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Fonseca CS, Baker SL, Dobyns L, Janabi M, Jagust WJ, Harrison TM. Tau accumulation and atrophy predict amyloid independent cognitive decline in aging. Alzheimers Dement 2024; 20:2526-2537. [PMID: 38334195 PMCID: PMC11032527 DOI: 10.1002/alz.13654] [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: 08/24/2023] [Revised: 11/15/2023] [Accepted: 11/30/2023] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Amyloid beta (Aβ) and tau pathology are cross-sectionally associated with atrophy and cognitive decline in aging and Alzheimer's disease (AD). METHODS We investigated relationships between concurrent longitudinal measures of Aβ (Pittsburgh compound B [PiB] positron emission tomography [PET]), tau (flortaucipir [FTP] PET), atrophy (structural magnetic resonance imaging), episodic memory (EM), and non-memory (NM) in 78 cognitively healthy older adults (OA). RESULTS Entorhinal FTP change was correlated with EM decline regardless of Aβ, but meta-temporal FTP and global PiB change were only associated with EM and NM decline in Aβ+ OA. Voxel-wise analyses revealed significant associations between temporal lobe FTP change and EM decline in all groups. PiB and FTP change were not associated with structural change, suggesting a functional or microstructural mechanism linking these measures to cognitive decline. DISCUSSION Our results show that longitudinal Aβ is linked to cognitive decline only in the presence of elevated Aβ, but longitudinal temporal lobe tau is associated with memory decline regardless of Aβ status. HIGHLIGHTS Entorhinal tau change was associated with memory decline in older adults (OA), regardless of amyloid beta (Aβ). Greater meta-region of interest (ROI) tau change correlated with memory decline in Aβ+ OA. Voxel-wise temporal tau change correlated with memory decline, regardless of Aβ. Meta-ROI tau and global amyloid change correlated with non-memory change in Aβ+ OA. Tau and amyloid accumulation were not associated with structural change in OA.
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Affiliation(s)
- Corrina S. Fonseca
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - Lindsey Dobyns
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Mustafa Janabi
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - William J. Jagust
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Theresa M. Harrison
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
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Yang Z, Kinney JW, Cordes D. Uptake of 18F-AV45 in the Putamen Provides Additional Insights into Alzheimer's Disease beyond the Cortex. Biomolecules 2024; 14:157. [PMID: 38397394 PMCID: PMC10886857 DOI: 10.3390/biom14020157] [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: 11/14/2023] [Revised: 01/09/2024] [Accepted: 01/17/2024] [Indexed: 02/25/2024] Open
Abstract
Cortical uptake in brain amyloid positron emission tomography (PET) is increasingly used for the biological diagnosis of Alzheimer's disease (AD); however, the clinical and biological relevance of the striatum beyond the cortex in amyloid PET scans remains unclear. A total of 513 amyloid-positive participants having 18F-AV45 amyloid PET scans available were included in the analysis. The associations between cognitive scores and striatal uptake were analyzed. The participants were categorized into three groups based on the residual from the linear fitting between 18F-AV45 uptake in the putamen and the cortex in the order of HighP > MidP > LowP group. We then examined the differences between these three groups in terms of clinical diagnosis, APOE genotype, CSF phosphorylated tau (ptau) concentration, hippocampal volume, entorhinal thickness, and cognitive decline rate to evaluate the additional insights provided by the putamen beyond the cortex. The 18F-AV45 uptake in the putamen was more strongly associated with ADAS-cog13 and MoCA scores (p < 0.001) compared to the uptake in the caudate nucleus. Despite comparable cortical uptakes, the HighP group had a two-fold higher risk of being ε4-homozygous or diagnosed with AD dementia compared to the LowP group. These three groups had significantly different CSF ptau concentration, hippocampal volume, entorhinal thickness, and cognitive decline rate. These findings suggest that the assessment of 18F-AV45 uptake in the putamen is of unique value for evaluating disease severity and predicting disease progression.
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Affiliation(s)
- Zhengshi Yang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA;
- Department of Brain Health, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA;
| | - Jefferson W. Kinney
- Department of Brain Health, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA;
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA;
- Department of Brain Health, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA;
- Department of Psychology and Neuroscience, University of Colorado, Boulder, CO 80309, USA
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Frank A, Ismail Z, Wilson M, Gauthier S, Verret L, Hsiung GYR, Borrie M. Health System Change for Alzheimer's Disease-Modifying Therapies in Canada: Beginning the Discussion. Can J Neurol Sci 2023:1-9. [PMID: 38052729 DOI: 10.1017/cjn.2023.322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for 60%-70% of patients with dementia, and it is estimated that over one million Canadians will be living with dementia by 2030. Disease-modifying therapies (DMTs) targeting the underlying pathophysiology of AD are currently in development. Several models have demonstrated that the potential arrival of Alzheimer's DMTs will most likely overwhelm the already-constrained Canadian healthcare system. Canada does not have a strategy to address the extensive requirements of using DMTs, including providing an early diagnosis of AD, confirming DMT eligibility via amyloid biomarkers, and conducting ongoing treatment monitoring. Thus, a multidisciplinary group of experts involved in AD care in Canada gathered to review (1) the current barriers to diagnosis and management of AD; (2) how existing clinic models, including those used in multiple sclerosis (MS), could be applied to address key barriers in AD; and (3) how to design and implement optimal care pathways in the future. The actions outlined in this review will help clinicians and healthcare systems improve readiness to integrate the use of disease-modifying therapies in Alzheimer's disease, if such therapies are approved in Canada.
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Affiliation(s)
- Andrew Frank
- Bruyere Research Institute, and University of Ottawa, Ottawa, ON, Canada
| | - Zahinoor Ismail
- Departments of Psychiatry, Clinical Neurosciences, and Community Health Sciences, Hotchkiss Brain Institute and O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada
| | | | - Serge Gauthier
- McGill Center for Studies in Aging and Dementia Education Program, McGill University, Montreal, QC, Canada
| | - Louis Verret
- Service de Neurologie, Clinique Interdisciplinaire de Mémoire, CHU de Québec-Université Laval, Hôpital Enfant-Jésus, Québec, QC, Canada
| | - Ging-Yuek Robin Hsiung
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Michael Borrie
- Division of Geriatric Medicine, Lawson Health Research Institute, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
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Li M, Li Y, Schindler SE, Yen D, Sutcliffe S, Babulal GM, Benzinger TL, Lenze EJ, Bateman RJ. Design and feasibility of an Alzheimer's disease blood test study in a diverse community-based population. Alzheimers Dement 2023; 19:5387-5398. [PMID: 37204806 PMCID: PMC10657331 DOI: 10.1002/alz.13125] [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: 02/03/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 05/20/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) blood tests are likely to become increasingly important in clinical practice, but they need to be evaluated in diverse groups before use in the general population. METHODS This study enrolled a community-based sample of older adults in the St. Louis, Missouri, USA area. Participants completed a blood draw, Eight-Item Informant Interview to Differentiate Aging and Dementia (AD8® ), Montreal Cognitive Assessment (MoCA), and survey about their perceptions of the blood test. A subset of participants completed additional blood collection, amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), and Clinical Dementia Rating (CDR® ). RESULTS Of the 859 participants enrolled in this ongoing study, 20.6% self-identified as Black or African American. The AD8 and MoCA correlated moderately with the CDR. The blood test was well accepted by the cohort, but it was perceived more positively by White and highly educated individuals. DISCUSSION Studying an AD blood test in a diverse population is feasible and may accelerate accurate diagnosis and implementation of effective treatments. HIGHLIGHTS A diverse group of older adults was recruited to evaluate a blood amyloid test. The enrollment rate was high and the blood test was well accepted by participants. Cognitive impairment screens have moderate performance in a diverse population. Alzheimer's disease blood tests are likely to be feasible for use in real-world settings.
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Affiliation(s)
- Melody Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- The Tracy Family Stable Isotope Labeling Quantitation Center for Neurodegenerative Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- The Tracy Family Stable Isotope Labeling Quantitation Center for Neurodegenerative Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Daniel Yen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Siobhan Sutcliffe
- Department of Surgery – Public Health Sciences, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Ganesh M. Babulal
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Eric J. Lenze
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- The Tracy Family Stable Isotope Labeling Quantitation Center for Neurodegenerative Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
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Telser J, Grossmann K, Wohlwend N, Risch L, Saely CH, Werner P. Phosphorylated tau in Alzheimer's disease. Adv Clin Chem 2023; 116:31-111. [PMID: 37852722 DOI: 10.1016/bs.acc.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
There is a need for blood biomarkers to detect individuals at different Alzheimer's disease (AD) stages because obtaining cerebrospinal fluid-based biomarkers is invasive and costly. Plasma phosphorylated tau proteins (p-tau) have shown potential as such biomarkers. This systematic review was conducted according to the PRISMA guidelines and aimed to determine whether quantification of plasma tau phosphorylated at threonine 181 (p-tau181), threonine 217 (p-tau217) and threonine 231 (p-tau231) is informative in the diagnosis of AD. All p-tau isoforms increase as a function of Aβ-accumulation and discriminate healthy individuals from those at preclinical AD stages with high accuracy. P-tau231 increases earliest, followed by p-tau181 and p-tau217. In advanced stages, all p-tau isoforms are associated with the clinical classification of AD and increase with disease severity, with the greatest increase seen for p-tau217. This is also reflected by a better correlation of p-tau217 with Aβ scans, whereas both, p-tau217 and p-tau181 correlated equally with tau scans. However, at the very advanced stages, p-tau181 begins to plateau, which may mirror the trajectory of the Aβ pathology and indicate an association with a more intermediate risk of AD. Across the AD continuum, the incremental increase in all biomarkers is associated with structural changes in widespread brain regions and underlying cognitive decline. Furthermore, all isoforms differentiate AD from non-AD neurodegenerative disorders, making them specific for AD. Incorporating p-tau181, p-tau217 and p-tau231 in clinical use requires further studies to examine ideal cut-points and harmonize assays.
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Affiliation(s)
- Julia Telser
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Kirsten Grossmann
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Niklas Wohlwend
- Laboratory Dr. Risch, Vaduz, Liechtenstein; Department of Internal Medicine Spital Grabs, Spitalregion Rheintal Werdenberg Sarganserland, Grabs, Switzerland
| | - Lorenz Risch
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein; University Institute of Clinical Chemistry, University Hospital and University of Bern, Inselspital, Bern, Switzerland
| | - Christoph H Saely
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT), Feldkirch, Austria
| | - Philipp Werner
- Department of Neurology, State Hospital of Rankweil, Academic Teaching Hospital, Rankweil, Austria.
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Yesantharao L, Cai Y, Schrack JA, Gross AL, Wang H, Bilgel M, Dougherty R, Simonsick EM, Ferrucci L, Resnick SM, Agrawal Y. Sensory impairment and beta-amyloid deposition in the Baltimore longitudinal study of aging. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12407. [PMID: 37139098 PMCID: PMC10150164 DOI: 10.1002/dad2.12407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 12/19/2022] [Accepted: 01/19/2023] [Indexed: 05/05/2023]
Abstract
Introduction Beta-amyloid (Aβ) plaque deposition is a biomarker of preclinical Alzheimer's disease (AD). Impairments in sensory function are associated with cognitive decline. We sought to investigate the relationship between PET-indicated Aβ deposition and sensory impairment. Methods Using data from 174 participants ≥55 years in the Baltimore Longitudinal Study of Aging, we analyzed associations between sensory impairments and Aβ deposition measured by PET and Pittsburgh Compound B (PiB) mean cortical distribution volume ratio (cDVR). Results The combinations of hearing and proprioceptive impairment and hearing, vision, and proprioceptive impairment, were positively correlated with cDVR (β = 0.087 and p = 0.036, β = 0.110 and p = 0.018, respectively). In stratified analyses of PiB+ participants, combinations of two, three, and four sensory impairments (all involving proprioception) were associated with higher cDVR. Discussion Our findings suggest a relationship between multi-sensory impairment (notably proprioceptive impairment) and Aβ deposition, which could reflect sensory impairment as an indicator or potentially a risk factor for Aβ deposition.
