1
|
Katsumi Y, Howe IA, Eckbo R, Wong B, Quimby M, Hochberg D, McGinnis SM, Putcha D, Wolk DA, Touroutoglou A, Dickerson BC. Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease. Brain 2025; 148:1329-1344. [PMID: 39412999 PMCID: PMC11969453 DOI: 10.1093/brain/awae327] [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: 04/09/2024] [Revised: 08/31/2024] [Accepted: 10/01/2024] [Indexed: 10/18/2024] Open
Abstract
Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16); logopenic variant Primary Progressive Aphasia (n = 15); and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent MRI, tau PET and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, P < 0.001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = 0.30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = 0.10), tau in other functional networks (R2 = 0.11-0.26) and the magnitude of cortical atrophy (R2 = 0.20) and amyloid burden (R2 = 0.09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients 1 year later. This simple measure could aid the development of a personalized prognostic, monitoring and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.
Collapse
Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Inola A Howe
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Daisy Hochberg
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Scott M McGinnis
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain/Mind Medicine, Department of Neurology, Brigham & Women’s Hospital, Boston, MA 02115, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain/Mind Medicine, Department of Neurology, Brigham & Women’s Hospital, Boston, MA 02115, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| |
Collapse
|
2
|
Rikken RM, Coomans EM, de Koning LA, Visser D, Neutelings E, den Braber A, Collij LE, Golla SSV, Barkhof F, Visser PJ, Scheltens P, van der Flier WM, Boellaard R, Ossenkoppele R, Vijverberg EGB, van de Giessen E. Characterizing visual read tau-PET-negative participants with Alzheimer's disease dementia. Alzheimers Dement 2025; 21:e14423. [PMID: 40219781 PMCID: PMC11992537 DOI: 10.1002/alz.14423] [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: 07/02/2024] [Revised: 10/09/2024] [Accepted: 11/01/2024] [Indexed: 04/14/2025]
Abstract
INTRODUCTION A subset of amyloid beta (Aβ)-positive Alzheimer's disease (AD) patients is tau-positron emission tomography (PET) negative. We aimed to characterize this subgroup using [18F]flortaucipir PET visual read (VR), as this is important for prognosis and selection for therapies. METHODS Aβ-positive VR tau-PET-negative AD dementia patients (AD A+T-) were compared to tau-PET-positive AD patients (AD A+T+) and control groups (CU A-T-; CU A+T-) included from the Amsterdam-based cohort and Alzheimer's Disease Neuroimaging Initiative (ADNI). We compared [18F]flortaucipir binding in an early- and late-stage tau ROI, atrophy, cognition, and co-pathologies. RESULTS AD A+T- were older, showed less hippocampal atrophy and slower cognitive decline compared to AD A+T+. In ADNI, AD A+T- showed higher early-stage tau binding compared to both control groups and more late-stage tau compared to CU A-T-, but no tau accumulation over time. DISCUSSION VR tau-PET-negative AD patients show neurodegenerative and cognitive processes consistent with the AD trajectory, but milder progression compared to tau-PET-positive AD patients. HIGHLIGHTS We used the novel Food and Drug Administration (FDA)-approved VR method for defining tau-PET positivity. AD A+T- patients were older and showed less atrophy and cognitive decline than AD A+T+. We did not find convincing evidence of tau accumulation in AD A+T- or copathologies. The group of AD A+T- patients is likely very heterogeneous.
Collapse
Affiliation(s)
- Roos M. Rikken
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Emma M. Coomans
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Lotte A. de Koning
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Denise Visser
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Eline Neutelings
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
- Biological PsychiatryVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Lyduine E. Collij
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Clinical Memory Research Unit, Clinical Sciences Malmö, Faculty of MedicineLund University, Skånes Universitetssjukhus, VE MinnessjukdomarMalmöSweden
| | - Sandeep S. V. Golla
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | | | - Frederik Barkhof
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
- Alzheimer Center Limburg, School for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of NeurogeriatricsKarolinska InstitutetSolnaSweden
| | - Philip Scheltens
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
- Epidemiology & Data ScienceVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Ronald Boellaard
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
- Clinical Memory Research Unit, Clinical Sciences Malmö, Faculty of MedicineLund University, Skånes Universitetssjukhus, VE MinnessjukdomarMalmöSweden
| | - Everard G. B. Vijverberg
- Alzheimer Center Amsterdam, NeurologyVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdam UMC location VUmcAmsterdamThe Netherlands
| | - Elsmarieke van de Giessen
- Radiology & Nuclear MedicineVrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam UMC location VUmcAmsterdamThe Netherlands
| | | |
Collapse
|
3
|
Masters CL. Neuropathology meets chemical and genetic pathology head-on: a personal perspective. Pathology 2025; 57:191-195. [PMID: 39668075 DOI: 10.1016/j.pathol.2024.11.001] [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] [Received: 10/16/2024] [Revised: 10/31/2024] [Accepted: 11/05/2024] [Indexed: 12/14/2024]
Abstract
Medical science has made revolutionary discoveries around the nosology and aetiology of the neurodegenerative diseases. Dementia is the second leading cause of death in Australia. My colleagues and I are now looking at therapeutics which potentially can delay or prevent the onset of Alzheimer's disease (AD). Advances in diagnosis allow detection of preclinical AD. Neuropathologists working closely with chemical and genetic pathologists have a major role to play in pushing diagnostics and therapeutics to the forefront of clinical management of these diseases.
Collapse
Affiliation(s)
- Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Vic, Australia.
| |
Collapse
|
4
|
Putcha D, Katsumi Y, Touroutoglou A, Eloyan A, Taurone A, Thangarajah M, Aisen P, Dage JL, Foroud T, Jack CR, Kramer JH, Nudelman KNH, Raman R, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Grant IM, Honig LS, Johnson ECB, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Womack K, Carrillo MC, Rabinovici GD, Dickerson BC, Apostolova LG, Hammers DB. Heterogeneous clinical phenotypes of sporadic early-onset Alzheimer's disease: a neuropsychological data-driven approach. Alzheimers Res Ther 2025; 17:38. [PMID: 39915859 PMCID: PMC11800584 DOI: 10.1186/s13195-025-01689-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Accepted: 01/31/2025] [Indexed: 02/09/2025]
Abstract
BACKGROUND The clinical presentations of early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease are distinct, with EOAD having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) described EOAD as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the phenotypic range of EOAD presentation, we applied a neuropsychological data-driven method to subtype the LEADS cohort. METHODS Neuropsychological test performance from 169 amyloid-positive EOAD participants were analyzed. Education-corrected normative comparisons were made using a sample of 98 cognitively normal participants. Comparing the relative levels of impairment between each cognitive domain, we applied a cut-off of 1 SD below all other domain scores to indicate a phenotype of "predominant" impairment in a given cognitive domain. Individuals were otherwise considered to have multidomain impairment. Whole-cortex general linear modeling of cortical atrophy was applied as an MRI-based validation of these distinct clinical phenotypes. RESULTS We identified 6 phenotypic subtypes of EOAD: Dysexecutive Predominant (22% of sample), Amnestic Predominant (11%), Language Predominant (11%), Visuospatial Predominant (15%), Mixed Amnestic/Dysexecutive Predominant (11%), and Multidomain (30%). These phenotypes did not differ by age, sex, or years of education. The APOE ɛ4 genotype was enriched in the Amnestic Predominant group, who were also rated as least impaired. Cortical thickness analysis validated these clinical phenotypes with dissociations in atrophy patterns observed between the Dysexecutive and Amnestic Predominant groups. In contrast to the heterogeneity observed from our neuropsychological data-driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic-predominant, 9% were non-amnestic, 4% met criteria for Posterior Cortical Atrophy, and 5% met criteria for Primary Progressive Aphasia. CONCLUSION A neuropsychological data-driven method to phenotype EOAD individuals uncovered a more detailed understanding of the presenting heterogeneity in this atypical AD sample compared to clinical judgment alone. Clinicians and patients may over-report memory dysfunction at the expense of non-memory symptoms. These findings have important implications for diagnostic accuracy and treatment considerations.
Collapse
Affiliation(s)
- Deepti Putcha
- Frontotemporal Disorders Unit and Massachusetts Alzheimer's Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 149 13th St, Charlestown, Boston, MA, 02129, USA.
| | - Yuta Katsumi
- Frontotemporal Disorders Unit and Massachusetts Alzheimer's Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 149 13th St, Charlestown, Boston, MA, 02129, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit and Massachusetts Alzheimer's Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 149 13th St, Charlestown, Boston, MA, 02129, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, RI, 02912, USA
| | - Alexander Taurone
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, RI, 02912, USA
| | - Maryanne Thangarajah
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, RI, 02912, USA
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, 92093, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Joel H Kramer
- Department of Neurology, University of CA - San Francisco, San Francisco, CA, 94143, USA
| | - Kelly N H Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Rema Raman
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, 92093, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, AZ, 85351, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic in Florida, Jacksonville, FL, 32224, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, 33140, USA
| | | | - Ian M Grant
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Erik C B Johnson
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Joseph C Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, TX, 77030, USA
| | - Mario F Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21218, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, RI, 02912, USA
| | - Emily Rogalski
- Department of Neurology, University of Chicago, Chicago, IL, 60615, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, RI, 02912, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, 94305, USA
| | - R Scott Turner
- Department of Neurology, Georgetown University, Washington, DC, 20057, USA
| | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, IL, 60631, USA
| | - Gil D Rabinovici
- Department of Neurology, University of CA - San Francisco, San Francisco, CA, 94143, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit and Massachusetts Alzheimer's Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 149 13th St, Charlestown, Boston, MA, 02129, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, IN, 46202, USA
| | - Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| |
Collapse
|
5
|
Rabinovici GD, Knopman DS, Arbizu J, Benzinger TLS, Donohoe KJ, Hansson O, Herscovitch P, Kuo PH, Lingler JH, Minoshima S, Murray ME, Price JC, Salloway SP, Weber CJ, Carrillo MC, Johnson KA. Updated Appropriate Use Criteria for Amyloid and Tau PET: A Report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup. J Nucl Med 2025:jnumed.124.268756. [PMID: 39778970 DOI: 10.2967/jnumed.124.268756] [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: 09/05/2024] [Accepted: 09/05/2024] [Indexed: 01/11/2025] Open
Abstract
The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. Methods: The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities. Results: For amyloid PET, 7 scenarios were rated as appropriate, 2 as uncertain, and 8 as rarely appropriate. For tau PET, 5 scenarios were rated as appropriate, 6 as uncertain, and 6 as rarely appropriate. Conclusion: AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease.
Collapse
Affiliation(s)
- Gil D Rabinovici
- Department of Neurology and Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California;
| | - David S Knopman
- Mayo Clinic Neurology and Neurosurgery, Rochester, Minnesota
| | - Javier Arbizu
- Department of Nuclear Medicine, University of Navarra Clinic, Pamplona, Spain
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri; Knight Alzheimer's Disease Research Center, School of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Kevin J Donohoe
- Nuclear Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Peter Herscovitch
- Positron Emission Tomography Department, National Institutes of Health Clinical Center, Bethesda, Maryland
| | - Phillip H Kuo
- Medical Imaging, Medicine, and Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Jennifer H Lingler
- Department of Health and Community Systems, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah
| | | | - Julie C Price
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Stephen P Salloway
- Department of Neurology and Psychiatry the Warren Alpert School of Medicine, Brown University, Providence, Rhode Island
- Butler Hospital Memory and Aging Program, Providence, Rhode Island
| | | | | | - Keith A Johnson
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
- Molecular Neuroimaging, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts; and
- Departments of Neurology and Radiology, Massachusetts General Hospital, Boston, Massachusetts
| |
Collapse
|
6
|
Rabinovici GD, Knopman DS, Arbizu J, Benzinger TLS, Donohoe KJ, Hansson O, Herscovitch P, Kuo PH, Lingler JH, Minoshima S, Murray ME, Price JC, Salloway SP, Weber CJ, Carrillo MC, Johnson KA. Updated appropriate use criteria for amyloid and tau PET: A report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup. Alzheimers Dement 2025; 21:e14338. [PMID: 39776249 PMCID: PMC11772739 DOI: 10.1002/alz.14338] [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: 07/19/2024] [Revised: 09/09/2024] [Accepted: 09/10/2024] [Indexed: 01/11/2025]
Abstract
INTRODUCTION The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. METHODS The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities. RESULTS For amyloid PET, seven scenarios were rated as appropriate, two as uncertain, and eight as rarely appropriate. For tau PET, five scenarios were rated as appropriate, six as uncertain, and six as rarely appropriate. DISCUSSION AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease. HIGHLIGHTS A multidisciplinary workgroup convened by the Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging updated the appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. The goal of these updated AUC is to assist clinicians in identifying clinical scenarios in which amyloid or tau PET may be useful for guiding the diagnosis and management of patients who have, or are at risk for, cognitive decline These updated AUC are intended for dementia specialists who spend a significant proportion of their clinical effort caring for patients with cognitive complaints, as well as serve as a general reference for a broader audience interested in implementation of amyloid and tau PET in clinical practice.
Collapse
Affiliation(s)
- Gil D. Rabinovici
- Department of Neurology and Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | | | - Javier Arbizu
- Department of Nuclear MedicineUniversity of Navarra ClinicPamplonaSpain
| | - Tammie L. S. Benzinger
- Mallinckrodt Institute of RadiologyWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
- Knight Alzheimer's Disease Research CenterWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Kevin J. Donohoe
- Nuclear Medicine, Beth Israel Deaconess Medical CenterBostonMassachusettsUSA
| | - Oskar Hansson
- Department of Clinical Sciences MalmöClinical Memory Research UnitFaculty of MedicineLund UniversityLundSweden
- Memory Clinic, Skåne University HospitalSkånes universitetssjukhusMalmöSweden
| | - Peter Herscovitch
- Positron Emission Tomography DepartmentNational Institutes of Health Clinical CenterBethesdaMarylandUSA
| | - Phillip H. Kuo
- Medical Imaging, Medicine, and Biomedical EngineeringUniversity of ArizonaTucsonArizonaUSA
| | - Jennifer H. Lingler
- Department of Health and Community SystemsUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Satoshi Minoshima
- Department of Radiology and Imaging SciencesUniversity of UtahSalt Lake CityUtahUSA
| | | | - Julie C. Price
- Department of RadiologyMassachusetts General Hospital, BostonCharlestownMassachusettsUSA
| | - Stephen P. Salloway
- Department of Neurology and Psychiatry the Warren Alpert School of Medicine at Brown UniversityProvidenceRhode IslandUSA
- Butler Hospital Memory and Aging ProgramProvidenceRhode IslandUSA
| | | | - Maria C. Carrillo
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalBostonMassachusettsUSA
| | - Keith A. Johnson
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalBostonMassachusettsUSA
- Molecular Neuroimaging, Massachusetts General HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
- Departments of Neurology and RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| |
Collapse
|
7
|
Villain N, Michalon R. What is Alzheimer's disease? An analysis of nosological perspectives from the 20th and 21st centuries. Eur J Neurol 2024; 31:e16302. [PMID: 38618742 PMCID: PMC11464395 DOI: 10.1111/ene.16302] [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: 03/13/2024] [Revised: 03/28/2024] [Accepted: 03/29/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND Recent US proposals suggest defining Alzheimer's disease (AD) based on β-amyloidosis alone. This sparked debates that echoed historical ones about the significance of brain lesions and clinical phenotype. METHODS This review covers debates on AD nosology through three key periods: AD's discovery in German-speaking countries in the early 20th century, its redefinition in Anglo-Saxon countries in the 1960s-1980s, and current debates on the biological or clinicobiological definitions of AD. Key players' opinions are focused on. RESULTS At the beginning of the 20th century, AD was defined as a clinicopathological entity. Debates arose around the pathological anchor, which included extended neurofibrillary tangles versus neuritic plaques (Alzheimer vs. Fischer) and its association with senile dementia (Kraepelin). In the 1960s-1980s, the debate shifted towards whether AD could be diagnosed using qualitative or quantitative neuropathological features and whether it was a unique process (Terry and Katzman) or had subtypes (Roth). The current definition proposed by the US Alzheimer's Association is based purely on biological β-amyloid abnormalities and represents a double break: from the historical clinicopathological definition of AD and from the historical emphasis on tau or combined tau and β-amyloid high levels of pathology. Conversely, the clinicobiological proposal of the International Working Group remains aligned with historical concepts of AD. CONCLUSIONS This historical perspective illustrates the unresolved questions surrounding AD pathogenesis, role of lesions, and the clinical phenotype, especially for sporadic cases. The intense nosological debates throughout the history of AD also illustrate the diversity of theoretical frameworks for defining disease in medicine.
