorders, Beijing Geriatric Hospital, Beijing, China
| | - Huixuan Ma
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Minmin Zhan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Aihong Zhou
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Fen Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Xiumei Zuo
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Cuibai Wei
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
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10
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Skipper JI, Aliko S, Brown S, Jo YJ, Lo S, Molimpakis E, Lametti DR. Reorganization of the Neurobiology of Language After Sentence Overlearning. Cereb Cortex 2021; 32:2447-2468. [PMID: 34585723 PMCID: PMC9157312 DOI: 10.1093/cercor/bhab354] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/27/2021] [Accepted: 08/29/2021] [Indexed: 11/14/2022] Open
Abstract
It is assumed that there are a static set of "language regions" in the brain. Yet, language comprehension engages regions well beyond these, and patients regularly produce familiar "formulaic" expressions when language regions are severely damaged. These suggest that the neurobiology of language is not fixed but varies with experiences, like the extent of word sequence learning. We hypothesized that perceiving overlearned sentences is supported by speech production and not putative language regions. Participants underwent 2 sessions of behavioral testing and functional magnetic resonance imaging (fMRI). During the intervening 15 days, they repeated 2 sentences 30 times each, twice a day. In both fMRI sessions, they "passively" listened to those sentences, novel sentences, and produced sentences. Behaviorally, evidence for overlearning included a 2.1-s decrease in reaction times to predict the final word in overlearned sentences. This corresponded to the recruitment of sensorimotor regions involved in sentence production, inactivation of temporal and inferior frontal regions involved in novel sentence listening, and a 45% change in global network organization. Thus, there was a profound whole-brain reorganization following sentence overlearning, out of "language" and into sensorimotor regions. The latter are generally preserved in aphasia and Alzheimer's disease, perhaps explaining residual abilities with formulaic expressions in both.
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Affiliation(s)
| | - Sarah Aliko
- Experimental Psychology, University College London, London, UK.,London Interdisciplinary Biosciences Consortium, University College London, London, UK
| | - Stephen Brown
- Natural Sciences, University College London, London, UK
| | - Yoon Ju Jo
- Experimental Psychology, University College London, London, UK
| | - Serena Lo
- Speech and Language Sciences, University College London, London, UK
| | - Emilia Molimpakis
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Daniel R Lametti
- Experimental Psychology, University College London, London, UK.,Department of Psychology, Acadia University, Nova Scotia, Canada
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11
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Almkvist O, Brüggen K, Nordberg A. Subcortical and Cortical Regions of Amyloid-β Pathology Measured by 11C-PiB PET Are Differentially Associated with Cognitive Functions and Stages of Disease in Memory Clinic Patients. J Alzheimers Dis 2021; 81:1613-1624. [PMID: 33967046 DOI: 10.3233/jad-201612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND The effect of regional brain amyloid-β (Aβ) pathology on specific cognitive functions is incompletely known. OBJECTIVE The relationship between Aβ and cognitive functions was investigated in this cross-sectional multicenter study of memory clinic patients. METHODS The participants were patients diagnosed with Alzheimer's disease (AD, n = 83), mild cognitive impairment (MCI, n = 60), and healthy controls (HC, n = 32), who had been scanned by 11C-PiB PET in 13 brain regions of both hemispheres and who had been assessed by cognitive tests covering seven domains. RESULTS Hierarchic multiple regression analyses were performed on each cognitive test as dependent variable, controlling for demographic characteristics and APOE status (block 1) and PiB measures in 13 brain regions (block 2) as independent variables. The model was highly significant for each cognitive test and most strongly for tests of episodic memory (learning and retention) versus PiB in putamen, visuospatially demanding tests (processing and retention) versus the occipital lobe, semantic fluency versus the parietal lobe, attention versus posterior gyrus cinguli, and executive function versus nucleus accumbens. In addition, education had a positively and APOE status a negatively significant effect on cognitive tests. CONCLUSION Five subcortical and cortical regions with Aβ pathology are differentially associated with cognitive functions and stages of disease in memory clinic patients.
