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Schöll M, Vrillon A, Ikeuchi T, Quevenco FC, Iaccarino L, Vasileva-Metodiev SZ, Burnham SC, Hendrix J, Epelbaum S, Zetterberg H, Palmqvist S. Cutting through the noise: A narrative review of Alzheimer's disease plasma biomarkers for routine clinical use. J Prev Alzheimers Dis 2025:100056. [PMID: 39814656 DOI: 10.1016/j.tjpad.2024.100056] [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: 10/31/2024] [Revised: 12/16/2024] [Accepted: 12/30/2024] [Indexed: 01/18/2025]
Abstract
As novel, anti-amyloid therapies have become more widely available, access to timely and accurate diagnosis has become integral to ensuring optimal treatment of patients with early-stage Alzheimer's disease (AD). Plasma biomarkers are a promising tool for identifying AD pathology; however, several technical and clinical factors need to be considered prior to their implementation in routine clinical use. Given the rapid pace of advancements in the field and the wide array of available biomarkers and tests, this review aims to summarize these considerations, evaluate available platforms, and discuss the steps needed to bring plasma biomarker testing to the clinic. We focus on plasma phosphorylated(p)-tau, specifically plasma p-tau217, as a robust candidate across both primary and secondary care settings. Despite the high performance and robustness demonstrated in research, plasma p-tau217, like all plasma biomarkers, can be affected by analytical and pre-analytical variability as well as patient comorbidities, sex, ethnicity, and race. This review also discusses the advantages of the two-point cut-off approach to mitigating these factors, and the challenges raised by the resulting intermediate range measurements, where clinical guidance is still unclear. Further validation of plasma p-tau217 in heterogeneous, real-world cohorts will help to increase confidence in testing and support establishing a standardized approach. Plasma biomarkers are poised to become a more affordable and less invasive alternative to PET and CSF testing. However, understanding the factors that impact plasma biomarker measurement and interpretation is critical prior to their implementation in routine clinical use.
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Affiliation(s)
- M Schöll
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK; Department of Neuropsychiatry, Sahlgrenska University Hospital, Mölndal, Sweden
| | - A Vrillon
- French Institute of Health and Medical Research (Inserm), Paris, France
| | - T Ikeuchi
- Niigata University Brain Research Institute, Niigata, Japan
| | - F C Quevenco
- Eli Lilly and Company, Indianapolis, IN, United States
| | - L Iaccarino
- Eli Lilly and Company, Indianapolis, IN, United States
| | | | - S C Burnham
- Eli Lilly and Company, Indianapolis, IN, United States
| | - J Hendrix
- Eli Lilly and Company, Indianapolis, IN, United States
| | - S Epelbaum
- Eli Lilly and Company, Indianapolis, IN, United States
| | - H Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - S Palmqvist
- Clinical Memory Research Unit, Clinical Sciences in Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Sweden.
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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.
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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
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Huang KL, Hsiao IT, Huang CW, Huang CG, Chang HI, Huang SH, Lin KJ, Ma MC, Huang CC, Chang CC. The Taiwan-ADNI workflow toward integrating plasma p-tau217 into prediction models for the risk of Alzheimer's disease and tau burden. Alzheimers Dement 2025. [PMID: 39777990 DOI: 10.1002/alz.14297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 09/04/2024] [Accepted: 09/05/2024] [Indexed: 01/11/2025]
Abstract
INTRODUCTION We integrated plasma biomarkers from the Taiwan Alzheimer's Disease Neuroimaging Initiative and propose a workflow to identify individuals showing amyloid-positive positron emission tomography (PET) with low/intermediate tau burden based on [18F]Florzolotau PET-based quantification. METHODS We assessed 361 participants across the Alzheimer's disease (AD) and non-AD continuum and measured plasma phosphorylated tau (p-tau)217, p-tau181, amyloid beta (Aβ)42/40 ratio, neurofilament light chain, and glial fibrillary acidic protein levels at two medical centers. We evaluated the diagnostic potential of these biomarkers. RESULTS Among all plasma biomarkers, p-tau217 had the highest consistency with amyloid PET results (area under the curve = 0.94), and a cutoff value could have reduced the number of confirmatory amyloid PET scans by 57.5%. In amyloid PET-positive cases intending to use anti-amyloid therapy, p-tau217 level, along with clinical parameters, had the highest predictive ability for low/intermediate tau burden. DISCUSSION A two-step workflow based on p-tau217 and confirmatory amyloid PET could accurately classify AD patients showing low/intermediate tau burden. HIGHLIGHTS The emergence of anti-amyloid therapy increases the need to accurately diagnose Alzheimer's disease (AD). The use of plasma biomarkers, especially phosphorylated tau 217 (p-tau217), can help in the diagnosis of AD. P-tau217 is a better predictor of amyloid positron emission tomography (PET) positivity than other core biomarkers. In amyloid PET-positive individuals, p-tau217 can predict tau burden. We propose a two-step workflow to identify AD cases suitable for treatment.
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Affiliation(s)
- Kuo-Lun Huang
- Department of Neurology, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan
| | - Ing-Tsung Hsiao
- Department of Medical Imaging and Radiological Sciences and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
- Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan
| | - Chi-Wei Huang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung City, Taiwan
| | - Chung-Guei Huang
- Department of Medical Laboratory, Linkou Chang Gung Memorial Hospital, Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan
| | - Hsin-I Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung City, Taiwan
| | - Shu-Hua Huang
- Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung City, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan
| | - Mi-Chia Ma
- Department of Statistics, College of Management, National Cheng Kung University, Tainan, Taiwan
| | - Chin-Chang Huang
- Department of Neurology, Linkou Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan
| | - Chiung-Chih Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung City, Taiwan
- School of Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
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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. [PMID: 39776249 DOI: 10.1002/alz.14338] [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: 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.
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Affiliation(s)
- Gil D Rabinovici
- Department of Neurology and Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - David S Knopman
- Mayo Clinic Neurology and Neurosurgery, Rochester, Minnesota, USA
| | - Javier Arbizu
- Department of Nuclear Medicine, University of Navarra Clinic, Pamplona, Spain
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
| | - Kevin J Donohoe
- Nuclear Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Oskar Hansson
- Department of Clinical Sciences Malmö, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Skånes universitetssjukhus, Malmö, Sweden
| | - Peter Herscovitch
- Positron Emission Tomography Department, National Institutes of Health Clinical Center, Bethesda, Maryland, USA
| | - Phillip H Kuo
- Medical Imaging, Medicine, and Biomedical Engineering, University of Arizona, Tucson, Arizona, USA
| | - Jennifer H Lingler
- Department of Health and Community Systems, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Julie C Price
- Department of Radiology, Massachusetts General Hospital, Boston, Charlestown, Massachusetts, USA
| | - Stephen P Salloway
- Department of Neurology and Psychiatry the Warren Alpert School of Medicine at Brown University, Providence, Rhode Island, USA
- Butler Hospital Memory and Aging Program, Providence, Rhode Island, USA
| | | | - Maria C Carrillo
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Keith A Johnson
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Molecular Neuroimaging, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Departments of Neurology and Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
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Khalafi M, Dartora WJ, McIntire LBJ, Butler TA, Wartchow KM, Hojjati SH, Razlighi QR, Shirbandi K, Zhou L, Chen K, Xi K, Banerjee S, Foldi N, Pahlajani S, Glodzik L, Li Y, de Leon MJ, Chiang GC. Diagnostic accuracy of phosphorylated tau217 in detecting Alzheimer's disease pathology among cognitively impaired and unimpaired: A systematic review and meta-analysis. Alzheimers Dement 2024. [PMID: 39711334 DOI: 10.1002/alz.14458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Revised: 11/08/2024] [Accepted: 11/13/2024] [Indexed: 12/24/2024]
Abstract
Our review summarizes the diagnostic accuracy of plasma and cerebrospinal fluid (CSF) phosphorylated tau 217 (p-tau217) in detecting amyloid and tau pathology on positron emission tomography (PET). We systematically reviewed studies that reported the diagnostic accuracy of plasma and CSF p-tau217, searching MEDLINE/PubMed, Scopus, and Web of Science through August 2024. The accuracy of p-tau217 in predicting amyloid and tau pathology on PET was evaluated in 30 studies. Both plasma and CSF p-tau217 effectively detect amyloid and tau PET deposition. Plasma p-tau217 showed 82% sensitivity for detecting amyloid and 83% for tau, with 86% and 83% specificity, respectively. CSF p-tau217 had 79% sensitivity for amyloid and 91% for tau, with 91% and 84% specificity. p-tau217 effectively identifies Alzheimer's disease (AD) pathology. Plasma p-tau217 was comparable to CSF p-tau217 in detecting amyloid deposition on PET. Despite being less sensitive for detecting tau deposition on PET, plasma p-tau217 can be an efficient screening tool for underlying AD pathology. HIGHLIGHTS: Plasma phosphorylated tau 217 (p-tau217) serves as a viable biomarker alternative to cerebrospinal fluid p-tau217 due to the strong concordance between their results. Plasma p-tau217 accurately identifies amyloid and tau positron emission tomography (PET) positivity, exhibiting a low rate of false negatives and positives, thereby establishing it as a reliable diagnostic tool for Alzheimer's disease (AD). Plasma p-tau217 demonstrates slightly higher accuracy in predicting amyloid PET positivity compared to tau PET positivity. Plasma p-tau217 demonstrates higher predictive accuracy in detecting AD pathology among cognitively impaired individuals, compared to cognitively unimpaired individuals, suggesting its enhanced utility as a diagnostic biomarker in clinical settings.
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Affiliation(s)
- Mohammad Khalafi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - William J Dartora
- Lipidomics and Biomarker Discovery Lab, Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Laura Beth J McIntire
- Lipidomics and Biomarker Discovery Lab, Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Tracy A Butler
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Krista M Wartchow
- Lipidomics and Biomarker Discovery Lab, Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Seyed Hani Hojjati
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Qolamreza R Razlighi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Kiarash Shirbandi
- Biomedical Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Liangdong Zhou
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Kewei Chen
- Banner Alzheimer's Institute, Banner Health, Phoenix, Arizona, USA
- College of Health Solutions, Arizona State University, Phoenix, Arizona, USA
| | - Ke Xi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Samprit Banerjee
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Nancy Foldi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Silky Pahlajani
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Lidia Glodzik
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Yi Li
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Mony J de Leon
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
| | - Gloria C Chiang
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, New York, USA
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Trelle AN, Young CB, Vossler H, Ramos Benitez J, Cody KA, Mendiola JH, Swarovski MS, Guen YL, Feinstein I, Butler RR, Channappa D, Romero A, Park J, Shahid-Besanti M, Corso NK, Chau K, Smith AN, Skylar-Scott I, Yutsis MV, Fredericks CA, Tian L, Younes K, Kerchner GA, Deutsch GK, Davidzon GA, Sha SJ, Henderson VW, Longo FM, Greicius MD, Wyss-Coray T, Andreasson KI, Poston KL, Wagner AD, Mormino EC, Wilson EN. Plasma Aβ 42/Aβ 40 is sensitive to early cerebral amyloid accumulation and predicts risk of cognitive decline across the Alzheimer's disease spectrum. Alzheimers Dement 2024. [PMID: 39713875 DOI: 10.1002/alz.14442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 10/24/2024] [Accepted: 10/27/2024] [Indexed: 12/24/2024]
Abstract
INTRODUCTION The availability of amyloid beta (Aβ) targeting therapies for Alzheimer's disease (AD) is increasing the demand for scalable biomarkers that are sensitive to early cerebral Aβ accumulation. METHODS We evaluated fully-automated Lumipulse plasma Aβ42/Aβ40 immunoassays for detecting cerebral Aβ in 457 clinically unimpaired (CU) and clinically impaired (CI) Stanford Alzheimer's Disease Research Center (Stanford ADRC) participants and 186 CU in the Stanford Aging and Memory Study (SAMS). Longitudinal change in ADRC plasma Aβ42/Aβ40 and cognition and cross-sectional associations with SAMS memory and tau positron emission tomography (PET) were examined. RESULTS Plasma Aβ42/Aβ40 exhibited high performance in detecting amyloid positivity defined by PET (area under the curve [AUC]: 0.885, 95% confidence interval [CI]: 0.816-0.955). Once abnomal, plasma Aβ42/Aβ40 remained low and predicted cognitive decline in both CU and CI individuals. Among SAMS CU, plasma Aβ42/Aβ40 was associated with poorer hippocampal-dependent memory and elevated tau accumulation. DISCUSSION Lumipulse plasma Aβ42/Aβ40 is a scalable assay for detection of cerebral Aβ and prediction of risk for cognitive decline across the AD continuum. HIGHLIGHTS Lumipulse plasma amyloid beta (Aβ)42/Aβ40 exhibited high accuracy in detecting amyloid positivity. Plasma amyloid-positive (Aβ+) individuals exhibited stability of Aβ42/Aβ40 over time. Plasma Aβ42/Aβ40 predicted future cognitive decline across the Alzheimer's disease (AD) spectrum. Plasma Aβ42/Aβ40 was sensitive to memory and tau burden in clinically unimpaired older adults.
