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Arleo A, Bareš M, Bernard JA, Bogoian HR, Bruchhage MMK, Bryant P, Carlson ES, Chan CCH, Chen LK, Chung CP, Dotson VM, Filip P, Guell X, Habas C, Jacobs HIL, Kakei S, Lee TMC, Leggio M, Misiura M, Mitoma H, Olivito G, Ramanoël S, Rezaee Z, Samstag CL, Schmahmann JD, Sekiyama K, Wong CHY, Yamashita M, Manto M. Consensus Paper: Cerebellum and Ageing. CEREBELLUM (LONDON, ENGLAND) 2024; 23:802-832. [PMID: 37428408 PMCID: PMC10776824 DOI: 10.1007/s12311-023-01577-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Given the key roles of the cerebellum in motor, cognitive, and affective operations and given the decline of brain functions with aging, cerebellar circuitry is attracting the attention of the scientific community. The cerebellum plays a key role in timing aspects of both motor and cognitive operations, including for complex tasks such as spatial navigation. Anatomically, the cerebellum is connected with the basal ganglia via disynaptic loops, and it receives inputs from nearly every region in the cerebral cortex. The current leading hypothesis is that the cerebellum builds internal models and facilitates automatic behaviors through multiple interactions with the cerebral cortex, basal ganglia and spinal cord. The cerebellum undergoes structural and functional changes with aging, being involved in mobility frailty and related cognitive impairment as observed in the physio-cognitive decline syndrome (PCDS) affecting older, functionally-preserved adults who show slowness and/or weakness. Reductions in cerebellar volume accompany aging and are at least correlated with cognitive decline. There is a strongly negative correlation between cerebellar volume and age in cross-sectional studies, often mirrored by a reduced performance in motor tasks. Still, predictive motor timing scores remain stable over various age groups despite marked cerebellar atrophy. The cerebello-frontal network could play a significant role in processing speed and impaired cerebellar function due to aging might be compensated by increasing frontal activity to optimize processing speed in the elderly. For cognitive operations, decreased functional connectivity of the default mode network (DMN) is correlated with lower performances. Neuroimaging studies highlight that the cerebellum might be involved in the cognitive decline occurring in Alzheimer's disease (AD), independently of contributions of the cerebral cortex. Grey matter volume loss in AD is distinct from that seen in normal aging, occurring initially in cerebellar posterior lobe regions, and is associated with neuronal, synaptic and beta-amyloid neuropathology. Regarding depression, structural imaging studies have identified a relationship between depressive symptoms and cerebellar gray matter volume. In particular, major depressive disorder (MDD) and higher depressive symptom burden are associated with smaller gray matter volumes in the total cerebellum as well as the posterior cerebellum, vermis, and posterior Crus I. From the genetic/epigenetic standpoint, prominent DNA methylation changes in the cerebellum with aging are both in the form of hypo- and hyper-methylation, and the presumably increased/decreased expression of certain genes might impact on motor coordination. Training influences motor skills and lifelong practice might contribute to structural maintenance of the cerebellum in old age, reducing loss of grey matter volume and therefore contributing to the maintenance of cerebellar reserve. Non-invasive cerebellar stimulation techniques are increasingly being applied to enhance cerebellar functions related to motor, cognitive, and affective operations. They might enhance cerebellar reserve in the elderly. In conclusion, macroscopic and microscopic changes occur in the cerebellum during the lifespan, with changes in structural and functional connectivity with both the cerebral cortex and basal ganglia. With the aging of the population and the impact of aging on quality of life, the panel of experts considers that there is a huge need to clarify how the effects of aging on the cerebellar circuitry modify specific motor, cognitive, and affective operations both in normal subjects and in brain disorders such as AD or MDD, with the goal of preventing symptoms or improving the motor, cognitive, and affective symptoms.