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Affiliation(s)
- Lekha Yesantharao
- Department of Otolaryngology ‐ Head and Neck SurgeryJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Yurun Cai
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Jennifer A. Schrack
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Alden L. Gross
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Hang Wang
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Murat Bilgel
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Ryan Dougherty
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | | | - Luigi Ferrucci
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Susan M. Resnick
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Yuri Agrawal
- Department of Otolaryngology ‐ Head and Neck SurgeryJohns Hopkins School of MedicineBaltimoreMarylandUSA
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7
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Sibilano E, Brunetti A, Buongiorno D, Lassi M, Grippo A, Bessi V, Micera S, Mazzoni A, Bevilacqua V. An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG. J Neural Eng 2023; 20. [PMID: 36745929 DOI: 10.1088/1741-2552/acb96e] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 02/06/2023] [Indexed: 02/08/2023]
Abstract
Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals.Approach. EEG recordings of 17 healthy controls (HCs), 56 subjective cognitive decline (SCD) and 45 mild cognitive impairment (MCI) subjects were acquired at resting state. After preprocessing, we selected sections corresponding to eyes-closed condition. Five different datasets were created by extracting delta, theta, alpha, beta and delta-to-theta frequency bands using bandpass filters. To classify SCDvsMCI and HCvsSCDvsMCI, we propose a framework based on the transformer architecture, which uses multi-head attention to focus on the most relevant parts of the input signals. We trained and validated the model on each dataset with a leave-one-subject-out cross-validation approach, splitting the signals into 10 s epochs. Subjects were assigned to the same class as the majority of their epochs. Classification performances of the transformer were assessed for both epochs and subjects and compared with other DL models.Main results. Results showed that the delta dataset allowed our model to achieve the best performances for the discrimination of SCD and MCI, reaching an Area Under the ROC Curve (AUC) of 0.807, while the highest results for the HCvsSCDvsMCI classification were obtained on alpha and theta with a micro-AUC higher than 0.74.Significance. We demonstrated that DL approaches can support the adoption of non-invasive and economic techniques as EEG to stratify patients in the clinical population at risk for AD. This result was achieved since the attention mechanism was able to learn temporal dependencies of the signal, focusing on the most discriminative patterns, achieving state-of-the-art results by using a deep model of reduced complexity. Our results were consistent with clinical evidence that changes in brain activity are progressive when considering early stages of AD.
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Affiliation(s)
- Elena Sibilano
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy
| | - Antonio Brunetti
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy
| | - Domenico Buongiorno
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy
| | - Michael Lassi
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56025 Pisa, Italy
| | | | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliera Careggi, Florence, Italy
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56025 Pisa, Italy.,Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Alberto Mazzoni
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56025 Pisa, Italy
| | - Vitoantonio Bevilacqua
- Department of Electrical and Information Engineering, Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy
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James SN, Nicholas JM, Lu K, Keshavan A, Lane CA, Parker T, Buchanan SM, Keuss SE, Murray-Smith H, Wong A, Cash DM, Malone IB, Barnes J, Sudre CH, Coath W, Modat M, Ourselin S, Crutch SJ, Kuh D, Fox NC, Schott JM, Richards M. Adulthood cognitive trajectories over 26 years and brain health at 70 years of age: findings from the 1946 British Birth Cohort. Neurobiol Aging 2023; 122:22-32. [PMID: 36470133 PMCID: PMC10564626 DOI: 10.1016/j.neurobiolaging.2022.10.003] [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: 04/17/2020] [Revised: 10/06/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022]
Abstract
Few studies can address how adulthood cognitive trajectories relate to brain health in 70-year-olds. Participants (n = 468, 49% female) from the 1946 British birth cohort underwent 18F-Florbetapir PET/MRI. Cognitive function was measured in childhood (age 8 years) and across adulthood (ages 43, 53, 60-64 and 69 years) and was examined in relation to brain health markers of β-amyloid (Aβ) status, whole brain and hippocampal volume, and white matter hyperintensity volume (WMHV). Taking into account key contributors of adult cognitive decline including childhood cognition, those with greater Aβ and WMHV at age 70 years had greater decline in word-list learning memory in the preceding 26 years, particularly after age 60. In contrast, those with smaller whole brain and hippocampal volume at age 70 years had greater decline in processing search speed, subtly manifest from age 50 years. Subtle changes in memory and processing speed spanning 26 years of adulthood were associated with markers of brain health at 70 years of age, consistent with detectable prodromal cognitive effects in early older age.
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Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK.
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, UK; Department of Medicine, Division of Brain Sciences, Imperial College London
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastien Ourselin
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
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Namsrai T, Ambikairajah A, Cherbuin N. Poorer sleep impairs brain health at midlife. Sci Rep 2023; 13:1874. [PMID: 36725955 PMCID: PMC9892039 DOI: 10.1038/s41598-023-27913-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 01/10/2023] [Indexed: 02/03/2023] Open
Abstract
Sleep is an emerging risk factor for dementia but its association with brain health remains unclear. This study included UK Biobank (n = 29,545; mean age = 54.65) participants at imaging visit with sleep measures and brain scans, and a subset (n = 14,206) with cognitive measures. Multiple linear regression analyses were conducted to study the associations between sleep and brain health. Every additional hour of sleep above 7 h/day was associated with 0.10-0.25% lower brain volumes. In contrast, a negative non-linear association was observed between sleep duration, grey matter, and hippocampal volume. Both longer (> 9 h/day) and shorter sleep (< 6 h/day) durations were associated with lower brain volumes and cognitive measures (memory, reaction time, fluid intelligence). Additionally, daytime dozing was associated with lower brain volumes (grey matter and left hippocampus volume) and lower cognitive measures (reaction time and fluid intelligence). Poor sleep (< 6 h/day, > 9 h/day, daytime dozing) at midlife was associated with lower brain health. Sleep may be an important target to improve brain health into old age and delay the onset of dementia.
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Affiliation(s)
- Tergel Namsrai
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, 54 Mills Road, Canberra, ACT, 2601, Australia
| | - Ananthan Ambikairajah
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, 54 Mills Road, Canberra, ACT, 2601, Australia.,Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, ACT, 2617, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, 54 Mills Road, Canberra, ACT, 2601, Australia.
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10
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Modelling Alzheimer's disease using human brain organoids: current progress and challenges. Expert Rev Mol Med 2022; 25:e3. [PMID: 36517884 DOI: 10.1017/erm.2022.40] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterised by gradual memory loss and declining cognitive and executive functions. AD is the most common cause of dementia, affecting more than 50 million people worldwide, and is a major health concern in society. Despite decades of research, the cause of AD is not well understood and there is no effective curative treatment so far. Therefore, there is an urgent need to increase understanding of AD pathophysiology in the hope of developing a much-needed cure. Dissecting the cellular and molecular mechanisms of AD pathogenesis has been challenging as the most commonly used model systems such as transgenic animals and two-dimensional neuronal culture do not fully recapitulate the pathological hallmarks of AD. The recent advent of three-dimensional human brain organoids confers unique opportunities to study AD in a humanised model system by encapsulating many aspects of AD pathology. In the present review, we summarise the studies of AD using human brain organoids that recapitulate the major pathological components of AD including amyloid-β and tau aggregation, neuroinflammation, mitochondrial dysfunction, oxidative stress and synaptic and circuitry dysregulation. Additionally, the current challenges and future directions of the brain organoids modelling system are discussed.
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11
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Betthauser TJ, Bilgel M, Koscik RL, Jedynak BM, An Y, Kellett KA, Moghekar A, Jonaitis EM, Stone CK, Engelman CD, Asthana S, Christian BT, Wong DF, Albert M, Resnick SM, Johnson SC. Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts. Brain 2022; 145:4065-4079. [PMID: 35856240 PMCID: PMC9679170 DOI: 10.1093/brain/awac213] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 04/24/2022] [Accepted: 05/20/2022] [Indexed: 01/25/2023] Open
Abstract
Alzheimer's disease biomarkers are becoming increasingly important for characterizing the longitudinal course of disease, predicting the timing of clinical and cognitive symptoms, and for recruitment and treatment monitoring in clinical trials. In this work, we develop and evaluate three methods for modelling the longitudinal course of amyloid accumulation in three cohorts using amyloid PET imaging. We then use these novel approaches to investigate factors that influence the timing of amyloid onset and the timing from amyloid onset to impairment onset in the Alzheimer's disease continuum. Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Baltimore Longitudinal Study of Aging (BLSA) and the Wisconsin Registry for Alzheimer's Prevention (WRAP). Amyloid PET was used to assess global amyloid burden. Three methods were evaluated for modelling amyloid accumulation using 10-fold cross-validation and holdout validation where applicable. Estimated amyloid onset age was compared across all three modelling methods and cohorts. Cox regression and accelerated failure time models were used to investigate whether sex, apolipoprotein E genotype and e4 carriage were associated with amyloid onset age in all cohorts. Cox regression was used to investigate whether apolipoprotein E (e4 carriage and e3e3, e3e4, e4e4 genotypes), sex or age of amyloid onset were associated with the time from amyloid onset to impairment onset (global clinical dementia rating ≥1) in a subset of 595 ADNI participants that were not impaired before amyloid onset. Model prediction and estimated amyloid onset age were similar across all three amyloid modelling methods. Sex and apolipoprotein E e4 carriage were not associated with PET-measured amyloid accumulation rates. Apolipoprotein E genotype and e4 carriage, but not sex, were associated with amyloid onset age such that e4 carriers became amyloid positive at an earlier age compared to non-carriers, and greater e4 dosage was associated with an earlier amyloid onset age. In the ADNI, e4 carriage, being female and a later amyloid onset age were all associated with a shorter time from amyloid onset to impairment onset. The risk of impairment onset due to age of amyloid onset was non-linear and accelerated for amyloid onset age >65. These findings demonstrate the feasibility of modelling longitudinal amyloid accumulation to enable individualized estimates of amyloid onset age from amyloid PET imaging. These estimates provide a more direct way to investigate the role of amyloid and other factors that influence the timing of clinical impairment in Alzheimer's disease.
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Affiliation(s)
- Tobey J Betthauser
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging,
National Institutes of Health, Baltimore, MD,
USA
| | - Rebecca L Koscik
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine
and Public Health, Madison, WI, USA
| | - Bruno M Jedynak
- Department of Mathematics and Statistics, Portland State
University, Portland, OR, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging,
National Institutes of Health, Baltimore, MD,
USA
| | - Kristina A Kellett
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
| | - Abhay Moghekar
- Laboratory of Behavioral Neuroscience, National Institute on Aging,
National Institutes of Health, Baltimore, MD,
USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine
and Public Health, Madison, WI, USA
| | - Charles K Stone
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
| | - Corinne D Engelman
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine
and Public Health, Madison, WI, USA
- Department of Population Health Sciences, University of Wisconsin-Madison
School of Medicine and Public Health, Madison,
WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine
and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton
Veterans Hospital, Madison, WI, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of
Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison School of
Medicine and Public Health, Madison, WI, USA
| | - Dean F Wong
- Department of Radiology, Mallinckrodt Institute of Radiology, Neurology,
Psychiatry and Neuroscience, Washington University School of Medicine,
St. Louis, MO, USA
| | - Marilyn Albert
- Department of Neurology, Division of Cognitive Neuroscience, Johns Hopkins
University School of Medicine, Baltimore, MD,
USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging,
National Institutes of Health, Baltimore, MD,
USA
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin
School of Medicine and Public Health, Madison,
WI, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine
and Public Health, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine
and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton
Veterans Hospital, Madison, WI, USA
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Hidisoglu E, Kantar D, Ozdemir S, Yargicoglu P. Cognitive dysfunctions and spontaneous EEG alterations induced by hippocampal amyloid pathology in rats. Adv Med Sci 2022; 67:328-337. [PMID: 36058175 DOI: 10.1016/j.advms.2022.08.003] [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: 03/19/2022] [Revised: 06/13/2022] [Accepted: 08/17/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE We aimed to determine the effects of different doses of amyloid-beta (Aβ) peptide on learning and memory, and whether the changes in brain oscillations induced by dose-dependent accumulation of Aβ could be used as biomarkers to detect early stages of Alzheimer's disease (AD). MATERIAL AND METHODS Male albino Wistar rats aged 3 months were randomly divided into four groups (n = 12/group) obtained by i. h. Injection (to the dorsal hippocampus) of saline or different doses of 0.01 μg/μl, 0.1 μg/μl, and 1 μg/μl of Aβ. After two weeks of recovery period, open field and novel object recognition tests were performed and spontaneous EEG recordings were obtained. Later, hippocampus tissues were collected for Western blot and ELISA analysis. RESULTS A significant decrement in recognition memory was observed in 0.1 μg/μl, and 1 μg/μl injected groups. In addition, Aβ accumulation induced significant decrement of the expression of NeuN, SNAP-25, SYP, and PSD-95 proteins, and led to the increment of GFAP expression in hippocampus. Moreover, we detected remarkable alterations in spontaneous brain activity. The hippocampal Aβ levels were negatively correlated with hippocampal gamma power and positively correlated with hippocampal theta power. Also, we observed significant changes in coherence values, indicating the functional connectivity between different brain regions, after the accumulation of Aβ. Especially, there was a significant correlation between changes in frontohippocampal theta coherence and in frontotemporal theta coherence. CONCLUSIONS Our findings indicate that Aβ peptide induces AD-like molecular changes at certain doses, and these changes could be detected by evaluating brain oscillations.