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Affiliation(s)
- Ove Almkvist
- Division of Clinical Geriatrics, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.,Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Katharina Brüggen
- Division of Clinical Geriatrics, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden
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12
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Pardilla-Delgado E, Torrico-Teave H, Sanchez JS, Ramirez-Gomez LA, Baena A, Bocanegra Y, Vila-Castelar C, Fox-Fuller JT, Guzmán-Vélez E, Martínez J, Alvarez S, Ochoa-Escudero M, Lopera F, Quiroz YT. Associations between subregional thalamic volume and brain pathology in autosomal dominant Alzheimer's disease. Brain Commun 2021; 3:fcab101. [PMID: 34095834 PMCID: PMC8172494 DOI: 10.1093/braincomms/fcab101] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 02/01/2021] [Accepted: 03/19/2021] [Indexed: 12/02/2022] Open
Abstract
Histopathological reports suggest that subregions of the thalamus, which regulates multiple physiological and cognitive processes, are not uniformly affected by Alzheimer's disease. Despite this, structural neuroimaging studies often consider the thalamus as a single region. Identification of in vivo Alzheimer's-dependent volumetric changes in thalamic subregions may aid the characterization of early nuclei-specific neurodegeneration in Alzheimer's disease. Here, we leveraged access to the largest single-mutation cohort of autosomal-dominant Alzheimer's disease to test whether cross-sectional abnormalities in subregional thalamic volumes are evident in non-demented mutation carriers (n = 31), compared to non-carriers (n = 36), and whether subregional thalamic volume is associated with age, markers of brain pathology and cognitive performance. Using automatic parcellation we examined the thalamus in six subregions (anterior, lateral, ventral, intralaminar, medial, and posterior) and their relation to age and brain pathology (amyloid and tau), as measured by PET imaging. No between-group differences were observed in the volume of the thalamic subregions. In carriers, lower volume in the medial subregion was related to increased cortical amyloid and entorhinal tau burden. These findings suggest that thalamic Alzheimer's-related volumetric reductions are not uniform even in preclinical and prodromal stages of autosomal-dominant Alzheimer's disease and therefore, this structure should not be considered as a single, unitary structure in Alzheimer's disease research.
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Affiliation(s)
| | | | - Justin S Sanchez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | | | - Ana Baena
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin 050010, Colombia
| | - Yamile Bocanegra
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin 050010, Colombia
| | - Clara Vila-Castelar
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Joshua T Fox-Fuller
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Boston University, Boston, MA 02215, USA
| | | | - Jairo Martínez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | | | | | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin 050010, Colombia
| | - Yakeel T Quiroz
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin 050010, Colombia
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13
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Yang FN, Bronshteyn M, Flowers SA, Dawson M, Kumar P, Rebeck GW, Turner RS, Moore DJ, Ellis RJ, Jiang X. Low CD4+ cell count nadir exacerbates the impacts of APOE ε4 on functional connectivity and memory in adults with HIV. AIDS 2021; 35:727-736. [PMID: 33587445 PMCID: PMC8318747 DOI: 10.1097/qad.0000000000002840] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
OBJECTIVE Nearly half of individuals living with HIV in the USA are now 50 or older. This rapidly ageing populace may be at an increasingly greater risk of Alzheimer's disease. However, the potential interaction between HIV-disease and Alzheimer's disease pathogenesis (i.e. Alzheimer's disease genetic risk factors) on brain function remains an open question. The present study aimed to investigate the impact of APOE ε4 on brain function in middle-aged to older people with HIV (PWH), as well as the putative interaction between ε4 and HIV disease severity. METHODS Ninety-nine PWH participated in a cross-sectional study (56.3 ± 6.5 years, range 41-70 years, 27 women, 26 ε4 carriers and 73 noncarriers). Structural MRI and resting-state functional MRI were collected to assess alterations in brain structure and functional connectivity, respectively. RESULTS APOE ε4 was associated with worse memory performance and reduced functional connectivity in the memory network. The functional connectivity reduction was centred at the caudate nucleus rather than hippocampus and correlated with worse memory performance. In ε4 carriers, low CD4+ cell count nadir was associated with reduced functional connectivity in the memory network, but this association was absent in noncarriers. Furthermore, there was an indirect detrimental impact of ε4 on memory performance through memory network functional connectivity. However, this indirect effect was contingent on CD4+ cell count nadir, that is the indirect effect of ε4 on memory was only significant when CD4+ cell count nadir was low. INTERPRETATION APOE ε4 is associated with reduced memory and reduced functional connectivity within the memory network, and low CD4+ cell count nadir -- indicating a history of severe immunosuppression -- may exacerbate the effects of ε4.