Collapse
Affiliation(s)
- Nicolas Villain
- Sorbonne Université, INSERM U1127, CNRS 7225, Institut du Cerveau–ICMParisFrance
- Department of NeurologyInstitute of Memory and Alzheimer's Disease, AP‐HP Sorbonne Université, Pitié‐Salpêtrière HospitalParisFrance
| | - Robin Michalon
- École des Hautes Etudes en Sciences SocialesParisFrance
- CAK‐CRHST – Centre Alexandre Koyré – Centre de Recherche en Histoire des Sciences et des TechniquesParisFrance
| |
Collapse
|
8
|
Corriveau-Lecavalier N, Adams JN, Fischer L, Molloy EN, Maass A. Cerebral hyperactivation across the Alzheimer's disease pathological cascade. Brain Commun 2024; 6:fcae376. [PMID: 39513091 PMCID: PMC11542485 DOI: 10.1093/braincomms/fcae376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 09/18/2024] [Accepted: 10/23/2024] [Indexed: 11/15/2024] Open
Abstract
Neuronal dysfunction in specific brain regions or across distributed brain networks is a known feature of Alzheimer's disease. An often reported finding in the early stage of the disease is the presence of increased functional MRI (fMRI) blood oxygenation level-dependent signal under task conditions relative to cognitively normal controls, a phenomenon known as 'hyperactivation'. However, research in the past decades yielded complex, sometimes conflicting results. The magnitude and topology of fMRI hyperactivation patterns have been found to vary across the preclinical and clinical spectrum of Alzheimer's disease, including concomitant 'hypoactivation' in some cases. These incongruences are likely due to a range of factors, including the disease stage at which the cohort is examined, the brain areas or networks studied and the fMRI paradigm utilized to evoke these functional abnormalities. Additionally, a perennial question pertains to the nature of hyperactivation in the context of Alzheimer's disease. Some propose it reflects compensatory mechanisms to sustain cognitive performance, while others suggest it is linked to the pathological disruption of a highly regulated homeostatic cycle that contributes to, or even drives, disease progression. Providing a coherent narrative for these empirical and conceptual discrepancies is paramount to develop disease models, understand the synergy between hyperactivation and the Alzheimer's disease pathological cascade and tailor effective interventions. We first provide a comprehensive overview of functional brain changes spanning the course from normal ageing to the clinical spectrum of Alzheimer's disease. We then highlight evidence supporting a close relationship between fMRI hyperactivation and in vivo markers of Alzheimer's pathology. We primarily focus on task-based fMRI studies in humans, but also consider studies using different functional imaging techniques and animal models. We then discuss the potential mechanisms underlying hyperactivation in the context of Alzheimer's disease and provide a testable framework bridging hyperactivation, ageing, cognition and the Alzheimer's disease pathological cascade. We conclude with a discussion of future challenges and opportunities to advance our understanding of the fundamental disease mechanisms of Alzheimer's disease, and the promising development of therapeutic interventions incorporating or aimed at hyperactivation and large-scale functional systems.
Collapse
Affiliation(s)
- Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55902, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota 55902 USA
| | - Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine 92697, CA, USA
| | - Larissa Fischer
- German Center for Neurodegenerative Diseases, Magdeburg 39120, Germany
| | - Eóin N Molloy
- German Center for Neurodegenerative Diseases, Magdeburg 39120, Germany
- Division of Nuclear Medicine, Department of Radiology & Nuclear Medicine, Faculty of Medicine, Otto von Guericke University Magdeburg, Magdeburg 39120, Germany
| | - Anne Maass
- German Center for Neurodegenerative Diseases, Magdeburg 39120, Germany
- Institute for Biology, Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
| |
Collapse
|
9
|
Vermeiren MR, Somsen J, Luurtsema G, Reesink FE, Verwey NA, Hempenius L, Tolboom N, Biessels GJ, Biesbroek JM, Vernooij MW, Veldhuijzen van Zanten SEM, Seelaar H, Coomans EM, Teunissen CE, Lemstra AW, van Harten AC, Visser LNC, van der Flier WM, van de Giessen E, Ossenkoppele R. The impact of tau-PET in a selected memory clinic cohort: rationale and design of the TAP-TAU study. Alzheimers Res Ther 2024; 16:230. [PMID: 39427210 PMCID: PMC11490118 DOI: 10.1186/s13195-024-01588-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Accepted: 09/29/2024] [Indexed: 10/21/2024]
Abstract
BACKGROUND Tau-PET is a diagnostic tool with high sensitivity and specificity for discriminating Alzheimer's disease (AD) dementia from other neurodegenerative disorders in well-controlled research environments. The role of tau-PET in real-world clinical practice, however, remains to be established. The aim of the TAP-TAU study is therefore to investigate the impact of tau-PET in clinical practice. METHODS TAP-TAU is a prospective, longitudinal multi-center study in 300 patients (≥ 50 years old) with mild cognitive impairment or mild dementia across five Dutch memory clinics. Patients are eligible if diagnostic certainty is < 85% after routine dementia screening and if the differential diagnosis includes AD. More specifically, we will include patients who (i) are suspected of having mixed pathology (e.g., AD and vascular pathology), (ii) have an atypical clinical presentation, and/or (iii) show conflicting or inconclusive outcomes on other tests (e.g., magnetic resonance imaging or cerebrospinal fluid). Participants will undergo a [18F]flortaucipir tau-PET scan, blood-based biomarker sampling, and fill out questionnaires on patient reported outcomes and experiences. The primary outcomes are change (pre- versus post- tau-PET) in diagnosis, diagnostic certainty, patient management and patient anxiety and uncertainty. Secondary outcome measures are head-to-head comparisons between tau-PET and less invasive and lower cost diagnostic tools such as novel blood-based biomarkers and artificial intelligence-based classifiers. RESULTS TAP-TAU has been approved by the Medical Ethics Committee of the Amsterdam UMC. The first participant is expected to be included in October 2024. CONCLUSIONS In TAP-TAU, we will investigate the added clinical value of tau-PET in a real-world clinical setting, including memory clinic patients with diagnostic uncertainty after routine work-up. Findings of our study may contribute to recommendations regarding which patients would benefit most from assessment with tau-PET. This study is timely in the dawning era of disease modifying treatments as an accurate etiological diagnosis becomes increasingly important. TRIAL REGISTRATION This trial is registered and authorized on December 21st, 2023 in EU Clinical Trials with registration number 2023-505430-10-00.
Collapse
Affiliation(s)
- Marie R Vermeiren
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands.
| | - Joost Somsen
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Gert Luurtsema
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Fransje E Reesink
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Nicolaas A Verwey
- Department of Neurology, Medical Center Leeuwarden, Leeuwarden, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | | | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - J Matthijs Biesbroek
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
- Department of Neurology, Diakonessenhuis Hospital, Utrecht, Netherlands
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | | | - Harro Seelaar
- Department of Neurology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Emma M Coomans
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | | | - Afina W Lemstra
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Leonie N C Visser
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Psychology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Epidemiology and Data Science, Amsterdam UMC, Amsterdam, Netherlands
| | - Elsmarieke van de Giessen
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, Netherlands.
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
| |
Collapse
|
10
|
Lui E, Venkatraman VK, Finch S, Chua M, Li TQ, Sutton BP, Steward CE, Moffat B, Cyarto EV, Ellis KA, Rowe CC, Masters CL, Lautenschlager NT, Desmond PM. 3T sodium-MRI as predictor of neurocognition in nondemented older adults: a cross sectional study. Brain Commun 2024; 6:fcae307. [PMID: 39318783 PMCID: PMC11420980 DOI: 10.1093/braincomms/fcae307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 06/13/2024] [Accepted: 09/10/2024] [Indexed: 09/26/2024] Open
Abstract
Dementia is a burgeoning global problem. Novel magnetic resonance imaging (MRI) metrics beyond volumetry may bring new insight and aid clinical trial evaluation of interventions early in the Alzheimer's disease course to complement existing imaging and clinical metrics. To determine whether: (i) normalized regional sodium-MRI values (Na-SI) are better predictors of neurocognitive status than volumetry (ii) cerebral amyloid PET status improves modelling. Nondemented older adult (>60 years) volunteers of known Alzheimer's Disease Assessment Scale (ADAS-Cog11), Mini-Mental State Examination (MMSE) and Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neurocognitive test scores, ApolipoproteinE (APOE) e4 +/- cerebral amyloid PET status were prospectively recruited for 3T sodium-MRI brain scans. Left and right hippocampal, entorhinal and precuneus volumes and Na-SI (using the proportional intensity scaling normalization method with field inhomogeneity and partial volume corrections) were obtained after segmentation and co-registration of 3D-T1-weighted proton images. Descriptive statistics, correlation and best-subset regression analyses were performed. In our 76 nondemented participants (mean(standard deviation) age 75(5) years; woman 47(62%); cognitively unimpaired 54/76(71%), mildly cognitively impaired 22/76(29%)), left hippocampal Na-SI, not volume, was preferentially in the best models for predicting MMSE (Odds Ratio (OR) = 0.19(Confidence Interval (CI) = 0.07,0.53), P-value = 0.001) and ADAS-Cog11 (Beta(B) = 1.2(CI = 0.28,2.1), P-value = 0.01) scores. In the entorhinal analysis, right entorhinal Na-SI, not volume, was preferentially selected in the best model for predicting ADAS-Cog11 (B = 0.94(CI = 0.11,1.8), P-value = 0.03). While right entorhinal Na-SI and volume were both selected for MMSE modelling (Na-SI OR = 0.23(CI = 0.09,0.6), P-value = 0.003; volume OR = 2.6(CI = 1.0,6.6), P-value = 0.04), independently, Na-SI explained more of the variance (Na-SI R 2 = 10.3; volume R 2 = 7.5). No imaging variable was selected in the best CERAD models. Adding cerebral amyloid status improved model fit (Akaike Information Criterion increased 2.0 for all models, P-value < 0.001-0.045). Regional Na-SI were more predictive of MMSE and ADAS-Cog11 scores in our nondemented older adult cohort than volume, hippocampal more robust than entorhinal region of interest. Positive amyloid status slightly further improved model fit.
Collapse
Affiliation(s)
- Elaine Lui
- Department of Radiology, The University of Melbourne, Parkville, 3050 Victoria, Australia
- Department of Medical Imaging, The Royal Melbourne Hospital, Parkville, 3050 Victoria, Australia
| | - Vijay K Venkatraman
- Department of Radiology, The University of Melbourne, Parkville, 3050 Victoria, Australia
- Department of Medical Imaging, The Royal Melbourne Hospital, Parkville, 3050 Victoria, Australia
| | - Sue Finch
- Statistical Consulting Centre, University of Melbourne, Parkville, 3010 Victoria, Australia
| | - Michelle Chua
- Department of Medical Imaging, The Royal Melbourne Hospital, Parkville, 3050 Victoria, Australia
| | - Tie-Qiang Li
- Department of Clinical Science, Intervention and Technology, Karolinska Institute, 171 77 Stockholm, Sweden
| | - Bradley P Sutton
- Beckman Institute for Advance Science and Technology, University of Illinois at Urbana Champaign, Champaign, IL 61801, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
| | - Christopher E Steward
- Department of Radiology, The University of Melbourne, Parkville, 3050 Victoria, Australia
- Department of Medical Imaging, The Royal Melbourne Hospital, Parkville, 3050 Victoria, Australia
| | - Bradford Moffat
- Department of Radiology, The University of Melbourne, Parkville, 3050 Victoria, Australia
| | - Elizabeth V Cyarto
- Australian Centre for Health Services Innovation and Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, Queensland 4059, Australia
| | - Kathryn A Ellis
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, The University of Melbourne, Melbourne, 3010 Victoria, Australia
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, 3010 Victoria, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, Melbourne, 3084 Victoria, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, 3052 Victoria, Australia
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, 3052 Victoria, Australia
| | - Nicola T Lautenschlager
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, The University of Melbourne, Melbourne, 3010 Victoria, Australia
- Royal Melbourne Hospital Mental Health Service, Royal Melbourne Hospital, Parkville, Melbourne, 3052 Victoria, Australia
| | - Patricia M Desmond
- Department of Radiology, The University of Melbourne, Parkville, 3050 Victoria, Australia
- Department of Medical Imaging, The Royal Melbourne Hospital, Parkville, 3050 Victoria, Australia
| |
Collapse
|
11
|
Ingrassia L, Boluda S, Potier MC, Haïk S, Jimenez G, Kar A, Racoceanu D, Delatour B, Stimmer L. Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software. J Neuropathol Exp Neurol 2024; 83:752-762. [PMID: 38812098 PMCID: PMC11333827 DOI: 10.1093/jnen/nlae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024] Open
Abstract
Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotation database with 5013 NPs and 5143 NFTs. We next trained two U-Net convolutional neural networks for detection and segmentation of NPs or NFTs, achieving high accuracy and consistency (mean Dice similarity coefficient: NPs, 0.77; NFTs, 0.81). The workflow showed high generalization performance across different cases. This study serves as a proof-of-concept for the utilization of proprietary image analysis software (Visiopharm) in the automated deep learning segmentation of NPs and NFTs, demonstrating that AI can significantly improve the annotation quality of complex neuropathological features and enable the creation of highly precise models for identifying these markers in AD brain sections.