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Affiliation(s)
- Enis Hidisoglu
- Department of Drug Science and Technology, Turin University, Corso Raffaello 30, 10125, Torino, Italy; Akdeniz University Faculty of Medicine Department of Biophysics, Antalya, Turkey.
| | - Deniz Kantar
- Akdeniz University Faculty of Medicine Department of Biophysics, Antalya, Turkey
| | - Semir Ozdemir
- Akdeniz University Faculty of Medicine Department of Biophysics, Antalya, Turkey
| | - Piraye Yargicoglu
- Akdeniz University Faculty of Medicine Department of Biophysics, Antalya, Turkey
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13
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Studart-Neto A, Coutinho AM. From clinical phenotype to proteinopathy: molecular neuroimaging in neurodegenerative dementias. ARQUIVOS DE NEURO-PSIQUIATRIA 2022; 80:24-35. [PMID: 35976328 PMCID: PMC9491407 DOI: 10.1590/0004-282x-anp-2022-s138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
Neurodegenerative dementias are characterized by the abnormal accumulation of misfolded proteins. However, its diagnostic criteria are still based on the clinical phenotype. The development of biomarkers allowed in vivo detection of pathophysiological processes. This article aims to make a non-systematic review of the use of molecular neuroimaging as a biomarker. Molecular neuroimaging is based on the use of radiotracers for image acquisition. The radiotracer most used in PET is 18F-fluorodeoxyglucose (FDG), with which it is possible to study the regional brain glucose metabolism. The pattern of regional hypometabolism provides neuroanatomical information on the neurodegenerative process, which, in turn, has a good specificity for each type of proteinopathy. FDG is very useful in the differential diagnosis of neurodegenerative dementias through the regional pattern of involvement, including dementia with Lewy bodies and the spectrum of frontotemporal dementia. More recently, radiotracers with specific ligands to some of the pathological proteins have been developed. Pittsburgh compound B (PIB) labeled with 11C and the ligands that use 18F (florbetapir, florbetaben and flutemetamol) are the most used radiotracers for the detection of insoluble β-amyloid peptide in Alzheimer's disease (AD). A first generation of ligands for tau protein has been developed, but it has some affinity for other non-tau protein aggregates. A second generation has the advantage of having a higher affinity for hyperphosphorylated tau protein, including in primary tauopathies.
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Affiliation(s)
- Adalberto Studart-Neto
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo, SP, Brazil
| | - Artur Martins Coutinho
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Radiologia e Oncologia, Divisão e Laboratório de Medicina Nuclear (LIM 43), São Paulo, SP, Brazil
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14
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Barrett-Young A, Ambler A, Cheyne K, Guiney H, Kokaua J, Steptoe B, Tham YC, Wilson GA, Wong TY, Poulton R. Associations Between Retinal Nerve Fiber Layer and Ganglion Cell Layer in Middle Age and Cognition From Childhood to Adulthood. JAMA Ophthalmol 2022; 140:262-268. [PMID: 35142821 PMCID: PMC8832305 DOI: 10.1001/jamaophthalmol.2021.6082] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
IMPORTANCE The retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL) have been proposed as potential biomarkers for Alzheimer disease (AD). Although a number of studies have shown that knowing the thickness of RNFL and GCL can help differentiate between patients with AD and healthy controls, it is unclear whether these associations are observable earlier in life. OBJECTIVE To examine whether RNFL and GCL thickness was associated with global cognitive performance in middle age and in childhood and with a decline in cognitive performance from childhood to adulthood and whether RNFL and GCL thickness was associated with decline in specific cognitive domains over the same period. DESIGN, SETTING, AND PARTICIPANTS This longitudinal cohort study involved members of the Dunedin Multidisciplinary Health and Development Study, a longitudinal representative birth cohort from New Zealand (n = 1037). Participants were born in 1972 to 1973 and followed up until age 45 years, with 94% of the living cohort still participating. MAIN OUTCOMES AND MEASURES Cognitive performance (Full Scale IQ, processing speed, perceptual reasoning, and verbal comprehension) measured at ages 7, 9, and 11 years (mean value) and age 45 years, and RNFL and GCL thickness measured via optical coherence tomography (OCT) at age 45 years. RESULTS Data were analyzed between August 2020 and April 2021. Data from 865 participants were included in the present study (50.2% male, 49.8% female; 92.2% of the 938 study members seen at age 45 years). Of the 73 participants who were excluded, 63 were excluded because of issues with OCT scans and 10 were excluded because of diseases affecting the retina. Thinner RNFL and GCL were associated with lower Full Scale IQ in childhood and at age 45 years. Thinner RNFL was also associated with a greater decline in processing speed from childhood to adulthood. CONCLUSIONS AND RELEVANCE RNFL and GCL thickness in middle age was associated with cognitive performance in childhood and adulthood, and thinner RNFL with a decline in processing speed between childhood and adulthood. These data emphasize the potential utility of OCT measures as biomarkers of cognitive function; however, further longitudinal studies are needed to determine whether retinal thinning precedes cognitive decline and whether other confounding factors may account for this association.
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Affiliation(s)
- Ashleigh Barrett-Young
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Antony Ambler
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Department of Psychology, University of Otago, Dunedin, New Zealand,Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Kirsten Cheyne
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Hayley Guiney
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Jesse Kokaua
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Centre for Pacific Health, Va’a o Tautai, University of Otago, Dunedin, New Zealand
| | - Barbara Steptoe
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Yih Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore,Duke-NUS Medical School, Singapore
| | - Graham A. Wilson
- Department of Medicine, University of Otago, Dunedin, New Zealand
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore,Duke-NUS Medical School, Singapore
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand,Department of Psychology, University of Otago, Dunedin, New Zealand
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15
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Stevens DA, Workman CI, Kuwabara H, Butters MA, Savonenko A, Nassery N, Gould N, Kraut M, Joo JH, Kilgore J, Kamath V, Holt DP, Dannals RF, Nandi A, Onyike CU, Smith GS. Regional amyloid correlates of cognitive performance in ageing and mild cognitive impairment. Brain Commun 2022; 4:fcac016. [PMID: 35233522 PMCID: PMC8882008 DOI: 10.1093/braincomms/fcac016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 12/03/2021] [Accepted: 02/02/2022] [Indexed: 11/13/2022] Open
Abstract
Beta-amyloid deposition is one of the earliest pathological markers associated with Alzheimer's disease. Mild cognitive impairment in the setting of beta-amyloid deposition is considered to represent a preclinical manifestation of Alzheimer's disease. In vivo imaging studies are unique in their potential to advance our understanding of the role of beta-amyloid deposition in cognitive deficits in Alzheimer's disease and in mild cognitive impairment. Previous work has shown an association between global cortical measures of beta-amyloid deposition ('amyloid positivity') in mild cognitive impairment with greater cognitive deficits and greater risk of progression to Alzheimer's disease. The focus of the present study was to examine the relationship between the regional distribution of beta-amyloid deposition and specific cognitive deficits in people with mild cognitive impairment and cognitively normal elderly individuals. Forty-seven participants with multi-domain, amnestic mild cognitive impairment (43% female, aged 57-82 years) and 37 healthy, cognitively normal comparison subjects (42% female, aged 55-82 years) underwent clinical and neuropsychological assessments and high-resolution positron emission tomography with the radiotracer 11C-labelled Pittsburgh compound B to measure beta-amyloid deposition. Brain-behaviour partial least-squares analysis was conducted to identify spatial patterns of beta-amyloid deposition that correlated with the performance on neuropsychological assessments. Partial least-squares analysis identified a single significant (P < 0.001) latent variable which accounted for 80% of the covariance between demographic and cognitive measures and beta-amyloid deposition. Performance in immediate verbal recall (R = -0.46 ± 0.07, P < 0.001), delayed verbal recall (R = -0.39 ± 0.09, P < 0.001), immediate visual-spatial recall (R = -0.39 ± 0.08, P < 0.001), delayed visual-spatial recall (R = -0.45 ± 0.08, P < 0.001) and semantic fluency (R = -0.33 ± 0.11, P = 0.002) but not phonemic fluency (R = -0.05 ± 0.12, P < 0.705) negatively covaried with beta-amyloid deposition in the identified regions. Partial least-squares analysis of the same cognitive measures with grey matter volumes showed similar associations in overlapping brain regions. These findings suggest that the regional distribution of beta-amyloid deposition and grey matter volumetric decreases is associated with deficits in executive function and memory in mild cognitive impairment. Longitudinal analysis of these relationships may advance our understanding of the role of beta-amyloid deposition in relation to grey matter volumetric decreases in cognitive decline.
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Affiliation(s)
- Daniel A. Stevens
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Clifford I. Workman
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Hiroto Kuwabara
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Meryl A. Butters
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Alena Savonenko
- Department of Pathology (Neuropathology), School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Najilla Nassery
- Department of General Internal Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Neda Gould
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Kraut
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jin Hui Joo
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jessica Kilgore
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Vidya Kamath
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Daniel P. Holt
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Robert F. Dannals
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Ayon Nandi
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Chiadi U. Onyike
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Gwenn S. Smith
- Division of Geriatric Psychiatry and Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Division of Nuclear Medicine and Molecular Imaging, Russell H. Morgan Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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Li J, Zheng C, Ge Q, Yan S, Paranjpe MD, Hu S, Zhou Y. Association between long-term donepezil treatment and brain regional amyloid and tau burden among individuals with mild cognitive impairment assessed using 18 F-AV-45 and 18 F-AV-1451 PET. J Neurosci Res 2021; 100:670-680. [PMID: 34882830 DOI: 10.1002/jnr.24995] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 10/16/2021] [Accepted: 11/06/2021] [Indexed: 11/06/2022]
Abstract
This study aims to investigate the association between long-term donepezil treatment and brain neuropathological burden and cognitive function in mild cognitive impairment (MCI) patients. Preprocessed 18 F-AV-45 amyloid and 18 F-AV-1451 tau positron emission tomography (PET) images, magnetic resonance imaging images (MRIs), demographic information, and donepezil use status were downloaded from 255 MCI participants enrolled in the Alzheimer's Disease Neuroimaging Initiative database. Partial volume correction was applied to all PET images. Structural MRIs were used for PET spatial normalization. Regions of interest (ROIs) were defined in standard space, and standardized uptake value ratio (SUVR) images relative to the cerebellum were computed. Multiple linear regression with the least absolute shrinkage selector operator was performed to analyze the effect of long-term donepezil treatment on (a) the SUVR of each 18 F-AV-45 or 18 F-AV-1451 brain PET ROI after adjusting for age, sex, education, ApoE ε4 status, and AD-associated disease risk factors; and (b) cognitive performance after adjusting for age, sex education, ApoE ε4 status, AD-associated disease risk factors, and regional amyloid or tau burden. In adjusted models, long-term donepezil treatment was associated with greater amyloid load in the orbital frontal, superior frontal, parietal, posterior precuneus, posterior cingulate, lateral temporal, inferior temporal and fusiform regions, and tau burden in the posterior cingulate, entorhinal and parahippocampal gyrus. Long-term donepezil treatment was also associated with worse performance on the 13-item Alzheimer's Disease Assessment Scale-Cognitive subscale after adjusting for AD-related risk factors and regional brain amyloid or tau load. These results indicate that long-term donepezil treatment is associated with increased regional amyloid and tau burden and worse cognitive performance among individuals with MCI. Our study highlights the importance of using noninvasive and quantitative 18 F-AV-45 and 18 F-AV-1451 PET to elucidate the consequences of drug administration in AD studies.
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Affiliation(s)
- Jian Li
- Department of Nuclear Medicine (PET Center), Xiangya Hospital Central South University, Changsha, China.,Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Chaojie Zheng
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
| | - Qi Ge
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
| | - Shaozhen Yan
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Manish D Paranjpe
- Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA, USA
| | - Shuo Hu
- Department of Nuclear Medicine (PET Center), Xiangya Hospital Central South University, Changsha, China.,Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital Central South University, Changsha, China
| | - Yun Zhou
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
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17
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Gold BT, Shao X, Sudduth TL, Jicha GA, Wilcock DM, Seago ER, Wang DJ. Water exchange rate across the blood-brain barrier is associated with CSF amyloid-β 42 in healthy older adults. Alzheimers Dement 2021; 17:2020-2029. [PMID: 33949773 PMCID: PMC8717840 DOI: 10.1002/alz.12357] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 03/19/2021] [Accepted: 04/07/2021] [Indexed: 01/21/2023]
Abstract
INTRODUCTION We tested if water exchange across the blood-brain barrier (BBB), estimated with a noninvasive magnetic resonance imaging (MRI) technique, is associated with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and neuropsychological function. METHODS Forty cognitively normal older adults (67-86 years old) were scanned with diffusion-prepared, arterial spin labeling (DP-ASL), which estimates water exchange rate across the BBB (kw ). Participants also underwent CSF draw and neuropsychological testing. Multiple linear regression models were run with kw as a predictor of CSF concentrations and neuropsychological scores. RESULTS In multiple brain regions, BBB kw was positively associated with CSF amyloid beta (Aβ)42 concentration levels. BBB kw was only moderately associated with neuropsychological performance. DISCUSSION Our results suggest that low water exchange rate across the BBB is associated with low CSF Aβ42 concentration. These findings suggest that kw may be a promising noninvasive indicator of BBB Aβ clearance functions, a possibility which should be further tested in future research.