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Affiliation(s)
- Alexandra N Trelle
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Christina B Young
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Hillary Vossler
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Javier Ramos Benitez
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Karly A Cody
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Justin H Mendiola
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Michelle S Swarovski
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Yann Le Guen
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Palo Alto, California, USA
| | - Igor Feinstein
- Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, California, USA
| | - Robert R Butler
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Divya Channappa
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - America Romero
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jennifer Park
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Marian Shahid-Besanti
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Nicole K Corso
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Kelly Chau
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Amanda N Smith
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Irina Skylar-Scott
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Maya V Yutsis
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | | | - Lu Tian
- Biomedical Data Science and Statistics, Stanford University, Stanford, California, USA
| | - Kyan Younes
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Geoffrey A Kerchner
- Pharma Research and Early Development, F. Hoffmann-La Roche, Ltd., Basel, Switzerland
| | - Gayle K Deutsch
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | | | - Sharon J Sha
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
| | - Victor W Henderson
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- Department of Epidemiology & Population Health, Stanford University, Stanford, California, USA
| | - Frank M Longo
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, California, USA
| | - Michael D Greicius
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, California, USA
| | - Tony Wyss-Coray
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, California, USA
| | - Katrin I Andreasson
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, California, USA
| | - Kathleen L Poston
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, California, USA
- Neurosurgery, Stanford University, Stanford, California, USA
| | - Anthony D Wagner
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- Psychology, Stanford University, Stanford, California, USA
| | - Elizabeth C Mormino
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
| | - Edward N Wilson
- Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, California, USA
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Zilioli A, Rosenberg A, Mohanty R, Matton A, Granberg T, Hagman G, Lötjönen J, Kivipelto M, Westman E. Brain MRI volumetry and atrophy rating scales as predictors of amyloid status and eligibility for anti-amyloid treatment in a real-world memory clinic setting. J Neurol 2024; 272:84. [PMID: 39708177 DOI: 10.1007/s00415-024-12853-9] [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: 08/21/2024] [Revised: 12/02/2024] [Accepted: 12/03/2024] [Indexed: 12/23/2024]
Abstract
Predicting amyloid status is crucial in light of upcoming disease-modifying therapies and the need to identify treatment-eligible patients with Alzheimer's disease. In our study, we aimed to predict CSF-amyloid status and eligibility for anti-amyloid treatment in a memory clinic by (I) comparing the performance of visual/automated rating scales and MRI volumetric analysis and (II) combining MRI volumetric data with neuropsychological tests and APOE4 status. Two hundred ninety patients underwent a comprehensive assessment. The cNeuro cMRI software (Combinostics Oy) provided automated computed rating scales and volumetric analysis. Amyloid status was determined using data-driven CSF biomarker cutoffs (Aβ42/Aβ40 ratio), and eligibility for anti-Aβ treatment was assessed according to recent recommendations published after the FDA approval of the anti-Aβ drug aducanumab. The automated rating scales and volumetric analysis demonstrated higher performance compared to visual assessment in predicting Aβ status, especially for parietal-GCA (AUC = 0.70), MTA (AUC = 0.66) scores, hippocampal (AUC = 0.68), and angular gyrus (AUC = 0.69) volumes, despite low global accuracy. When we combined hippocampal and angular gyrus volumes with RAVLT immediate recall and APOE4 status, we achieved the highest accuracy (AUC = 0.82), which remained high even in predicting anti-Aβ treatment eligibility (AUC = 0.81). Our study suggests that automated analysis of atrophy rating scales and brain volumetry outperforms operator-dependent visual rating scales. When combined with neuropsychological and genetic information, this computerized approach may play a crucial role not only in a research context but also in a real-world memory clinic. This integration results in a high level of accuracy for predicting amyloid-CSF status and anti-Aβ treatment eligibility.
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Affiliation(s)
- A Zilioli
- Department of Neurology, University-Hospital of Parma, Parma, Italy
| | - A Rosenberg
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - R Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - A Matton
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - T Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - G Hagman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | | | - M Kivipelto
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden.
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8
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Eratne D, Collins S, Nestor PJ, Pond D, Velakoulis D, Yates M, Masters CL. Using cerebrospinal fluid biomarkers to diagnose Alzheimer's disease: an Australian perspective. Front Psychiatry 2024; 15:1488494. [PMID: 39703457 PMCID: PMC11656523 DOI: 10.3389/fpsyt.2024.1488494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Accepted: 11/04/2024] [Indexed: 12/21/2024] Open
Abstract
Cerebrospinal fluid (CSF) biomarkers are currently the only clinically validated biofluid diagnostic test for Alzheimer's Disease (AD) available in Australia. Testing of CSF biomarkers via lumbar puncture (LP), including quantification of amyloid-β peptide, total tau protein, and phosphorylated tau, can give insight into underlying pathophysiological changes and provide greater certainty in confirming or excluding the presence of Alzheimer's disease changes compared to standard clinical and radiological assessments. Despite CSF analysis being a safe and cost-effective diagnostic method, the use of CSF biomarkers in the evaluation of potential AD remains limited in Australian clinical practice due to a variety of factors, including regional access challenges, concerns over the perceived invasiveness of LP and a lack of confidence among clinicians in interpreting the results. The advent of disease-modifying therapies as a potential new treatment strategy to reduce the rate of progression in people with AD will drive the demand for early diagnosis of AD. This perspective argues for broader adoption of CSF biomarker testing by providing evidence-based, clinically informed expert guidance on when and why to consider CSF biomarker testing.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry Centre, The Royal Melbourne Hospital, Melbourne, VIC, Australia
- National Dementia Diagnostics Laboratory, The Florey Institute, The University of Melbourne, Melbourne, VIC, Australia
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Steven Collins
- National Dementia Diagnostics Laboratory, The Florey Institute, The University of Melbourne, Melbourne, VIC, Australia
- Department of Medicine The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia
| | - Peter J. Nestor
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
- Mater Public Hospital, South Brisbane, QLD, Australia
| | - Dimity Pond
- Wicking Dementia Research and Teaching Centre, University of Tasmania, Hobart, TAS, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Centre, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Mark Yates
- Grampians Health, Ballarat, VIC, Australia
- Deakin University, Burwood, VIC, Australia
| | - Colin L. Masters
- National Dementia Diagnostics Laboratory, The Florey Institute, The University of Melbourne, Melbourne, VIC, Australia
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Collij LE, Bollack A, La Joie R, Shekari M, Bullich S, Roé‐Vellvé N, Koglin N, Jovalekic A, Garciá DV, Drzezga A, Garibotto V, Stephens AW, Battle M, Buckley C, Barkhof F, Farrar G, Gispert JD. Centiloid recommendations for clinical context-of-use from the AMYPAD consortium. Alzheimers Dement 2024; 20:9037-9048. [PMID: 39564918 PMCID: PMC11667534 DOI: 10.1002/alz.14336] [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: 07/16/2024] [Revised: 09/10/2024] [Accepted: 09/23/2024] [Indexed: 11/21/2024]
Abstract
Amyloid-PET quantification through the tracer-independent Centiloid (CL) scale has emerged as an essential tool for the accurate measurement of amyloid-β (Aβ) pathology in Alzheimer's disease (AD) patients. The AMYPAD consortium set out to integrate existing literature and recent work from the consortium to provide clinical context-of-use recommendations for the CL scale. Compared to histopathology, visual reads, and cerebrospinal fluid, CL quantification accurately reflects the amount of AD pathology. With high certainty, a CL value below 10 excludes the presence of Aβ pathology, while a value above 30 corresponds well with pathological amounts. Values falling in between these two cutoffs ("intermediate range") are related to an increased risk of disease progression. Together, CL quantification is a valuable adjunct to visual assessments of amyloid-PET images. An abnormal amyloid biomarker assessment is a key criterion to determine eligibility for anti-amyloid disease-modifying therapies, and amyloid-PET quantification can add further value by precisely monitoring amyloid clearance, and hence guiding patient management decisions. HIGHLIGHTS: Centiloid (CL) quantification robustly reflects of the amount of Aβ pathology. CL < 10/CL > 30 reflects Aβ-negativity/positivity thresholds with high certainty. CL quantification is a valuable adjunct to visual assessments of amyloid-PET. CL quantification can support trial design and treatment management. CL quantification could support the identification of early or emerging Aβ pathology.
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Affiliation(s)
- Lyduine E. Collij
- Department of Radiology & Nuclear Medicine, Amsterdam UMCVrije UniversiteitAmsterdamThe Netherlands
- Brain ImagingAmsterdam NeuroscienceAmsterdamThe Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of MedicineLund UniversityMalmöSweden
| | - Ariane Bollack
- GE HealthcareChalfont St GilesBuckinghamshireUK
- Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Renaud La Joie
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research CenterPasqual Maragall FoundationWellingtonBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
| | | | | | | | | | - David Valléz Garciá
- Department of Radiology & Nuclear Medicine, Amsterdam UMCVrije UniversiteitAmsterdamThe Netherlands
- Brain ImagingAmsterdam NeuroscienceAmsterdamThe Netherlands
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Institute of Neuroscience and Medicine (INM‐2), Molecular Organization of the Brain, ForschungszentrumJülichGermany
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular ImagingUniversity Hospitals of GenevaGenevaSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
- CIBM Center for Biomedical ImagingLausanneZwitserland
| | | | - Mark Battle
- GE HealthcareChalfont St GilesBuckinghamshireUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam UMCVrije UniversiteitAmsterdamThe Netherlands
- Brain ImagingAmsterdam NeuroscienceAmsterdamThe Netherlands
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Gill Farrar
- GE HealthcareChalfont St GilesBuckinghamshireUK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research CenterPasqual Maragall FoundationWellingtonBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- CIBER Bioingeniería, Biomateriales y Nanomedicina (CIBER‐BBN)MadridSpain
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Quinn JF, Gray NE. Fluid Biomarkers in Dementia Diagnosis. Continuum (Minneap Minn) 2024; 30:1790-1800. [PMID: 39620844 DOI: 10.1212/con.0000000000001497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2024]
Abstract
OBJECTIVE This article familiarizes neurologists with the currently available CSF and plasma biomarkers for the diagnosis of dementia and diagnosis-dependent treatment decisions. LATEST DEVELOPMENTS For Alzheimer disease, the recent US Food and Drug Administration (FDA) approval of monoclonal antibody therapy has increased the urgency of confirming the pathologic diagnosis with biomarkers before initiating therapy. The new availability of disease-modifying therapies also highlights the need for biomarkers to monitor efficacy over time. Both of these needs have been partially addressed by the emergence of improved blood-based biomarkers for Alzheimer disease. Regarding other forms of dementia, the latest development is a CSF assay for aggregated α-synuclein, which permits the biomarker confirmation of synuclein pathology in Lewy body dementia. ESSENTIAL POINTS CSF biomarkers for the diagnosis of Alzheimer disease, Lewy body dementia, and Creutzfeldt-Jakob disease are well established. Blood-based biomarkers for dementia diagnosis are emerging and rapidly evolving. Sensitivity and specificity for diagnosis continue to improve, and they are being incorporated into diagnostic decisions. Fluid biomarkers for monitoring the efficacy of therapy are not yet established. Because serial CSF examinations are impractical, the validation of blood-based biomarkers of disease activity will be critical for addressing this unmet need.