Collapse
Affiliation(s)
- Lea Ingrassia
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Susana Boluda
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
- Department of Neuropathology Raymond Escourolle, AP-HP, Pitié-Salpêtrière University Hospital, Paris, France
| | - Marie-Claude Potier
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Stéphane Haïk
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
- AP-HP, Cellule Nationale de Référence des MCJ, Salpêtrière Hospital, Paris, France
| | - Gabriel Jimenez
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Anuradha Kar
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Daniel Racoceanu
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Benoît Delatour
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Lev Stimmer
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| |
Collapse
|
12
|
Giorgio J, Jonson C, Wang Y, Yokoyama JS, Wang J, Jagust W. Variable and interactive effects of Sex, APOE ε4 and TREM2 on the deposition of tau in entorhinal and neocortical regions. RESEARCH SQUARE 2024:rs.3.rs-4804430. [PMID: 39149503 PMCID: PMC11326369 DOI: 10.21203/rs.3.rs-4804430/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
The canonical AD pathological cascade posits that the accumulation of amyloid beta ( Aβ ) is the initiating event, accelerating the accumulation of tau in the entorhinal cortex (EC), which subsequently spreads into the neocortex. Here in a sample of over 1300 participants with multimodal imaging and genetic information we queried how genetic variation affects these stages of the AD cascade. We observed that females and APOE- ε4 homozygotes are more susceptible to the effects of Aβ on the primary accumulation of tau, with greater EC tau for a given level of Aβ . Furthermore, we observed for individuals who have rare risk variants in Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) and/or APOE- ε4 homozygotes there was a greater spread of primary tau from the EC into the neocortex. These findings offer insights into the function of sex, APOE and microglia in AD progression, and have implications for determining personalised treatment with drugs targeting Aβ and tau.
Collapse
Affiliation(s)
- Joseph Giorgio
- Department of Neuroscience, University of California Berkeley, Berkeley, California, USA, 94720
- School of Psychological Sciences, College of Engineering, Science and the Environment, University of Newcastle, Newcastle, New South Wales, Australia, 2308
| | - Caroline Jonson
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC, USA, 20037
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, CA, USA, 94158
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA, 94158
| | - Yilin Wang
- Department of Statistics and Actuarial Science, The University of Iowa, Iowa City, IA, USA
| | - Jennifer S. Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA, 94158
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Jingshen Wang
- Division of Biostatistics, University of California Berkeley, Berkeley, California, USA, 94720
| | - William Jagust
- Department of Neuroscience, University of California Berkeley, Berkeley, California, USA, 94720
| | | | | |
Collapse
|
13
|
Hey JA, Abushakra S, Blennow K, Reiman EM, Hort J, Prins ND, Sheardova K, Kesslak P, Shen L, Zhu X, Albayrak A, Paul J, Schaefer JF, Power A, Tolar M. Effects of Oral ALZ-801/Valiltramiprosate on Plasma Biomarkers, Brain Hippocampal Volume, and Cognition: Results of 2-Year Single-Arm, Open-Label, Phase 2 Trial in APOE4 Carriers with Early Alzheimer's Disease. Drugs 2024; 84:811-823. [PMID: 38902571 PMCID: PMC11289173 DOI: 10.1007/s40265-024-02067-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/14/2024] [Indexed: 06/22/2024]
Abstract
INTRODUCTION ALZ-801/valiltramiprosate is a small-molecule oral inhibitor of beta amyloid (Aβ) aggregation and oligomer formation being studied in a phase 2 trial in APOE4 carriers with early Alzheimer's disease (AD) to evaluate treatment effects on fluid and imaging biomarkers and cognitive assessments. METHODS The single-arm, open-label phase 2 trial was designed to evaluate the effects of the ALZ-801 265 mg tablet taken twice daily (after 2 weeks once daily) on plasma fluid AD biomarkers, hippocampal volume (HV), and cognition over 104 weeks in APOE4 carriers. The study enrolled subjects aged 50-80 years, with early AD [Mini-Mental State Examination (MMSE) ≥ 22, Clinical Dementia Rating-Global (CDR-G) 0.5 or 1], apolipoprotein E4 (APOE4) genotypes including APOE4/4 and APOE3/4 genotypes, and positive cerebrospinal fluid (CSF) AD biomarkers or prior amyloid scans. The primary outcome was plasma p-tau181, HV evaluated by magnetic resonance imaging (MRI) was the key secondary outcome, and plasma Aβ42 and Aβ40 were the secondary biomarker outcomes. The cognitive outcomes were the Rey Auditory Verbal Learning Test and the Digit Symbol Substitution Test. Safety and tolerability evaluations included treatment-emergent adverse events and amyloid-related imaging abnormalities (ARIA). The study was designed and powered to detect 15% reduction from baseline in plasma p-tau181 at the 104-week endpoint. A sample size of 80 subjects provided adequate power to detect this difference at a significance level of 0.05 using a two-sided paired t-test. RESULTS The enrolled population of 84 subjects (31 homozygotes and 53 heterozygotes) was 52% females, mean age 69 years, MMSE 25.7 [70% mild cognitive impairment (MCI), 30% mild AD] with 55% on cholinesterase inhibitors. Plasma p-tau181 reduction from baseline was significant (31%, p = 0.045) at 104 weeks and all prior visits; HV atrophy was significantly reduced (p = 0.0014) compared with matched external controls from an observational Early AD study. Memory scores showed minimal decline from baseline over 104 weeks and correlated significantly with decreased HV atrophy (Spearman's 0.44, p = 0.002). Common adverse events were COVID infection and mild nausea, and no drug-related serious adverse events were reported. Of 14 early terminations, 6 were due to nonserious treatment-emergent adverse events and 1 death due to COVID. There was no vasogenic brain edema observed on MRI over 104 weeks. CONCLUSIONS The effect of ALZ-801 on reducing plasma p-tau181 over 2 years demonstrates target engagement and supports its anti-Aβ oligomer action that leads to a robust decrease in amyloid-induced brain neurodegeneration. The significant correlation between reduced HV atrophy and cognitive stability over 2 years suggests a disease-modifying effect of ALZ-801 treatment in patients with early AD. Together with the favorable safety profile with no events of vasogenic brain edema, these results support further evaluation of ALZ-801 in a broader population of APOE4 carriers, who represent two-thirds of patients with AD. TRIAL REGISTRATION https://clinicaltrials.gov/study/NCT04693520 .
Collapse
Affiliation(s)
- John A Hey
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA.
| | - Susan Abushakra
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| | - Kaj Blennow
- Neurochemical Pathology and Diagnostics Research Group, Department of Neuroscience and Physiology, University of Gothenburg, Molndal, Sweden
| | - Eric M Reiman
- Banner Alzheimer's Institute and University of Arizona, Phoenix, AZ, USA
| | - Jakub Hort
- Memory Clinic, Department of Neurology, Second Faculty of Medicine and Motol University Hospital, Charles University, Praha, Czech Republic
| | | | - Katerina Sheardova
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Patrick Kesslak
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| | - Larry Shen
- Pharmapace Biometrics Solutions, a Unit of Wuxi AppTec, San Diego, CA, USA
| | - Xinyi Zhu
- Pharmapace Biometrics Solutions, a Unit of Wuxi AppTec, San Diego, CA, USA
| | - Adem Albayrak
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| | - Jijo Paul
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| | - Jean F Schaefer
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| | - Aidan Power
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| | - Martin Tolar
- Alzheon, Inc., 111 Speen St., Suite 306, Framingham, MA, USA
| |
Collapse
|
14
|
Pina‐Escudero SD, La Joie R, Spina S, Hwang J, Miller ZA, Huang EJ, Grant H, Mundada NS, Boxer AL, Gorno‐Tempini ML, Rosen HJ, Kramer JH, Miller BL, Seeley WW, Rabinovici GD, Grinberg LT. Comorbid neuropathology and atypical presentation of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12602. [PMID: 39040464 PMCID: PMC11262028 DOI: 10.1002/dad2.12602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 12/07/2023] [Accepted: 01/19/2024] [Indexed: 07/24/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) neuropathological changes present with amnestic and nonamnestic (atypical) syndromes. The contribution of comorbid neuropathology as a substratum of atypical expression of AD remains under investigated. METHODS We examined whether atypical AD exhibited increased comorbid neuropathology compared to typical AD and if such neuropathologies contributed to the accelerated clinical decline in atypical AD. RESULTS We examined 60 atypical and 101 typical AD clinicopathological cases. The number of comorbid pathologies was similar between the groups (p = 0.09). Argyrophilic grain disease was associated with atypical presentation (p = 0.008) after accounting for sex, age of onset, and disease duration. Vascular brain injury was more common in typical AD (p = 0.022). Atypical cases had a steeper Mini-Mental Status Examination (MMSE) decline over time (p = 0.033). DISCUSSION Comorbid neuropathological changes are unlikely to contribute to atypical AD presentation and the steeper cognitive decline seen in this cohort. Highlights Autopsy cohort of 60 atypical and 101 typical AD; does comorbid pathology explain atypical presentation?Atypical versus Typical AD: No significant differences in comorbid neuropathologies were found (p = 0.09).Argyrophilic Grain Disease Association: significantly correlates with atypical AD presentations, suggesting a unique neuropathological pattern (p = 0.008).Vascular Brain Injury Prevalence: Vascular brain injury is more common in typical AD than in atypical AD (p = 0.022).Cognitive Decline in Atypical AD: Atypical AD patients experience a steeper cognitive decline measured by MMSE than those with typical AD despite lacking more comorbid neuropathology, highlighting the severity of atypical AD pathogenesis (p = 0.033).
Collapse
Affiliation(s)
- Stefanie D. Pina‐Escudero
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Renaud La Joie
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Salvatore Spina
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ji‐Hye Hwang
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Zachary A. Miller
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Eric J. Huang
- Department of PathologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Harli Grant
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Nidhi S. Mundada
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Adam L. Boxer
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Maria Luisa Gorno‐Tempini
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Howard J. Rosen
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Joel H. Kramer
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - William W. Seeley
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of PathologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Gil D. Rabinovici
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Lea Tenenholz Grinberg
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of PathologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of PathologyUniversity of Sao PauloSao PauloSao PauloBrazil
| |
Collapse
|
15
|
Ourry V, Binette AP, St-Onge F, Strikwerda-Brown C, Chagnot A, Poirier J, Breitner J, Arenaza-Urquijo EM, Rabin JS, Buckley R, Gonneaud J, Marchant NL, Villeneuve S. How Do Modifiable Risk Factors Affect Alzheimer's Disease Pathology or Mitigate Its Effect on Clinical Symptom Expression? Biol Psychiatry 2024; 95:1006-1019. [PMID: 37689129 DOI: 10.1016/j.biopsych.2023.09.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 08/11/2023] [Accepted: 09/03/2023] [Indexed: 09/11/2023]
Abstract
Epidemiological studies show that modifiable risk factors account for approximately 40% of the population variability in risk of developing dementia, including sporadic Alzheimer's disease (AD). Recent findings suggest that these factors may also modify disease trajectories of people with autosomal-dominant AD. With positron emission tomography imaging, it is now possible to study the disease many years before its clinical onset. Such studies can provide key knowledge regarding pathways for either the prevention of pathology or the postponement of its clinical expression. The former "resistance pathway" suggests that modifiable risk factors could affect amyloid and tau burden decades before the appearance of cognitive impairment. Alternatively, the resilience pathway suggests that modifiable risk factors may mitigate the symptomatic expression of AD pathology on cognition. These pathways are not mutually exclusive and may appear at different disease stages. Here, in a narrative review, we present neuroimaging evidence that supports both pathways in sporadic AD and autosomal-dominant AD. We then propose mechanisms for their protective effect. Among possible mechanisms, we examine neural and vascular mechanisms for the resistance pathway. We also describe brain maintenance and functional compensation as bases for the resilience pathway. Improved mechanistic understanding of both pathways may suggest new interventions.
Collapse
Affiliation(s)
- Valentin Ourry
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada.
| | - Alexa Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada; Clinical Memory Research Unit, Department of Clinical Sciences, Lunds Universitet, Malmö, Sweden
| | - Frédéric St-Onge
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada; Integrated Program in Neuroscience, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Cherie Strikwerda-Brown
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada; School of Psychological Science, The University of Western Australia, Perth, Western Australia, Australia
| | - Audrey Chagnot
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Judes Poirier
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - John Breitner
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Eider M Arenaza-Urquijo
- Environment and Health over the Lifecourse Programme, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Jennifer S Rabin
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada; Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada; Rehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada
| | - Rachel Buckley
- Melbourne School of Psychological Sciences University of Melbourne, Parkville, Victoria, Australia; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Julie Gonneaud
- Normandie University, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders," Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Caen, France
| | - Natalie L Marchant
- Division of Psychiatry, University College London, London, United Kingdom
| | - Sylvia Villeneuve
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Douglas Mental Health University Institute, Montreal, Quebec, Canada; McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
| |
Collapse
|
16
|
Koivumäki M, Ekblad L, Lantero-Rodriguez J, Ashton NJ, Karikari TK, Helin S, Parkkola R, Lötjönen J, Zetterberg H, Blennow K, Rinne JO, Snellman A. Blood biomarkers of neurodegeneration associate differently with amyloid deposition, medial temporal atrophy, and cerebrovascular changes in APOE ε4-enriched cognitively unimpaired elderly. Alzheimers Res Ther 2024; 16:112. [PMID: 38762725 PMCID: PMC11102270 DOI: 10.1186/s13195-024-01477-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 05/06/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β (Aβ) plaques, neurofibrillary tau tangles, and neurodegeneration in the brain parenchyma. Here, we aimed to (i) assess differences in blood and imaging biomarkers used to evaluate neurodegeneration among cognitively unimpaired APOE ε4 homozygotes, heterozygotes, and non-carriers with varying risk for sporadic AD, and (ii) to determine how different cerebral pathologies (i.e., Aβ deposition, medial temporal atrophy, and cerebrovascular pathology) contribute to blood biomarker concentrations in this sample. METHODS Sixty APOE ε4 homozygotes (n = 19), heterozygotes (n = 21), and non-carriers (n = 20) ranging from 60 to 75 years, were recruited in collaboration with Auria biobank (Turku, Finland). Participants underwent Aβ-PET ([11C]PiB), structural brain MRI including T1-weighted and T2-FLAIR sequences, and blood sampling for measuring serum neurofilament light chain (NfL), plasma total tau (t-tau), plasma N-terminal tau fragments (NTA-tau) and plasma glial fibrillary acidic protein (GFAP). [11C]PiB standardized uptake value ratio was calculated for regions typical for Aβ accumulation in AD. MRI images were analysed for regional volumes, atrophy scores, and volumes of white matter hyperintensities. Differences in biomarker levels and associations between blood and imaging biomarkers were tested using uni- and multivariable linear models (unadjusted and adjusted for age and sex). RESULTS Serum NfL concentration was increased in APOE ε4 homozygotes compared with non-carriers (mean 21.4 pg/ml (SD 9.5) vs. 15.5 pg/ml (3.8), p = 0.013), whereas other blood biomarkers did not differ between the groups (p > 0.077 for all). From imaging biomarkers, hippocampal volume was significantly decreased in APOE ε4 homozygotes compared with non-carriers (6.71 ml (0.86) vs. 7.2 ml (0.7), p = 0.029). In the whole sample, blood biomarker levels were differently predicted by the three measured cerebral pathologies; serum NfL concentration was associated with cerebrovascular pathology and medial temporal atrophy, while plasma NTA-tau associated with medial temporal atrophy. Plasma GFAP showed significant association with both medial temporal atrophy and Aβ pathology. Plasma t-tau concentration did not associate with any of the measured pathologies. CONCLUSIONS Only increased serum NfL concentrations and decreased hippocampal volume was observed in cognitively unimpaired APOEε4 homozygotes compared to non-carriers. In the whole population the concentrations of blood biomarkers were affected in distinct ways by different pathologies.