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Affiliation(s)
- Brian T. Gold
- Department of NeuroscienceSanders‐Brown Center on AgingLexingtonKentuckyUSA
- Sanders‐Brown Center on AgingLexingtonKentuckyUSA
- Magnetic Resonance Imaging and Spectroscopy CenterCollege of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT)Mark & Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Gregory A. Jicha
- Sanders‐Brown Center on AgingLexingtonKentuckyUSA
- Department of NeurologySanders‐Brown Center on AgingLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders‐Brown Center on AgingLexingtonKentuckyUSA
- Department of PhysiologySanders‐Brown Center on AgingLexingtonKentuckyUSA
| | - Elayna R. Seago
- Department of NeuroscienceSanders‐Brown Center on AgingLexingtonKentuckyUSA
| | - Danny J.J. Wang
- Laboratory of FMRI Technology (LOFT)Mark & Mary Stevens Neuroimaging and Informatics InstituteKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of NeurologyKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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18
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Duarte-Abritta B, Sánchez SM, Abulafia C, Gustafson DR, Vázquez S, Sevlever G, Castro MN, Fiorentini L, Villarreal MF, Guinjoan SM. Amyloid and anatomical correlates of executive functioning in middle-aged offspring of patients with late-onset Alzheimer's disease. Psychiatry Res Neuroimaging 2021; 316:111342. [PMID: 34365076 DOI: 10.1016/j.pscychresns.2021.111342] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/02/2021] [Accepted: 06/18/2021] [Indexed: 12/13/2022]
Abstract
A traditional hallmark of cognitive impairment associated with late-onset Alzheimer´s disease (LOAD) is episodic memory impairment. However, early alterations have been identified in brain regions associated with executive function in asymptomatic, middle-age offspring of patients with LOAD (O-LOAD) compared to those with no family history. We hypothesized that executive function among O-LOAD would correlate with structural and amyloid brain imaging differently from those without a family history of LOAD (control subjects, CS). Executive function, cortical thickness, and in-vivo Aβ deposits were quantified in 30 O-LOAD and 25 CS. Associations were observed among O-LOAD only. Cortical thickness in the left lateral orbitofrontal cortex was positively associated with Design Fluency. The Stroop Color and Word Test, correlated positively with right rostral mid-frontal cortex thickness. Trails Making Test-B was inversely related to left medial orbitofrontal thickness. Tower of London total time was positively associated with β-amyloid deposition in the right precuneus. These results support previous evidence that early executive dysfunction might reflect subtle, early changes in persons at risk of LOAD and suggests that executive function alterations deserve further exploration in the LOAD literature.
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Affiliation(s)
- Bárbara Duarte-Abritta
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Stella-Maris Sánchez
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Departamento de Física, Facultad de Cs. Exactas y Naturales, Universidad de Buenos Aires, Argentina
| | - Carolina Abulafia
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Institute for Biomedical Research (BIOMED), Pontifical Catholic University of Argentina, Buenos Aires, Argentina
| | - Deborah R Gustafson
- Department of Neurology, State University of New York University Downstate Health Sciences University, United States
| | - Silvia Vázquez
- Centro de imágenes moleculares (CIM), Fundación FLENI, Argentina
| | - Gustavo Sevlever
- Departamento de Neuropatología y Biología Molecular, Fundación FLENI, Buenos Aires, Argentina
| | - Mariana N Castro
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires, Argentina; Servicio de Psiquiatría, Fundación FLENI, Buenos Aires, Argentina
| | - Leticia Fiorentini
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Servicio de Psiquiatría, Fundación FLENI, Buenos Aires, Argentina
| | - Mirta F Villarreal
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Departamento de Física, Facultad de Cs. Exactas y Naturales, Universidad de Buenos Aires, Argentina
| | - Salvador M Guinjoan
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Departamento de Fisiología, Facultad de Medicina, Universidad de Buenos Aires, Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires, Argentina; Neurofisiología I, Facultad de Psicología, Universidad de Buenos Aires, Argentina; Laureate Institute for Brain Research, OK, United States.
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19
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Collij LE, Mastenbroek SE, Salvadó G, Wink AM, Visser PJ, Barkhof F, van Berckel BN, Lopes Alves I. Regional amyloid accumulation predicts memory decline in initially cognitively unimpaired individuals. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12216. [PMID: 34368416 PMCID: PMC8327468 DOI: 10.1002/dad2.12216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 05/04/2021] [Accepted: 06/04/2021] [Indexed: 01/02/2023]
Abstract
INTRODUCTION The value of quantitative longitudinal and regional amyloid beta (Aβ) measurements in predicting cognitive decline in initially cognitively unimpaired (CU) individuals remains to be determined. METHODS We selected 133 CU individuals with two or more [11C]Pittsburgh compound B ([11C]PiB) scans and neuropsychological data from Open Access Series of Imaging Studies (OASIS-3). Baseline and annualized distribution volume ratios were computed for a global composite and four regional clusters. The predictive value of Aβ measurements (baseline, slope, and interaction) on longitudinal cognitive performance was examined. RESULTS Global performance could only be predicted by Aβ burden in an early cluster (precuneus, lateral orbitofrontal, and insula) and the precuneus region of interest (ROI) by itself significantly improved the model. Precuneal Aβ burden was also predictive of immediate and delayed episodic memory performance. In Aβ subjects at baseline (N = 93), lateral orbitofrontal Aβ burden predicted working and semantic memory performance. DISCUSSION Quantifying longitudinal and regional changes in Aβ can improve the prediction of cognitive functioning in initially CU individuals.
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Affiliation(s)
- Lyduine E. Collij
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Sophie E. Mastenbroek
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
| | - Alle Meije Wink
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Pieter Jelle Visser
- Amsterdam UMCAlzheimer Center and department of NeurologyVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Frederik Barkhof
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
- Medical Physics and Biomedical EngineeringCentre for Medical Image ComputingUCLLondonUK
| | - Bart. N.M. van Berckel
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Isadora Lopes Alves
- Amsterdam UMCDepartment of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdamNetherlands
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20
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Lagarde J, Olivieri P, Bottlaender M, Sarazin M. Diagnosi clinicolaboratoristica della malattia di Alzheimer. Neurologia 2021. [DOI: 10.1016/s1634-7072(21)45320-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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21
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Costa M, Páez A. Emerging insights into the role of albumin with plasma exchange in Alzheimer's disease management. Transfus Apher Sci 2021; 60:103164. [PMID: 34083161 DOI: 10.1016/j.transci.2021.103164] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative process that inexorably leads to progressive deterioration of cognition function and, ultimately, death. Central pathophysiologic features of AD include the accumulation of extracellular plaques comprised of amyloid-β peptide (Aβ) and the presence of intraneuronal neurofibrillary tangles. However, a large body of evidence suggests that oxidative stress and inflammation are major contributors to the pathogenesis and progression of AD. To date, available pharmacologic treatments are only symptomatic. Clinical trials focused on amyloid and non-amyloid-targeted treatments with small molecule pharmacotherapy and immunotherapies have accumulated a long list of failures. Considering that around 90 % of the circulating Aβ is bound to albumin, and that a dynamic equilibrium exists between peripheral and central Aβ, plasma exchange with albumin replacement has emerged as a new approach in a multitargeted AD therapeutic strategy (AMBAR Program). In plasma exchange, a patient's plasma is removed by plasmapheresis to eliminate toxic endogenous substances, including Aβ and functionally impaired albumin. The fluid replacement used is therapeutic albumin, which acts not only as a plasma volume expander but also has numerous pleiotropic functions (e.g., circulating Aβ- binding capacity, transporter, detoxifier, antioxidant) that are clinically relevant for the treatment of AD. Positive results from the AMBAR Program (phase 1, 2, an 2b/3 trials), i.e., slower decline or stabilization of disease symptoms in the most relevant clinical efficacy and safety endpoints, offer a glimmer of hope to both AD patients and caregivers.
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Affiliation(s)
| | - Antonio Páez
- Alzheimer's Research Group, Grifols, Barcelona, Spain.
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22
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Opwonya J, Doan DNT, Kim SG, Kim JI, Ku B, Kim S, Park S, Kim JU. Saccadic Eye Movement in Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review and Meta-Analysis. Neuropsychol Rev 2021; 32:193-227. [PMID: 33959887 PMCID: PMC9090874 DOI: 10.1007/s11065-021-09495-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 03/01/2021] [Indexed: 11/30/2022]
Abstract
Alzheimer’s disease (AD) is the leading cause of dementia, and mild cognitive impairment (MCI) is considered the transitional state to AD dementia (ADD) and other types of dementia, whose symptoms are accompanied by altered eye movement. In this work, we reviewed the existing literature and conducted a meta-analysis to extract relevant eye movement parameters that are significantly altered owing to ADD and MCI. We conducted a systematic review of 35 eligible original publications in saccade paradigms and a meta-analysis of 27 articles with specified task conditions, which used mainly gap and overlap conditions in both prosaccade and antisaccade paradigms. The meta-analysis revealed that prosaccade and antisaccade latencies and frequency of antisaccade errors showed significant alterations for both MCI and ADD. First, both prosaccade and antisaccade paradigms differentiated patients with ADD and MCI from controls, however, antisaccade paradigms was more effective than prosaccade paradigms in distinguishing patients from controls. Second, during prosaccade in the gap and overlap conditions, patients with ADD had significantly longer latencies than patients with MCI, and the trend was similar during antisaccade in the gap condition as patients with ADD had significantly more errors than patients with MCI. The anti-effect magnitude was similar between controls and patients, and the magnitude of the latency of the gap effect varied among healthy controls and MCI and ADD subjects, but the effect size of the latency remained large in both patients. These findings suggest that, using gap effect, anti-effect, and specific choices of saccade paradigms and conditions, distinctions could be made between MCI and ADD patients as well as between patients and controls.
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Affiliation(s)
- Julius Opwonya
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
- Korean Convergence Medicine, University of Science and Technology, Daejeon, Republic of Korea
| | - Dieu Ni Thi Doan
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
- Korean Convergence Medicine, University of Science and Technology, Daejeon, Republic of Korea
| | - Seul Gee Kim
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Joong Il Kim
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Boncho Ku
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Soochan Kim
- Department of Electrical and Electronic Engineering, Hankyong National University, Anseong, Republic of Korea
| | - Sunju Park
- Department of Preventive Medicine, College of Korean Medicine, Daejeon University, Daejeon, Republic of Korea.
| | - Jaeuk U Kim
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea.
- Korean Convergence Medicine, University of Science and Technology, Daejeon, Republic of Korea.
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23
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Kim CM, Montal V, Diez I, Orwig W, Sepulcre J. Network interdigitations of Tau and amyloid-beta deposits define cognitive levels in aging. Hum Brain Mapp 2021; 42:2990-3004. [PMID: 33955621 PMCID: PMC8193537 DOI: 10.1002/hbm.25350] [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: 07/31/2020] [Revised: 12/16/2020] [Accepted: 01/11/2021] [Indexed: 12/18/2022] Open
Abstract
Amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles are pathological hallmarks of Alzheimer's disease (AD); their contribution to neurodegeneration and clinical manifestations are critical in understanding preclinical AD. At present, the mechanisms related to Aβ and tau pathogenesis leading to cognitive decline in older adults remain largely unknown. Here, we examined graph theory‐based positron emission tomography (PET) analytical approaches, within and between tau and Aβ PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aβ and tau deposits, along with cognitive test scores in CN at both baseline and 2‐year follow‐up (FU). We found highly significant Aβ‐tau network integrations in AD vulnerable areas, as well as significant associations between those Aβ‐tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aβ and tau deposits in heteromodal areas of the human brain. They support a network‐based interaction between Aβ and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia.
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Affiliation(s)
- Chan-Mi Kim
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Victor Montal
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centro de Investigacón Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - William Orwig
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | | | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
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24
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Lam S, Lipton RB, Harvey DJ, Zammit AR, Ezzati A. White matter hyperintensities and cognition across different Alzheimer's biomarker profiles. J Am Geriatr Soc 2021; 69:1906-1915. [PMID: 33891712 DOI: 10.1111/jgs.17173] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 03/15/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND/OBJECTIVES To examine the association between white matter hyperintensities (WMH) and cognitive domains such as memory and executive function (EF) across different clinical and biomarker categories of Alzheimer's disease (AD). DESIGN Cross-sectional study. SETTING Alzheimer's Disease Neuroimaging Initiative. PARTICIPANTS A total of 216 cognitively normal (CN) participants and 407 participants with mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) at baseline. MEASUREMENTS Based on the 2018 research framework, participants were classified using AT(N) (amyloid-β deposition [A], pathologic tau [T], and neurodegeneration [(N)]) biomarkers into one of three categories: biomarker negative [A - T- (N)-], amyloid negative but other biomarker positive [A - T ± (N)+ or A - T + (N)±] or amyloid positive [A + T ± (N)±]. Linear regression models were then used to examine the association between WMH and memory composite scores and EF composite scores. RESULTS Higher WMH burden was associated with worse EF in both CN and MCI subgroups while a significant association between WMH and memory was only found in the MCI subgroup. Furthermore, WMH was associated with EF in the group with A - T ± (N)+ or A - T + (N)± biomarker category, but not for A - T - (N)- (normal biomarker) and A + T ± (N) ± (AD pathology). The association between higher WMH and worse memory was independent of amyloid levels in individuals with MCI with evidence of AD pathology. CONCLUSION Vascular disease, as indexed by WMH, independent of AD pathology affects cognitive function in both CN and MCI subgroups. Future studies using the AT(N) research framework should consider white matter lesions as a key biomarker contributing to the clinical presentation of AD.