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Affiliation(s)
- Fan Nils Yang
- Departments of Neuroscience, Georgetown University Medical Center, Washington, DC 20057, USA
| | - Margarita Bronshteyn
- Departments of Neuroscience, Georgetown University Medical Center, Washington, DC 20057, USA
| | - Sarah A. Flowers
- Departments of Neuroscience, Georgetown University Medical Center, Washington, DC 20057, USA
| | - Matthew Dawson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Princy Kumar
- Department of Neurology, Georgetown University Medical Center, Washington, DC 20057, USA
| | - G. William Rebeck
- Departments of Neuroscience, Georgetown University Medical Center, Washington, DC 20057, USA
| | - R. Scott Turner
- Department of Medicine, Georgetown University Medical Center, Washington, DC 20057, USA
| | - David J. Moore
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ronald J. Ellis
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Xiong Jiang
- Departments of Neuroscience, Georgetown University Medical Center, Washington, DC 20057, USA
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14
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De Vocht J, Blommaert J, Devrome M, Radwan A, Van Weehaeghe D, De Schaepdryver M, Ceccarini J, Rezaei A, Schramm G, van Aalst J, Chiò A, Pagani M, Stam D, Van Esch H, Lamaire N, Verhaegen M, Mertens N, Poesen K, van den Berg LH, van Es MA, Vandenberghe R, Vandenbulcke M, Van den Stock J, Koole M, Dupont P, Van Laere K, Van Damme P. Use of Multimodal Imaging and Clinical Biomarkers in Presymptomatic Carriers of C9orf72 Repeat Expansion. JAMA Neurol 2021; 77:1008-1017. [PMID: 32421156 PMCID: PMC7417970 DOI: 10.1001/jamaneurol.2020.1087] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Question Can metabolic brain changes be detected in presymptomatic individuals who are carriers of a hexanucleotide repeat expansion in the C9orf72 gene (preSxC9) using time-of-flight fluorine 18–labeled fluorodeoxyglucose positron emission tomographic imaging and magnetic resonance imaging, and what is the association between the mutation and clinical and fluid biomarkers of amyotrophic lateral sclerosis and frontotemporal dementia? Findings In a case-control study including 17 preSxC9 participants and 25 healthy controls, fluorine 18–labeled fluorodeoxyglucose positron emission tomographic imaging noted significant clusters of relative hypometabolism in frontotemporal regions, the insular cortices, basal ganglia, and thalami in the preSxC9 participants. Use of this strategy allowed detection of changes at an individual level. Meaning Glucose metabolic changes appear to occur early in the sequence of events leading to manifest amyotrophic lateral sclerosis and frontotemporal dementia. Fluorine 18–labeled fluorodeoxyglucose positron emission tomographic imaging may provide a sensitive biomarker of a presymptomatic phase of disease. Importance During a time with the potential for novel treatment strategies, early detection of disease manifestations at an individual level in presymptomatic carriers of a hexanucleotide repeat expansion in the C9orf72 gene (preSxC9) is becoming increasingly relevant. Objectives To evaluate changes in glucose metabolism before symptom onset of amyotrophic lateral sclerosis or frontotemporal dementia in preSxC9 using simultaneous fluorine 18–labeled fluorodeoxyglucose ([18F]FDG positron emission tomographic (PET) and magnetic resonance imaging as well as the mutation’s association with clinical and fluid biomarkers. Design, Setting, and Participants A prospective, case-control study enrolled 46 participants from November 30, 2015, until December 11, 2018. The study was conducted at the neuromuscular reference center of the University Hospitals Leuven, Leuven, Belgium. Main Outcomes and Measures Neuroimaging data were spatially normalized and analyzed at the voxel level at a height threshold of P < .001, cluster-level familywise error–corrected threshold of P < .05, and statistical significance was set at P < .05 for the volume-of-interest level analysis, using Benjamini-Hochberg correction for multiple correction. W-score maps were computed using the individuals serving as controls as a reference to quantify the degree of [18F]FDG PET abnormality. The threshold for abnormality on the W-score maps was designated as an absolute W-score greater than or equal to 1.96. Neurofilament levels and performance on cognitive and neurologic examinations were determined. All hypothesis tests were 1-sided. Results Of the 42 included participants, there were 17 with the preSxC9 mutation (12 women [71%]; mean [SD] age, 51 [9] years) and 25 healthy controls (12 women [48%]; mean [SD] age, 47 [10] years). Compared with control participants, significant clusters of relative hypometabolism were found in frontotemporal regions, basal ganglia, and thalami of preSxC9 participants and relative hypermetabolism in the peri-Rolandic region, superior frontal gyrus, and precuneus cortex. W-score frequency maps revealed reduced glucose metabolism with local maxima in the insular cortices, central opercular cortex, and thalami in up to 82% of preSxC9 participants and increased glucose metabolism in the precentral gyrus and precuneus cortex in up to 71% of preSxC9 participants. Other findings in the preSxC9 group were upper motor neuron involvement in 10 participants (59%), cognitive abnormalities in 5 participants (29%), and elevated neurofilament levels in 3 of 16 individuals (19%) who underwent lumbar puncture. Conclusions and Relevance The results suggest that [18F]FDG PET can identify glucose metabolic changes in preSxC9 at an individual level, preceding significantly elevated neurofilament levels and onset of symptoms.