Collapse
Affiliation(s)
- Mikko Koivumäki
- Turku PET Centre, Turku University Hospital, University of Turku, Turku, Finland.
| | - Laura Ekblad
- Turku PET Centre, Turku University Hospital, University of Turku, Turku, Finland
- Department of Geriatric Medicine, Turku University Hospital and University of Turku, Turku, Finland
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- Department of Old Age Psychiatry, Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Semi Helin
- Turku PET Centre, Turku University Hospital, University of Turku, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Juha O Rinne
- Turku PET Centre, Turku University Hospital, University of Turku, Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, Turku, Finland
| | - Anniina Snellman
- Turku PET Centre, Turku University Hospital, University of Turku, Turku, Finland
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| |
Collapse
|
17
|
Iaccarino L, Llibre-Guerra JJ, McDade E, Edwards L, Gordon B, Benzinger T, Hassenstab J, Kramer JH, Li Y, Miller BL, Miller Z, Morris JC, Mundada N, Perrin RJ, Rosen HJ, Soleimani-Meigooni D, Strom A, Tsoy E, Wang G, Xiong C, Allegri R, Chrem P, Vazquez S, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Salloway S, Fox NC, Day GS, Gorno-Tempini ML, Boxer AL, La Joie R, Bateman R, Rabinovici GD. Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2024; 6:fcae159. [PMID: 38784820 PMCID: PMC11114609 DOI: 10.1093/braincomms/fcae159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 03/14/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.
Collapse
Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jorge J Llibre-Guerra
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Tammie Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Jason Hassenstab
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Richard J Perrin
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Elena Tsoy
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Silvia Vazquez
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Colin L Masters
- Department of Neuroscience, Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, Indiana, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich 80539, Germany
- German Center for Neurodegenerative Diseases, Munich 81377, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Stephen Salloway
- Memory & Aging Program, Butler Hospital, Brown University in Providence, RI 02906, USA
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- 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
| | - Randall Bateman
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Gil D Rabinovici
- 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, CA 94143, USA
| |
Collapse
|
18
|
Wei B, Xu Y, Du Y, Zhou J, Zhong F, Wu C, Lou Y. Feasibility of Using Magnetic Resonance Spectroscopy Test Biomarkers to Diagnose Alzheimer's Disease: Systematic Evaluation and Meta-Analysis. ACTAS ESPANOLAS DE PSIQUIATRIA 2024; 52:161-171. [PMID: 38622011 PMCID: PMC11016455 DOI: 10.62641/aep.v52i2.1552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia, resulting in impairments in memory, cognition, decision-making, and social skills. Thus, accurate preclinical diagnosis of Alzheimer's disease is paramount. The identification of biomarkers for Alzheimer's disease through magnetic resonance spectroscopy (MRS) represents a novel adjunctive diagnostic approach. OBJECTIVE This study conducted a meta-analysis of the diagnostic results of this technology to explore its feasibility and accuracy. METHODS PubMed, Cochrane Library, EMBASE, and Web of Science databases were searched without restrictions, with the search period extending up to July 31, 2022. The search strategy employed a combination of subject headings and keywords. All retrieved documents underwent screening by two researchers, who selected them for meta-analysis. The included literature was analyzed using Review Manager 5.4 software, with corresponding bias maps, forest plots, and summary receiver operating characteristic (SROC) curves generated and analyzed. RESULTS A total of 344 articles were retrieved initially, with 11 articles meeting the criteria for inclusion in the analysis. The analysis encompassed data from approximately 1766 patients. In the forest plot, both sensitivity (95% CI) and specificity (95% CI) approached 1. Examining the true positive rate, false positive rate, true negative rate, and false negative rate, all studies on the summary receiver operating characteristic (SROC) curve clustered in the upper left quadrant, suggesting a very high accuracy of biomarkers detected by MRS for diagnosing Alzheimer's disease. CONCLUSION The detection of biomarkers by MRS demonstrates feasibility and high accuracy in diagnosing AD. This technology holds promise for widespread adoption in the clinical diagnosis of AD in the future.
Collapse
Affiliation(s)
- Bo Wei
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Yiqin Xu
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Ye Du
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Jie Zhou
- Department of Radiology, Shaoxing Seventh People's Hospital (Affiliated Mental Health Center, Medical College of Shaoxing University), 312000 Shaoxing, Zhejiang, China
| | - Fangfang Zhong
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Chenglong Wu
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Yiping Lou
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| |
Collapse
|
19
|
Therriault J, Schindler SE, Salvadó G, Pascoal TA, Benedet AL, Ashton NJ, Karikari TK, Apostolova L, Murray ME, Verberk I, Vogel JW, La Joie R, Gauthier S, Teunissen C, Rabinovici GD, Zetterberg H, Bateman RJ, Scheltens P, Blennow K, Sperling R, Hansson O, Jack CR, Rosa-Neto P. Biomarker-based staging of Alzheimer disease: rationale and clinical applications. Nat Rev Neurol 2024; 20:232-244. [PMID: 38429551 DOI: 10.1038/s41582-024-00942-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/05/2024] [Indexed: 03/03/2024]
Abstract
Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-β and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.
Collapse
Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, Quebec, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa Lessa Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- NIHR Biomedical Research Centre, South London and Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Liana Apostolova
- Department of Neurology, University of Indiana School of Medicine, Indianapolis, IN, USA
| | | | - Inge Verberk
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Jacob W Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Clinical Sciences, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Charlotte Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip Scheltens
- Alzheimer Centre Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Reisa Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
20
|
Lee J, Burkett BJ, Min HK, Senjem ML, Dicks E, Corriveau-Lecavalier N, Mester CT, Wiste HJ, Lundt ES, Murray ME, Nguyen AT, Reichard RR, Botha H, Graff-Radford J, Barnard LR, Gunter JL, Schwarz CG, Kantarci K, Knopman DS, Boeve BF, Lowe VJ, Petersen RC, Jack CR, Jones DT. Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning. Brain 2024; 147:980-995. [PMID: 37804318 PMCID: PMC10907092 DOI: 10.1093/brain/awad346] [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: 02/20/2023] [Revised: 08/30/2023] [Accepted: 09/24/2023] [Indexed: 10/09/2023] Open
Abstract
Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.
Collapse
Affiliation(s)
- Jeyeon Lee
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea
| | - Brian J Burkett
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hoon-Ki Min
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Carly T Mester
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Emily S Lundt
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ross R Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| |
Collapse
|
21
|
Whitwell JL. Atypical clinical variants of Alzheimer's disease: are they really atypical? Front Neurosci 2024; 18:1352822. [PMID: 38482142 PMCID: PMC10933030 DOI: 10.3389/fnins.2024.1352822] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 02/15/2024] [Indexed: 02/12/2025] Open
Abstract
Alzheimer's disease (AD) is a neuropathological disorder defined by the deposition of the proteins, tau and β-amyloid. Alzheimer's disease is commonly thought of as a disease of the elderly that is associated with episodic memory loss. However, the very first patient described with AD was in her 50's with impairments in multiple cognitive domains. It is now clear that AD can present with multiple different non-amnestic clinical variants which have been labeled as atypical variants of AD. Instead of these variants of AD being considered "atypical," I propose that they provide an excellent disease model of AD and reflect the true clinical heterogeneity of AD. The atypical variants of AD usually have a relatively young age at onset, and they show striking cortical tau deposition on molecular PET imaging which relates strongly with patterns of neurodegeneration and clinical outcomes. In contrast, elderly patients with AD show less tau deposition on PET, and neuroimaging and clinical outcomes are confounded by other age-related pathologies, including TDP-43 and vascular pathology. There is also considerable clinical and anatomical heterogeneity across atypical and young-onset amnestic variants of AD which reflects the fact that AD is a disease that causes impairments in multiple cognitive domains. Future studies should focus on careful characterization of cognitive impairment in AD and consider the full clinical spectrum of AD, including atypical AD, in the design of research studies investigating disease mechanisms in AD and clinical treatment trials, particularly with therapeutics targeting tau.
Collapse
|
22
|
St-Onge F, Chapleau M, Breitner JCS, Villeneuve S, Pichet Binette A. Tau accumulation and its spatial progression across the Alzheimer's disease spectrum. Brain Commun 2024; 6:fcae031. [PMID: 38410618 PMCID: PMC10896475 DOI: 10.1093/braincomms/fcae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/30/2023] [Accepted: 02/05/2024] [Indexed: 02/28/2024] Open
Abstract
The accumulation of tau abnormality in sporadic Alzheimer's disease is believed typically to follow neuropathologically defined Braak staging. Recent in-vivo PET evidence challenges this belief, however, as accumulation patterns for tau appear heterogeneous among individuals with varying clinical expressions of Alzheimer's disease. We, therefore, sought a better understanding of the spatial distribution of tau in the preclinical and clinical phases of sporadic Alzheimer's disease and its association with cognitive decline. Longitudinal tau-PET data (1370 scans) from 832 participants (463 cognitively unimpaired, 277 with mild cognitive impairment and 92 with Alzheimer's disease dementia) were obtained from the Alzheimer's Disease Neuroimaging Initiative. Among these, we defined thresholds of abnormal tau deposition in 70 brain regions from the Desikan atlas, and for each group of regions characteristic of Braak staging. We summed each scan's number of regions with abnormal tau deposition to form a spatial extent index. We then examined patterns of tau pathology cross-sectionally and longitudinally and assessed their heterogeneity. Finally, we compared our spatial extent index of tau uptake with a temporal meta-region of interest-a commonly used proxy of tau burden-assessing their association with cognitive scores and clinical progression. More than 80% of amyloid-beta positive participants across diagnostic groups followed typical Braak staging, both cross-sectionally and longitudinally. Within each Braak stage, however, the pattern of abnormality demonstrated significant heterogeneity such that the overlap of abnormal regions across participants averaged less than 50%, particularly in persons with mild cognitive impairment. Accumulation of tau progressed more rapidly among cognitively unimpaired and participants with mild cognitive impairment (1.2 newly abnormal regions per year) compared to participants with Alzheimer's disease dementia (less than 1 newly abnormal region per year). Comparing the association of tau pathology and cognitive performance our spatial extent index was superior to the temporal meta-region of interest for identifying associations with memory in cognitively unimpaired individuals and explained more variance for measures of executive function in patients with mild cognitive impairments and Alzheimer's disease dementia. Thus, while participants broadly followed Braak stages, significant individual regional heterogeneity of tau binding was observed at each clinical stage. Progression of the spatial extent of tau pathology appears to be fastest in cognitively unimpaired and persons with mild cognitive impairment. Exploring the spatial distribution of tau deposits throughout the entire brain may uncover further pathological variations and their correlation with cognitive impairments.
Collapse
Affiliation(s)
- Frédéric St-Onge
- Integrated Program in Neuroscience, Faculty of Medicine, McGill University, Montreal, QC H3A 2B4, Canada
- Research Center of the Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
| | - Marianne Chapleau
- Faculty of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - John C S Breitner
- Research Center of the Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC H3A 1Y2, Canada
| | - Sylvia Villeneuve
- Research Center of the Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC H3A 1Y2, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC H3A 2B4, Canada
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Malmö 205 02, Sweden
| |
Collapse
|
23
|
Samudra N, Lerner H, Yack L, Walsh CM, Kirsch HE, Kudo K, Yballa C, La Joie R, Gorno‐Tempini ML, Spina S, Seeley WW, Neylan TC, Miller BL, Rabinovici GD, Boxer A, Grinberg LT, Rankin KP, Nagarajan SS, Ranasinghe KG. Spatiotemporal characteristics of neurophysiological changes in patients with four-repeat tauopathies. Ann Clin Transl Neurol 2024; 11:525-535. [PMID: 38226843 PMCID: PMC10863921 DOI: 10.1002/acn3.51974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 12/01/2023] [Accepted: 12/05/2023] [Indexed: 01/17/2024] Open
Abstract
INTRODUCTION Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD), are the most common four-repeat tauopathies (4RT), and both frequently occur with varying degree of Alzheimer's disease (AD) copathology. Intriguingly, patients with 4RT and patients with AD are at opposite ends of the wakefulness spectrum-AD showing reduced wakefulness and excessive sleepiness whereas 4RT showing decreased homeostatic sleep. The neural mechanisms underlying these distinct phenotypes in the comorbid condition of 4RT and AD are unknown. The objective of the current study was to define the alpha oscillatory spectrum, which is prominent in the awake resting-state in the human brain, in patients with primary 4RT, and how it is modified in comorbid AD-pathology. METHOD In an autopsy-confirmed case series of 4R-tauopathy patients (n = 10), whose primary neuropathological diagnosis was either PSP (n = 7) or CBD (n = 3), using high spatiotemporal resolution magnetoencephalography (MEG), we quantified the spectral power density within alpha-band (8-12 Hz) and examined how this pattern was modified in increasing AD-copathology. For each patient, their regional alpha power was compared to an age-matched normative control cohort (n = 35). RESULT Patients with 4RT showed increased alpha power but in the presence of AD-copathology alpha power was reduced. CONCLUSIONS Alpha power increase in PSP-tauopathy and reduction in the presence of AD-tauopathy is consistent with the observation that neurons activating wakefulness-promoting systems are preserved in PSP but degenerated in AD. These results highlight the selectively vulnerable impacts in 4RT versus AD-tauopathy that may have translational significance on disease-modifying therapies for specific proteinopathies.