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Affiliation(s)
- Sharon Lam
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Richard B Lipton
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA.,Department of Neurology, Montefiore Medical Center, Bronx, New York, USA.,Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Danielle J Harvey
- Department of Public Health Sciences, University of California-Davis, Davis, California, USA
| | - Andrea R Zammit
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Ali Ezzati
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA.,Department of Neurology, Montefiore Medical Center, Bronx, New York, USA
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25
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Abstract
This article presents an overview of imaging agents for PET that have been applied for research and diagnostic purposes in patients affected by dementia. Classified by the target which the agents visualize, seven groups of tracers can be distinguished, namely radiopharmaceuticals for: (1) Misfolded proteins (ß-amyloid, tau, α-synuclein), (2) Neuroinflammation (overexpression of translocator protein), (3) Elements of the cholinergic system, (4) Elements of monoamine neurotransmitter systems, (5) Synaptic density, (6) Cerebral energy metabolism (glucose transport/ hexokinase), and (7) Various other proteins. This last category contains proteins involved in mechanisms underlying neuroinflammation or cognitive impairment, which may also be potential therapeutic targets. Many receptors belong to this category: AMPA, cannabinoid, colony stimulating factor 1, metabotropic glutamate receptor 1 and 5 (mGluR1, mGluR5), opioid (kappa, mu), purinergic (P2X7, P2Y12), sigma-1, sigma-2, receptor for advanced glycation endproducts, and triggering receptor expressed on myeloid cells-1, besides several enzymes: cyclooxygenase-1 and 2 (COX-1, COX-2), phosphodiesterase-5 and 10 (PDE5, PDE10), and tropomyosin receptor kinase. Significant advances in neuroimaging have been made in the last 15 years. The use of 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) for quantification of regional cerebral glucose metabolism is well-established. Three tracers for ß-amyloid plaques have been approved by the Food and Drug Administration and European Medicines Agency. Several tracers for tau neurofibrillary tangles are already applied in clinical research. Since many novel agents are in the preclinical or experimental stage of development, further advances in nuclear medicine imaging can be expected in the near future. PET studies with established tracers and tracers for novel targets may result in early diagnosis and better classification of neurodegenerative disorders and in accurate monitoring of therapy trials which involve these targets. PET data have prognostic value and may be used to assess the response of the human brain to interventions, or to select the appropriate treatment strategy for an individual patient.
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Affiliation(s)
- Aren van Waarde
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, Groningen, the Netherlands.
| | - Sofia Marcolini
- University of Groningen, University Medical Center Groningen, Department of Neurology, Groningen, the Netherlands
| | - Peter Paul de Deyn
- University of Groningen, University Medical Center Groningen, Department of Neurology, Groningen, the Netherlands; University of Antwerp, Born-Bunge Institute, Neurochemistry and Behavior, Campus Drie Eiken, Wilrijk, Belgium
| | - Rudi A J O Dierckx
- University of Groningen, University Medical Center Groningen, Department of Nuclear Medicine and Molecular Imaging, Groningen, the Netherlands; Ghent University, Ghent, Belgium
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26
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Abstract
Amyloid-β (Aβ) PET imaging has now been available for over 15 years. The ability to detect Aβ in vivo has greatly improved the clinical and research landscape of Alzheimer's disease (AD) and other neurodegenerative conditions. Aβ imaging provides very reliable, accurate, and reproducible measurements of regional and global Aβ burden in the brain. It has proved invaluable in anti-Aβ therapy trials, and is now recognized as a powerful diagnostic tool. The appropriate use of Aβ PET, when combined with comprehensive clinical evaluation by a dementia-trained specialist, can improve the accuracy of a clinical diagnosis of AD and substantially alter management. It can assist in differentiating AD from other neurodegenerative conditions, often by its ability to rule out the presence of Aβ. When combined with tau imaging, further increase in specificity for the diagnosis of AD can be achieved. The integration of Aβ PET, in conjunction with biomarkers of tau, neurodegeneration and neuroinflammation, into large, longitudinal, observational cohort studies continues to increase our understanding of the development of AD. Its incorporation into clinical trials has been pivotal in defining the most effective anti-Aβ biological therapies and optimal dosing so that effective disease modifying therapy now appears imminent. Aβ deposition is a gradual and protracted process, permitting a wide treatment window for anti-Aβ therapies and Aβ PET has made trials in this preclinical AD period feasible. Continuing improvement in Aβ tracer target to background ratio is allowing trials in earlier AD that tailor drug dosage to Aβ level. The quest to standardize quantification and define universally applicable thresholds for all Aβ tracers has produced the Centiloid method. Centiloid values that correlate well with neuropathologic findings and prognosis have been identified. Rapid cloud-based automated individual scan analysis is now possible and does not require MRI. Challenges remain, particularly around cross camera standardized uptake value ratio variation that need to be addressed. This review will compare available Aβ radiotracers, discuss approaches to quantification, as well as the clinical and research applications of Aβ PET.
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Affiliation(s)
- Natasha Krishnadas
- Florey Department of Neurosciences and Mental Health, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victoria, Australia; Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia
| | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia; Health and Biosecurity Flagship, The Australian eHealth Research Centre, CSIRO, Victoria, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Victoria, Australia; The Australian Dementia Network (ADNeT), Melbourne, Australia; The University of Melbourne, Victoria, Australia.
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27
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Winer JR, Mander BA, Kumar S, Reed M, Baker SL, Jagust WJ, Walker MP. Sleep Disturbance Forecasts β-Amyloid Accumulation across Subsequent Years. Curr Biol 2020; 30:4291-4298.e3. [PMID: 32888482 PMCID: PMC7642104 DOI: 10.1016/j.cub.2020.08.017] [Citation(s) in RCA: 94] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/08/2020] [Accepted: 08/05/2020] [Indexed: 12/13/2022]
Abstract
Experimental sleep-wake disruption in rodents and humans causally modulates β-amyloid (Aβ) dynamics (e.g., [1-3]). This leads to the hypothesis that, beyond cross-sectional associations, impaired sleep structure and physiology could represent prospective biomarkers of the speed with which Aβ accumulates over time. Here, we test the hypothesis that initial baseline measures of non-rapid eye movement (NREM) sleep slow-wave activity (SWA) and sleep quality (efficiency) provide future forecasting sensitivity to the rate of Aβ accumulation over subsequent years. A cohort of clinically normal older adults was assessed using objective sleep polysomnography in combination with longitudinal tracking of Aβ accumulation with [11C]PiB positron emission tomography (PET) imaging. Both the proportion of NREM SWA below 1 Hz and the measure of sleep efficiency predicted the speed (slope) of subsequent Aβ deposition over time, and these associations remained robust when taking into account additional cofactors of interest (e.g., age, sex, sleep apnea). Moreover, these measures were specific, such that no other macro- and microphysiological architecture metrics of sleep demonstrated such sensitivity. Our data support the proposal that objective sleep markers could be part of a set of biomarkers that statistically forecast the longitudinal trajectory of cortical Aβ deposition in the human brain. Sleep may therefore represent a potentially affordable, scalable, repeatable, and non-invasive tool for quantifying of Aβ pathological progression, prior to cognitive symptoms of Alzheimer's disease (AD).
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Affiliation(s)
- Joseph R Winer
- Center for Human Sleep Science, Department of Psychology, University of California, Berkeley, Berkeley Way West, Berkeley, CA 94720, USA
| | - Bryce A Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine, 101 The City Drive, Orange, CA 92697, USA
| | - Samika Kumar
- Center for Human Sleep Science, Department of Psychology, University of California, Berkeley, Berkeley Way West, Berkeley, CA 94720, USA
| | - Mark Reed
- Center for Human Sleep Science, Department of Psychology, University of California, Berkeley, Berkeley Way West, Berkeley, CA 94720, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
| | - William J Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, 132 Barker Hall, Berkeley, CA 94720, USA
| | - Matthew P Walker
- Center for Human Sleep Science, Department of Psychology, University of California, Berkeley, Berkeley Way West, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, 132 Barker Hall, Berkeley, CA 94720, USA.
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28
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Raghavan NS, Dumitrescu L, Mormino E, Mahoney ER, Lee AJ, Gao Y, Bilgel M, Goldstein D, Harrison T, Engelman CD, Saykin AJ, Whelan CD, Liu JZ, Jagust W, Albert M, Johnson SC, Yang HS, Johnson K, Aisen P, Resnick SM, Sperling R, De Jager PL, Schneider J, Bennett DA, Schrag M, Vardarajan B, Hohman TJ, Mayeux R. Association Between Common Variants in RBFOX1, an RNA-Binding Protein, and Brain Amyloidosis in Early and Preclinical Alzheimer Disease. JAMA Neurol 2020; 77:1288-1298. [PMID: 32568366 PMCID: PMC7309575 DOI: 10.1001/jamaneurol.2020.1760] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/06/2020] [Indexed: 01/27/2023]
Abstract
Importance Genetic studies of Alzheimer disease have focused on the clinical or pathologic diagnosis as the primary outcome, but little is known about the genetic basis of the preclinical phase of the disease. Objective To examine the underlying genetic basis for brain amyloidosis in the preclinical phase of Alzheimer disease. Design, Setting, and Participants In the first stage of this genetic association study, a meta-analysis was conducted using genetic and imaging data acquired from 6 multicenter cohort studies of healthy older individuals between 1994 and 2019: the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study, the Berkeley Aging Cohort Study, the Wisconsin Registry for Alzheimer's Prevention, the Biomarkers of Cognitive Decline Among Normal Individuals cohort, the Baltimore Longitudinal Study of Aging, and the Alzheimer Disease Neuroimaging Initiative, which included Alzheimer disease and mild cognitive impairment. The second stage was designed to validate genetic observations using pathologic and clinical data from the Religious Orders Study and Rush Memory and Aging Project. Participants older than 50 years with amyloid positron emission tomographic (PET) imaging data and DNA from the 6 cohorts were included. The largest cohort, the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study (n = 3154), was the PET screening cohort used for a secondary prevention trial designed to slow cognitive decline associated with brain amyloidosis. Six smaller, longitudinal cohort studies (n = 1160) provided additional amyloid PET imaging data with existing genetic data. The present study was conducted from March 29, 2019, to February 19, 2020. Main Outcomes and Measures A genome-wide association study of PET imaging amyloid levels. Results From the 4314 analyzed participants (age, 52-96 years; 2478 participants [57%] were women), a novel locus for amyloidosis was noted within RBFOX1 (β = 0.61, P = 3 × 10-9) in addition to APOE. The RBFOX1 protein localized around plaques, and reduced expression of RBFOX1 was correlated with higher amyloid-β burden (β = -0.008, P = .002) and worse cognition (β = 0.007, P = .006) during life in the Religious Orders Study and Rush Memory and Aging Project cohort. Conclusions and Relevance RBFOX1 encodes a neuronal RNA-binding protein known to be expressed in neuronal tissues and may play a role in neuronal development. The findings of this study suggest that RBFOX1 is a novel locus that may be involved in the pathogenesis of Alzheimer disease.