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Affiliation(s)
- Joke De Vocht
- KU Leuven, Department of Neurosciences, Experimental Neurology, B-3000 Leuven, Belgium.,KU Leuven, University Hospitals Leuven, University Psychiatric Center, Adult Psychiatry, B-3000 Leuven, Belgium.,University Hospitals Leuven, Department of Neurology, B-3000 Leuven, Belgium.,VIB - Center of Brain & Disease Research, Laboratory of Neurobiology, B-3000 Leuven, Belgium
| | | | - Martijn Devrome
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Ahmed Radwan
- KU Leuven, Department of Imaging and Pathology, Translational MRI, B-3000 Leuven, Belgium
| | - Donatienne Van Weehaeghe
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Maxim De Schaepdryver
- KU Leuven, Department of Neurosciences, Laboratory for Molecular Neurobiomarker Research, B-3000 Leuven, Belgium
| | - Jenny Ceccarini
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Ahmadreza Rezaei
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Georg Schramm
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - June van Aalst
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Adriano Chiò
- ALS Center, Rita Levi Montalcini Department of Neuroscience, University of Turin, Turin, Italy
| | - Marco Pagani
- Institute of Cognitive Sciences and Technologies, CNR, Rome, Italy.,Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Daphne Stam
- KU Leuven, Leuven Brain Institute, Laboratory for Translational Neuropsychiatry, B-3000 Leuven, Belgium
| | - Hilde Van Esch
- University Hospitals Leuven, Center for Human Genetics, B-3000 Leuven, Belgium
| | - Nikita Lamaire
- University Hospitals Leuven, Department of Neurology, B-3000 Leuven, Belgium
| | - Marianne Verhaegen
- KU Leuven, University Hospitals Leuven, University Psychiatric Center, Adult Psychiatry, B-3000 Leuven, Belgium
| | - Nathalie Mertens
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Koen Poesen
- KU Leuven, Department of Neurosciences, Laboratory for Molecular Neurobiomarker Research, B-3000 Leuven, Belgium
| | - Leonard H van den Berg
- Brain Center Rudolf Magnus, Department of Neurology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Michael A van Es
- Brain Center Rudolf Magnus, Department of Neurology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Rik Vandenberghe
- University Hospitals Leuven, Department of Neurology, B-3000 Leuven, Belgium.,KU Leuven, Department of Neurosciences, Laboratory for Cognitive Neurology, B-3000 Leuven, Belgium
| | - Mathieu Vandenbulcke
- KU Leuven, Leuven Brain Institute, Laboratory for Translational Neuropsychiatry, B-3000 Leuven, Belgium.,KU Leuven, University Psychiatric Center, Geriatric Psychiatry, B-3000 Leuven, Belgium
| | - Jan Van den Stock
- KU Leuven, Leuven Brain Institute, Laboratory for Translational Neuropsychiatry, B-3000 Leuven, Belgium.,KU Leuven, University Psychiatric Center, Geriatric Psychiatry, B-3000 Leuven, Belgium
| | - Michel Koole
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Patrick Dupont
- KU Leuven, Department of Neurosciences, Laboratory for Cognitive Neurology, B-3000 Leuven, Belgium
| | - Koen Van Laere
- KU Leuven, University Hospitals Leuven, Department of Imaging and Pathology, Division of Nuclear Medicine, B-3000 Leuven, Belgium
| | - Philip Van Damme
- KU Leuven, Department of Neurosciences, Experimental Neurology, B-3000 Leuven, Belgium.,University Hospitals Leuven, Department of Neurology, B-3000 Leuven, Belgium.,VIB - Center of Brain & Disease Research, Laboratory of Neurobiology, B-3000 Leuven, Belgium
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15
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Ravanfar P, Loi SM, Syeda WT, Van Rheenen TE, Bush AI, Desmond P, Cropley VL, Lane DJR, Opazo CM, Moffat BA, Velakoulis D, Pantelis C. Systematic Review: Quantitative Susceptibility Mapping (QSM) of Brain Iron Profile in Neurodegenerative Diseases. Front Neurosci 2021; 15:618435. [PMID: 33679303 PMCID: PMC7930077 DOI: 10.3389/fnins.2021.618435] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/07/2021] [Indexed: 12/11/2022] Open
Abstract
Iron has been increasingly implicated in the pathology of neurodegenerative diseases. In the past decade, development of the new magnetic resonance imaging technique, quantitative susceptibility mapping (QSM), has enabled for the more comprehensive investigation of iron distribution in the brain. The aim of this systematic review was to provide a synthesis of the findings from existing QSM studies in neurodegenerative diseases. We identified 80 records by searching MEDLINE, Embase, Scopus, and PsycInfo databases. The disorders investigated in these studies included Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Wilson's disease, Huntington's disease, Friedreich's ataxia, spinocerebellar ataxia, Fabry disease, myotonic dystrophy, pantothenate-kinase-associated neurodegeneration, and mitochondrial membrane protein-associated neurodegeneration. As a general pattern, QSM revealed increased magnetic susceptibility (suggestive of increased iron content) in the brain regions associated with the pathology of each disorder, such as the amygdala and caudate nucleus in Alzheimer's disease, the substantia nigra in Parkinson's disease, motor cortex in amyotrophic lateral sclerosis, basal ganglia in Huntington's disease, and cerebellar dentate nucleus in Friedreich's ataxia. Furthermore, the increased magnetic susceptibility correlated with disease duration and severity of clinical features in some disorders. Although the number of studies is still limited in most of the neurodegenerative diseases, the existing evidence suggests that QSM can be a promising tool in the investigation of neurodegeneration.