Collapse
Affiliation(s)
- Niyatee Samudra
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Hannah Lerner
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Leslie Yack
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
- Department of PsychiatrySan Francisco Veterans Affairs, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Christine M. Walsh
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Heidi E. Kirsch
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCalifornia94143USA
- Epilepsy Center, Department of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Kiwamu Kudo
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCalifornia94143USA
- Medical Imaging Business CenterRicoh CompanyKanazawaJapan
| | - Claire Yballa
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Renaud La Joie
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Maria L. Gorno‐Tempini
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Salvatore Spina
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - William W. Seeley
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Thomas C. Neylan
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
- Department of PsychiatrySan Francisco Veterans Affairs, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Bruce L. Miller
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCalifornia94143USA
| | - Adam Boxer
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Lea T. Grinberg
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
- Department of PathologyUniversity of CaliforniaSan FranciscoCalifornia94158USA
- Department of PathologyUniversity of Sao Paulo Medical SchoolSao PauloBrazil
| | - Katherine P. Rankin
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| | - Srikantan S. Nagarajan
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCalifornia94143USA
| | - Kamalini G. Ranasinghe
- Memory and Aging Center, Department of NeurologyWeill Institute for Neurosciences, University of California San FranciscoSan FranciscoCalifornia94158USA
| |
Collapse
|
24
|
Edwards L, Thomas KR, Weigand AJ, Edmonds EC, Clark AL, Brenner EK, Banks SJ, Gilbert PE, Nation DA, Delano-Wood L, Bondi MW, Bangen KJ. Pulse pressure and APOE ε4 dose interact to affect cerebral blood flow in older adults without dementia. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100206. [PMID: 38328026 PMCID: PMC10847851 DOI: 10.1016/j.cccb.2024.100206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/20/2023] [Accepted: 01/14/2024] [Indexed: 02/09/2024]
Abstract
This study assessed whether the effect of vascular risk on cerebral blood flow (CBF) varies by gene dose of apolipoprotein (APOE) ε4 alleles. 144 older adults without dementia from the Alzheimer's Disease Neuroimaging Initiative underwent arterial spin labeling and T1-weighted MRI, APOE genotyping, fluorodeoxyglucose positron emission tomography (FDG-PET), lumbar puncture, and blood pressure (BP) assessment. Vascular risk was assessed using pulse pressure (systolic BP - diastolic BP). CBF was examined in six AD-vulnerable regions: entorhinal cortex, hippocampus, inferior temporal cortex, inferior parietal cortex, rostral middle frontal gyrus, and medial orbitofrontal cortex. Linear regressions tested the interaction between APOE ε4 dose and pulse pressure on CBF in each region, adjusting for age, sex, cognitive classification, antihypertensive medication use, FDG-PET, reference CBF region, and AD biomarker positivity. There was a significant interaction between pulse pressure and APOE ɛ4 dose on CBF in the entorhinal cortex, hippocampus, and inferior parietal cortex, such that higher pulse pressure was associated with lower CBF only among ε4 homozygous participants. These findings demonstrate that the association between pulse pressure and regional CBF differs by APOE ε4 dose, suggesting that targeting modifiable vascular risk factors may be particularly important for those genetically at risk for AD.
Collapse
Affiliation(s)
- Lauren Edwards
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Kelsey R. Thomas
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Alexandra J. Weigand
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Emily C. Edmonds
- Banner Alzheimer's Institute, Tucson, AZ, USA
- Departments of Neurology and Psychology, University of Arizona, Tucson, AZ, USA
| | - Alexandra L. Clark
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - Einat K. Brenner
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Sarah J. Banks
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Paul E. Gilbert
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Daniel A. Nation
- Department of Psychology, University of California Irvine, Irvine, CA, USA
| | - Lisa Delano-Wood
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Psychology Service, VA San Diego Healthcare System, San Diego, CA, USA
| | - Mark W. Bondi
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Psychology Service, VA San Diego Healthcare System, San Diego, CA, USA
| | - Katherine J. Bangen
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| |
Collapse
|
25
|
Matuskova V, Veverova K, Jester DJ, Matoska V, Ismail Z, Sheardova K, Horakova H, Cerman J, Laczó J, Andel R, Hort J, Vyhnalek M. Mild behavioral impairment in early Alzheimer's disease and its association with APOE and BDNF risk genetic polymorphisms. Alzheimers Res Ther 2024; 16:21. [PMID: 38279143 PMCID: PMC10811933 DOI: 10.1186/s13195-024-01386-y] [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: 04/13/2023] [Accepted: 01/04/2024] [Indexed: 01/28/2024]
Abstract
BACKGROUND Mild behavioral impairment (MBI) has been commonly reported in early Alzheimer's disease (AD) but rarely using biomarker-defined samples. It is also unclear whether genetic polymorphisms influence MBI in such individuals. We thus aimed to examine the association between the cognitive status of participants (amnestic mild cognitive impairment (aMCI-AD) vs cognitively normal (CN) older adults) and MBI severity. Within aMCI-AD, we further examined the association between APOE and BDNF risk genetic polymorphisms and MBI severity. METHODS We included 62 aMCI-AD participants and 50 CN older adults from the Czech Brain Aging Study. The participants underwent neurological, comprehensive neuropsychological examination, APOE and BDNF genotyping, and magnetic resonance imaging. MBI was diagnosed with the Mild Behavioral Impairment Checklist (MBI-C), and the diagnosis was based on the MBI-C total score ≥ 7. Additionally, self-report instruments for anxiety (the Beck Anxiety Inventory) and depressive symptoms (the Geriatric Depression Scale-15) were administered. The participants were stratified based on the presence of at least one risk allele in genes for APOE (i.e., e4 carriers and non-carriers) and BDNF (i.e., Met carriers and non-carriers). We used linear regressions to examine the associations. RESULTS MBI was present in 48.4% of the aMCI-AD individuals. Compared to the CN, aMCI-AD was associated with more affective, apathy, and impulse dyscontrol but not social inappropriateness or psychotic symptoms. Furthermore, aMCI-AD was related to more depressive but not anxiety symptoms on self-report measures. Within the aMCI-AD, there were no associations between APOE e4 and BDNF Met and MBI-C severity. However, a positive association between Met carriership and self-reported anxiety appeared. CONCLUSIONS MBI is frequent in aMCI-AD and related to more severe affective, apathy, and impulse dyscontrol symptoms. APOE and BDNF polymorphisms were not associated with MBI severity separately; however, their combined effect warrants further investigation.
Collapse
Affiliation(s)
- Veronika Matuskova
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Katerina Veverova
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
| | - Dylan J Jester
- Women's Operational Military Exposure Network (WOMEN), VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Vaclav Matoska
- Department of Clinical Biochemistry, Hematology and Immunology, Homolka Hospital, Prague, Czech Republic
| | - Zahinoor Ismail
- Departments of Psychiatry and Clinical Neurosciences, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
| | - Katerina Sheardova
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Hana Horakova
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
- Department of Clinical Psychology, Motol University Hospital, Prague, Czech Republic
| | - Jiri Cerman
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Jan Laczó
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
| | - Ross Andel
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
- Center for Innovation in Healthy and Resilient Aging, Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA
| | - Jakub Hort
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Martin Vyhnalek
- Department of Neurology, Memory Clinic, Charles University, Second Faculty of Medicine and Motol University Hospital, V Uvalu 84, 150 06, Prague, Czech Republic.
| |
Collapse
|
26
|
Jann K, Cen S, Santos M, Aksman L, Wijesinghe D, Zhang R, Lynch K, Ringman JM, Wang DJ. Effect of Genetic Risk on the Relationship Between rs-fMRI Complexity and Tau and Amyloid PET in Alzheimer's Disease. J Alzheimers Dis 2024; 101:429-435. [PMID: 39177598 PMCID: PMC11529977 DOI: 10.3233/jad-240459] [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] [Accepted: 07/03/2024] [Indexed: 08/24/2024]
Abstract
Reduced functional magnetic resonance imaging (fMRI)-complexity in Alzheimer's disease (AD) progression has been demonstrated and found to be associated with tauopathy and cognition. However, association of fMRI-complexity with amyloid and influence of genetic risk (APOEɛ4) remain unknown. Here we investigate the association between fMRI-complexity, tau-PET, and amyloid-PET as well as influence of APOE genotype using multivariate generalized linear models. We show that fMRI-complexity has a strong association with tau but not amyloid deposition and that the presence of an APOEɛ4 allele enhances this effect. Thus fMRI-complexity provides a surrogate marker of impaired brain functionality in AD progression.
Collapse
Affiliation(s)
- Kay Jann
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Steven Cen
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Mariella Santos
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Leon Aksman
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Dilmini Wijesinghe
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ru Zhang
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kirsten Lynch
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John M. Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Danny J. Wang
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | |
Collapse
|
27
|
Blazhenets G, Soleimani-Meigooni DN, Thomas W, Mundada N, Brendel M, Vento S, VandeVrede L, Heuer HW, Ljubenkov P, Rojas JC, Chen MK, Amuiri AN, Miller Z, Gorno-Tempini ML, Miller BL, Rosen HJ, Litvan I, Grossman M, Boeve B, Pantelyat A, Tartaglia MC, Irwin DJ, Dickerson BC, Baker SL, Boxer AL, Rabinovici GD, La Joie R. [ 18F]PI-2620 Binding Patterns in Patients with Suspected Alzheimer Disease and Frontotemporal Lobar Degeneration. J Nucl Med 2023; 64:1980-1989. [PMID: 37918868 PMCID: PMC10690126 DOI: 10.2967/jnumed.123.265856] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 09/27/2023] [Indexed: 11/04/2023] Open
Abstract
Tau PET has enabled the visualization of paired helical filaments of 3 or 4 C-terminal repeat tau in Alzheimer disease (AD), but its ability to detect aggregated tau in frontotemporal lobar degeneration (FTLD) spectrum disorders is uncertain. We investigated 2-(2-([18F]fluoro)pyridin-4-yl)-9H-pyrrolo[2,3-b:4,5c']dipyridine ([18F]PI-2620), a newer tracer with ex vivo evidence for binding to FTLD tau, in a convenience sample of patients with suspected FTLD and AD using a static acquisition protocol and parametric SUV ratio (SUVr) images. Methods: We analyzed [18F]PI-2620 PET data from 65 patients with clinical diagnoses associated with AD or FTLD neuropathology; most (60/65) also had amyloid-β (Aβ) PET. Scans were acquired 30-60 min after injection; SUVr maps (reference, inferior cerebellar cortex) were created for the full acquisition and for 10-min truncated sliding windows (30-40, 35-45,…50-60 min). Age- and sex-adjusted z score maps were computed for each patient, relative to 23 Aβ-negative cognitively healthy controls (HC). Mean SUVr in the globus pallidus, substantia nigra, subthalamic nuclei, dentate nuclei, white matter, and temporal gray matter was extracted for the full and truncated windows. Results: Patients with suspected AD neuropathology (Aβ-positive patients with mild cognitive impairment or AD dementia) showed high-intensity temporoparietal cortex-predominant [18F]PI-2620 binding. At the group level, patients with clinical diagnoses associated with FTLD (progressive supranuclear palsy with Richardson syndrome [PSP Richardson syndrome], corticobasal syndrome, and nonfluent-variant primary progressive aphasia) exhibited higher globus pallidus SUVr than did HCs; pallidal retention was highest in the PSP Richardson syndrome group, in whom SUVr was correlated with symptom severity (ρ = 0.53, P = 0.05). At the individual level, only half of PSP Richardson syndrome, corticobasal syndrome, and nonfluent-variant primary progressive aphasia patients had a pallidal SUVr above that of HCs. Temporal SUVr discriminated AD patients from HCs with high accuracy (area under the receiver operating characteristic curve, 0.94 [95% CI, 0.83-1.00]) for all time windows, whereas discrimination between patients with PSP Richardson syndrome and HCs using pallidal SUVr was fair regardless of time window (area under the receiver operating characteristic curve, 0.77 [95% CI, 0.61-0.92] at 30-40 min vs. 0.81 [95% CI, 0.66-0.96] at 50-60 min; P = 0.67). Conclusion: [18F]PI-2620 SUVr shows an intense and consistent signal in AD but lower-intensity, heterogeneous, and rapidly decreasing binding in patients with suspected FTLD. Further work is needed to delineate the substrate of [18F]PI-2620 binding and the usefulness of [18F]PI2620 SUVr quantification outside the AD continuum.
Collapse
Affiliation(s)
- Ganna Blazhenets
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Wesley Thomas
- Lawrence Berkeley National Laboratory, Berkeley, California
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Stephanie Vento
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Lawren VandeVrede
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Hilary W Heuer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Peter Ljubenkov
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Julio C Rojas
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Miranda K Chen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Alinda N Amuiri
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Maria L Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Howie J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Irene Litvan
- University of California, San Diego, San Diego, California
| | - Murray Grossman
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | | | - David J Irwin
- Penn FTD Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California;
| |
Collapse
|
28
|
Lv X, Cheng Z, Wang Q, Gao F, Dai L, Du C, Liu C, Xie Q, Shen Y, Shi J. High burdens of phosphorylated tau protein and distinct precuneus atrophy in sporadic early-onset Alzheimer's disease. Sci Bull (Beijing) 2023; 68:2817-2826. [PMID: 37919158 DOI: 10.1016/j.scib.2023.10.019] [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: 07/15/2023] [Revised: 09/16/2023] [Accepted: 10/17/2023] [Indexed: 11/04/2023]
Abstract
Early-onset Alzheimer's disease (EOAD) is a rare devastating subclassification of Alzheimer's disease (AD). EOAD affects individuals <65 years old, and accounts for 5%-10% of all AD cases. Previous studies on EOAD primarily focused on familial forms, whereas research on sporadic EOAD (sEOAD), which represents 85%-90% of EOAD cases, is limited. In this prospective cohort study, participants were recruited between 2018 and 2023 and included patients with sEOAD (n = 110), late-onset AD (LOAD, n = 89), young controls (YC, n = 50), and older controls (OC, n = 25). All AD patients fulfilled the diagnostic criteria based on biomarker evidence. Familial EOAD patients or non-AD dementia patients were excluded. Single molecule array technology was used to measure fluid biomarkers, including cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ) 40, Aβ42, phosphorylated tau (P-tau) 181, total tau (T-tau), serum neurofilament light chain and glial fibrillary acidic protein (GFAP). Patients with sEOAD exhibited more severe executive function impairment and bilateral precuneus atrophy (P < 0.05, family-wise error corrected) than patients with LOAD. Patients with sEOAD showed elevated CSF and plasma P-tau181 levels (154.0 ± 81.2 pg/mL, P = 0.002; and 6.1 ± 2.3 pg/mL, P = 0.046). Moreover, precuneus atrophy was significantly correlated with serum GFAP levels in sEOAD (P < 0.001). Serum GFAP levels (area under the curve (AUC) = 96.0%, cutoff value = 154.3 pg/mL) displayed excellent diagnostic value in distinguishing sEOAD patients from the control group. These preliminary findings highlight the crucial role of tau protein phosphorylation in the pathogenesis and progression of sEOAD.