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Affiliation(s)
- Neha S. Raghavan
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- The Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Elizabeth Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
| | - Emily R. Mahoney
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Annie J. Lee
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
| | - Yizhe Gao
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - David Goldstein
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
| | - Theresa Harrison
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Corinne D. Engelman
- Department of Population Health Sciences, University of Wisconsin, School of Medicine and Public Health, Madison
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, School of Medicine, Indiana University, Indianapolis
- Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis
| | | | - Jimmy Z. Liu
- Research and Early Development, Biogen Inc, Cambridge, Massachusetts
| | - William Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Sterling C. Johnson
- Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison
| | - Hyun-Sik Yang
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Keith Johnson
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Reisa Sperling
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Philip L. De Jager
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York
- Cell Circuits Program, Broad Institute, Cambridge, Massachusetts
| | - Julie Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Matthew Schrag
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Badri Vardarajan
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- The Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Richard Mayeux
- Department of Neurology, Columbia University Medical Center, New York, New York
- Department of Neurology, The New York Presbyterian Hospital, New York
- Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University Medical Center, New York, New York
- The Institute for Genomic Medicine, Columbia University Medical Center, New York, New York
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Hedderich DM, Drost R, Goldhardt O, Ortner M, Müller-Sarnowski F, Diehl-Schmid J, Zimmer C, Förstl H, Yakushev I, Jahn T, Grimmer T. Regional Cerebral Associations Between Psychometric Tests and Imaging Biomarkers in Alzheimer's Disease. Front Psychiatry 2020; 11:793. [PMID: 32903760 PMCID: PMC7438836 DOI: 10.3389/fpsyt.2020.00793] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 07/23/2020] [Indexed: 11/23/2022] Open
Abstract
Recently, imaging biomarkers have gained importance for the characterization of patients with Alzheimer's disease; however, the relationship between regional biomarker expression and cognitive function remains unclear. In our study, we investigated associations between scores on CERAD neuropsychological assessment battery (CERAD-NAB) subtests with regional glucose metabolism, cortical thickness and amyloid deposition in patients with early Alzheimer's disease (AD) using [18F]-fluorodeoxyglucose (FDG), structural MRI, and 11C-Pittsburgh Compound B (PiB) positron emission tomography (PET), respectively. A total of 76 patients (mean age 68.4 ± 8.5 years, 57.9% male) with early AD (median global clinical dementia rating (CDR) score = 0.5, range: 0.5-2.0) were studied. Associations were investigated by correlation and multiple regression analyses. Scores on cognitive subtests were most closely predicted by regional glucose metabolism with explained variance up to a corrected R² of 0.518, followed by cortical thickness and amyloid deposition. Prediction of cognitive subtest performance was increased up to a corrected R² of 0.622 for Word List-Delayed Recall, when biomarker information from multiple regions and multiple modalities were included. For verbal, visuoconstructive and mnestic domains the closest associations with FDG-PET imaging were found in the left lateral temporal lobe, right parietal lobe, and posterior cingulate cortex, respectively. Decreased cortical thickness in parietal regions was most predictive of impaired subtest performance. Remarkably, cerebral amyloid deposition significantly predicted cognitive function in about half of the subtests but with smaller extent of variance explained (corrected R² ≤ 0.220). We conclude that brain metabolism and atrophy affect cognitive performance in a regionally distinct way. Significant predictions of cognitive function by PiB-PET in half of CERAD-NAB subtests suggest functional relevance even in symptomatic patients with AD, challenging the concept of plateauing cortical amyloid deposition early in the disease course. Our results underscore the complex spatial relationship between different imaging biomarkers.
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Affiliation(s)
- Dennis M. Hedderich
- Department of Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - René Drost
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Oliver Goldhardt
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marion Ortner
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Felix Müller-Sarnowski
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Hans Förstl
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Igor Yakushev
- TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Nuclear Medicine, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Thomas Jahn
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
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30
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Kauppi K, Rönnlund M, Nordin Adolfsson A, Pudas S, Adolfsson R. Effects of polygenic risk for Alzheimer's disease on rate of cognitive decline in normal aging. Transl Psychiatry 2020; 10:250. [PMID: 32709845 PMCID: PMC7381667 DOI: 10.1038/s41398-020-00934-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 06/24/2020] [Accepted: 07/09/2020] [Indexed: 12/11/2022] Open
Abstract
Most people's cognitive abilities decline with age, with significant and partly genetically driven, individual differences in rate of change. Although APOE ɛ4 and genetic scores for late-onset Alzheimer's disease (LOAD) have been related to cognitive decline during preclinical stages of dementia, there is limited knowledge concerning genetic factors implied in normal cognitive aging. In the present study, we examined three potential genetic predictors of age-related cognitive decline as follows: (1) the APOE ɛ4 allele, (2) a polygenic score for general cognitive ability (PGS-cog), and (3) a polygenic risk score for late-onset AD (PRS-LOAD). We examined up to six time points of cognitive measurements in the longitudinal population-based Betula study, covering a 25-year follow-up period. Only participants that remained alive and non-demented until the most recent dementia screening (1-3 years after the last test occasion) were included (n = 1087). Individual differences in rate of cognitive change (composite score) were predicted by the PRS-LOAD and APOE ɛ4, but not by PGS-cog. To control for the possibility that the results reflected a preclinical state of Alzheimer's disease in some participants, we re-ran the analyses excluding cognitive data from the last test occasion to model cognitive change up-until a minimum of 6 years before potential onset of clinical Alzheimers. Strikingly, the association of PRS-LOAD, but not APOE ɛ4, with cognitive change remained. The results indicate that PRS-LOAD predicts individual difference in rate of cognitive decline in normal aging, but it remains to be determined to what extent this reflects preclinical Alzheimer's disease brain pathophysiology and subsequent risk to develop the disease.
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Affiliation(s)
- Karolina Kauppi
- Department of Integrative Medical Biologi, Umeå University, Umeå, Sweden. .,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Michael Rönnlund
- grid.12650.300000 0001 1034 3451Department of Psychology, Umeå University, Umeå, Sweden
| | | | - Sara Pudas
- grid.12650.300000 0001 1034 3451Department of Integrative Medical Biologi, Umeå University, Umeå, Sweden
| | - Rolf Adolfsson
- grid.12650.300000 0001 1034 3451Department of Clinical Sciences, Umeå University, Umeå, Sweden
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31
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Yu L, Petyuk VA, Tasaki S, Boyle PA, Gaiteri C, Schneider JA, De Jager PL, Bennett DA. Association of Cortical β-Amyloid Protein in the Absence of Insoluble Deposits With Alzheimer Disease. JAMA Neurol 2020; 76:818-826. [PMID: 31009033 DOI: 10.1001/jamaneurol.2019.0834] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Importance β-Amyloid deposits are a pathologic hallmark of Alzheimer disease (AD). However, the extent to which cortical β-amyloid protein in the absence of insoluble deposits is associated with classic features of AD appear to be unknown. Objective To examine the associations of cortical β-amyloid protein in the absence of insoluble deposits with cognitive decline, neurofibrillary tangles, other age-associated neuropathologic conditions, and APOE. Design, Setting, and Participants This analysis combines data from 2 community-based clinicopathologic cohort studies of aging. The Religious Orders Study started in 1994, and the Rush Memory and Aging Project started in 1997. Both studies are ongoing. Participants without known dementia were enrolled and agreed to annual clinical evaluations and brain donation after death. Primary analyses focused on individuals without β-amyloid deposits. Data analyses occurred in mid-September 2018. Main Outcomes and Measures β-Amyloid protein abundance was measured by targeted proteomics using selected reaction monitoring. β-Amyloid deposits were detected using immunohistochemistry. Other neuropathologic indices were quantified via uniform structured evaluation. Linear mixed models were used to examine the association of β-amyloid protein with cognitive decline. Regression models examined the protein associations with neuropathologic outcomes and the APOE genotype. Results By mid-September 2018, 3575 older persons were enrolled, and 1559 had died and undergone brain autopsy. Proteomic data were collected in 1208 individuals, and 5 with missing cognitive scores were excluded. Of the remaining 1203, primary analyses focused on 148 individuals (12.3%) without β-amyloid deposits. In this group, the mean (SD) age at death was 87.0 (7.0) years, and 84 individuals (56.8%) were women. In the absence of β-amyloid deposits, we did not observe an association of β-amyloid protein with decline in episodic memory, but the protein was associated with faster rates of decline in processing speed (mean [SE] change, -0.014 [0.005]; P = .008) and visuospatial abilities (mean [SE] change, -0.013 [0.005]; P = .006). We did not observe protein association with paired helical filament tau tangle density. The protein was associated with amyloid angiopathy (odds ratio, 1.38 [95% CI, 1.15-1.67]; P < .001) but no other brain pathology. The associations with cognitive decline were unchanged after controlling for amyloid angiopathy. Neither APOE ε4 nor a polygenic Alzheimer risk score was associated with β-amyloid protein. Conclusions and Relevance Cortical β-amyloid protein was associated with faster cognitive decline in the absence of β-amyloid deposits, which supports the role of cortical soluble β-amyloid as a neurotoxic agent in aging. The lack of protein association with paired helical filament tau tangles, episodic memory decline, or strong genetic drivers of deposited β-amyloid suggests an underlying neuropathologic change that may differ from that of AD.
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Affiliation(s)
- Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | | | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | - Patricia A Boyle
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois.,Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois.,Department of Pathology, Rush University Medical Center, Chicago, Illinois
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, New York, New York.,Cell Circuits Program, Broad Institute, Cambridge, Massachusetts
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
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32
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Li L, Wu DH, Li HQ, Tan L, Xu W, Dong Q, Tan L, Yu JT. Association of Cerebral Microbleeds with Cognitive Decline: A Longitudinal Study. J Alzheimers Dis 2020; 75:571-579. [PMID: 32310166 DOI: 10.3233/jad-191257] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Lin Li
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Dan-Hong Wu
- Department of Neurology, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Hong-Qi Li
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lin Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei Xu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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33
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Rentz DM, Papp KV. Commentary on Composite cognitive and functional measures for early stage Alzheimer's disease trials. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12012. [PMID: 33521233 PMCID: PMC7819348 DOI: 10.1002/dad2.12012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Revised: 02/03/2020] [Accepted: 02/03/2020] [Indexed: 11/29/2022]
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Beta-amyloid (Aβ) uptake by PET imaging in older HIV+ and HIV- individuals. J Neurovirol 2020; 26:382-390. [PMID: 32270469 DOI: 10.1007/s13365-020-00836-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 02/13/2020] [Accepted: 02/24/2020] [Indexed: 10/24/2022]
Abstract
The causes of cognitive impairment among older HIV+ individuals may overlap with causes among elderly HIV seronegative (HIV-) individuals. The objective of this study was to determine if beta-amyloid (Aβ) deposition measured by [18F] AV-45 (florbetapir) positron emission tomography (PET) is increased in older HIV+ individuals compared to HIV- individuals. Forty-eight HIV+ and 25 HIV- individuals underwent [18F] AV-45 PET imaging. [18F] AV-45 binding to Aβ was measured by standardized uptake value ratios (SUVR) relative to the cerebellum in 16 cortical and subcortical regions of interest. Global and regional cortical SUVRs were compared by (1) serostatus, (2) HAND stage, and (3) age decade, comparing individuals in their 50s and > 60s. There were no differences in median global cortical SUVR stratified by HIV serostatus or HAND stage. The proportion of HIV+ participants in their 50s with elevated global amyloid uptake (SUVR > 1.40) was significantly higher than the proportion in HIV- participants (67% versus 25%, p = 0.04), and selected regional SUVR values were also higher (p < 0.05) in HIV+ compared to HIV- participants in their 50s. However, these group differences were not seen in participants in their 60s. In conclusion, PET imaging found no differences in overall global Aβ deposition stratified by HIV serostatus or HAND stage. Although there was some evidence of increased Aβ deposition in HIV+ individuals in their 50s compared to HIV- individuals which might indicate premature aging, the most parsimonious explanation for this is the relatively small sample size in this cross-sectional cohort study.
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Guo T, Landau SM, Jagust WJ. Detecting earlier stages of amyloid deposition using PET in cognitively normal elderly adults. Neurology 2020; 94:e1512-e1524. [PMID: 32188766 PMCID: PMC7251521 DOI: 10.1212/wnl.0000000000009216] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 11/14/2019] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To examine the feasibility of using cross-sectional PET to identify cognitive decliners among β-amyloid (Aβ)-negative cognitively normal (CN) elderly adults. METHODS We determined the highest Aβ-affected region by ranking baseline and accumulation rates of florbetapir-PET regions in 355 CN elderly adults using 18F-florbetapir-PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The banks of the superior temporal sulcus (BANKSSTS) were found as the highest Aβ-affected region, and Aβ positivity in this region was defined as above the lowest boundary of BANKSSTS standardized uptake value ratio of Aβ+ (ADNI-defined COMPOSITE region) CN individuals. The entire CN cohort was divided as follows: stage 0, BANKSSTS-COMPOSITE-; stage 1, BANKSSTS+COMPOSITE-; and stage 2, BANKSSTS+COMPOSITE+. Linear mixed-effect (LME) models investigated subsequent longitudinal cognitive change, and 18F-flortaucipir (FTP)-PET was measured 4.8 ± 1.6 years later to track tau deposition. RESULTS LME analysis revealed that individuals in stage 1 (n = 64) and stage 2 (n = 99) showed 2.5 (p < 0.05) and 4.8 (p < 0.001) times faster memory decline, respectively, than those in stage 0 (n = 191) over >4 years of mean follow-up. Compared to stage 0, both stage 1 (p < 0.05) and stage 2 (p < 0.001) predicted higher FTP in entorhinal cortex. CONCLUSIONS Nominally Aβ- CN individuals with high Aβ in BANKSSTS are at increased risk of cognitive decline, probably showing an earlier stage of Aβ deposition. Our findings may help elucidate the association between brain Aβ accumulation and cognition in Aβ- CN cohorts. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in elderly CN individuals those with high PET-identified superior temporal sulcus Aβ burden have an increased risk of cognitive decline.