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11
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Imbimbo BP, Lista S, Imbimbo C, Nisticò R. Are we close to using Alzheimer blood biomarkers in clinical practice? Neural Regen Res 2024; 19:2583-2585. [PMID: 38808992 PMCID: PMC11168525 DOI: 10.4103/nrr.nrr-d-23-01945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/03/2024] [Accepted: 01/16/2024] [Indexed: 05/30/2024] Open
Affiliation(s)
- Bruno P. Imbimbo
- Department of Research & Development, Chiesi Farmaceutici, Parma, Italy
| | - Simone Lista
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain
| | - Camillo Imbimbo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Robert Nisticò
- School of Pharmacy, University of Rome “Tor Vergata”, Rome, Italy
- Laboratory of Pharmacology of Synaptic Plasticity, EBRI Rita Levi-Montalcini Foundation, Rome, Italy
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12
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Kovacech B, Cullen NC, Novak P, Hanes J, Kontsekova E, Katina S, Parrak V, Fresser M, Vanbrabant J, Feldman HH, Winblad B, Stoops E, Vanmechelen E, Zilka N. Post hoc analysis of ADAMANT, a phase 2 clinical trial of active tau immunotherapy with AADvac1 in patients with Alzheimer's disease, positive for plasma p-tau217. Alzheimers Res Ther 2024; 16:254. [PMID: 39580468 PMCID: PMC11585249 DOI: 10.1186/s13195-024-01620-7] [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: 09/13/2024] [Accepted: 11/11/2024] [Indexed: 11/25/2024]
Abstract
BACKGROUND The spread of tau pathology closely correlates with the disease course and cognitive decline in Alzheimer's disease (AD). Tau-targeting immunotherapies are being developed to stop the spread of tau pathology and thus halt disease progression. In this post hoc analysis of the ADAMANT clinical trial, we examined the performance of AADvac1, an active immunotherapy targeting the microtubule-binding region (MTBR) of tau, in a subgroup of participants with elevated plasma p-tau217, indicating AD-related neuropathological changes. METHODS ADAMANT was a 24-month, randomized, placebo-controlled, parallel-group, double-blinded, multicenter, phase 2 clinical trial in subjects with mild AD. The trial participants were randomized 3:2 to receive six doses of AADvac1 or placebo at 4-week intervals, followed by five booster doses at 14-week intervals. The primary outcome was safety. The secondary outcomes were the Clinical Dementia Rating-Sum of Boxes (CDR-SB), the Alzheimer's Disease Cooperative Study - Activities of Daily Living score for Mild Cognitive Impairment 18-item version (ADCS-ADL-MCI-18), and immunogenicity. Volumetric MRI, plasma neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were exploratory outcomes. The inclusion criterion for this post-hoc analysis was a baseline plasma p-tau217 level above the cutoff for AD. RESULTS Among 196 ADAMANT participants, 137 were positive for plasma p-tau217 (mean age 71.4 years, 59% women). AADvac1 was safe and well tolerated in this subgroup. AADvac1 reduced the rate of accumulation of log-plasma NfL by 56% and that of GFAP by 73%. The treatment differences in the CDR-SB and ADCS-ADL-MCI-18 scores favored AADvac1 but were not statistically significant. AADvac1 had no effect on whole-brain volume but nonsignificantly reduced the loss of brain cortical tissue in several regions. Importantly, the impact on the study outcomes was more pronounced in participants with higher anti-tau antibody levels. CONCLUSIONS These results suggest that AADvac1 tau immunotherapy can reduce plasma biomarkers of neurodegeneration and neuroinflammation. These findings and possible observations on brain atrophy and cognition are hypothesis-generating and warrant further evaluation in a larger clinical trial. TRIAL REGISTRATION EudraCT 2015-000630-30 (primary) and NCT02579252.
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Affiliation(s)
- Branislav Kovacech
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia.
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Clinical Research Centre, Jan Waldenströms Gata 35, 202 13, Malmö, Sweden
| | - Petr Novak
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia
| | - Jozef Hanes
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia
| | - Eva Kontsekova
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102 Bratislava, Slovakia and Institute of Neuroimmunology, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84510, Slovakia
| | - Stanislav Katina
- Department of Mathematics and Statistics, Axon Neuroscience R&D Services SE, Bratislava, Slovakia, and (current) Masaryk University, Kotlářská 267/2, Brno, 611 37, Czech Republic
| | - Vojtech Parrak
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia
| | - Michal Fresser
- Axon Neuroscience SE, 4 Arch. Makariou & Kalogreon, 6016, Larnaca, Cyprus
| | | | - Howard H Feldman
- Department of Neurosciences, Alzheimer's Disease Cooperative Study, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Bengt Winblad
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, BioClinicum, 171 64, Solna, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 141 86, Stockholm, Sweden
| | - Erik Stoops
- ADx NeuroSciences NV, Technologiepark 6, 9052, Ghent, Belgium
| | | | - Norbert Zilka
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia.
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13
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Barbosa BJAP, Resende EDPF, Castilhos RM, Borelli WV, Frota NAF, Balthazar MLF, Amato ACS, Smid J, Barbosa MT, Coutinho AM, de Souza LC, Schilling LP, da Silva MNM, Fernandes GBP, Bertolucci PHF, Nitrini R, Engelhardt E, Forlenza OV, Caramelli P, Brucki SMD, Studart A. Use of anti-amyloid therapies for Alzheimer's disease in Brazil: a position paper from the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Dement Neuropsychol 2024; 18:e2024C002. [PMID: 39534440 PMCID: PMC11556288 DOI: 10.1590/1980-5764-dn-2024-c002] [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: 08/14/2024] [Accepted: 08/19/2024] [Indexed: 11/16/2024] Open
Abstract
Novel therapies for Alzheimer's disease, particularly anti-amyloid drugs like lecanemab and donanemab, have shown modest clinical benefits but also significant risks. The present paper highlights the challenges of access to diagnosis, cost-effectiveness, safety, and the need for more representation of diverse populations in clinical trials. Recommendations include careful patient selection, risk-benefit analysis, and the importance of proven amyloid pathology for treatment. Future work involves further research on anti-amyloid therapies in Brazil and the development of more effective treatments for Alzheimer's disease.
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Affiliation(s)
- Breno José Alencar Pires Barbosa
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal de Pernambuco, Centro de Ciências Médicas, Área Acadêmica de Neuropsiquiatria, Recife PE, Brazil
- Universidade Federal de Pernambuco, Hospital das Clínicas, Empresa Brasileira de Serviços Hospitalares, Serviço de Neurologia, Recife PE, Brazil
| | - Elisa de Paula França Resende
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal de Minas Gerais, Faculdade de Medicina, Unidade de Neurologia Cognitiva e do Comportamento, Belo Horizonte MG, Brazil
| | - Raphael Machado Castilhos
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Hospital de Clínicas de Porto Alegre, Serviço de Neurologia, Centro de Neurologia Cognitiva e Comportamental, Porto Alegre RS, Brazil
| | - Wyllians Vendramini Borelli
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal do Rio Grande do Sul, Instituto de Ciências Básicas da Saúde, Departamento de Ciências Morfológicas, Porto Alegre RS, Brazil
| | - Norberto Anízio Ferreira Frota
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Hospital Geral de Fortaleza, Serviço de Neurologia, Fortaleza CE, Brazil
- Universidade de Fortaleza, Fortaleza CE, Brazil
| | - Marcio Luiz Figueredo Balthazar
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Departamento de Neurologia, Campinas SP, Brazil
| | - Augusto Celso Scarparo Amato
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Departamento de Radiologia, Campinas SP, Brazil
| | - Jerusa Smid
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brazil
| | - Maira Tonidandel Barbosa
- Universidade Federal de Minas Gerais, Faculdade de Medicina, Unidade de Neurologia Cognitiva e do Comportamento, Belo Horizonte MG, Brazil
| | - Artur Martins Coutinho
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Instituto de Radiologia, Centro de Medicina Nuclear, Laboratório de Investigação Médica (LIM 43), São Paulo SP, Brazil
- Hospital Sírio-Libanês, Medicina Nuclear e Serviço de PET-CT, São Paulo SP, Brazil
| | - Leonardo Cruz de Souza
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal de Minas Gerais, Faculdade de Medicina, Unidade de Neurologia Cognitiva e do Comportamento, Belo Horizonte MG, Brazil
| | - Lucas Porcello Schilling
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Pontifícia Universidade do Rio Grande do Sul, Escola de Medicina, Serviço de Neurologia, Porto Alegre RS, Brazil
| | - Mari Nilva Maia da Silva
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Hospital Nina Rodrigues, Serviço de Neuropsiquiatria, São Luís MA, Brazil
| | | | - Paulo Henrique Ferreira Bertolucci
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal de São Paulo, Escola Paulista de Medicina, Departamento de Neurologia e Neurocirurgia, São Paulo SP, Brazil
| | - Ricardo Nitrini
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brazil
| | - Eliasz Engelhardt
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal do Rio de Janeiro, Instituto de Neurologia Deolindo Couto, Rio de Janeiro RJ, Brazil
- Universidade Federal do Rio de Janeiro, Instituto de Psiquiatria, Rio de Janeiro RJ, Brazil
| | - Orestes Vicente Forlenza
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Instituto de Psiquiatria, Laboratório de Neurociências, São Paulo SP, Brazil
| | - Paulo Caramelli
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade Federal de Minas Gerais, Faculdade de Medicina, Unidade de Neurologia Cognitiva e do Comportamento, Belo Horizonte MG, Brazil
| | - Sonia Maria Dozzi Brucki
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brazil
| | - Adalberto Studart
- Academia Brasileira de Neurologia, Departamento Científico de Neurologia Cognitiva e do Envelhecimento, São Paulo SP, Brazil
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brazil
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Woo MS, Therriault J, Jonaitis EM, Wilson R, Langhough RE, Rahmouni N, Benedet AL, Ashton NJ, Tissot C, Lantero-Rodriguez J, Macedo AC, Servaes S, Wang YT, Arias JF, Hosseini SA, Betthauser TJ, Lussier FZ, Hopewell R, Triana-Baltzer G, Kolb HC, Jeromin A, Kobayashi E, Massarweh G, Friese MA, Klostranec J, Vilali P, Pascoal TA, Gauthier S, Zetterberg H, Blennow K, Johnson SC, Rosa-Neto P. Identification of late-stage tau accumulation using plasma phospho-tau217. EBioMedicine 2024; 109:105413. [PMID: 39500009 PMCID: PMC11570195 DOI: 10.1016/j.ebiom.2024.105413] [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: 04/10/2024] [Revised: 10/02/2024] [Accepted: 10/08/2024] [Indexed: 11/17/2024] Open
Abstract
BACKGROUND Blood-based disease staging across the Alzheimer's disease (AD) continuum holds the promise to identify individuals that profit from disease-modifying therapies. We set out to identify Braak V+ (Braak V and/or VI) tau PET-positive individuals within amyloid-β (Aβ)-positive individuals using plasma biomarkers. METHODS In this cross-sectional study, we assessed 289 individuals from the TRIAD cohort and 306 individuals from the WRAP study across the AD continuum. The participants were evaluated by amyloid-PET with [18F]AZD4694 or [11C]PiB and tau-PET with [18F]MK6240 and measured plasma levels included total tau, phospho-tau isoforms (pTau) pTau-181, pTau-217, pTau-231, and N-terminal tau (NTA-tau). We evaluated the performances of plasma biomarkers using different analytic platforms to predict Braak V+ positivity in Aβ+ individuals. FINDINGS Highest associations with Braak V+ tau positivity in Aβ+ individuals were found for plasma pTau-217+Janssen (AUC [CI95%] = 0.97 [0.94, 1.0]) and ALZpath pTau-217 (AUC [CI95%] = 0.93 [0.86, 1.0]) in TRIAD. Plasma ALZpath pTau-217 separated Braak V+ tau PET-positive individuals in the WRAP longitudinal study (AUC [CI95%] = 0.97 [0.94, 1.0]). INTERPRETATION Thus, we demonstrate that using adjusted cut-offs, plasma pTau-217 identifies individuals with later Braak stage tau accumulation which will be helpful to stratify patients for treatments and clinical studies. FUNDING This research is supported by the Weston Brain Institute, Canadian Institutes of Health Research (CIHR) [MOP-11-51-31; RFN 152985, 159815, 162303], Canadian Consortium of Neurodegeneration and Aging (CCNA; MOP-11-51-31 -team 1), the Alzheimer's Association [NIRG-12-92090, NIRP-12-259245], Brain Canada Foundation (CFI Project 34874; 33397), the Fonds de Recherche du Québec-Santé (FRQS; Chercheur Boursier, 2020-VICO-279314). P.R-N and SG are members of the CIHR-CCNA Canadian Consortium of Neurodegeneration in Aging. Colin J. Adair Charitable Foundation.