Collapse
Affiliation(s)
- Xinyi Lv
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Zhaozhao Cheng
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Qiong Wang
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Feng Gao
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China; Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Linbin Dai
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China; Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Chen Du
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Chang Liu
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Qiang Xie
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Yong Shen
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China; Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China; Anhui Province Key Laboratory of Biomedical Aging Research, University of Science and Technology of China, Hefei 230001, China.
| | - Jiong Shi
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China; Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
| |
Collapse
|
29
|
Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
Collapse
Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
| | | | | |
Collapse
|
30
|
Cho H, Mundada NS, Apostolova LG, Carrillo MC, Shankar R, Amuiri AN, Zeltzer E, Windon CC, Soleimani-Meigooni DN, Tanner JA, Heath CL, Lesman-Segev OH, Aisen P, Eloyan A, Lee HS, Hammers DB, Kirby K, Dage JL, Fagan A, Foroud T, Grinberg LT, Jack CR, Kramer J, Kukull WA, Murray ME, Nudelman K, Toga A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez M, Musiek E, Onyike CU, Riddle M, Rogalski EJ, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Koeppe R, Iaccarino L, Dickerson BC, La Joie R, Rabinovici GD. Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Alzheimers Dement 2023; 19 Suppl 9:S98-S114. [PMID: 37690109 PMCID: PMC10807231 DOI: 10.1002/alz.13453] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 09/12/2023]
Abstract
INTRODUCTION We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). METHODS We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification. RESULTS 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. DISCUSSION LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. HIGHLIGHTS 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.
Collapse
Affiliation(s)
- Hanna Cho
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - Nidhi S Mundada
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Ranjani Shankar
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Alinda N Amuiri
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Ehud Zeltzer
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Charles C Windon
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - David N Soleimani-Meigooni
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Jeremy A Tanner
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Courtney Lawhn Heath
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Diagnostic Imaging, Sheba Medical Center, Tel HaShomer, Israel
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Rhode Island, USA
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Anne Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Lea T Grinberg
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Pathology, University of California - San Francisco, San Francisco, California, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel Kramer
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Rhode Island, USA
| | - Emily J Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert Koeppe
- Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Renaud La Joie
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Gil D Rabinovici
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| |
Collapse
|
31
|
Touroutoglou A, Katsumi Y, Brickhouse M, Zaitsev A, Eckbo R, Aisen P, Beckett L, Dage JL, Eloyan A, Foroud T, Ghetti B, Griffin P, Hammers D, Jack CR, Kramer JH, Iaccarino L, Joie RL, Mundada NS, Koeppe R, Kukull WA, Murray ME, Nudelman K, Polsinelli AJ, Rumbaugh M, Soleimani-Meigooni DN, Toga A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Womack K, Carrillo MC, Rabinovici GD, Apostolova LG, Dickerson BC. The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort. Alzheimers Dement 2023; 19 Suppl 9:S74-S88. [PMID: 37850549 PMCID: PMC10829523 DOI: 10.1002/alz.13466] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 10/19/2023]
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment. DISCUSSION The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD. HIGHLIGHTS We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.
Collapse
Affiliation(s)
- Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Michael Brickhouse
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Zaitsev
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ryan Eckbo
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Laurel Beckett
- Department of Public Health Sciences, University of California - Davis, Davis, California, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Bernardino Ghetti
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Dustin Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel H Kramer
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Renaud La Joie
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Nidhi S Mundada
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Angelina J Polsinelli
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic in Florida, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - R Scott Turner
- Department of Neurology, Georgetown University, Washington, D.C., USA
| | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Gil D Rabinovici
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
32
|
Llibre-Guerra JJ, Iaccarino L, Coble D, Edwards L, Li Y, McDade E, Strom A, Gordon B, Mundada N, Schindler SE, Tsoy E, Ma Y, Lu R, Fagan AM, Benzinger TLS, Soleimani-Meigooni D, Aschenbrenner AJ, Miller Z, Wang G, Kramer JH, Hassenstab J, Rosen HJ, Morris JC, Miller BL, Xiong C, Perrin RJ, Allegri R, Chrem P, Surace E, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Fox NC, Day G, Gorno-Tempini ML, Boxer AL, La Joie R, Rabinovici GD, Bateman R. Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2023; 5:fcad280. [PMID: 37942088 PMCID: PMC10629466 DOI: 10.1093/braincomms/fcad280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/02/2023] [Accepted: 10/17/2023] [Indexed: 11/10/2023] Open
Abstract
Approximately 5% of Alzheimer's disease cases have an early age at onset (<65 years), with 5-10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer's disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer's disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer's disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer's disease enrolled at the University of California San Francisco Alzheimer's Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer's disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P < 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P < 0.001), Trail Making Test Part B (P < 0.001) and digit span (P < 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer's disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer's disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.
Collapse
Affiliation(s)
| | - Leonardo Iaccarino
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Dean Coble
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Amelia Strom
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Malinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Elena Tsoy
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yinjiao Ma
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Ruijin Lu
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Tammie L S Benzinger
- Malinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO 63108, USA
| | - David Soleimani-Meigooni
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | | | - Zachary Miller
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Howard J Rosen
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Bruce L Miller
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
- Department of Pathology and Immunology, Washington University in St Louis, St. Louis, MO 63108, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Ezequiel Surace
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Colin L Masters
- Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
- Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich 80539, Germany
- German Center for Neurodegenerative Diseases, Munich 81377, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Gil D Rabinovici
- Department of Neurology, UCSF 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
| | - Randall Bateman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| |
Collapse
|
33
|
Sokołowski A, Roy ARK, Goh SM, Hardy EG, Datta S, Cobigo Y, Brown JA, Spina S, Grinberg L, Kramer J, Rankin KP, Seeley WW, Sturm VE, Rosen HJ, Miller BL, Perry DC. Neuropsychiatric symptoms and imbalance of atrophy in behavioral variant frontotemporal dementia. Hum Brain Mapp 2023; 44:5013-5029. [PMID: 37471695 PMCID: PMC10502637 DOI: 10.1002/hbm.26428] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 05/25/2023] [Accepted: 07/05/2023] [Indexed: 07/22/2023] Open
Abstract
Behavioral variant frontotemporal dementia is characterized by heterogeneous frontal, insular, and anterior temporal atrophy patterns that vary along left-right and dorso-ventral axes. Little is known about how these structural imbalances impact clinical symptomatology. The goal of this study was to assess the frequency of frontotemporal asymmetry (right- or left-lateralization) and dorsality (ventral or dorsal predominance of atrophy) and to investigate their clinical correlates. Neuropsychiatric symptoms and structural images were analyzed for 250 patients with behavioral variant frontotemporal dementia. Frontotemporal atrophy was most often symmetric while left-lateralized (9%) and right-lateralized (17%) atrophy were present in a minority of patients. Atrophy was more often ventral (32%) than dorsal (3%) predominant. Patients with right-lateralized atrophy were characterized by higher severity of abnormal eating behavior and hallucinations compared to those with left-lateralized atrophy. Subsequent analyses clarified that eating behavior was associated with right atrophy to a greater extent than a lack of left atrophy, and hallucinations were driven mainly by right atrophy. Dorsality analyses showed that anxiety, euphoria, and disinhibition correlated with ventral-predominant atrophy. Agitation, irritability, and depression showed greater severity with a lack of regional atrophy, including in dorsal regions. Aberrant motor behavior and apathy were not explained by asymmetry or dorsality. This study provides additional insight into how anatomical heterogeneity influences the clinical presentation of patients with behavioral variant frontotemporal dementia. Behavioral symptoms can be associated not only with the presence or absence of focal atrophy, but also with right/left or dorsal/ventral imbalance of gray matter volume.
Collapse
Affiliation(s)
- Andrzej Sokołowski
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Ashlin R. K. Roy
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Sheng‐Yang M. Goh
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Emily G. Hardy
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Samir Datta
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Yann Cobigo
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Jesse A. Brown
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Lea Grinberg
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Joel Kramer
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Katherine P. Rankin
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - William W. Seeley
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Department of PathologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Virginia E. Sturm
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Howard J. Rosen
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - David C. Perry
- Department of Neurology, Memory and Aging Center, UCSF Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| |
Collapse
|
34
|
Chow FC, Mundada NS, Abohashem S, La Joie R, Iaccarino L, Arechiga VM, Swaminathan S, Rabinovici GD, Epel ES, Tawakol A, Hsue PY. Psychological stress is associated with arterial inflammation in people living with treated HIV infection. Brain Behav Immun 2023; 113:21-28. [PMID: 37369339 DOI: 10.1016/j.bbi.2023.06.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 06/05/2023] [Accepted: 06/22/2023] [Indexed: 06/29/2023] Open
Abstract
Stress and depression are increasingly recognized as cerebrovascular risk factors, including among high stress populations such as people living with HIV infection (PLWH). Stress may contribute to stroke risk through activation of neural inflammatory pathways. In this cross-sectional study, we examined the relationships between stress, systemic and arterial inflammation, and metabolic activity in stress-related brain regions on 18F-fluorodeoxyglucose (FDG)-PET in PLWH. Participants were recruited from a parent trial evaluating the impact of alirocumab on radiologic markers of cardiovascular risk in people with treated HIV infection. We administered a stress battery to assess different forms of psychological stress, specifying the Perceived Stress Scale as the primary stress measure, and quantified plasma markers of inflammation and immune activation. Participants underwent FDG-PET of the brain, neck, and chest. Age- and sex-matched control participants without HIV infection were selected for brain FDG-PET comparisons. Among PLWH, we used nonparametric pairwise correlations, partial correlations, and linear regression to investigate the association between stress and 1) systemic inflammation; 2) atherosclerotic inflammation on FDG-PET; and metabolic activity in 3) brain regions in which glucose metabolism differed significantly by HIV serostatus; and 4) in a priori defined stress-responsive regions of interest (ROI) and stress-related neural network activity (i.e., ratio of amygdala to ventromedial prefrontal cortex or temporal lobe activity). We studied 37 PLWH (mean age 60 years, 97% men) and 29 control participants without HIV (mean age 62 years, 97% men). Among PLWH, stress was significantly correlated with systemic inflammation (r = 0.33, p = 0.041) and arterial inflammation in the carotid (r = 0.41, p = 0.023) independent of age, race/ethnicity, traditional vascular risk factors and health-related behaviors. In voxel-wise analyses, metabolic activity in a cluster corresponding to the anterior medial temporal lobes, including the bilateral amygdalae, was significantly lower in PLWH compared with controls. However, we did not find a significant positive relationship between stress and this cluster of decreased metabolic activity in PLWH, a priori defined stress-responsive ROI, or stress-related neural network activity. In conclusion, psychological stress was associated with systemic and carotid arterial inflammation in this group of PLWH with treated infection. These data provide preliminary evidence for a link between psychological stress, inflammation, and atherosclerosis as potential drivers of excess cerebrovascular risk among PLWH.
Collapse
Affiliation(s)
- Felicia C Chow
- Departments of Neurology and Medicine (Infectious Diseases) and Weill Institute for Neurosciences, University of California, San Francisco, USA.
| | - Nidhi S Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Shady Abohashem
- Cardiovascular Imaging Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Victor M Arechiga
- Department of Medicine (Cardiology), University of California, San Francisco, USA
| | - Shreya Swaminathan
- Department of Medicine (Cardiology), University of California, San Francisco, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Elissa S Epel
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Ahmed Tawakol
- Cardiovascular Imaging Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, USA; Department of Medicine (Cardiology), Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Priscilla Y Hsue
- Department of Medicine (Cardiology), University of California, San Francisco, USA
| |
Collapse
|
35
|
Ferrari-Souza JP, Bellaver B, Ferreira PCL, Benedet AL, Povala G, Lussier FZ, Leffa DT, Therriault J, Tissot C, Soares C, Wang YT, Chamoun M, Servaes S, Macedo AC, Vermeiren M, Bezgin G, Kang MS, Stevenson J, Rahmouni N, Pallen V, Poltronetti NM, Cohen A, Lopez OL, Klunk WE, Soucy JP, Gauthier S, Souza DO, Triana-Baltzer G, Saad ZS, Kolb HC, Karikari TK, Villemagne VL, Tudorascu DL, Ashton NJ, Zetterberg H, Blennow K, Zimmer ER, Rosa-Neto P, Pascoal TA. APOEε4 potentiates amyloid β effects on longitudinal tau pathology. NATURE AGING 2023; 3:1210-1218. [PMID: 37749258 PMCID: PMC10592050 DOI: 10.1038/s43587-023-00490-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 08/16/2023] [Indexed: 09/27/2023]
Abstract
The mechanisms by which the apolipoprotein E ε4 (APOEε4) allele influences the pathophysiological progression of Alzheimer's disease (AD) are poorly understood. Here we tested the association of APOEε4 carriership and amyloid-β (Aβ) burden with longitudinal tau pathology. We longitudinally assessed 94 individuals across the aging and AD spectrum who underwent clinical assessments, APOE genotyping, magnetic resonance imaging, positron emission tomography (PET) for Aβ ([18F]AZD4694) and tau ([18F]MK-6240) at baseline, as well as a 2-year follow-up tau-PET scan. We found that APOEε4 carriership potentiates Aβ effects on longitudinal tau accumulation over 2 years. The APOEε4-potentiated Aβ effects on tau-PET burden were mediated by longitudinal plasma phosphorylated tau at threonine 217 (p-tau217+) increase. This longitudinal tau accumulation as measured by PET was accompanied by brain atrophy and clinical decline. Our results suggest that the APOEε4 allele plays a key role in Aβ downstream effects on the aggregation of phosphorylated tau in the living human brain.
Collapse
Affiliation(s)
- João Pedro Ferrari-Souza
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Bruna Bellaver
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Pâmela C L Ferreira
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa L Benedet
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Guilherme Povala
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Firoza Z Lussier
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Douglas T Leffa
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Cécile Tissot
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Carolina Soares
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Arthur C Macedo
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Marie Vermeiren
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Gleb Bezgin
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Min Su Kang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Artificial Intelligence and Computational Neurosciences Laboratory, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Vanessa Pallen
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Nina Margherita Poltronetti
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Ann Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Oscar L Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Diogo O Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Ziad S Saad
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, USA
| | - Hartmuth C Kolb
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, USA
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Victor L Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- UW Department of Medicine, School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Biological Sciences: Pharmacology and Therapeuctis, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| |
Collapse
|
36
|
Mundada NS, Rojas JC, Vandevrede L, Thijssen EH, Iaccarino L, Okoye OC, Shankar R, Soleimani-Meigooni DN, Lago AL, Miller BL, Teunissen CE, Heuer H, Rosen HJ, Dage JL, Jagust WJ, Rabinovici GD, Boxer AL, La Joie R. Head-to-head comparison between plasma p-tau217 and flortaucipir-PET in amyloid-positive patients with cognitive impairment. Alzheimers Res Ther 2023; 15:157. [PMID: 37740209 PMCID: PMC10517500 DOI: 10.1186/s13195-023-01302-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 09/07/2023] [Indexed: 09/24/2023]
Abstract
BACKGROUND Plasma phosphorylated tau (p-tau) has emerged as a promising biomarker for Alzheimer's disease (AD). Studies have reported strong associations between p-tau and tau-PET that are mainly driven by differences between amyloid-positive and amyloid-negative patients. However, the relationship between p-tau and tau-PET is less characterized within cognitively impaired patients with a biomarker-supported diagnosis of AD. We conducted a head-to-head comparison between plasma p-tau217 and tau-PET in patients at the clinical stage of AD and further assessed their relationships with demographic, clinical, and biomarker variables. METHODS We retrospectively included 87 amyloid-positive patients diagnosed with MCI or dementia due to AD who underwent structural MRI, amyloid-PET (11C-PIB), tau-PET (18F-flortaucipir, FTP), and blood draw assessments within 1 year (age = 66 ± 10, 48% female). Amyloid-PET was quantified in Centiloids (CL) while cortical tau-PET binding was measured using standardized uptake value ratios (SUVRs) referenced against inferior cerebellar cortex. Plasma p-tau217 concentrations were measured using an electrochemiluminescence-based assay on the Meso Scale Discovery platform. MRI-derived cortical volume was quantified with FreeSurfer. Mini-Mental State Examination (MMSE) scores were available at baseline (n = 85) and follow-up visits (n = 28; 1.5 ± 0.7 years). RESULTS Plasma p-tau217 and cortical FTP-SUVR were correlated (r = 0.61, p < .001), especially in temporo-parietal and dorsolateral frontal cortices. Both higher p-tau217 and FTP-SUVR values were associated with younger age, female sex, and lower cortical volume, but not with APOE-ε4 carriership. PIB-PET Centiloids were weakly correlated with FTP-SUVR (r = 0.26, p = 0.02), but not with p-tau217 (r = 0.10, p = 0.36). Regional PET-plasma associations varied with amyloid burden, with p-tau217 being more strongly associated with tau-PET in temporal cortex among patients with moderate amyloid-PET burden, and with tau-PET in primary cortices among patients with high amyloid-PET burden. Higher p-tau217 and FTP-SUVR values were independently associated with lower MMSE scores cross-sectionally, while only baseline FTP-SUVR predicted longitudinal MMSE decline when both biomarkers were included in the same model. CONCLUSION Plasma p-tau217 and tau-PET are strongly correlated in amyloid-PET-positive patients with MCI or dementia due to AD, and they exhibited comparable patterns of associations with demographic variables and with markers of downstream neurodegeneration.