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Affiliation(s)
- Angelo Arleo
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Martin Bareš
- First Department of Neurology, Faculty of Medicine, Masaryk University and St. Anne's Teaching Hospital, Brno, Czech Republic
- Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, USA
| | - Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, 4235 TAMU, College Station, TX, 77843, USA
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, USA
| | - Hannah R Bogoian
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Muriel M K Bruchhage
- Department of Psychology, Stavanger University, Institute of Social Sciences, Kjell Arholms Gate 41, 4021, Stavanger, Norway
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Centre for Neuroimaging Sciences, Box 89, De Crespigny Park, London, PO, SE5 8AF, UK
- Rhode Island Hospital, Department for Diagnostic Imaging, 1 Hoppin St, Providence, RI, 02903, USA
- Department of Paediatrics, Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA
| | - Patrick Bryant
- Freie Universität Berlin, Fachbereich Mathematik und Informatik, Arnimallee 12, 14195, Berlin, Germany
| | - Erik S Carlson
- Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA
- Geriatric Research, Education and Clinical Center, Veteran's Affairs Medical Center, Puget Sound, Seattle, WA, USA
| | - Chetwyn C H Chan
- Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China
| | - Liang-Kung Chen
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
- Center for Geriatric and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
- Taipei Municipal Gan-Dau Hospital (managed by Taipei Veterans General Hospital), Taipei, Taiwan
| | - Chih-Ping Chung
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Vonetta M Dotson
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Gerontology Institute, Georgia State University, Atlanta, GA, USA
| | - Pavel Filip
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Xavier Guell
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christophe Habas
- CHNO Des Quinze-Vingts, INSERM-DGOS CIC 1423, 28 rue de Charenton, 75012, Paris, France
- Université Versailles St Quentin en Yvelines, Paris, France
| | - Heidi I L Jacobs
- School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Tatia M C Lee
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
- Laboratory of Neuropsychology and Human Neuroscience, Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Maria Leggio
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy
| | - Maria Misiura
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy
| | - Stephen Ramanoël
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
- Université Côte d'Azur, LAMHESS, Nice, France
| | - Zeynab Rezaee
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health, NIH, Bethesda, USA
| | - Colby L Samstag
- Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA
- Geriatric Research, Education and Clinical Center, Veteran's Affairs Medical Center, Puget Sound, Seattle, WA, USA
| | - Jeremy D Schmahmann
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Ataxia Center, Cognitive Behavioural neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaoru Sekiyama
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan
| | - Clive H Y Wong
- Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China
| | - Masatoshi Yamashita
- Research Center for Child Mental Development, University of Fukui, Fukui, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan
| | - Mario Manto
- Service de Neurologie, Médiathèque Jean Jacquy, CHU-Charleroi, Charleroi, Belgium.
- Service des Neurosciences, University of Mons, Mons, Belgium.
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4
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Bollack A, Markiewicz PJ, Wink AM, Prosser L, Lilja J, Bourgeat P, Schott JM, Coath W, Collij LE, Pemberton HG, Farrar G, Barkhof F, Cash DM. Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies. Neuroimage 2023; 280:120313. [PMID: 37595816 DOI: 10.1016/j.neuroimage.2023.120313] [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] [Received: 01/05/2023] [Revised: 05/29/2023] [Accepted: 08/04/2023] [Indexed: 08/20/2023] Open
Abstract
PURPOSE Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. METHODS Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation. RESULTS All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL. CONCLUSION Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.
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Affiliation(s)
- Ariane Bollack
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK.
| | - Pawel J Markiewicz
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Alle Meije Wink
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands
| | - Lloyd Prosser
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | | | | | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Lyduine E Collij
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Hugh G Pemberton
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; GE HealthCare, Amersham, UK; Queen Square Institute of Neurology, University College London, UK
| | | | - Frederik Barkhof
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Queen Square Institute of Neurology, University College London, UK
| | - David M Cash
- Queen Square Institute of Neurology, University College London, UK; UK Dementia Research Institute at University College London, London, UK
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5
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Muñoz E, Jodar M, Guerrero J, Compta Y, Perissinotti A, Álvarez‐Mora MI, Falgàs N, Rodríguez‐Revenga L, Sánchez‐Valle R. Spastic Paraplegia and Cognitive Impairment Due to a De Novo Pathogenic Variant in Presenilin-1. Mov Disord Clin Pract 2022; 10:148-150. [PMID: 36699002 PMCID: PMC9847302 DOI: 10.1002/mdc3.13588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 09/09/2022] [Accepted: 09/27/2022] [Indexed: 01/28/2023] Open
Affiliation(s)
- Esteban Muñoz
- Parkinson's Disease and Movement Disorders Unit, Neurology Service, Institut Clínic de Neurociències, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), European Reference Network‐Rare Neurological Diseases (ERN‐RND)University of BarcelonaBarcelonaCataloniaSpain
| | - Meritxell Jodar
- Biochemistry and Molecular Genetics Department, Hospital Clinic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)University of BarcelonaBarcelonaCataloniaSpain
| | - Jairo Guerrero
- Parkinson's Disease and Movement Disorders Unit, Neurology Service, Institut Clínic de Neurociències, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), European Reference Network‐Rare Neurological Diseases (ERN‐RND)University of BarcelonaBarcelonaCataloniaSpain
| | - Yaroslau Compta