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Affiliation(s)
- Marcel S Woo
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Centre Hamburg Eppendorf, 20251, Hamburg, Germany; Department of Neurology, University Medical Centre Hamburg Eppendorf, 20251, Hamburg, Germany; Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada.
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada; Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53726, USA
| | - Rachael Wilson
- Wisconsin Alzheimer's Disease Research Centre, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA
| | - Rebecca E Langhough
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53726, USA
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada
| | - Andrea Lessa Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, S-431 80, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, S-431 80, Mölndal, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 40530, Gothenburg, Sweden
| | - Cécile Tissot
- Molecular Biophysics and Integrated Bioimaging Department, Lawrence Berkeley National Laboratory, Berkeley, 510, CA, USA
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, S-431 80, Mölndal, Sweden
| | - Arthur C Macedo
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada; Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada; Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Jaime Fernandez Arias
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada
| | - Seyyed Ali Hosseini
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53726, USA
| | - Firoza Z Lussier
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - Robert Hopewell
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Medical Innovation (formerly Janssen Research & Development), La Jolla, CA, 92121, USA
| | - Hartmuth C Kolb
- Neuroscience Biomarkers, Johnson and Johnson Medical Innovation (formerly Janssen Research & Development), La Jolla, CA, 92121, USA
| | | | - Eliane Kobayashi
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, S-431 80, Mölndal, Sweden
| | - Gassan Massarweh
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Manuel A Friese
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Centre Hamburg Eppendorf, 20251, Hamburg, Germany
| | - Jesse Klostranec
- Montreal Neurologic Institute and Hospital, Department of Diagnostic and Interventional Neuroradiology, McGill University Health Centre, 3801 Rue University, Montréal, QC, H3A 2B4, Canada
| | - Paolo Vilali
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada; Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Tharick A Pascoal
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada; Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada
| | - Henrik Zetterberg
- Wisconsin Alzheimer's Disease Research Centre, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA; Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, S-431 80, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-431 80, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1E 6BT, UK; UK Dementia Research Institute at UCL, London, WC1E 6BT, UK; Hong Kong Centre for Neurodegenerative Diseases, Clear Water Bay, 518172 Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, S-431 80, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-431 80, Mölndal, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, 53726, USA; Wisconsin Alzheimer's Disease Research Centre, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53726, USA
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, QC H4H 1R3, Canada; Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, QC H3A 1A1, Canada.
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15
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Schindler SE, Petersen KK, Saef B, Tosun D, Shaw LM, Zetterberg H, Dage JL, Ferber K, Triana‐Baltzer G, Du‐Cuny L, Li Y, Coomaraswamy J, Baratta M, Mordashova Y, Saad ZS, Raunig DL, Ashton NJ, Meyers EA, Rubel CE, Rosenbaugh EG, Bannon AW, Potter WZ. Head-to-head comparison of leading blood tests for Alzheimer's disease pathology. Alzheimers Dement 2024; 20:8074-8096. [PMID: 39394841 PMCID: PMC11567821 DOI: 10.1002/alz.14315] [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: 06/06/2024] [Revised: 09/10/2024] [Accepted: 09/11/2024] [Indexed: 10/14/2024]
Abstract
INTRODUCTION Blood tests have the potential to improve the accuracy of Alzheimer's disease (AD) clinical diagnosis, which will enable greater access to AD-specific treatments. This study compared leading commercial blood tests for amyloid pathology and other AD-related outcomes. METHODS Plasma samples from the Alzheimer's Disease Neuroimaging Initiative were assayed with AD blood tests from C2N Diagnostics, Fujirebio Diagnostics, ALZPath, Janssen, Roche Diagnostics, and Quanterix. Outcomes measures were amyloid positron emission tomography (PET), tau PET, cortical thickness, and dementia severity. Logistic regression models assessed the classification accuracies of individual or combined plasma biomarkers for binarized outcomes, and Spearman correlations evaluated continuous relationships between individual plasma biomarkers and continuous outcomes. RESULTS Measures of plasma p-tau217, either individually or in combination with other plasma biomarkers, had the strongest relationships with all AD outcomes. DISCUSSION This study identified the plasma biomarker analytes and assays that most accurately classified amyloid pathology and other AD-related outcomes. HIGHLIGHTS Plasma p-tau217 measures most accurately classified amyloid and tau status. Plasma Aβ42/Aβ40 had relatively low accuracy in classification of amyloid status. Plasma p-tau217 measures had higher correlations with cortical thickness than NfL. Correlations of plasma biomarkers with dementia symptoms were relatively low.
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Affiliation(s)
| | - Kellen K. Petersen
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Benjamin Saef
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Duygu Tosun
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Henrik Zetterberg
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCLLondonUK
- Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyQueen SquareLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Jeffrey L. Dage
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
- Stark Neurosciences Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - Kyle Ferber
- Biogen, Biomarkers GroupCambridgeMassachusettsUSA
| | - Gallen Triana‐Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative MedicineSan DiegoCaliforniaUSA
| | - Lei Du‐Cuny
- AbbVieLudwigshafen am RheinRheinland‐PfalzGermany
| | - Yan Li
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | | | | | | | - Ziad S. Saad
- Neuroscience Biomarkers, Johnson and Johnson Innovative MedicineSan DiegoCaliforniaUSA
| | | | - Nicholas J. Ashton
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Banner Alzheimer's InstitutePhoenixArizonaUSA
- Banner Sun Health Research InstituteSun CityArizonaUSA
| | | | | | - Erin G. Rosenbaugh
- The Foundation for the National Institutes of HealthNorth BethesdaMarylandUSA
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16
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Warmenhoven N, Salvadó G, Janelidze S, Mattsson-Carlgren N, Bali D, Orduña Dolado A, Kolb H, Triana-Baltzer G, Barthélemy NR, Schindler SE, Aschenbrenner AJ, Raji CA, Benzinger TLS, Morris JC, Ibanez L, Timsina J, Cruchaga C, Bateman RJ, Ashton N, Arslan B, Zetterberg H, Blennow K, Pichet Binette A, Hansson O. A comprehensive head-to-head comparison of key plasma phosphorylated tau 217 biomarker tests. Brain 2024:awae346. [PMID: 39468767 DOI: 10.1093/brain/awae346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/23/2024] [Accepted: 10/26/2024] [Indexed: 10/30/2024] Open
Abstract
Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarker for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort, including both cognitively unimpaired and cognitively impaired individuals, were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU] and p-tau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, the FDA-approved p-tau181/Aβ42Elecsys, and p-tau181Elecsys. All plasma p-tau217 tests exhibited a high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (Pdiff<0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (Pdiff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (Pdiff=0.025). Plasma %p-tau217WashU exhibited stronger associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more associated with Aβ-PET load than plasma p-tau217Janssen (Pdiff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all Pdiff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; Pdiff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217NULISA showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test, which needs to be determined by future reviews incorporating results from multiple cohorts.
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Affiliation(s)
- Noëlle Warmenhoven
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, 205 02, Malmö, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, 223 62, Lund, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
| | - Anna Orduña Dolado
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA 92123, USA
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA 92123, USA
| | - Nicolas R Barthélemy
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Andrew J Aschenbrenner
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Cyrus A Raji
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis 63110, MO, USA
| | - Tammie L S Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis 63110, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO 63110, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO 63110, USA
| | - Randall J Bateman
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63108, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Nicholas Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, 431 39, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute, London, SE5 9RT, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London SE5 8AF, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, 4011, Stavanger, Norway
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, 431 39, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, 431 39, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 80, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London W1T 7NF, UK
- Hong Kong Center for Neurodegenerative Diseases, 17 Science Park W Ave, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792-2420, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, 431 39, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 80, Mölndal, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 211 46, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, 205 02, Malmö, Sweden
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17
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Lehmann S, Schraen-Maschke S, Vidal JS, Delaby C, Buee L, Blanc F, Paquet C, Allinquant B, Bombois S, Gabelle A, Hanon O. Clinical value of plasma ALZpath pTau217 immunoassay for assessing mild cognitive impairment. J Neurol Neurosurg Psychiatry 2024; 95:1046-1053. [PMID: 38658136 PMCID: PMC11503049 DOI: 10.1136/jnnp-2024-333467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 04/04/2024] [Indexed: 04/26/2024]
Abstract
BACKGROUND Among plasma biomarkers for Alzheimer's disease (AD), pTau181 and pTau217 are the most promising. However, transition from research to routine clinical use will require confirmation of clinical performance in prospective cohorts and evaluation of cofounding factors. METHOD pTau181 and pTau217 were quantified using, Quanterix and ALZpath, SIMOA assays in the well-characterised prospective multicentre BALTAZAR (Biomarker of AmyLoid pepTide and AlZheimer's diseAse Risk) cohort of participants with mild cognitive impairment (MCI). RESULTS Among participants with MCI, 55% were Aβ+ and 29% developed dementia due to AD. pTau181 and pTau217 were higher in the Aβ+ population with fold change of 1.5 and 2.7, respectively. MCI that converted to AD also had higher levels than non-converters, with HRs of 1.38 (1.26 to 1.51) for pTau181 compared with 8.22 (5.45 to 12.39) for pTau217. The area under the curve for predicting Aβ+ was 0.783 (95% CI 0.721 to 0.836; cut-point 2.75 pg/mL) for pTau181 and 0.914 (95% CI 0.868 to 0.948; cut-point 0.44 pg/mL) for pTau217. The high predictive power of pTau217 was not improved by adding age, sex and apolipoprotein E ε4 (APOEε4) status, in a logistic model. Age, APOEε4 and renal dysfunction were associated with pTau levels, but the clinical performance of pTau217 was only marginally altered by these factors. Using a two cut-point approach, a 95% positive predictive value for Aβ+ corresponded to pTau217 >0.8 pg/mL and a 95% negative predictive value at <0.23 pg/mL. At these two cut-points, the percentages of MCI conversion were 56.8% and 9.7%, respectively, while the annual rates of decline in Mini-Mental State Examination were -2.32 versus -0.65. CONCLUSIONS Plasma pTau217 and pTau181 both correlate with AD, but the fold change in pTau217 makes it better to diagnose cerebral amyloidosis, and predict cognitive decline and conversion to AD dementia.