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Affiliation(s)
- Tengfei Guo
- From the Helen Wills Neuroscience Institute (T.G., S.M.L., W.J.J.), University of California; and Molecular Biophysics and Integrated Bioimaging (T.G., S.M.L., W.J.J.), Lawrence Berkeley National Laboratory, CA.
| | - Susan M Landau
- From the Helen Wills Neuroscience Institute (T.G., S.M.L., W.J.J.), University of California; and Molecular Biophysics and Integrated Bioimaging (T.G., S.M.L., W.J.J.), Lawrence Berkeley National Laboratory, CA
| | - William J Jagust
- From the Helen Wills Neuroscience Institute (T.G., S.M.L., W.J.J.), University of California; and Molecular Biophysics and Integrated Bioimaging (T.G., S.M.L., W.J.J.), Lawrence Berkeley National Laboratory, CA
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Lin C, Ly M, Karim HT, Wei W, Snitz BE, Klunk WE, Aizenstein HJ. The effect of amyloid deposition on longitudinal resting-state functional connectivity in cognitively normal older adults. Alzheimers Res Ther 2020; 12:7. [PMID: 31907079 PMCID: PMC6945413 DOI: 10.1186/s13195-019-0573-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 12/23/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND Pathological processes contributing to Alzheimer's disease begin decades prior to the onset of clinical symptoms. There is significant variation in cognitive changes in the presence of pathology, functional connectivity may be a marker of compensation to amyloid; however, this is not well understood. METHODS We recruited 64 cognitively normal older adults who underwent neuropsychological testing and biannual magnetic resonance imaging (MRI), amyloid imaging with Pittsburgh compound B (PiB)-PET, and glucose metabolism (FDG)-PET imaging for up to 6 years. Resting-state MRI was used to estimate connectivity of seven canonical neural networks using template-based rotation. Using voxel-wise paired t-tests, we identified neural networks that displayed significant changes in connectivity across time. We investigated associations among amyloid and longitudinal changes in connectivity and cognitive function by domains. RESULTS Left middle frontal gyrus connectivity within the memory encoding network increased over time, but the rate of change was lower with greater amyloid. This was no longer significant in an analysis where we limited the sample to only those with two time points. We found limited decline in cognitive domains overall. Greater functional connectivity was associated with better attention/processing speed and executive function (independent of time) in those with lower amyloid but was associated with worse function with greater amyloid. CONCLUSIONS Increased functional connectivity serves to preserve cognitive function in normal aging and may fail in the presence of pathology consistent with compensatory models.
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Affiliation(s)
- Chemin Lin
- Department of Psychiatry, Keelung Chang Chung Memorial Hospital, Keelung, Taiwan
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Ly
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wenjing Wei
- The Third Xiangya Hospital of Central South University, Changsha, Hunan, China
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Western Psychiatric Institute and Clinic, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
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Yee E, Popuri K, Beg MF. Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score. Hum Brain Mapp 2020; 41:5-16. [PMID: 31507022 PMCID: PMC7268066 DOI: 10.1002/hbm.24783] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 07/27/2019] [Accepted: 08/18/2019] [Indexed: 01/31/2023] Open
Abstract
18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). The AD pathology is progressive, and leads to structural and functional alterations that lie on a continuum. There is a need to quantify the altered metabolism patterns that exist on a continuum into a simple measure. This work proposes a 3D convolutional neural network with residual connections that generates a probability score useful for interpreting the FDG-PET images along the continuum of AD. This network is trained and tested on images of stable normal control and stable Dementia of the Alzheimer's type (sDAT) subjects, achieving an AUC of 0.976 via repeated fivefold cross-validation. An independent test set consisting of images in between the two extreme ends of the DAT spectrum is used to further test the generalization performance of the network. Classification performance of 0.811 AUC is achieved in the task of predicting conversion of mild cognitive impairment to DAT for conversion time of 0-3 years. The saliency and class activation maps, which highlight the regions of the brain that are most important to the classification task, implicate many known regions affected by DAT including the posterior cingulate cortex, precuneus, and hippocampus.
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Affiliation(s)
- Evangeline Yee
- School of Engineering ScienceSimon Fraser UniversityBurnabyBCCanada
| | - Karteek Popuri
- School of Engineering ScienceSimon Fraser UniversityBurnabyBCCanada
| | - Mirza Faisal Beg
- School of Engineering ScienceSimon Fraser UniversityBurnabyBCCanada
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Karim HT, Tudorascu DL, Cohen A, Price JC, Lopresti B, Mathis C, Klunk W, Snitz BE, Aizenstein HJ. Relationships Between Executive Control Circuit Activity, Amyloid Burden, and Education in Cognitively Healthy Older Adults. Am J Geriatr Psychiatry 2019; 27:1360-1371. [PMID: 31402087 PMCID: PMC7047647 DOI: 10.1016/j.jagp.2019.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 07/01/2019] [Accepted: 07/15/2019] [Indexed: 11/30/2022]
Abstract
INTRODUCTION In cognitively healthy older adults, amyloid-beta (Aβ) burden is associated with greater activity on task-based functional magnetic resonance imaging. Higher levels of functional activation are associated with other factors along with amyloid and the authors investigated these relationships as well as how they relate to Aβ in cognitively healthy older adults. METHODS The authors recruited cognitive healthy older adults (N = 50) from the Pittsburgh community that underwent extensive cognitive batteries, activation during a working memory (digit symbol substitution task, DSST), positron emission tomography scan for Pittsburgh Compound B (PiB, measuring amyloid), and other demographic measures. The authors tested the association between DSST activation and global PiB, neurocognitive batteries, and education. RESULTS The authors found that the DSST robustly activated expected structures involved in working memory. The authors found that greater global Aβ deposition was associated with greater DSST activation in the right calcarine, precuneus, middle temporal as well as the left insula and inferior frontal gyrus. The authors also found that greater education was associated with lower DSST activation - however this was not significant after adjusting for Aβ. DISCUSSION Greater amyloid was associated with greater activation, which may represent compensatory activation. Greater education was associated with lower activation, which may represent more efficient activation (i.e., less activation for the same task). After adjusting for amyloid, education was not significantly associated with activation suggesting that during the preclinical stage amyloid is the primary determinant of activation. Further, activation was not associated with cognitive function. Compensatory activation in the preclinical stage may help maintain cognitive function.
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Affiliation(s)
| | | | - Ann Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - Julie C. Price
- Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Brian Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - Chester Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - William Klunk
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA,Department of Neurology, University of Pittsburgh, Pittsburgh, PA
| | - Beth E. Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
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39
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Gallagher M, Okonkwo OC, Resnick SM, Jagust WJ, Benzinger TLS, Rapp PR. What are the threats to successful brain and cognitive aging? Neurobiol Aging 2019; 83:130-134. [PMID: 31732016 PMCID: PMC6859944 DOI: 10.1016/j.neurobiolaging.2019.04.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Accepted: 04/23/2019] [Indexed: 12/11/2022]
Abstract
The structure and function of the brain change over the life span. Aged brains often accumulate pathologic lesions, such as amyloid plaques and tau tangles, which lead to diminished cognitive ability in some, but not all, individuals. The basis of this vulnerability and resilience is unclear. Age-related changes can alter neural firing patterns and ability to form new memories. Risk factors for cognitive decline include male sex and apolipoprotein E genotype. Physical activity seems to be protective against cognitive decline. Longitudinal studies have shown that, although the onset of amyloid pathology and associated cognitive decline can vary greatly, once it begins, the rate of deposition is similar among affected individuals. This session of the Cognitive Aging Summit III explored fixed and modifiable factors that can threaten cognitive function in aging adults and approaches to modulate at least some of these risks.
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Affiliation(s)
- Michela Gallagher
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Ozioma C Okonkwo
- Department of Medicine and Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Peter R Rapp
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA.
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40
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Musaeus CS, Engedal K, Høgh P, Jelic V, Mørup M, Naik M, Oeksengaard AR, Snaedal J, Wahlund LO, Waldemar G, Andersen BB. Oscillatory connectivity as a diagnostic marker of dementia due to Alzheimer’s disease. Clin Neurophysiol 2019; 130:1889-1899. [DOI: 10.1016/j.clinph.2019.07.016] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 05/26/2019] [Accepted: 07/03/2019] [Indexed: 12/27/2022]
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41
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Lowe AJ, Paquola C, Vos de Wael R, Girn M, Lariviere S, Tavakol S, Caldairou B, Royer J, Schrader DV, Bernasconi A, Bernasconi N, Spreng RN, Bernhardt BC. Targeting age-related differences in brain and cognition with multimodal imaging and connectome topography profiling. Hum Brain Mapp 2019; 40:5213-5230. [PMID: 31444896 PMCID: PMC6864903 DOI: 10.1002/hbm.24767] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/29/2019] [Accepted: 08/05/2019] [Indexed: 02/06/2023] Open
Abstract
Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open‐access healthy cohort (n = 102, age range = 30–89 years) with MRI and Aβ PET data, we estimated age‐related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface‐based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting‐state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory‐motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long‐axis. While age‐related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher‐order transmodal regions. Age‐related atrophy was greater toward the posterior end of the hippocampal long‐axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography‐specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain‐based biomarkers of aging.
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Affiliation(s)
- Alexander J Lowe
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Manesh Girn
- Laboratory of Brain and Cognition, Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Sara Lariviere
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Dewi V Schrader
- Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - R Nathan Spreng
- Laboratory of Brain and Cognition, Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.,Department of Psychiatry and Psychology, McGill University, Montreal, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
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42
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McDonough IM, Letang SK, Stinson EA. Dementia Risk Elevates Brain Activity During Memory Retrieval: A Functional MRI Analysis of Middle Aged and Older Adults. J Alzheimers Dis 2019; 70:1005-1023. [DOI: 10.3233/jad-190035] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Ian M. McDonough
- Department of Psychology, The University of Alabama, Tuscaloosa, AL, USA
| | - Sarah K. Letang
- Department of Psychology, The University of Alabama, Tuscaloosa, AL, USA
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43
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Gomez G, Beason-Held LL, Bilgel M, An Y, Wong DF, Studenski S, Ferrucci L, Resnick SM. Metabolic Syndrome and Amyloid Accumulation in the Aging Brain. J Alzheimers Dis 2019; 65:629-639. [PMID: 30103324 DOI: 10.3233/jad-180297] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Recent studies show links between metabolic syndrome and Alzheimer's disease (AD) neuropathology. Understanding the link between vascular-related health conditions and dementia will help target at risk populations and inform clinical strategies for early detection and prevention of AD. OBJECTIVE To determine whether metabolic syndrome is associated with global cerebral amyloid-β (Aβ) positivity and longitudinal Aβ accumulation. METHODS Prospective study of 165 participants who underwent (11)C-Pittsburgh compound B (PiB) PET neuroimaging to measure Aβ, from June 2005 to May 2016. Metabolic syndrome was defined using the revised Third Adults Treatment Panel of the National Cholesterol Education Program criteria. Participants were classified as PiB+/-. Linear mixed effects models assessed the relationships between baseline metabolic syndrome and PiB status and regional Aβ change over time. RESULTS A total of 165 cognitively normal participants of the Baltimore Longitudinal Study of Aging (BLSA) Neuroimaging substudy, aged 55-92 years (mean baseline age = 76.4 years, 85 participants were male), received an average of 2.5 PET-PiB scans over an average interval of 2.6 (3.08 SD) years between first and last visits. Metabolic syndrome was not associated with baseline PiB positivity or concurrent regional Aβ. Metabolic syndrome was associated with increased rates of Aβ accumulation in superior parietal and precuneus regions over time in the PiB+ group. Elevated fasting glucose and blood pressure showed individual associations with accelerated Aβ accumulation. CONCLUSION Metabolic syndrome was associated with accelerated Aβ accumulation in PiB+ individuals and may be an important factor in the progression of AD pathology.
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Affiliation(s)
- Gabriela Gomez
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Lori L Beason-Held
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Murat Bilgel
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Yang An
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Dean F Wong
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Stephanie Studenski
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Luigi Ferrucci
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Susan M Resnick
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
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44
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Yeung LK, Hale C, Last BS, Andrews H, Sloan RP, Honig LS, Small SA, Brickman AM. Cerebrospinal fluid amyloid levels are associated with delayed memory retention in cognitively normal biomarker-negative older adults. Neurobiol Aging 2019; 84:90-97. [PMID: 31520793 DOI: 10.1016/j.neurobiolaging.2019.08.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 08/07/2019] [Accepted: 08/11/2019] [Indexed: 01/22/2023]
Abstract
Alzheimer's disease is defined by abnormal levels of amyloid and tau biomarkers. Even cognitively normal older adults with clinically relevant amyloid and tau levels perform worse on memory tests. However, it is unclear if the relationship between biomarker level and memory extends below clinical thresholds. We hypothesized that even subclinical biomarker levels are associated with memory when measured with neuropsychological tests designed to detect dysfunction in preclinical disease states. In a group of cognitively normal, "biomarker-negative" older men and women, we investigated the relationship between cerebrospinal fluid biomarker levels and memory measured with the ModRey, a list-learning task designed to assess memory in preclinical and cognitively normal adults. Cerebrospinal amyloid levels were associated with ModRey memory retention, the proportion of information retained after a delay period. When older adults with mild impairment were included, cerebrospinal fluid tau levels were also associated with ModRey retention. The association of amyloid and tau levels with memory was independent of each other. These results suggest cognitive changes associated with Alzheimer's disease pathology might occur earlier than currently thought.