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Affiliation(s)
- Parsa Ravanfar
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Samantha M Loi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Warda T Syeda
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Ashley I Bush
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience & Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Patricia Desmond
- Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia.,Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Darius J R Lane
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience & Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Carlos M Opazo
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Bradford A Moffat
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
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16
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Li B, Zhang M, Riphagen J, Morrison Yochim K, Li B, Liu J, Salat DH. Prediction of clinical and biomarker conformed Alzheimer's disease and mild cognitive impairment from multi-feature brain structural MRI using age-correction from a large independent lifespan sample. Neuroimage Clin 2020; 28:102387. [PMID: 32871388 PMCID: PMC7476071 DOI: 10.1016/j.nicl.2020.102387] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 02/06/2023]
Abstract
Structural neuroimaging has been applied to the identification of individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, these methods are greatly impacted by age limiting their utility for detection of preclinical pathology. We built linear models for age based on multiple combined structural features using a large independent lifespan sample of 272 healthy adults across a wide age range from the Human Connectome Project Aging study. These models were then used to create a new support vector machine (SVM) training model in 136 AD and 268 control participants based on residues of fit from the expected age-effects relationship. Subsequent validation assessed the accuracy of the SVM model in new datasets. Finally, we applied the classifier to 276 individuals with MCI to evaluate prediction for early impairment and longitudinal cognitive change. The optimal 10-fold cross-validation accuracy was 93.07%, compared to 91.83% without age detrending. In the validation dataset, the classifier for AD obtained an accuracy of 84.85% (56/66), sensitivity of 85.36% (35/41) and specificity of 84% (21/25). Classification accuracy was improved when using the lifespan sample as opposed to the classification sample. Importantly, we observed cross-sectional greater AD specific biomarkers, as well as faster cognitive decline in MCI who were classified as more 'AD-like' (MCI-AD), and these effects were pronounced in individuals who were late MCI. The top five contributive features were volumes of left hippocampus, right hippocampus, left amygdala, the thickness of left and right middle temporal & parahippocampus gyrus. Linear detrending for age in SVM for combined structural features resulted in good performance for recognition of AD and AD-specific biomarkers, as well as prediction of MCI progression. Such procedures may be used in future work to enhance prediction in samples with atypical age distributions.
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Affiliation(s)
- Binyin Li
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Department of Neurology, Ruijin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Miao Zhang
- Department of Nuclear Medicine, Ruijin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Joost Riphagen
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Kathryn Morrison Yochim
- MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jun Liu
- Department of Neurology, Ruijin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - David 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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17
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Wan M, Xia R, Lin H, Qiu P, He J, Ye Y, Tao J, Chen L, Zheng G. Volumetric and Diffusion Abnormalities in Subcortical Nuclei of Older Adults With Cognitive Frailty. Front Aging Neurosci 2020; 12:202. [PMID: 32848700 PMCID: PMC7399332 DOI: 10.3389/fnagi.2020.00202] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 06/11/2020] [Indexed: 01/24/2023] Open
Abstract
Background: Cognitive frailty (CF) is defined as the simultaneous presence of physical frailty and cognitive impairment among older adults without dementia. Previous studies have revealed that neuropathological changes may contribute to the degeneration of subcortical nuclei in the process of cognitive impairment. However, it is unclear in CF. The aim of this study is to investigate the changes in subcortical nuclei in older adults with CF and their relationship with cognitive decline and physical frailty. Methods: A total of 26 older adults with CF and 26 matched healthy subjects were enrolled. Cognitive function and physical frailty were assessed with the Montreal Cognitive Assessment (MoCA) scale (Fuzhou version) and the Chinese version of the Edmonton Frailty Scale (EFS). Volumetric and diffusion tensor imaging (DTI) parameters of subcortical nuclei were measured with structural and DTI brain magnetic resonance imaging (MRI) and compared between groups. Partial correlation analysis was conducted between subcortical nuclei volumes, MoCA scores, and physical frailty indexes. Results: Significant volume reductions were found in five subcortical nuclei, including the bilateral thalami, left caudate, right pallidum, and accumbens area, in older adults with CF (P < 0.05), and the bilateral thalami was most obvious. Decreased fractional anisotropy and relative anisotropy values were observed only in the left thalamus in the CF group (P < 0.05). No group differences were found in apparent diffusion coefficient (ADC) values. The MoCA scores were positively correlated with the volumes of the bilateral thalami, right pallidum, and accumbens area (P < 0.05). Negative correlations were found between the physical frailty index and the volumes of the bilateral thalami, caudate, pallidum, and right accumbens area (P < 0.05). Conclusion: Microstructural changes occur in the subcortical nuclei of older adults with CF, and these changes are correlated with cognitive decline and physical frailty. Therefore, microstructural atrophy of the subcortical nuclei may be involved in the pathological progression of CF.