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Affiliation(s)
- Sylvain Lehmann
- LBPC-PPC, Université de Montpellier, INM INSERM, IRMB CHU de Montpellier, Montpellier, France
| | - Susanna Schraen-Maschke
- Université Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, F-59000, Lille, France
| | - Jean-Sébastien Vidal
- Université Paris Cité, EA 4468, APHP, Hospital Broca, Memory Resource and Research Centre of de Paris-Broca-Ile de France, F-75013, Paris, Île-de-France, France
| | - Constance Delaby
- LBPC-PPC, Université de Montpellier, INM INSERM, IRMB CHU de Montpellier, Montpellier, France
- Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau - Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Luc Buee
- Université Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, F-59000, Lille, France
| | - Frédéric Blanc
- Université de Strasbourg, Hôpitaux Universitaires de Strasbourg, Memory Resource and Research Centre of Strasbourg/Colmar, French National Centre for Scientific Research (CNRS), ICube Laboratory and Fédération de Médecine Translationnelle de Strasbourg (FMTS), Team Imagerie Multimodale Intégrative en Santé (IMIS)/Neurocrypto, F-67000, Strasbourg, France
| | - Claire Paquet
- Université Paris Cité, GHU APHP Nord Lariboisière Fernand Widal, Centre de Neurologie Cognitive, F-75010, Paris, France
| | - Bernadette Allinquant
- UMR-S1266, Université Paris Cité, Institute of Psychiatry and Neuroscience, Inserm, Paris, France
| | - Stéphanie Bombois
- Université Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, F-59000, Lille, France
- Assistance Publique-Hôpitaux de Paris (AP-HP), Département de Neurologie, Centre des Maladies Cognitives et Comportementales, GH Pitié-Salpêtrière, Paris, France
| | - Audrey Gabelle
- Université de Montpellier, Memory Research and Resources center, department of Neurology, Inserm INM NeuroPEPs team, F-34000, Montpellier, France
| | - Olivier Hanon
- Université Paris Cité, EA 4468, APHP, Hospital Broca, Memory Resource and Research Centre of de Paris-Broca-Ile de France, F-75013, Paris, Île-de-France, France
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Palmqvist S, Tideman P, Mattsson-Carlgren N, Schindler SE, Smith R, Ossenkoppele R, Calling S, West T, Monane M, Verghese PB, Braunstein JB, Blennow K, Janelidze S, Stomrud E, Salvadó G, Hansson O. Blood Biomarkers to Detect Alzheimer Disease in Primary Care and Secondary Care. JAMA 2024; 332:1245-1257. [PMID: 39068545 PMCID: PMC11284636 DOI: 10.1001/jama.2024.13855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 06/27/2024] [Indexed: 07/30/2024]
Abstract
Importance An accurate blood test for Alzheimer disease (AD) could streamline the diagnostic workup and treatment of AD. Objective To prospectively evaluate a clinically available AD blood test in primary care and secondary care using predefined biomarker cutoff values. Design, Setting, and Participants There were 1213 patients undergoing clinical evaluation due to cognitive symptoms who were examined between February 2020 and January 2024 in Sweden. The biomarker cutoff values had been established in an independent cohort and were applied to a primary care cohort (n = 307) and a secondary care cohort (n = 300); 1 plasma sample per patient was analyzed as part of a single batch for each cohort. The blood test was then evaluated prospectively in the primary care cohort (n = 208) and in the secondary care cohort (n = 398); 1 plasma sample per patient was sent for analysis within 2 weeks of collection. Exposure Blood tests based on plasma analyses by mass spectrometry to determine the ratio of plasma phosphorylated tau 217 (p-tau217) to non-p-tau217 (expressed as percentage of p-tau217) alone and when combined with the amyloid-β 42 and amyloid-β 40 (Aβ42:Aβ40) plasma ratio (the amyloid probability score 2 [APS2]). Main Outcomes and Measures The primary outcome was AD pathology (determined by abnormal cerebrospinal fluid Aβ42:Aβ40 ratio and p-tau217). The secondary outcome was clinical AD. The positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and area under the curve (AUC) values were calculated. Results The mean age was 74.2 years (SD, 8.3 years), 48% were women, 23% had subjective cognitive decline, 44% had mild cognitive impairment, and 33% had dementia. In both the primary care and secondary care assessments, 50% of patients had AD pathology. When the plasma samples were analyzed in a single batch in the primary care cohort, the AUC was 0.97 (95% CI, 0.95-0.99) when the APS2 was used, the PPV was 91% (95% CI, 87%-96%), and the NPV was 92% (95% CI, 87%-96%); in the secondary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 83%-93%), and the NPV was 87% (95% CI, 82%-93%). When the plasma samples were analyzed prospectively (biweekly) in the primary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 81%-94%), and the NPV was 90% (95% CI, 84%-96%); in the secondary care cohort, the AUC was 0.97 (95% CI, 0.95-0.98) when the APS2 was used, the PPV was 91% (95% CI, 87%-95%), and the NPV was 91% (95% CI, 87%-95%). The diagnostic accuracy was high in the 4 cohorts (range, 88%-92%). Primary care physicians had a diagnostic accuracy of 61% (95% CI, 53%-69%) for identifying clinical AD after clinical examination, cognitive testing, and a computed tomographic scan vs 91% (95% CI, 86%-96%) using the APS2. Dementia specialists had a diagnostic accuracy of 73% (95% CI, 68%-79%) vs 91% (95% CI, 88%-95%) using the APS2. In the overall population, the diagnostic accuracy using the APS2 (90% [95% CI, 88%-92%]) was not different from the diagnostic accuracy using the percentage of p-tau217 alone (90% [95% CI, 88%-91%]). Conclusions and Relevance The APS2 and percentage of p-tau217 alone had high diagnostic accuracy for identifying AD among individuals with cognitive symptoms in primary and secondary care using predefined cutoff values. Future studies should evaluate how the use of blood tests for these biomarkers influences clinical care.
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Affiliation(s)
- Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Pontus Tideman
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Neurology Clinic, Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Susanna Calling
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Malmö, Sweden
- University Clinic Primary Care, Skåne, Sweden
| | - Tim West
- C2N Diagnostics LLC, St Louis, Missouri
| | | | | | | | - Kaj Blennow
- Paris Brain Institute, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Lab, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | - 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
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Salloway S, Rowe C, Burns JM. Are Blood Tests for Alzheimer Disease Ready for Prime Time? JAMA 2024; 332:1240-1241. [PMID: 39068544 DOI: 10.1001/jama.2024.12814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Affiliation(s)
- Stephen Salloway
- Departments of Psychiatry and Neurology, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Christopher Rowe
- Department of Molecular Imaging, Austin Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Australian Dementia Network, University of Melbourne, Melbourne, Australia
| | - Jeffrey M Burns
- Alzheimer's Disease Research Center, University of Kansas Medical Center, Lawrence
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20
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Martino-Adami PV, Chatterjee M, Kleineidam L, Weyerer S, Bickel H, Wiese B, Riedel-Heller SG, Scherer M, Blennow K, Zetterberg H, Wagner M, Schneider A, Ramirez A. Prognostic value of Alzheimer's disease plasma biomarkers in the oldest-old: a prospective primary care-based study. THE LANCET REGIONAL HEALTH. EUROPE 2024; 45:101030. [PMID: 39253733 PMCID: PMC11381503 DOI: 10.1016/j.lanepe.2024.101030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 07/26/2024] [Accepted: 07/30/2024] [Indexed: 09/11/2024]
Abstract
Background Blood-based biomarkers offer a promising, less invasive, and more cost-effective alternative for Alzheimer's disease screening compared to cerebrospinal fluid or imaging biomarkers. However, they have been extensively studied only in memory clinic-based cohorts. We aimed to validate them in a more heterogeneous, older patient population from primary care. Methods We measured plasma Aβ42/Aβ40, P-tau181, NfL, and GFAP in 1007 individuals without dementia, aged 79-94 years, from the longitudinal, primary care-based German AgeCoDe study. We assessed the association with cognitive decline, disease progression, and the capacity to predict future dementia of the Alzheimer's type (DAT). We also evaluated biomarker dynamics in 305 individuals with a follow-up sample (∼8 years later). Findings Higher levels of P-tau181 (HR = 1.32 [95% CI: 1.17-1.51]), NfL (HR = 1.19 [95% CI: 1.03-1.36]), and GFAP (HR = 1.36 [95% CI: 1.22-1.52]), and a lower Aβ42/Aβ40 ratio (HR = 0.80 [95% CI: 0.68-0.95]) were associated with an increased risk of progressing to clinically-diagnosed DAT. Additionally, higher levels of P-tau181 (β = -0.49 [95% CI: -0.71 to 0.26]), NfL (β = -0.29 [95% CI: -0.52 to 0.06]), and GFAP (β = -0.60 [95% CI: -0.83 to 0.38]) were linked to faster cognitive decline. A two-step DAT prediction strategy combining initial MMSE with biomarkers improved the identification of individuals in the prodromal stage for potential treatment eligibility. Biomarker levels changed over time, with increases in P-tau181 (β = 0.19 [95% CI: 0.14-0.25]), NfL (β = 2.88 [95% CI: 2.18-3.59]), and GFAP (β = 8.23 [95% CI: 6.71-9.75]). NfL (β = 2.47 [95% CI: 1.04-3.89]) and GFAP (β = 4.45 [95% CI: 1.38-7.51]) exhibited a faster increase in individuals progressing to DAT. Interpretation Evaluating plasma biomarkers, alongside brief cognitive assessments, might enhance the precision of risk assessment for DAT progression in primary care. Funding Alzheimer Forschung Initiative, Bundesministerium für Bildung und Forschung.
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Affiliation(s)
- Pamela V Martino-Adami
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Madhurima Chatterjee
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
| | | | - Horst Bickel
- Department of Psychiatry, Technical University of Munich, Germany
| | - Birgitt Wiese
- Institute of General Practice, Hannover Medical School, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Germany
| | - Martin Scherer
- Department of Primary Medical Care, Center for Psychosocial Medicine, University Medical Center, Hamburg-Eppendorf, Germany
| | - 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
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, PR China
| | - 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 Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Psychiatry and Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, 7703 Floyd Curl Drive, 78229, San Antonio, TX, USA
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Straße 26, 50931, Cologne, Germany
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Karlsson L, Vogel J, Arvidsson I, Åström K, Strandberg O, Seidlitz J, Bethlehem RAI, Stomrud E, Ossenkoppele R, Ashton NJ, Zetterberg H, Blennow K, Palmqvist S, Smith R, Janelidze S, Joie RL, Rabinovici GD, Binette AP, Mattsson-Carlgren N, Hansson O. A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.31.24308264. [PMID: 38853877 PMCID: PMC11160861 DOI: 10.1101/2024.05.31.24308264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET composites from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded the most accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study uncovers current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.