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Affiliation(s)
- Lok-Kin Yeung
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Christiane Hale
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Briana S Last
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Howard Andrews
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Richard P Sloan
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Lawrence S Honig
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Scott A Small
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Radiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA.
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45
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Musaeus CS, Engedal K, Høgh P, Jelic V, Mørup M, Naik M, Oeksengaard AR, Snaedal J, Wahlund LO, Waldemar G, Andersen BB. EEG Theta Power Is an Early Marker of Cognitive Decline in Dementia due to Alzheimer's Disease. J Alzheimers Dis 2019; 64:1359-1371. [PMID: 29991135 DOI: 10.3233/jad-180300] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Quantitative EEG (qEEG) power could potentially be used as a diagnostic tool for Alzheimer's disease (AD) and may further our understanding of the pathophysiology. However, the early qEEG power changes of AD are not well understood. OBJECTIVE To investigate the early changes in qEEG power and the possible correlation with memory function and cerebrospinal fluid biomarkers. In addition, whether qEEG power could discriminate between AD, mild cognitive impairment (MCI), and older healthy controls (HC) at the individual level. METHODS Standard EEGs from 138 HC, 117 MCI, and 117 AD patients were included from six Nordic memory clinics. All EEGs were recorded consecutively before the diagnosis and were not used for the consensus diagnosis. Absolute and relative power was calculated for both eyes closed and open condition. RESULTS At group level using relative power, we found significant increases globally in the theta band and decreases in high frequency power in the temporal regions for eyes closed for AD and, to a lesser extent, for MCI compared to HC. Relative theta power was significantly correlated with multiple neuropsychological measures and had the largest correlation coefficient with total tau. At the individual level, the classification rate for AD and HC was 72.9% for relative power with eyes closed. CONCLUSION Our findings suggest that the increase in relative theta power may be the first change in patients with dementia due to AD. At the individual level, we found a moderate classification rate for AD and HC when using EEGs alone.
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Affiliation(s)
- Christian Sandøe Musaeus
- Department of Neurology, Danish Dementia Research Centre (DDRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Knut Engedal
- Norwegian National Advisory Unit on Ageing and Health (Ageing and Health), Vestfold Hospital Trust and Oslo University Hospital, Ullevaal, Oslo, Norway
| | - Peter Høgh
- Regional Dementia Research Center, Department of Neurology, Zealand University Hospital, Roskilde, Denmark and Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Vesna Jelic
- Department of Neurobiology, Division of Clinical Geriatrics, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital-Huddinge, Sweden
| | - Morten Mørup
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Lyngby, Denmark
| | - Mala Naik
- Department of Geriatric Medicine, Haraldsplass Deaconess Hospital, Bergen, Norway
| | - Anne-Rita Oeksengaard
- Department of Neurobiology, Division of Clinical Geriatrics, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Jon Snaedal
- Department of Geriatric Medicine, Landspítali University Hospital, Reykjavik, Iceland
| | - Lars-Olof Wahlund
- Department of Neurobiology, Division of Clinical Geriatrics, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Gunhild Waldemar
- Department of Neurology, Danish Dementia Research Centre (DDRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Birgitte Bo Andersen
- Department of Neurology, Danish Dementia Research Centre (DDRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
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46
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Wolf D, Fischer FU, Fellgiebel A. Impact of Resilience on the Association Between Amyloid-β and Longitudinal Cognitive Decline in Cognitively Healthy Older Adults. J Alzheimers Dis 2019; 70:361-370. [DOI: 10.3233/jad-190370] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Dominik Wolf
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany
- Center for Mental Health in Old Age, Mainz, Germany
| | - Florian U. Fischer
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany
- Center for Mental Health in Old Age, Mainz, Germany
| | - Andreas Fellgiebel
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany
- Center for Mental Health in Old Age, Mainz, Germany
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Bilgel M, An Y, Helphrey J, Elkins W, Gomez G, Wong DF, Davatzikos C, Ferrucci L, Resnick SM. Effects of amyloid pathology and neurodegeneration on cognitive change in cognitively normal adults. Brain 2019; 141:2475-2485. [PMID: 29901697 DOI: 10.1093/brain/awy150] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 04/15/2018] [Indexed: 11/13/2022] Open
Abstract
Understanding short-term cognitive decline in relation to Alzheimer's neuroimaging biomarkers in early stages of the development of neuropathology and neurodegeneration will inform participant recruitment and monitoring strategies in clinical trials aimed at prevention of cognitive impairment and dementia. We assessed associations among neuroimaging measures of cerebral amyloid pathology, a hallmark Alzheimer's neuropathology, hippocampal atrophy, and prospective cognition among 171 cognitively normal Baltimore Longitudinal Study of Aging participants (baseline age 56-95 years, 48% female, 562 cognitive assessments, 3.7 years follow-up). We categorized each individual based on dichotomous amyloid pathology (A) and hippocampal neurodegeneration (N) status at baseline: A-N-, A+N-, A-N+, A+N+. We conducted linear mixed effects analyses to assess cross-sectional and longitudinal trends in cognitive test z-scores by amyloid and neurodegeneration group. To investigate the effects of amyloid dose and degree of hippocampal atrophy, we assessed the associations of continuous mean cortical amyloid level and hippocampal volume with cognitive performance among individuals with detectable amyloid pathology at baseline. Individuals with amyloidosis or hippocampal atrophy had steeper longitudinal declines in verbal episodic memory and learning compared to those with neither condition (A+N- versus A-N-: β = - 0.069, P = 0.017; A-N+ versus A-N-: β = - 0.081, P = 0.025). Among individuals with hippocampal atrophy, amyloid positivity was associated with steeper declines in verbal memory (β = - 0.123, P = 0.015), visual memory (β = - 0.121, P = 0.036), language (β = - 0.144, P = 0.0004), and mental status (β = - 0.242, P = 0.002). Similarly, among individuals with amyloidosis, hippocampal atrophy was associated with steeper declines in verbal memory (β = - 0.135, P = 0.004), visual memory (β = - 0.141, P = 0.010), language (β = - 0.108, P = 0.006), and mental status (β = - 0.165, P = 0.022). Presence of both amyloidosis and hippocampal atrophy was associated with greater declines than would be expected by their additive contributions in visual memory (β = - 0.139, P = 0.036), language (β = - 0.132, P = 0.005), and mental status (β = - 0.170, P = 0.049). Neither amyloidosis nor hippocampal atrophy was predictive of declines in executive function, processing speed, or visuospatial ability. Among individuals with amyloidosis, higher baseline amyloid level was associated with lower concurrent visual memory, steeper declines in language, visuospatial ability, and mental status, whereas greater hippocampal atrophy was associated with steeper declines in category fluency. Our results suggest that both amyloid pathology and neurodegeneration have disadvantageous, in part synergistic, effects on prospective cognition. These cognitive effects are detectable early among cognitively normal individuals with amyloidosis, who are in preclinical stages of Alzheimer's disease according to research criteria. Our findings highlight the importance of early intervention to target both amyloidosis and atrophy to preserve cognitive function before further damage occurs.
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Affiliation(s)
- Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Jessica Helphrey
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Wendy Elkins
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Gabriela Gomez
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Dean F Wong
- Section of High Resolution PET Imaging, Division of Nuclear Medicine, Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Neurology and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
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48
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Liu M, Paranjpe MD, Zhou X, Duy PQ, Goyal MS, Benzinger TL, Lu J, Wang R, Zhou Y. Sex modulates the ApoE ε4 effect on brain tau deposition measured by 18F-AV-1451 PET in individuals with mild cognitive impairment. Theranostics 2019; 9:4959-4970. [PMID: 31410194 PMCID: PMC6691387 DOI: 10.7150/thno.35366] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Accepted: 05/20/2019] [Indexed: 01/25/2023] Open
Abstract
The strongest genetic risk factor for Alzheimer's disease (AD) is the Apolipoprotein E type 4 allele (ApoE ε4). The interaction between sex and ApoE ε4 carrier status on AD risk remains an area of intense investigation. We hypothesized that sex modulates the relationship between ApoE ε4 carrier status and brain tau deposition (a quantitative endophenotype in AD) in individuals with mild cognitive impairment (MCI). Methods: Preprocessed 18F-AV-1451 tau and 18F-AV-45 amyloid PET images, T1-weighted structural magnetic resonance imaging (MRI) scans, demographic information, and cerebrospinal fluid (CSF) total tau (t-tau) and phosphorylated tau (p-tau) measurements from 108 MCI subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were included. After downloading pre-processed images from ADNI, an iterative reblurred Van Cittertiteration partial volume correction (PVC) method was applied to all PET images. MRIs were used for PET spatial normalization. Regions of interest (ROIs) were defined in standard space, and standardized uptake value ratio (SUVR) images relative to cerebellum were computed. ApoE ε4 by sex interaction analyses on 18F-AV-1451 and CSF tau (t-tau, p-tau) were assessed using generalized linear models. The association between 18F-AV-1451 SUVR and CSF tau (t-tau, p-tau) was assessed. Results: After applying PVC and controlling for age, education level and global cortical 18F-AV-45 SUVR, we found that the entorhinal cortex, amygdala, parahippocampal gyrus, posterior cingulate, and occipital ROIs exhibited a significant ApoE ε4 by sex interaction effect (false discovery rate P < 0.1) among MCI individuals. We also found a significant ApoE ε4 by sex interaction effect on CSF t-tau and p-tau. 18F-AV-1451 SUVR in the 5 ROIs with ApoE ε4 by sex interaction was significantly correlated with CSF p-tau and t-tau. Conclusions: Our findings suggest that women are more susceptible to ApoE ε4-associated accumulation of neurofibrillary tangles in MCI compared to males. Both CSF tau (p-tau, t-tau) and brain tau PET are robust quantitative biomarkers for studying ApoE ε4 by sex effects on brain tau deposition in MCI participants.
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Mormino EC, Papp KV. Amyloid Accumulation and Cognitive Decline in Clinically Normal Older Individuals: Implications for Aging and Early Alzheimer's Disease. J Alzheimers Dis 2019; 64:S633-S646. [PMID: 29782318 DOI: 10.3233/jad-179928] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The aberrant accumulation of the amyloid protein is a critical and early event in the Alzheimer's disease (AD) cascade. Given the early involvement of this pathological process, it is not surprising that many clinically normal (CN) older individuals demonstrate evidence of abnormal Aβ at postmortem examination and in vivo using either CSF or PET imaging. Converging evidence across multiple research groups suggests that the presence of abnormal Aβ among CN individuals is associated with elevated risk of future clinical impairment and cognitive decline. Amyloid positivity in conjunction with biomarkers of neuronal injury offers further insight into which CN are most at risk for short-term decline. Although in its infancy, tau PET has demonstrated early increases among Aβ+ that will likely be an important indicator of risk among CN. Overall, the detection of early Aβ among CN individuals has provided an important opportunity to understand the contributions of this pathology to age-related cognitive decline and to explore early intervention with disease modifying strategies.
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Affiliation(s)
- Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Kathryn V Papp
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Ryan L, Hay M, Huentelman MJ, Duarte A, Rundek T, Levin B, Soldan A, Pettigrew C, Mehl MR, Barnes CA. Precision Aging: Applying Precision Medicine to the Field of Cognitive Aging. Front Aging Neurosci 2019; 11:128. [PMID: 31231204 PMCID: PMC6568195 DOI: 10.3389/fnagi.2019.00128] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 05/16/2019] [Indexed: 12/13/2022] Open
Abstract
The current "one size fits all" approach to our cognitive aging population is not adequate to close the gap between cognitive health span and lifespan. In this review article, we present a novel model for understanding, preventing, and treating age-related cognitive impairment (ARCI) based on concepts borrowed from precision medicine. We will discuss how multiple risk factors can be classified into risk categories because of their interrelatedness in real life, the genetic variants that increase sensitivity to, or ameliorate, risk for ARCI, and the brain drivers or common mechanisms mediating brain aging. Rather than providing a definitive model of risk for ARCI and cognitive decline, the Precision Aging model is meant as a starting point to guide future research. To that end, after briefly discussing key risk categories, genetic risks, and brain drivers, we conclude with a discussion of steps that must be taken to move the field forward.
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Affiliation(s)
- Lee Ryan
- Department of Psychology, College of Science, University of Arizona, Tucson, AZ, United States
| | - Meredith Hay
- Department of Physiology, University of Arizona, Tucson, AZ, United States
| | - Matt J. Huentelman
- Neurobehavioral Research Unit, Division of Neurological Disorders, Translational Genomics Research Institute (TGen), Phoenix, AZ, United States
| | - Audrey Duarte
- Center for Advanced Brain Imaging, School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States
| | - Tatjana Rundek
- Clinical and Translational Research Division, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Bonnie Levin
- Neuropsychology Division, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Anja Soldan
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Corinne Pettigrew
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Matthias R. Mehl
- Department of Psychology, College of Science, University of Arizona, Tucson, AZ, United States
| | - Carol A. Barnes
- Department of Psychology, College of Science, University of Arizona, Tucson, AZ, United States
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