Collapse
Affiliation(s)
- Nidhi S Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Julio C Rojas
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lawren Vandevrede
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Elisabeth H Thijssen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Neurodegeneration, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Ranjani Shankar
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Argentina L Lago
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Neurodegeneration, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Hillary Heuer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Howie J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
- Global Brain Health Institute, San Francisco, CA, USA.
| |
Collapse
|
37
|
Jagust WJ, Teunissen CE, DeCarli C. The complex pathway between amyloid β and cognition: implications for therapy. Lancet Neurol 2023; 22:847-857. [PMID: 37454670 DOI: 10.1016/s1474-4422(23)00128-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 03/11/2023] [Accepted: 03/27/2023] [Indexed: 07/18/2023]
Abstract
For decades, the hypothesis that brain deposition of the amyloid β protein initiates Alzheimer's disease has dominated research and clinical trials. Targeting amyloid β is starting to produce therapeutic benefit, although whether amyloid-lowering drugs will be widely and meaningfully effective is still unclear. Despite extensive in-vivo biomarker evidence in humans showing the importance of an amyloid cascade that drives cognitive decline, the amyloid hypothesis does not fully account for the complexity of late-life cognitive impairment. Multiple brain pathological changes, inflammation, and host factors of resilience might also be involved in contributing to the development of dementia. This variability suggests that the benefits of lowering amyloid β might depend on how strongly an amyloid pathway is manifest in an individual in relation to other coexisting pathophysiological processes. A new approach to research and treatment, which fully considers the multiple factors that drive cognitive decline, is necessary.
Collapse
Affiliation(s)
- William J Jagust
- School of Public Health, and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| |
Collapse
|
38
|
Quattrini G, Ferrari C, Pievani M, Geviti A, Ribaldi F, Scheffler M, Frisoni GB, Garibotto V, Marizzoni M. Unsupervised [ 18F]Flortaucipir cutoffs for tau positivity and staging in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2023; 50:3265-3275. [PMID: 37272955 PMCID: PMC10542510 DOI: 10.1007/s00259-023-06280-7] [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: 03/01/2023] [Accepted: 05/19/2023] [Indexed: 06/06/2023]
Abstract
PURPOSE Several [18F]Flortaucipir cutoffs have been proposed for tau PET positivity (T+) in Alzheimer's disease (AD), but none were data-driven. The aim of this study was to establish and validate unsupervised T+ cutoffs by applying Gaussian mixture models (GMM). METHODS Amyloid negative (A-) cognitively normal (CN) and amyloid positive (A+) AD-related dementia (ADRD) subjects from ADNI (n=269) were included. ADNI (n=475) and Geneva Memory Clinic (GMC) cohorts (n=98) were used for validation. GMM-based cutoffs were extracted for the temporal meta-ROI, and validated against previously published cutoffs and visual rating. RESULTS GMM-based cutoffs classified less subjects as T+, mainly in the A- CN (<3.4% vs >28.5%) and A+ CN (<14.5% vs >42.9%) groups and showed higher agreement with visual rating (ICC=0.91 vs ICC<0.62) than published cutoffs. CONCLUSION We provided reliable data-driven [18F]Flortaucipir cutoffs for in vivo T+ detection in AD. These cutoffs might be useful to select participants in clinical and research studies.
Collapse
Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, 25123, Brescia, Italy
| | - Clarissa Ferrari
- FONDAZIONE POLIAMBULANZA ISTITUTO OSPEDALIERO via Bissolati, 57, 25124, Brescia, Italy
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Andrea Geviti
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Federica Ribaldi
- LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Giovanni B Frisoni
- LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocentre, Faculty of Medicine, University of Geneva, 1205, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, 1205, Geneva, Switzerland
- Centre for Biomedical Imaging (CIBM), 1205, Geneva, Switzerland
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
- Biological Psychiatric Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
| |
Collapse
|
39
|
Falgàs N, Walsh CM, Yack L, Simon AJ, Allen IE, Kramer JH, Rosen HJ, Joie RL, Rabinovici G, Miller B, Spina S, Seeley WW, Ranasinghe K, Vossel K, Neylan TC, Grinberg LT. Alzheimer's disease phenotypes show different sleep architecture. Alzheimers Dement 2023; 19:3272-3282. [PMID: 36749893 PMCID: PMC10404632 DOI: 10.1002/alz.12963] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 12/16/2022] [Accepted: 12/22/2022] [Indexed: 02/09/2023]
Abstract
INTRODUCTION Sleep-wake disturbances are a prominent feature of Alzheimer's disease (AD). Atypical (non-amnestic) AD syndromes have different patterns of cortical vulnerability to AD. We hypothesized that atypical AD also shows differential vulnerability in subcortical nuclei that will manifest as different patterns of sleep dysfunction. METHODS Overnight electroencephalography monitoring was performed on 48 subjects, including 15 amnestic, 19 atypical AD, and 14 controls. AD was defined based on neuropathological or biomarker confirmation. We compared sleep architecture by visual scoring and spectral power analysis in each group. RESULTS Overall, AD cases showed increased sleep fragmentation and N1 sleep compared to controls. Compared to atypical AD groups, typical AD showed worse N3 sleep dysfunction and relatively preserved rapid eye movement (REM) sleep. DISCUSSION Results suggest differing effects of amnestic and atypical AD variants on slow wave versus REM sleep, respectively, corroborating the hypothesis of differential selective vulnerability patterns of the subcortical nuclei within variants. Optimal symptomatic treatment for sleep dysfunction in clinical phenotypes may differ. HIGHLIGHTS Alzheimer's disease (AD) variants show distinct patterns of sleep impairment. Amnestic/typical AD has worse N3 slow wave sleep (SWS) impairment compared to atypical AD. Atypical AD shows more rapid eye movement deficits than typical AD. Selective vulnerability patterns in subcortical areas may underlie sleep differences. Relatively preserved SWS may explain better memory scores in atypical versus typical AD.
Collapse
Affiliation(s)
- Neus Falgàs
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Christine M Walsh
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Leslie Yack
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- San Francisco Veterans Affairs Health Care System, San Francisco, California, USA
| | - Alexander J Simon
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Isabel E Allen
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - Joel H Kramer
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Department of Psychiatry, University of California, San Francisco, California, USA
| | - Howard J Rosen
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - Renaud La Joie
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Gil Rabinovici
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Bruce Miller
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - Salvatore Spina
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - William W Seeley
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Kamalini Ranasinghe
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Keith Vossel
- Mary S. Easton Center for Alzheimer's Disease Research, University of California Los Angeles, Los Angeles, California, USA
| | - Thomas C Neylan
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Department of Psychiatry, University of California, San Francisco, California, USA
| | - Lea T Grinberg
- Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Global Brain Health Institute, University of California, San Francisco, California, USA
- Department of Pathology, University of Sao Paulo Medical School, Sao Paulo, Brazil
- Department of Pathology, University of California, San Francisco, California, USA
| |
Collapse
|
40
|
Lamontagne-Kam D, Ulfat AK, Hervé V, Vu TM, Brouillette J. Implication of tau propagation on neurodegeneration in Alzheimer's disease. Front Neurosci 2023; 17:1219299. [PMID: 37483337 PMCID: PMC10360202 DOI: 10.3389/fnins.2023.1219299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 06/07/2023] [Indexed: 07/25/2023] Open
Abstract
Propagation of tau fibrils correlate closely with neurodegeneration and memory deficits seen during the progression of Alzheimer's disease (AD). Although it is not well-established what drives or attenuates tau spreading, new studies on human brain using positron emission tomography (PET) have shed light on how tau phosphorylation, genetic factors, and the initial epicenter of tau accumulation influence tau accumulation and propagation throughout the brain. Here, we review the latest PET studies performed across the entire AD continuum looking at the impact of amyloid load on tau pathology. We also explore the effects of structural, functional, and proximity connectivity on tau spreading in a stereotypical manner in the brain of AD patients. Since tau propagation can be quite heterogenous between individuals, we then consider how the speed and pattern of propagation are influenced by the starting localization of tau accumulation in connected brain regions. We provide an overview of some genetic variants that were shown to accelerate or slow down tau spreading. Finally, we discuss how phosphorylation of certain tau epitopes affect the spreading of tau fibrils. Since tau pathology is an early event in AD pathogenesis and is one of the best predictors of neurodegeneration and memory impairments, understanding the process by which tau spread from one brain region to another could pave the way to novel therapeutic avenues that are efficient during the early stages of the disease, before neurodegeneration induces permanent brain damage and severe memory loss.
Collapse
|
41
|
Williams T, Bathe T, Vo Q, Sacilotto P, McFarland K, Ruiz AJ, Hery GP, Sullivan P, Borchelt DR, Prokop S, Chakrabarty P. Humanized APOE genotypes influence lifespan independently of tau aggregation in the P301S mouse model of tauopathy. Acta Neuropathol Commun 2023; 11:99. [PMID: 37337279 DOI: 10.1186/s40478-023-01581-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 05/09/2023] [Indexed: 06/21/2023] Open
Abstract
Apolipoprotein (APOE) E4 isoform is a major risk factor of Alzheimer's disease and contributes to metabolic and neuropathological abnormalities during brain aging. To provide insights into whether APOE4 genotype is related to tau-associated neurodegeneration, we have generated human P301S mutant tau transgenic mice (PS19) that carry humanized APOE alleles (APOE2, APOE3 or APOE4). In aging mice that succumbed to paralysis, PS19 mice homozygous for APOE3 had the longest lifespan when compared to APOE4 and APOE2 homozygous mice (APOE3 > APOE4 ~ APOE2). Heterozygous mice with one human APOE and one mouse Apoe allele did not show any variations in lifespan. At end-stage, PS19 mice homozygous for APOE3 and APOE4 showed equivalent levels of phosphorylated tau burden, inflammation levels and ventricular volumes. Compared to these cohorts, PS19 mice homozygous for APOE2 showed lower induction of phosphorylation on selective epitopes, though the effect sizes were small and variable. In spite of this, the APOE2 cohort showed shorter lifespan relative to APOE3 homozygous mice. None of the cohorts accumulated appreciable levels of phosphorylated tau compartmentalized in the insoluble cell fraction. RNAseq analysis showed that the induction of immune gene expression was comparable across all the APOE genotypes in PS19 mice. Notably, the APOE4 homozygous mice showed additional induction of transcripts corresponding to the Alzheimer's disease-related plaque-induced gene signature. In human Alzheimer's disease brain tissues, we found no direct correlation between higher burden of phosphorylated tau and APOE4 genotype. As expected, there was a strong correlation between phosphorylated tau burden with amyloid deposition in APOE4-positive Alzheimer's disease cases. Overall, our results indicate that APOE3 genotype may confer some resilience to tauopathy, while APOE4 and APOE2 may act through multiple pathways to increase the pathogenicity in the context of tauopathy.
Collapse
Affiliation(s)
- Tristan Williams
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
- Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA
- Eli Lilly & Company, Indianapolis, IN, 46285, USA
| | - Tim Bathe
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
- Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA
| | - Quan Vo
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
| | - Patricia Sacilotto
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
- Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA
| | - Karen McFarland
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
- Department of Neurology, University of Florida, Gainesville, FL, 32610, USA
| | - Alejandra Jolie Ruiz
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
| | - Gabriela P Hery
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
| | | | - David R Borchelt
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
- Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA
- McKnight Brain Institute, University of Florida, Gainesville, FL, 32610, USA
| | - Stefan Prokop
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA
- Department of Pathology, Immunology & Laboratory Medicine, University of Florida, Gainesville, FL, 32610, USA
- Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, 32608, USA
| | - Paramita Chakrabarty
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, 32610, USA.
- Department of Neuroscience, University of Florida, Gainesville, FL, 32610, USA.
- McKnight Brain Institute, University of Florida, Gainesville, FL, 32610, USA.
| |
Collapse
|
42
|
St-Onge F, Chapleau M, Breitner JCS, Villeneuve S, Binette AP. Tau accumulation and its spatial progression across the Alzheimer's disease spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.02.23290880. [PMID: 37333413 PMCID: PMC10274981 DOI: 10.1101/2023.06.02.23290880] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The spread of tau abnormality in sporadic Alzheimer's disease is believed typically to follow neuropathologically defined Braak staging. Recent in-vivo positron emission tomography (PET) evidence challenges this belief, however, as spreading patterns for tau appear heterogenous among individuals with varying clinical expression of Alzheimer's disease. We therefore sought better understanding of the spatial distribution of tau in the preclinical and clinical phases of sporadic Alzheimer's disease and its association with cognitive decline. Longitudinal tau-PET data (1,370 scans) from 832 participants (463 cognitively unimpaired, 277 with mild cognitive impairment (MCI) and 92 with Alzheimer's disease dementia) were obtained from the Alzheimer's Disease Neuroimaging Initiative. Among these, we defined thresholds of abnormal tau deposition in 70 brain regions from the Desikan atlas, and for each group of regions characteristic of Braak staging. We summed each scan's number of regions with abnormal tau deposition to form a spatial extent index. We then examined patterns of tau pathology cross-sectionally and longitudinally and assessed their heterogeneity. Finally, we compared our spatial extent index of tau uptake with a temporal meta region of interest-a commonly used proxy of tau burden-assessing their association with cognitive scores and clinical progression. More than 80% of amyloid-beta positive participants across diagnostic groups followed typical Braak staging, both cross-sectionally and longitudinally. Within each Braak stage, however, the pattern of abnormality demonstrated significant heterogeneity such that overlap of abnormal regions across participants averaged less than 50%. The annual rate of change in number of abnormal tau-PET regions was similar among individuals without cognitive impairment and those with Alzheimer's disease dementia. Spread of disease progressed more rapidly, however, among participants with MCI. The latter's change on our spatial extent measure amounted to 2.5 newly abnormal regions per year, as contrasted with 1 region/year among the other groups. Comparing the association of tau pathology and cognitive performance in MCI and Alzheimer's disease dementia, our spatial extent index was superior to the temporal meta-ROI for measures of executive function. Thus, while participants broadly followed Braak stages, significant individual regional heterogeneity of tau binding was observed at each clinical stage. Progression of spatial extent of tau pathology appears to be fastest in persons with MCI. Exploring the spatial distribution of tau deposits throughout the entire brain may uncover further pathological variations and their correlation with impairments in cognitive functions beyond memory.