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Affiliation(s)
- Linda Karlsson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Jacob Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Clinical Sciences, SciLifeLab, Lund University, Lund, Sweden
| | - Ida Arvidsson
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Kalle Åström
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Jakob Seidlitz
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104 USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104 USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Richard A. I. Bethlehem
- University of Cambridge, Department of Psychology, Cambridge Biomedical Campus, Cambridge, CB2 3EB, UK
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience, King’s College London, London, UK
| | - 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, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D. Rabinovici
- Department of Neurology, Memory and Aging Center, 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
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Zhang S, Lu J, Jin Z, Xu H, Zhang D, Chen J, Wang J. Gut microbiota metabolites: potential therapeutic targets for Alzheimer's disease? Front Pharmacol 2024; 15:1459655. [PMID: 39355779 PMCID: PMC11442227 DOI: 10.3389/fphar.2024.1459655] [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: 07/04/2024] [Accepted: 09/05/2024] [Indexed: 10/03/2024] Open
Abstract
Background Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive decline in cognitive function, which significantly increases pain and social burden. However, few therapeutic interventions are effective in preventing or mitigating the progression of AD. An increasing number of recent studies support the hypothesis that the gut microbiome and its metabolites may be associated with upstream regulators of AD pathology. Methods In this review, we comprehensively explore the potential mechanisms and currently available interventions targeting the microbiome for the improvement of AD. Our discussion is structured around modern research advancements in AD, the bidirectional communication between the gut and brain, the multi-target regulatory effects of microbial metabolites on AD, and therapeutic strategies aimed at modulating gut microbiota to manage AD. Results The gut microbiota plays a crucial role in the pathogenesis of AD through continuous bidirectional communication via the microbiota-gut-brain axis. Among these, microbial metabolites such as lipids, amino acids, bile acids and neurotransmitters, especially sphingolipids and phospholipids, may serve as central components of the gut-brain axis, regulating AD-related pathogenic mechanisms including β-amyloid metabolism, Tau protein phosphorylation, and neuroinflammation. Additionally, interventions such as probiotic administration, fecal microbiota transplantation, and antibiotic use have also provided evidence supporting the association between gut microbiota and AD. At the same time, we propose an innovative strategy for treating AD: a healthy lifestyle combined with targeted probiotics and other potential therapeutic interventions, aiming to restore intestinal ecology and microbiota balance. Conclusion Despite previous efforts, the molecular mechanisms by which gut microbes act on AD have yet to be fully described. However, intestinal microorganisms may become an essential target for connecting the gut-brain axis and improving the symptoms of AD. At the same time, it requires joint exploration by multiple centers and multiple disciplines.
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Affiliation(s)
- Shanshan Zhang
- The School to Changchun University of Chinese Medicine, Changchun, China
| | - Jing Lu
- Research Center of Traditional Chinese Medicine, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China
| | - Ziqi Jin
- The School to Changchun University of Chinese Medicine, Changchun, China
| | - Hanying Xu
- Department of Encephalopathy, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China
| | - Dongmei Zhang
- Research Center of Traditional Chinese Medicine, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China
| | - Jianan Chen
- The School to Changchun University of Chinese Medicine, Changchun, China
| | - Jian Wang
- Department of Encephalopathy, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, China
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23
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Figdore DJ, Griswold M, Bornhorst JA, Graff‐Radford J, Ramanan VK, Vemuri P, Lowe VJ, Knopman DS, Jack CR, Petersen RC, Algeciras‐Schimnich A. Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays. Alzheimers Dement 2024; 20:6506-6516. [PMID: 39030981 PMCID: PMC11497693 DOI: 10.1002/alz.14140] [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: 05/06/2024] [Revised: 06/21/2024] [Accepted: 06/25/2024] [Indexed: 07/22/2024]
Abstract
INTRODUCTION We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p-tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice. METHODS Clinical performance of plasma p-tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia (n = 427). RESULTS Using a one-cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two-cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively. DISCUSSION This study provides a systematic framework for selection of assay-specific cutpoints for clinical use of plasma p-tau217 for determination of amyloid status. Our findings suggest that a two-cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results. HIGHLIGHTS Phosphorylated tau (p-tau)217 cutpoints for detection of amyloid pathology were established. A two-cutpoint approach exhibited the best performance for clinical laboratory use. p-tau217 assays differed in the percentage of results categorized as intermediate.
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Affiliation(s)
- Daniel J. Figdore
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
| | - Michael Griswold
- The MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Joshua A. Bornhorst
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
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24
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Ashton NJ, Keshavan A, Brum WS, Andreasson U, Arslan B, Droescher M, Barghorn S, Vanbrabant J, Lambrechts C, Van Loo M, Stoops E, Iyengar S, Ji H, Xu X, Forrest-Hay A, Zhang B, Luo Y, Jeromin A, Vandijck M, Bastard NL, Kolb H, Triana-Baltzer G, Bali D, Janelidze S, Yang SY, Demos C, Romero D, Sigal G, Wohlstadter J, Malyavantham K, Khare M, Jethwa A, Stoeckl L, Gobom J, Kac PR, Gonzalez-Ortiz F, Montoliu-Gaya L, Hansson O, Rissman RA, Carillo MC, Shaw LM, Blennow K, Schott JM, Zetterberg H. The Alzheimer's Association Global Biomarker Standardization Consortium (GBSC) plasma phospho-tau Round Robin study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.22.24312244. [PMID: 39228740 PMCID: PMC11370527 DOI: 10.1101/2024.08.22.24312244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
BACKGROUND Phosphorylated tau (p-tau) is a specific blood biomarker for Alzheimer's disease (AD) pathology. Multiple p-tau biomarkers on several analytical platforms are poised for clinical use. The Alzheimer's Association Global Biomarker Standardisation Consortium plasma phospho-tau Round Robin study engaged assay developers in a blinded case-control study on plasma p-tau, aiming to learn which assays provide the largest fold-changes in AD compared to non-AD, have the strongest relationship between plasma and cerebrospinal fluid (CSF), and show the most consistent relationships between methods (commutability) in measuring both patient samples and candidate reference materials (CRM). METHODS Thirty-three different p-tau biomarker assays, built on eight different analytical platforms, were used to quantify paired plasma and CSF samples from 40 participants. AD biomarker status was categorised as "AD pathology" (n=25) and "non-AD pathology" (n=15) by CSF Aβ42/Aβ40 (US-FDA; CE-IVDR) and p-tau181 (CE-IVDR) methods. The commutability of four CRM, at three concentrations, was assessed across assays. FINDINGS Plasma p-tau217 consistently demonstrated higher fold-changes between AD and non-AD pathology groups, compared to other p-tau epitopes. Fujirebio LUMIPULSE G, UGOT IPMS, and Lilly MSD p-tau217 assays provided the highest median fold-changes. In CSF, p-tau217 assays also performed best, and exhibited substantially larger fold-changes than their plasma counterparts, despite similar diagnostic performance. P-tau217 showed the strongest correlations between plasma assays (rho=0.81 to 0.97). Plasma p-tau levels were weakly-to-moderately correlated with CSF p-tau, and correlations were non-significant within the AD group alone. The evaluated CRM were not commutable across assays. INTERPRETATION Plasma p-tau217 measures had larger fold-changes and discriminative accuracies for detecting AD pathology, and better agreement across platforms than other plasma p-tau variants. Plasma and CSF markers of p-tau, measured by immunoassays, are not substantially correlated, questioning the interchangeability of their continuous relationship. Further work is warranted to understand the pathophysiology underlying this dissociation, and to develop suitable reference materials facilitating cross-assay standardisation. FUNDING Alzheimer's Association (#ADSF-24-1284328-C).
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Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Mathias Droescher
- AbbVie Deutschland GmbH & Co. KG, Neuroscience Research, Knollstrasse, 67061 Ludwigshafen, Germany
| | - Stefan Barghorn
- AbbVie Deutschland GmbH & Co. KG, Neuroscience Research, Knollstrasse, 67061 Ludwigshafen, Germany
| | | | | | - Maxime Van Loo
- ADx NeuroSciences N.V., Technologiepark 6, 9052 Ghent, Belgium
| | - Erik Stoops
- ADx NeuroSciences N.V., Technologiepark 6, 9052 Ghent, Belgium
| | | | - HaYeun Ji
- Alamar Biosciences, Inc., Fremont, CA, USA
| | - Xiaomei Xu
- Alamar Biosciences, Inc., Fremont, CA, USA
| | | | | | - Yuling Luo
- Alamar Biosciences, Inc., Fremont, CA, USA
| | | | | | | | | | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, California, USA
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22184, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22184, Sweden
| | | | | | - Daniel Romero
- Meso Scale Diagnostics, LLC., Rockville, Maryland, USA
| | - George Sigal
- Meso Scale Diagnostics, LLC., Rockville, Maryland, USA
| | | | | | | | | | | | - Johan Gobom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Przemysław R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22184, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
| | - Robert A Rissman
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA 92121, USA
| | - Maria C Carillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Leslie M Shaw
- Department of pathology & laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
- UK Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Science Park, Hong Kong, China
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Dyer AH, Dolphin H, O'Connor A, Morrison L, Sedgwick G, Young C, Killeen E, Gallagher C, McFeely A, Connolly E, Davey N, Claffey P, Doyle P, Lyons S, Gaffney C, Ennis R, McHale C, Joseph J, Knight G, Kelly E, O'Farrelly C, Fallon A, O'Dowd S, Bourke NM, Kennelly SP. Performance of plasma p-tau217 for the detection of amyloid-β positivity in a memory clinic cohort using an electrochemiluminescence immunoassay. Alzheimers Res Ther 2024; 16:186. [PMID: 39160628 PMCID: PMC11331802 DOI: 10.1186/s13195-024-01555-z] [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: 03/09/2024] [Accepted: 08/11/2024] [Indexed: 08/21/2024]
Abstract
BACKGROUND Plasma p-tau217 has emerged as the most promising blood-based marker (BBM) for the detection of Alzheimer Disease (AD) pathology, yet few studies have evaluated plasma p-tau217 performance in memory clinic settings. We examined the performance of plasma p-tau217 for the detection of AD using a high-sensitivity immunoassay in individuals undergoing diagnostic lumbar puncture (LP). METHODS Paired plasma and cerebrospinal fluid (CSF) samples were analysed from the TIMC-BRAiN cohort. Amyloid (Aβ) and Tau (T) pathology were classified based on established cut-offs for CSF Aβ42 and CSF p-tau181 respectively. High-sensitivity electrochemiluminescence (ECL) immunoassays were performed on paired plasma/CSF samples for p-tau217, p-tau181, Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light (NfL) and total tau (t-tau). Biomarker performance was evaluated using Receiver-Operating Curve (ROC) and Area-Under-the-Curve (AUC) analysis. RESULTS Of 108 participants (age: 69 ± 6.5 years; 54.6% female) with paired samples obtained at time of LP, 64.8% (n = 70/108) had Aβ pathology detected (35 with Mild Cognitive Impairment and 35 with mild dementia). Plasma p-tau217 was over three-fold higher in Aβ + (12.4 pg/mL; 7.3-19.2 pg/mL) vs. Aβ- participants (3.7 pg/mL; 2.8-4.1 pg/mL; Mann-Whitney U = 230, p < 0.001). Plasma p-tau217 exhibited excellent performance for the detection of Aβ pathology (AUC: 0.91; 95% Confidence Interval [95% CI]: 0.86-0.97)-greater than for T pathology (AUC: 0.83; 95% CI: 0.75-0.90; z = 1.75, p = 0.04). Plasma p-tau217 outperformed plasma p-tau181 for the detection of Aβ pathology (z = 3.24, p < 0.001). Of the other BBMs, only plasma GFAP significantly differed by Aβ status which significantly correlated with plasma p-tau217 in Aβ + (but not in Aβ-) individuals. Application of a two-point threshold at 95% and 97.5% sensitivities & specificities may have enabled avoidance of LP in 58-68% of cases. CONCLUSIONS Plasma p-tau217 measured using a high-sensitivity ECL immunoassay demonstrated excellent performance for detection of Aβ pathology in a real-world memory clinic cohort. Moving forward, clinical use of plasma p-tau217 to detect AD pathology may substantially reduce need for confirmatory diagnostic testing for AD pathology with diagnostic LP in specialist memory services.
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Affiliation(s)
- Adam H Dyer
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland.