- Parkinson's Disease and Movement Disorders Unit, Neurology Service, Institut Clínic de Neurociències, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), European Reference Network‐Rare Neurological Diseases (ERN‐RND)University of BarcelonaBarcelonaCataloniaSpain
| | - Andrés Perissinotti
- Nuclear Medicine Department, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Biomedical Research Networking Center of Bioengineering, Biomaterials, and NanomedicineInstituto de Salud Carlos III (CIBER‐BBN)BarcelonaSpain
| | - Maria I. Álvarez‐Mora
- Biochemistry and Molecular Genetics Department, Hospital Clinic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)University of BarcelonaBarcelonaCataloniaSpain
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit. Neurology Service. Institut Clínic de Neurociències, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)University of BarcelonaBarcelonaCataloniaSpain
| | - Laia Rodríguez‐Revenga
- Biochemistry and Molecular Genetics Department, Hospital Clinic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)University of BarcelonaBarcelonaCataloniaSpain
| | - Raquel Sánchez‐Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit. Neurology Service. Institut Clínic de Neurociències, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)University of BarcelonaBarcelonaCataloniaSpain
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6
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Abrahamson EE, Kofler JK, Becker CR, Price JC, Newell KL, Ghetti B, Murrell JR, McLean CA, Lopez OL, Mathis CA, Klunk WE, Villemagne VL, Ikonomovic MD. 11C-PiB PET can underestimate brain amyloid-β burden when cotton wool plaques are numerous. Brain 2022; 145:2161-2176. [PMID: 34918018 PMCID: PMC9630719 DOI: 10.1093/brain/awab434] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 10/02/2021] [Accepted: 10/20/2021] [Indexed: 09/01/2023] Open
Abstract
Individuals with familial Alzheimer's disease due to PSEN1 mutations develop high cortical fibrillar amyloid-β load but often have lower cortical 11C-Pittsburgh compound B (PiB) retention than Individuals with sporadic Alzheimer's disease. We hypothesized this is influenced by limited interactions of Pittsburgh compound B with cotton wool plaques, an amyloid-β plaque type common in familial Alzheimer's disease but rare in sporadic Alzheimer's disease. Histological sections of frontal and temporal cortex, caudate nucleus and cerebellum were obtained from 14 cases with sporadic Alzheimer's disease, 12 cases with familial Alzheimer's disease due to PSEN1 mutations, two relatives of a PSEN1 mutation carrier but without genotype information and three non-Alzheimer's disease cases. Sections were processed immunohistochemically using amyloid-β-targeting antibodies and the fluorescent amyloid stains cyano-PiB and X-34. Plaque load was quantified by percentage area analysis. Frozen homogenates from the same brain regions from five sporadic Alzheimer's disease and three familial Alzheimer's disease cases were analysed for 3H-PiB in vitro binding and concentrations of amyloid-β1-40 and amyloid-β1-42. Nine sporadic Alzheimer's disease, three familial Alzheimer's disease and three non-Alzheimer's disease participants had 11C-PiB PET with standardized uptake value ratios calculated using the cerebellum as the reference region. Cotton wool plaques were present in the neocortex of all familial Alzheimer's disease cases and one sporadic Alzheimer's disease case, in the caudate nucleus from four familial Alzheimer's disease cases, but not in the cerebellum. Cotton wool plaques immunolabelled robustly with 4G8 and amyloid-β42 antibodies but weakly with amyloid-β40 and amyloid-βN3pE antibodies and had only background cyano-PiB fluorescence despite labelling with X-34. Relative to amyloid-β plaque load, cyano-Pittsburgh compound B plaque load was similar in sporadic Alzheimer's disease while in familial Alzheimer's disease it was lower in the neocortex and the caudate nucleus. In both regions, insoluble amyloid-β1-42 and amyloid-β1-40 concentrations were similar in familial Alzheimer's disease and sporadic Alzheimer's disease groups, while 3H-PiB binding was lower in the familial Alzheimer's disease than the sporadic Alzheimer's disease group. Higher amyloid-β1-42 concentration associated with higher 3H-PiB binding in sporadic Alzheimer's disease but not familial Alzheimer's disease. 11C-PiB retention correlated with region-matched post-mortem amyloid-β plaque load; however, familial Alzheimer's disease cases with abundant cotton wool plaques had lower 11C-PiB retention than sporadic Alzheimer's disease cases with similar amyloid-β plaque loads. PiB has limited ability to detect amyloid-β aggregates in cotton wool plaques and may underestimate total amyloid-β plaque burden in brain regions with abundant cotton wool plaques.
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Affiliation(s)
- Eric E Abrahamson
- Department of Neurology, University of Pittsburgh School of Medicine. Pittsburgh, PA, USA
- Geriatric Research Education and Clinical Center, Pittsburgh VA Healthcare System, Pittsburgh, PA, USA
| | - Julia K Kofler
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Carl R Becker
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Julie C Price
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Massachusetts General Hospital, A. A. Martinos Center for Biomedical Imaging, Cambridge, MA, USA
| | - Kathy L Newell
- Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN, USA
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN, USA
| | - Jill R Murrell
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Catriona A McLean
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh School of Medicine. Pittsburgh, PA, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh School of Medicine. Pittsburgh, PA, USA
- Geriatric Research Education and Clinical Center, Pittsburgh VA Healthcare System, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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7
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Sirkis DW, Bonham LW, Johnson TP, La Joie R, Yokoyama JS. Dissecting the clinical heterogeneity of early-onset Alzheimer's disease. Mol Psychiatry 2022; 27:2674-2688. [PMID: 35393555 PMCID: PMC9156414 DOI: 10.1038/s41380-022-01531-9] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/07/2022] [Accepted: 03/16/2022] [Indexed: 12/14/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.
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Affiliation(s)
- Daniel W Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Luke W Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Taylor P Johnson
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA.
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