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Affiliation(s)
- Mingyue Wan
- 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
| | - Huiying Lin
- 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
| | - Jianquan He
- 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
| | - Jing Tao
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Fujian Key Laboratory of Rehabilitation Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lidian Chen
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.,Fujian Key Laboratory of Rehabilitation Technology, 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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18
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Um YH, Wang SM, Kim NY, Kang DW, Na HR, Lee CU, Lim HK. Effects of Moderate Intensity Exercise on the Cortical Thickness and Subcortical Volumes of Preclinical Alzheimer's Disease Patients: A Pilot Study. Psychiatry Investig 2020; 17:613-619. [PMID: 32570297 PMCID: PMC7324741 DOI: 10.30773/pi.2020.0214] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 06/09/2020] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE We aimed to explore the impact of moderate intensity exercise on the cortical thickness and subcortical volumes of preclinical Alzheimer's disease (AD) patients. METHODS Sixty-three preclinical AD patients with magnetic resonance imaging (MRI) and 18-florbetaben positron emission tomography (PET) data were enrolled in the study. Information on demographic characteristics, cognitive battery scores, self-reported exercise habits were attained. Structural magnetic resonance images were analyzed and processed using Freesurfer v6.0. RESULTS Compared to Exercise group, Non-Exercise group demonstrated reduced cortical thickness in left parstriangularis, rostral middle frontal, entorhinal, superior frontal, lingual, superior parietal, lateral occipital, inferior parietal gyrus, temporal pole, precuneus, insula, fusiform gyrus, right precuneus, superiorparietal, lateral orbitofrontal, rostral middle frontal, medial orbitofrontal, superior frontal, lingual, middle temporal gyrus, insula, supramarginal, parahippocampal, paracentral gyrus. Volumes of right thalamus, caudate, putamen, pallidum, hippocampus, amygdala were also reduced in Non-Exercise group. CONCLUSION Moderate intensity exercise affects cortical and subcortical structures in preclinical AD patients. Thus, physical exercise has a potential to be an effective intervention to prevent future cognitive decline in those at high risk of AD.
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Affiliation(s)
- Yoo Hyun Um
- Department of Psychiatry, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Nak-Young Kim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hae-Ran Na
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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19
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Quan M, Zhao T, Tang Y, Luo P, Wang W, Qin Q, Li T, Wang Q, Fang J, Jia J. Effects of gene mutation and disease progression on representative neural circuits in familial Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2020; 12:14. [PMID: 31937364 PMCID: PMC6961388 DOI: 10.1186/s13195-019-0572-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 12/23/2019] [Indexed: 02/08/2023]
Abstract
Background Although structural and functional changes of the striatum and hippocampus are present in familial Alzheimer’s disease, little is known about the effects of specific gene mutation or disease progression on their related neural circuits. This study was to evaluate the effects of known pathogenic gene mutation and disease progression on the striatum- and hippocampus-related neural circuits, including frontostriatal and hippocampus-posterior cingulate cortex (PCC) pathways. Methods A total of 102 healthy mutation non-carriers, 40 presymptomatic mutation carriers (PMC), and 30 symptomatic mutation carriers (SMC) of amyloid precursor protein (APP), presenilin 1 (PS1), or presenilin 2 gene, with T1 structural MRI, diffusion tensor imaging, and resting-state functional MRI were included. Representative neural circuits and their key nodes were obtained, including bilateral caudate-rostral middle frontal gyrus (rMFG), putamen-rMFG, and hippocampus-PCC. Volumes, diffusion indices, and functional connectivity of circuits were compared between groups and correlated with neuropsychological and clinical measures. Results In PMC, APP gene mutation carriers showed impaired diffusion indices of caudate-rMFG and putamen-rMFG circuits; PS1 gene mutation carriers showed increased fiber numbers of putamen-rMFG circuit. SMC showed increased diffusivity of the left hippocampus-PCC circuit and volume reduction of all regions as compared with PMC. Imaging measures especially axial diffusivity of the representative circuits were correlated with neuropsychological measures. Conclusions APP and PS1 gene mutations affect frontostriatal circuits in a different manner in familial Alzheimer’s disease; disease progression primarily affects the structure of hippocampus-PCC circuit. The structural connectivity of both frontostriatal and hippocampus-PCC circuits is associated with general cognitive function. Such findings may provide further information about the imaging biomarkers for early identification and prognosis of familial Alzheimer’s disease, and pave the way for early diagnosis, gene- or circuit-targeted treatment, and even prevention. Electronic supplementary material The online version of this article (10.1186/s13195-019-0572-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Meina Quan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Tan Zhao
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Yi Tang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Ping Luo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Wei Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Qi Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Tingting Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Qigeng Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Jiliang Fang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China. .,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China. .,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China.