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland.
| | - Helena Dolphin
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Laura Morrison
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Gavin Sedgwick
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Conor Young
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Emily Killeen
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Conal Gallagher
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Aoife McFeely
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Eimear Connolly
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Naomi Davey
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Paul Claffey
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Paddy Doyle
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Shane Lyons
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Christine Gaffney
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Ruth Ennis
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Cathy McHale
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Jasmine Joseph
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Graham Knight
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Emmet Kelly
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Cliona O'Farrelly
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Aoife Fallon
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean O'Dowd
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Nollaig M Bourke
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean P Kennelly
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
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Devanarayan V, Doherty T, Charil A, Sachdev P, Ye Y, Murali LK, Llano DA, Zhou J, Reyderman L, Hampel H, Kramer LD, Dhadda S, Irizarry MC. Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease. Alzheimers Dement 2024; 20:5617-5628. [PMID: 38940656 PMCID: PMC11350129 DOI: 10.1002/alz.14073] [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: 04/08/2024] [Revised: 05/24/2024] [Accepted: 05/24/2024] [Indexed: 06/29/2024]
Abstract
BACKGROUND This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aβ) 42/Aβ40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening. METHODS Quantification of plasma pTau217R and Aβ42/Aβ40 employed immunoprecipitation-mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts. RESULTS Models integrating pTau217R outperformed Aβ42/Aβ40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R-based models for low amyloid levels reduced PET scans by 70.5% to 78.6%. DISCUSSION pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aβ42/Aβ40's range. Combining it with plasma Aβ42/Aβ40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility. CLINICALTRIALS GOV IDENTIFIERS NCT02956486 (MissionAD1), NCT03036280 (MissionAD2), NCT04468659 (AHEAD3-45), NCT03887455 (ClarityAD) HIGHLIGHTS: Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid-PET Centiloid (CL) across a broad spectrum. Integrating pTau217R with Aβ42/Aβ40 extends the CL prediction upper limit to 89.1 CL. Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals. This model identifies subjects above or below various CL thresholds with high accuracy. pTau217R-based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid.
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Affiliation(s)
- Viswanath Devanarayan
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
- Department of MathematicsStatistics and Computer ScienceUniversity of Illinois ChicagoChicagoIllinoisUSA
| | | | - Arnaud Charil
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
| | | | - Yuanqing Ye
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
| | | | - Daniel A. Llano
- Carle Illinois College of MedicineUrbanaIllinoisUSA
- Department of Molecular and Integrative PhysiologyUniversity of Illinois Urbana‐ChampaignUrbanaIllinoisUSA
- Beckman Institute for Advanced Science and TechnologyUrbanaIllinoisUSA
| | - Jin Zhou
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
| | | | - Harald Hampel
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
| | - Lynn D. Kramer
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
| | - Shobha Dhadda
- Eisai Inc., Clinical Evidence GenerationNutleyNew JerseyUSA
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Nguyen Ho PT, Hoepel SJW, Rodriguez-Ayllon M, Luik AI, Vernooij MW, Neitzel J. Sleep, 24-Hour Activity Rhythms, and Subsequent Amyloid-β Pathology. JAMA Neurol 2024; 81:824-834. [PMID: 38913396 PMCID: PMC11197458 DOI: 10.1001/jamaneurol.2024.1755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 04/15/2024] [Indexed: 06/25/2024]
Abstract
Importance Sleep disturbances are common among older adults and have been associated with the development of Alzheimer disease (AD), such as amyloid-β (Aβ) pathology. For effective AD prevention, it is essential to pinpoint the specific disturbances in sleep and the underlying 24-hour activity rhythms that confer the highest risk of Aβ deposition. Objective To determine the associations of 24-hour activity rhythms and sleep with Aβ deposition in adults without dementia, to evaluate whether disrupted 24-hour activity and sleep may precede Aβ deposition, and to assess the role of the apolipoprotein E ε4 (APOE4) genotype. Design, Setting, and Participants This was an observational cohort study using data from the Rotterdam Study. Of 639 participants without dementia who underwent Aβ positron emission tomography (PET) from September 2018 to November 2021, 319 were included in the current study. Exclusion criteria were no APOE genotyping and no valid actigraphy data at the baseline visits from 2004 to 2006 or from 2012 to 2014. The mean (SD) follow-up was 7.8 (2.4) years. Data were analyzed from March 2023 to April 2024. Exposures Actigraphy (7 days and nights, objective sleep, and 24-hour activity rhythms), sleep diaries (self-reported sleep), Aβ42/40, phosphorylated tau (p-tau)181 and p-tau217 plasma assays, 18F-florbetaben PET (mean standard uptake value ratio [SUVR] in a large cortical region of interest), and APOE4 genotype. Main Outcomes and Measures Association of objective and self-reported sleep and 24-hour activity rhythms at baseline with brain Aβ PET burden at follow-up. Results The mean (range) age in the study population was 61.5 (48-80) years at baseline and 69.2 (60-88) years at follow-up; 150 (47%) were women. Higher intradaily variability at baseline, an indicator of fragmented 24-hour activity rhythms, was associated with higher Aβ PET burden at follow-up (β, 0.15; bootstrapped 95% CI, 0.04 to 0.26; bootstrapped P = .02, false discovery rate [FDR] P = .048). APOE genotype modified this association, which was stronger in APOE4 carriers (β, 0.38; bootstrapped 95% CI, 0.05 to 0.64; bootstrapped P = .03) compared to noncarriers (β, 0.07; bootstrapped 95% CI, -0.04 to 0.18; bootstrapped P = .19). The findings remained largely similar after excluding participants with AD pathology at baseline, suggesting that a fragmented 24-hour activity rhythm may have preceded Aβ deposition. No other objective or self-reported measure of sleep was associated with Aβ. Conclusions and Relevance Among community-dwelling adults included in this study, higher fragmentation of the 24-hour activity rhythms was associated with greater subsequent Aβ burden, especially in APOE4 carriers. These results suggest that rest-activity fragmentation could represent a modifiable risk factor for AD.
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Affiliation(s)
- Phuong Thuy Nguyen Ho
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, the Netherlands
| | - Sanne J. W. Hoepel
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, the Netherlands
| | - Maria Rodriguez-Ayllon
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, the Netherlands
| | - Annemarie I. Luik
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, the Netherlands
- Trimbos Institute—the Netherlands Institute of Mental Health and Addiction, Utrecht, the Netherlands
| | - Meike W. Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, the Netherlands
| | - Julia Neitzel
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
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28
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Jack CR, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, Molinuevo JL, Okonkwo OC, Pani L, Rafii MS, Scheltens P, Siemers E, Snyder HM, Sperling R, Teunissen CE, Carrillo MC. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement 2024; 20:5143-5169. [PMID: 38934362 PMCID: PMC11350039 DOI: 10.1002/alz.13859] [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: 02/07/2024] [Revised: 03/21/2024] [Accepted: 04/04/2024] [Indexed: 06/28/2024]
Abstract
The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.
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Affiliation(s)
| | - J. Scott Andrews
- Global Evidence & OutcomesTakeda Pharmaceuticals Company LimitedCambridgeMassachusettsUSA
| | - Thomas G. Beach
- Civin Laboratory for NeuropathologyBanner Sun Health Research InstituteSun CityArizonaUSA
| | - Teresa Buracchio
- Office of NeuroscienceU.S. Food and Drug AdministrationSilver SpringMarylandUSA
| | - Billy Dunn
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Ana Graf
- NovartisNeuroscience Global Drug DevelopmentBaselSwitzerland
| | - Oskar Hansson
- Department of Clinical Sciences Malmö, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, MalmöLundSweden
| | - Carole Ho
- DevelopmentDenali TherapeuticsSouth San FranciscoCaliforniaUSA
| | - William Jagust
- School of Public Health and Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Eric McDade
- Department of NeurologyWashington University St. Louis School of MedicineSt. LouisMissouriUSA
| | - Jose Luis Molinuevo
- Department of Global Clinical Development H. Lundbeck A/SExperimental MedicineCopenhagenDenmark
| | - Ozioma C. Okonkwo
- Department of Medicine, Division of Geriatrics and GerontologyUniversity of Wisconsin School of MedicineMadisonWisconsinUSA
| | - Luca Pani
- University of MiamiMiller School of MedicineMiamiFloridaUSA
| | - Michael S. Rafii
- Alzheimer's Therapeutic Research Institute (ATRI)Keck School of Medicine at the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Philip Scheltens
- Amsterdam University Medical Center (Emeritus)NeurologyAmsterdamthe Netherlands
| | - Eric Siemers
- Clinical ResearchAcumen PharmaceuticalsZionsvilleIndianaUSA
| | - Heather M. Snyder
- Medical & Scientific Relations DivisionAlzheimer's AssociationChicagoIllinoisUSA
| | - Reisa Sperling
- Department of Neurology, Brigham and Women's HospitalMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Charlotte E. Teunissen
- Department of Laboratory MedicineAmsterdam UMC, Neurochemistry LaboratoryAmsterdamthe Netherlands
| | - Maria C. Carrillo
- Medical & Scientific Relations DivisionAlzheimer's AssociationChicagoIllinoisUSA
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29
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Howe MD, Britton KJ, Joyce HE, Menard W, Emrani S, Kunicki ZJ, Faust MA, Dawson BC, Riddle MC, Huey ED, Janelidze S, Hansson O, Salloway SP. Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease. Alzheimers Res Ther 2024; 16:154. [PMID: 38971815 PMCID: PMC11227160 DOI: 10.1186/s13195-024-01521-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 06/26/2024] [Indexed: 07/08/2024]
Abstract
BACKGROUND With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-β (Aβ) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). METHODS In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific and BioFINDER-2 training data, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aβ-PET/CSF testing as the standard of truth. RESULTS Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aβ-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aβ positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required confirmatory testing. CONCLUSIONS This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aβ-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.
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Affiliation(s)
- Matthew D Howe
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA.
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA.
| | | | - Hannah E Joyce
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - William Menard
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Sheina Emrani
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Zachary J Kunicki
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Melanie A Faust
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Brittany C Dawson
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Meghan C Riddle
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Edward D Huey
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Stephen P Salloway
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
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Warmenhoven N, Salvadó G, Janelidze S, Mattsson-Carlgren N, Bali D, Dolado AO, Kolb H, Triana-Baltzer G, Barthélemy NR, Schindler SE, Aschenbrenner AJ, Raji CA, Benzinger TL, Morris JC, Ibanez L, Timsina J, Cruchaga C, Bateman RJ, Ashton N, Arslan B, Zetterberg H, Blennow K, Pichet Binette A, Hansson O. A Comprehensive Head-to-Head Comparison of Key Plasma Phosphorylated Tau 217 Biomarker Tests. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.02.24309629. [PMID: 39006421 PMCID: PMC11245081 DOI: 10.1101/2024.07.02.24309629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarkers for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU]and ptau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, and the FDA-approved p-tau181/Aβ42Elecsys and p-tau181Elecsys. All plasma p-tau217 tests exhibited high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (P diff<0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (P diff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (P diff=0.025). Plasma %p-tau217WashU exhibited higher associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more strongly associated with Aβ-PET load than plasma p-tau217Janssen (P diff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all P diff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; P diff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217Nulisa showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test.
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Affiliation(s)
- Noëlle Warmenhoven
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Anna Orduña Dolado
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, USA
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, USA
| | - Nicolas R. Barthélemy
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - 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
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Cyrus A. Raji
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- 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
| | - Laura Ibanez
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Randall J. Bateman
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
- 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
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicholas Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
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Ossenkoppele R, Salvadó G, Janelidze S, Binette AP, Bali D, Karlsson L, Palmqvist S, Mattsson-Carlgren N, Stomrud E, Therriault J, Rahmouni N, Rosa-Neto P, Coomans EM, van de Giessen E, van der Flier WM, Teunissen CE, Jonaitis EM, Johnson SC, Villeneuve S, Benzinger TL, Schindler SE, Bateman RJ, Doecke JD, Doré V, Feizpour A, Masters CL, Rowe C, Wiste HJ, Petersen RC, Jack CR, Hansson O. Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.12.24308824. [PMID: 38947004 PMCID: PMC11213114 DOI: 10.1101/2024.06.12.24308824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R2 PET=0.32 vs R2 PLASMA=0.32, pdifference=0.812) and with progression to mild cognitive impairment (Hazard ratio[HR]PET=1.56[1.43-1.70] vs HRPLASMA=1.63[1.50-1.77], pdifference=0.627). Combined plasma and PET models were superior to the single biomarker models (R2=0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD.