Collapse
Affiliation(s)
- Frédéric St-Onge
- Integrated Program in Neuroscience, Faculty of medicine, McGill University, Montreal, Qc, H3A 2B4, Canada
- Research Center of the Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada
| | - Marianne Chapleau
- Faculty of medicine, University of California San Francisco, San Francisco, CA, 94143, United-States
| | - John CS Breitner
- Research Center of the Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada
- Department of psychiatry, Faculty of medicine, McGill University, Montreal, QC, H3A 1Y2, Canada
| | - Sylvia Villeneuve
- Research Center of the Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada
- Department of psychiatry, Faculty of medicine, McGill University, Montreal, QC, H3A 1Y2, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, H3A 2B4, Canada
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Malmö, 205 02, Sweden
| |
Collapse
|
43
|
Abbate C. The Adult Neurogenesis Theory of Alzheimer's Disease. J Alzheimers Dis 2023:JAD221279. [PMID: 37182879 DOI: 10.3233/jad-221279] [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: 05/16/2023]
Abstract
Alzheimer's disease starts in neural stem cells (NSCs) in the niches of adult neurogenesis. All primary factors responsible for pathological tau hyperphosphorylation are inherent to adult neurogenesis and migration. However, when amyloid pathology is present, it strongly amplifies tau pathogenesis. Indeed, the progressive accumulation of extracellular amyloid-β deposits in the brain triggers a state of chronic inflammation by microglia. Microglial activation has a significant pro-neurogenic effect that fosters the process of adult neurogenesis and supports neuronal migration. Unfortunately, this "reactive" pro-neurogenic activity ultimately perturbs homeostatic equilibrium in the niches of adult neurogenesis by amplifying tau pathogenesis in AD. This scenario involves NSCs in the subgranular zone of the hippocampal dentate gyrus in late-onset AD (LOAD) and NSCs in the ventricular-subventricular zone along the lateral ventricles in early-onset AD (EOAD), including familial AD (FAD). Neuroblasts carrying the initial seed of tau pathology travel throughout the brain via neuronal migration driven by complex signals and convey the disease from the niches of adult neurogenesis to near (LOAD) or distant (EOAD) brain regions. In these locations, or in close proximity, a focus of degeneration begins to develop. Then, tau pathology spreads from the initial foci to large neuronal networks along neural connections through neuron-to-neuron transmission.
Collapse
Affiliation(s)
- Carlo Abbate
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| |
Collapse
|
44
|
de Flores R, Demeilliez-Servouin S, Kuhn E, Chauveau L, Landeau B, Delcroix N, Gonneaud J, Vivien D, Chételat G. Respective influence of beta-amyloid and APOE ε4 genotype on medial temporal lobe subregions in cognitively unimpaired older adults. Neurobiol Dis 2023; 181:106127. [PMID: 37061167 DOI: 10.1016/j.nbd.2023.106127] [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: 01/23/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 04/17/2023] Open
Abstract
Medial temporal lobe (MTL) subregions are differentially affected in Alzheimer's disease (AD), with a specific involvement of the entorhinal cortex (ERC), perirhinal cortex and hippocampal cornu ammonis (CA)1. While amyloid (Aβ) and APOEε4 are respectively the first molecular change and the main genetic risk factor in AD, their links with MTL atrophy remain relatively unclear. Our aim was to uncover these effects using baseline data from 130 participants included in the Age-Well study, for whom ultra-high-resolution structural MRI, amyloid-PET and APOEε4 genotype were available. No volume differences were observed between Aβ + (n = 24) and Aβ- (n = 103), nor between APOE4+ (n = 35) and APOE4- (n = 95) participants. However, our analyses showed that both Aβ and APOEε4 status interacted with age on CA1, which is known to be specifically atrophied in early AD. In addition, APOEε4 status moderated the effects of age on other subregions (subiculum, ERC), suggesting a more important contribution of APOEε4 than Aβ to MTL atrophy in cognitively unimpaired population. These results are crucial to develop MRI-based biomarkers to detect early AD.
Collapse
Affiliation(s)
- Robin de Flores
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France.
| | - Solène Demeilliez-Servouin
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Elizabeth Kuhn
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Léa Chauveau
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Brigitte Landeau
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | | | - Julie Gonneaud
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Denis Vivien
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Gaël Chételat
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| |
Collapse
|
45
|
Best J, Chapleau M, Rabinovici GD. Posterior cortical atrophy: clinical, neuroimaging, and neuropathological features. Expert Rev Neurother 2023; 23:227-236. [PMID: 36920752 DOI: 10.1080/14737175.2023.2190885] [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: 03/16/2023]
Abstract
INTRODUCTION Posterior Cortical Atrophy (PCA) is a neurodegenerative disorder characterized by impairment of higher-order visual processing in the setting of progressive atrophy of the parietal and occipital lobes. The underlying pathology is variable but most commonly Alzheimer's disease. The majority of individuals develop symptoms before 65 years of age; however, delayed diagnosis is common due to misattribution of symptoms to ocular rather than cortical pathology. AREAS COVERED The purpose of this review is to provide readers with an in-depth analysis of Posterior Cortical Atrophy syndrome, including clinical, imaging, pathological, and genetic features, management, and treatments. EXPERT OPINION Most patients present initially with a relatively pure visuoperceptual-visuospatial syndrome, though other cognitive domains become affected over time. Structural neuroimaging demonstrates parieto-occipital or temporo-occipital predominant atrophy. Cerebrospinal fluid Alzheimer's disease biomarkers, or amyloid/tau PET imaging can help evaluate for underlying Alzheimer's disease, which is the most common underlying neuropathology. The cornerstone of management is focused on nonpharmacologic measures. Early etiologic diagnosis is important with the arrival of disease-modifying therapies, especially for Alzheimer's disease.
Collapse
Affiliation(s)
- John Best
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.,Departments of Neurology, Radiology & Biomedical Imaging, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| |
Collapse
|
46
|
Hamza EA, Moustafa AA, Tindle R, Karki R, Nalla S, Hamid MS, El Haj M. Effect of APOE4 Allele and Gender on the Rate of Atrophy in the Hippocampus, Entorhinal Cortex, and Fusiform Gyrus in Alzheimer's Disease. Curr Alzheimer Res 2023; 19:CAR-EPUB-130079. [PMID: 36892120 DOI: 10.2174/1567205020666230309113749] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/21/2023] [Accepted: 02/25/2023] [Indexed: 03/10/2023]
Abstract
BACKGROUND The hippocampus, entorhinal cortex, and fusiform gyrus are brain areas that deteriorate during early-stage Alzheimer's disease (AD). The ApoE4 allele has been identified as a risk factor for AD development, is linked to an increase in the aggregation of amyloid ß (Aß) plaques in the brain, and is responsible for atrophy of the hippocampal area. However, to our knowledge, the rate of deterioration over time in individuals with AD, with or without the ApoE4 allele, has not been investigated. METHOD In this study, we, for the first time, analyze atrophy in these brain structures in AD patients with and without the ApoE4 using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. RESULTS It was found that the rate of decrease in the volume of these brain areas over 12 months was related to the presence of ApoE4. Further, we found that neural atrophy was not different for female and male patients, unlike prior studies, suggesting that the presence of ApoE4 is not linked to the gender difference in AD. CONCLUSION Our results confirm and extend previous findings, showing that the ApoE4 allele gradually impacts brain regions impacted by AD.
Collapse
Affiliation(s)
- Eid Abo Hamza
- Faculty of Education, Department of Mental Health, Tanta University, Egypt
- College of Education, Humanities & Social Sciences, Al Ain University, UAE
| | - Ahmed A Moustafa
- School of Psychology, Faculty of Society and Design, Bond University, Gold Coast, Queensland, Australia
- Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, South Africa
| | - Richard Tindle
- Department of Psychology, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia
| | - Rasu Karki
- Department of Psychology, Western Sydney University, Penrith, NSW, 2214, Australia
| | - Shahed Nalla
- Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, South Africa
| | | | - Mohamad El Haj
- Laboratoire de Psychologie des Pays de la Loire (LPPL - EA 4638), Nantes Université, Univ. Angers., Nantes, F-44000, France
- Clinical Gerontology Department, CHU Nantes, Bd Jacques Monod,Nantes, F44093, France
- Institut Universitaire de France, Paris, France
| |
Collapse
|
47
|
Corriveau-Lecavalier N, Gunter JL, Kamykowski M, Dicks E, Botha H, Kremers WK, Graff-Radford J, Wiepert DA, Schwarz CG, Yacoub E, Knopman DS, Boeve BF, Ugurbil K, Petersen RC, Jack CR, Terpstra MJ, Jones DT. Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease. Brain Commun 2023; 5:fcad058. [PMID: 37013176 PMCID: PMC10066575 DOI: 10.1093/braincomms/fcad058] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 12/15/2022] [Accepted: 03/07/2023] [Indexed: 03/09/2023] Open
Abstract
From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.
Collapse
Affiliation(s)
| | | | - Michael Kamykowski
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Essa Yacoub
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kamil Ugurbil
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Melissa J Terpstra
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Radiology, University of Missouri, Columbia, MO 65211, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| |
Collapse
|
48
|
Singh NA, Tosakulwong N, Graff-Radford J, Machulda MM, Pham NTT, Sintini I, Weigand SD, Schwarz CG, Senjem ML, Carrasquillo MM, Ertekin-Taner N, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. APOE ε4 influences medial temporal atrophy and tau deposition in atypical Alzheimer's disease. Alzheimers Dement 2023; 19:784-796. [PMID: 35691047 PMCID: PMC9742387 DOI: 10.1002/alz.12711] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Apolipoprotein E (APOE) ε4 is an important genetic risk factor for typical Alzheimer's disease (AD), influencing brain volume and tau burden. Little is known about its influence in atypical presentations of AD. METHODS An atypical AD cohort of 140 patients diagnosed with either posterior cortical atrophy or logopenic progressive aphasia underwent magnetic resonance imaging and positron emission tomography. Linear mixed effects models were fit to assess the influence of APOE ε4 on cross-sectional and longitudinal regional metrics. RESULTS At baseline, APOE ε4 carriers had smaller hippocampal and amygdala volumes and greater tau standardized uptake volume ratio in the hippocampus and entorhinal cortex compared to non-carriers while longitudinally, APOE ε4 non-carriers showed faster rates of atrophy and tau accumulation in the entorhinal cortex, with faster tau accumulation in the hippocampus. DISCUSSION APOE ε4 influences patterns of neurodegeneration and tau deposition and was associated with more medial temporal involvement, although there is evidence that non-carriers may be catching up over time.
Collapse
Affiliation(s)
| | | | | | - Mary M. Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Stephen D. Weigand
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | |
Collapse
|
49
|
Based on Tau PET Radiomics Analysis for the Classification of Alzheimer's Disease and Mild Cognitive Impairment. Brain Sci 2023; 13:brainsci13020367. [PMID: 36831910 PMCID: PMC9953966 DOI: 10.3390/brainsci13020367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/06/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are closely associated with Tau proteins accumulation. In this study, we aimed to implement radiomics analysis to discover high-order features from pathological biomarker and improve the classification accuracy based on Tau PET images. Two cross-racial independent cohorts from the ADNI database (121 AD patients, 197 MCI patients and 211 normal control (NC) subjects) and Huashan hospital (44 AD patients, 33 MCI patients and 36 NC subjects) were enrolled. The radiomics features of Tau PET imaging of AD related brain regions were computed for classification using a support vector machine (SVM) model. The radiomics model was trained and validated in the ADNI cohort and tested in the Huashan hospital cohort. The standard uptake value ratio (SUVR) and clinical scores model were also performed to compared with radiomics analysis. Additionally, we explored the possibility of using Tau PET radiomics features as a good biomarker to make binary identification of Tau-negative MCI versus Tau-positive MCI or apolipoprotein E (ApoE) ε4 carrier versus ApoE ε4 non-carrier. We found that the radiomics model demonstrated best classification performance in differentiating AD/MCI patients and NC in comparison to SUVR and clinical scores models, with an accuracy of 84.8 ± 4.5%, 73.1 ± 3.6% in the ANDI cohort. Moreover, the radiomics model also demonstrated greater performance in diagnosing AD than other methods in the Huashan hospital cohort, with an accuracy of 81.9 ± 6.1%. In addition, the radiomics model also showed the satisfactory classification performance in the MCI-tau subgroup experiment (72.3 ± 3.5%, 71.9 ± 3.6% and 63.7 ± 5.9%) and in the MCI-ApoE subgroup experiment (73.5 ± 4.3%, 70.1 ± 3.9% and 62.5 ± 5.4%). In conclusion, our study showed that based on Tau PET radiomics analysis has the potential to guide and facilitate clinical diagnosis, further providing evidence for identifying the risk factors in MCI patients.
Collapse
|
50
|
Yong KXX, Graff-Radford J, Ahmed S, Chapleau M, Ossenkoppele R, Putcha D, Rabinovici GD, Suarez-Gonzalez A, Schott JM, Crutch S, Harding E. Diagnosis and Management of Posterior Cortical Atrophy. Curr Treat Options Neurol 2023; 25:23-43. [PMID: 36820004 PMCID: PMC9935654 DOI: 10.1007/s11940-022-00745-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/10/2023]
Abstract
Purpose of review The study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps. Recent findings Recent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer's disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies. Summary PCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic - pharmacological and non-pharmacological - and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile - visual-spatial - rather than memory-led, predominantly young onset - and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.
Collapse
Affiliation(s)
- Keir X. X. Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | | | - Samrah Ahmed
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire UK
| | - Marianne Chapleau
- Memory and Aging Center, University of California San Francisco, San Francisco, CA USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
| | - Gil D. Rabinovici
- Department of Neurology, Radiology, and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | - Aida Suarez-Gonzalez
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Sebastian Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Emma Harding
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| |
Collapse
|