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20
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A β-sheet-targeted theranostic agent for diagnosing and preventing aggregation of pathogenic peptides in Alzheimer’s disease. Sci China Chem 2019. [DOI: 10.1007/s11426-019-9594-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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21
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Zhu K, Wang X, Sun B, Wu J, Lu H, Zhang X, Liang H, Zhang D, Liu C. Primary Age-Related Tauopathy in Human Subcortical Nuclei. Front Neurosci 2019; 13:529. [PMID: 31191227 PMCID: PMC6549797 DOI: 10.3389/fnins.2019.00529] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 05/07/2019] [Indexed: 12/29/2022] Open
Abstract
The present study aimed to determine the spatial distribution patterns of hyperphosphorylated tau-immunoreactive cells in subcortical nuclei of post-mortem human brain with primary age-related tauopathy (PART). Subcortical tauopathy has important pathological and clinical implications. Expression of tau was examined in different subcortical regions of definite PART cases with a Braak neurofibrillary tangle stage >0 and ≤IV, and with a Thal phase 0 (no beta-amyloid present). Post-mortem brain tissue of PART was studied using immunohistochemistry and subsequent semi-quantitative assessment with Braak NFT stage -matched pre-Alzheimer’s disease (AD) and AD cases as a control. Expression of tau was frequently found in subcortical nuclei including the substantia nigra, inferior colliculus, locus coeruleus, medulla oblongata in the brainstem, the caudate, putamen, nucleus globus pallidus in the striatum, the hypothalamus, thalamus, subthalamus in the diencephalon, and the cervical spinal cord in both PART and AD, but not in the dentate nucleus of the cerebellum. A positive correlation was found between the Braak NFT stage and the tau distribution (qualitative)/tau density (quantitative) in PART and AD. Brainstem nuclei were commonly involved in early PART with NFT Braak stage I/II, there was no preference among the substantia nigra, inferior colliculus, locus caeruleus and medulla oblongata. The prevalence and severity of tau pathology in subcortical nuclei of PART and AD were positively correlated with NFT Braak stage, suggesting that these nuclei were increasingly involved as PART and AD progressed. Subcortical nuclei were likely the sites initially affected by aging associated tau pathology, especially the brainstem nuclei including the substantia nigra, inferior colliculus, locus caeruleus and medulla oblongata.
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Affiliation(s)
- Keqing Zhu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China.,Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
| | - Xin Wang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China.,Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
| | - Bing Sun
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Juanli Wu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Lu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoling Zhang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Huazheng Liang
- Brain Structure and Function, Neuroscience Research Australia, Randwick, NSW, Australia.,Department of Neurology, Shanghai Fourth People's Hospital, Tongji University, Shanghai, China
| | - Dandan Zhang
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
| | - Chong Liu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China.,Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
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22
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Klein C, Roussel G, Brun S, Rusu C, Patte-Mensah C, Maitre M, Mensah-Nyagan AG. 5-HIAA induces neprilysin to ameliorate pathophysiology and symptoms in a mouse model for Alzheimer's disease. Acta Neuropathol Commun 2018; 6:136. [PMID: 30537985 PMCID: PMC6290545 DOI: 10.1186/s40478-018-0640-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 11/28/2018] [Indexed: 01/07/2023] Open
Abstract
Serotoninergic activation which decreases brain Aβ peptides is considered beneficial in mouse models for Alzheimer's disease (AD), but the mechanisms involved remain unclear. Because growing evidence suggested that the stimulation of proteases digesting Aβ, especially the endopeptidase neprilysin (NEP) may be effective for AD therapy/prevention, we explored the involvement of serotonin precursors and derivatives in NEP regulation. We found that 5-hydroxyindolacetic acid (5-HIAA), the final metabolite of serotonin, considered until now as a dead-end and inactive product of serotonin catabolism, significantly reduces brain Aβ in the transgenic APPSWE mouse model for AD-related Aβ pathology and in the phosphoramidon-induced cerebral NEP inhibition mouse model. 5-HIAA treatment improves memory performance in APPSWE mice. Furthermore, 5-HIAA and its precursors increase NEP level in vivo and in neuroblastoma cells. Inhibition of ERK 1/2 cascade by 5-HIAA or SCH772984 enhanced NEP levels, suggesting MAP-kinase pathway involvement in 5-HIAA-induced regulation of NEP expression. Our results provide the first demonstration that 5-HIAA is an active serotonin metabolite that increases brain Aβ degradation/clearance and improves symptoms in the APPSWE mouse model for AD.
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23
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Wang ML, Wei XE, Fu JL, Li W, Yu MM, Li PY, Li WB. Subcortical nuclei in Alzheimer's disease: a volumetric and diffusion kurtosis imaging study. Acta Radiol 2018; 59:1365-1371. [PMID: 29482345 DOI: 10.1177/0284185118758122] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background Previous studies revealed that subcortical nuclei were harmed in the process of Alzheimer's disease (AD). Purpose To investigate the volumetric and diffusion kurtosis imaging (DKI) parameter changes of subcortical nuclei in AD and their relationship with cognitive function. Materials and Methods A total of 17 mild AD patients, 15 moderate to severe AD patients, and 16 controls underwent neuropsychological tests and magnetic resonance imaging (MRI) scans. Volume, mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) were measured in hippocampus, thalamus, caudate, putamen, pallidum, and amygdala. MRI parameters were compared. Correlation analysis was performed between subcortical nuclei volume, DKI parameters, and MMSE score. Results Significant volume reduction was seen in the left hippocampus in mild AD, and the bilateral hippocampus, thalamus, putamen, left caudate, and right amygdala in moderate to severe AD ( P < 0.05). Increased MD values were observed in the left hippocampus, left amygdala, and right caudate in mild AD, and the bilateral hippocampus and right amygdala in moderate to severe AD ( P < 0.05). Decreased MK values were observed only in the bilateral hippocampus in moderate to severe AD ( P < 0.05). No group significances were found in FA value. MMSE score was positively correlated with the volume of the bilateral hippocampus, thalamus, and putamen, and MK value of the left hippocampus ( P < 0.05). A negative correlation was found with the MD value of the bilateral hippocampus and left amygdala ( P < 0.05). Conclusion Mild AD mainly has microscopic subcortical changes revealed by increased MD value, and moderate to severe AD mainly has macroscopic subcortical changes revealed by volume reduction. MK is more sensitive in severe AD than mild AD.
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Affiliation(s)
- Ming-Liang Wang
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Xiao-Er Wei
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Jian-Liang Fu
- Department of Neurology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Wei Li
- Department of Geriatrics, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Meng-Meng Yu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Peng-Yang Li
- Department of Cardiology, Peking University Aerospace School of Clinical Medicine, Peking University Health Science Center, Beijing, PR China
| | - Wen-Bin Li
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
- Imaging center, Kashgar Prefecture Second People’s Hospital, Kashgar, PR China
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Corticothalamic network dysfunction and Alzheimer's disease. Brain Res 2017; 1702:38-45. [PMID: 28919464 DOI: 10.1016/j.brainres.2017.09.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 09/11/2017] [Indexed: 12/11/2022]
Abstract
Alzheimer's disease (AD) is a devastating neurodegenerative disease that is characterized by progressive cognitive decline and a prominent loss of hippocampal-dependent memory. Therefore, much focus has been placed on understanding the function and dysfunction of the hippocampus in AD. However, AD is also accompanied by a number of other debilitating cognitive and behavioral alterations including deficits in attention, cognitive processing, and sleep maintenance. The underlying mechanisms that give rise to impairments in such diverse behavioral domains are unknown, and identifying them would shed insight into the multifactorial nature of AD as well as reveal potential new therapeutic targets to improve overall function in AD. We present here several lines of evidence that suggest that dysregulation of the corticothalamic network may be a common denominator that contributes to the diverse cognitive and behavioral alterations in AD. First, we will review the mechanisms by which this network regulates processes that include attention, cognitive processing, learning and memory, and sleep maintenance. Then we will review how these behavioral and cognitive domains are altered in AD. We will also discuss how dysregulation of tightly regulated activity in the corticothalamic network can give rise to non-convulsive seizures and other forms of epileptiform activity that have also been documented in both AD patients and transgenic mouse models of AD. In summary, the corticothalamic network has the potential to be a master regulator of diverse cognitive and behavioral domains that are affected in AD.
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