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Affiliation(s)
- Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Linda Karlsson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Emma M. Coomans
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Elsmarieke van de Giessen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Erin M. Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | | | - Sylvia Villeneuve
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Tammie L.S. Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Randall J. Bateman
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, United States
| | - James D. Doecke
- Australian eHealth Research Centre, CSIRO, Melbourne, Victoria, Australia
| | - Vincent Doré
- Australian eHealth Research Centre, CSIRO, Melbourne, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
| | - Azadeh Feizpour
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Heather J. Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Howe MD, Britton KJ, Joyce HE, Menard W, Emrani S, Kunicki ZJ, Faust MA, Dawson BC, Riddle MC, Huey ED, Janelidze S, Hansson O, Salloway SP. Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease. RESEARCH SQUARE 2024:rs.3.rs-3755419. [PMID: 38853872 PMCID: PMC11160917 DOI: 10.21203/rs.3.rs-3755419/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Background With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-β (Aβ) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). Methods In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific training data and BioFINDER-2, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aβ-PET/CSF testing as the standard of truth. Results Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aβ-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aβ positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required from confirmatory testing. Conclusions This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aβ-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.
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Yakoub Y, Gonzalez-Ortiz F, Ashton NJ, Déry C, Strikwerda-Brown C, St-Onge F, Ourry V, Schöll M, Geddes MR, Ducharme S, Montembeault M, Rosa-Neto P, Soucy JP, Breitner JCS, Zetterberg H, Blennow K, Poirier J, Villeneuve S. Plasma p-tau217 predicts cognitive impairments up to ten years before onset in normal older adults. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.09.24307120. [PMID: 38766113 PMCID: PMC11100946 DOI: 10.1101/2024.05.09.24307120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Importance Positron emission tomography (PET) biomarkers are the gold standard for detection of Alzheimer amyloid and tau in vivo . Such imaging can identify cognitively unimpaired (CU) individuals who will subsequently develop cognitive impartment (CI). Plasma biomarkers would be more practical than PET or even cerebrospinal fluid (CSF) assays in clinical settings. Objective Assess the prognostic accuracy of plasma p-tau217 in comparison to CSF and PET biomarkers for predicting the clinical progression from CU to CI. Design In a cohort of elderly at high risk of developing Alzheimer's dementia (AD), we measured the proportion of CU individuals who developed CI, as predicted by Aβ (A+) and/or tau (T+) biomarker assessment from plasma, CSF, and PET. Results from each method were compared with (A-T-) reference individuals. Data were analyzed from June 2023 to April 2024. Setting Longitudinal observational cohort. Participants Some 228 participants from the PREVENT-AD cohort were CU at the time of biomarker assessment and had 1 - 10 years of follow-up. Plasma was available from 215 participants, CSF from 159, and amyloid- and tau-PET from 155. Ninety-three participants had assessment using all three methods (main group of interest). Progression to CI was determined by clinical consensus among physicians and neuropsychologists who were blind to plasma, CSF, PET, and MRI findings, as well as APOE genotype. Exposures Plasma Aβ 42/40 was measured using IP-MS; CSF Aβ 42/40 using Lumipulse; plasma and CSF p-tau217 using UGOT assay. Aβ-PET employed the 18 F-NAV4694 ligand, and tau-PET used 18 F-flortaucipir. Main Outcome Prognostic accuracy of plasma, CSF, and PET biomarkers for predicting the development of CI in CU individuals. Results Cox proportional hazard models indicated a greater progression rate in all A+T+ groups compared to A-T-groups (HR = 6.61 [95% CI = 2.06 - 21.17] for plasma, 3.62 [1.49 - 8.81] for CSF and 9.24 [2.34 - 36.43] for PET). The A-T+ groups were small, but also characterized with individuals who developed CI. Plasma biomarkers identified about five times more T+ than PET. Conclusion and relevance Plasma p-tau217 assessment is a practical method for identification of persons who will develop cognitive impairment up to 10 years later. Key Points Question: Can plasma p-tau217 serve as a prognostic indicator for identifying cognitively unimpaired (CU) individuals at risk of developing cognitive impairments (CI)?Findings: In a longitudinal cohort of CU individuals with a family history of sporadic AD, almost all individuals with abnormal plasma p-tau217 concentrations developed CI within 10 years, regardless of plasma amyloid levels. Similar findings were obtained with CSF p-tau217 and tau-PET. Fluid p-tau217 biomarkers had the main advantage over PET of identifying five times more participants with elevated tau.Meaning: Elevated plasma p-tau217 levels in CU individuals strongly indicate future clinical progression.
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Hillerstrom H, Fisher R, Janicki MP, Chicoine B, Christian BT, Esbensen A, Esralew L, Fortea J, Hartley S, Hassenstab J, Keller SM, Krinsky‐McHale S, Lai F, Levin J, McCarron M, McDade E, Rebillat AS, Rosas HD, Silverman W, Strydom A, Zaman SH, Zetterberg H. Adapting prescribing criteria for amyloid-targeted antibodies for adults with Down syndrome. Alzheimers Dement 2024; 20:3649-3656. [PMID: 38480678 PMCID: PMC11095423 DOI: 10.1002/alz.13778] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 02/07/2024] [Accepted: 02/09/2024] [Indexed: 05/16/2024]
Abstract
Prior authorization criteria for Federal Drug Administration (FDA) approved immunotherapeutics, among the class of anti-amyloid monoclonal antibodies (mAbs), established by state drug formulary committees, are tailored for adults with late-onset Alzheimer's disease. This overlooks adults with Down syndrome (DS), who often experience dementia at a younger age and with different diagnostic assessment outcomes. This exclusion may deny DS adults access to potential disease-modifying treatments. To address this issue, an international expert panel convened to establish adaptations of prescribing criteria suitable for DS patients and parameters for access to Centers for Medicare & Medicaid Services (CMS) registries. The panel proposed mitigating disparities by modifying CMS and payer criteria to account for younger onset age, using alternative language and assessment instruments validated for cognitive decline in the DS population. The panel also recommended enhancing prescribing clinicians' diagnostic capabilities for DS and initiated awareness-raising activities within healthcare organizations. These efforts facilitated discussions with federal officials, aimed at achieving equity in access to anti-amyloid immunotherapeutics, with implications for national authorities worldwide evaluating these and other new disease-modifying therapeutics for Alzheimer's disease.
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Affiliation(s)
| | | | - Matthew P. Janicki
- Department of Disability and Human DevelopmentUniversity of Illinois ChicagoChicagoIllinoisUSA
- National Task Group on Intellectual Disabilities and Dementia PracticesRockportMaineUSA
| | - Brian Chicoine
- Advocate Health, Advocate Medical Group Adult Down Syndrome CenterAdvocate Lutheran General Hospital Family Medicine ResidencyPark RidgeIllinoisUSA
| | | | - Anna Esbensen
- Division of Developmental and Behavioral PediatricsCincinnati Children's Hospital Medical CenterUniversity of Cincinnati College of MedicineCincinnati Children's HospitalCincinnatiOhioUSA
| | - Lucille Esralew
- California Department of Developmental ServicesSacramentoCaliforniaUSA
| | - Juan Fortea
- Biomedical Research Institute Sant PauUniversitat Autònoma de BarcelonaBarcelonaSpain
- Department of NeurologyHospital de la Santa Creu i Sant PauBarcelonaSpain
| | - Sigan Hartley
- Waisman Center IDDRCUniversity of WisconsinMadisonWisconsinUSA
| | - Jason Hassenstab
- Departments of Neurology and Psychological & Brain SciencesKnight Alzheimer Disease Research CenterWashington UniversitySt. LouisMissouriUSA
| | - Seth M. Keller
- National Task Group on Intellectual Disabilities and Dementia PracticesRockportMaineUSA
- Neurology Associates of South JerseyLumbertonNew JerseyUSA
| | - Sharon Krinsky‐McHale
- Department of PsychologyNew York State Institute for Basic Research in Developmental DisabilitiesIslandNew YorkUSA
| | - Florence Lai
- MGH Neurology ResearchMass General Brigham HospitalMassachusetts General HospitalBostonMassachusettsUSA
| | - Johannes Levin
- Department of Neurology & German Center of Neurodegenerative Diseases (DZNE) e.V.Ludwig‐Maximilians UniversityMunichGermany
- Department of NeurologySahgrenska University HospitalMölndalSweden
| | - Mary McCarron
- Trinity Centre for Ageing and Intellectual DisabilityTrinity College, University of DublinDublinIreland
| | - Eric McDade
- Departments of Neurology and Psychological & Brain SciencesKnight Alzheimer Disease Research CenterWashington UniversitySt. LouisMissouriUSA
| | | | - Herminia Diana Rosas
- MGH Neurology ResearchMass General Brigham HospitalMassachusetts General HospitalBostonMassachusettsUSA
- Department of RadiologyAthinoula Martinos CenterMassachusetts General HospitalHarvard Medical SchoolCharlestownMassachusettsUSA
| | - Wayne Silverman
- Department of PediatricsUniversity of California IrvineIrvineCaliforniaUSA
| | - Andre Strydom
- Institute of PsychiatryPsychology and Neuroscience, Kings CollegeLondonUK
| | - Shahid H. Zaman
- Department of PsychiatryCambridge Intellectual and Developmental Disabilities Research GroupCambridge UniversityCambridgeUK
| | - Henrik Zetterberg
- Institute for Stroke and Dementia ResearchSahlgrenska Academy at the University of GothenburgMolndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMolndalSweden
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
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Lista S, Mapstone M, Caraci F, Emanuele E, López-Ortiz S, Martín-Hernández J, Triaca V, Imbimbo C, Gabelle A, Mielke MM, Nisticò R, Santos-Lozano A, Imbimbo BP. A critical appraisal of blood-based biomarkers for Alzheimer's disease. Ageing Res Rev 2024; 96:102290. [PMID: 38580173 DOI: 10.1016/j.arr.2024.102290] [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: 11/13/2023] [Revised: 03/18/2024] [Accepted: 03/31/2024] [Indexed: 04/07/2024]
Abstract
Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.
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Affiliation(s)
- Simone Lista
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain.
| | - Mark Mapstone
- Department of Neurology, Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA 92697, USA.
| | - Filippo Caraci
- Department of Drug and Health Sciences, University of Catania, Catania 95125, Italy; Neuropharmacology and Translational Neurosciences Research Unit, Oasi Research Institute-IRCCS, Troina 94018, Italy.
| | | | - Susana López-Ortiz
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain.
| | - Juan Martín-Hernández
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain.
| | - Viviana Triaca
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Rome 00015, Italy.
| | - Camillo Imbimbo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia 27100, Italy.
| | - Audrey Gabelle
- Memory Resources and Research Center, Montpellier University of Excellence i-site, Montpellier 34295, France.
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
| | - Robert Nisticò
- School of Pharmacy, University of Rome "Tor Vergata", Rome 00133, Italy; Laboratory of Pharmacology of Synaptic Plasticity, EBRI Rita Levi-Montalcini Foundation, Rome 00143, Italy.
| | - Alejandro Santos-Lozano
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain; Physical Activity and Health Research Group (PaHerg), Research Institute of the Hospital 12 de Octubre ('imas12'), Madrid 28041, Spain.
| | - Bruno P Imbimbo
- Department of Research and Development, Chiesi Farmaceutici, Parma 43122, Italy.
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Lantero-Rodriguez J, Salvadó G, Snellman A, Montoliu-Gaya L, Brum WS, Benedet AL, Mattsson-Carlgren N, Tideman P, Janelidze S, Palmqvist S, Stomrud E, Ashton NJ, Zetterberg H, Blennow K, Hansson O. Plasma N-terminal containing tau fragments (NTA-tau): a biomarker of tau deposition in Alzheimer's Disease. Mol Neurodegener 2024; 19:19. [PMID: 38365825 PMCID: PMC10874032 DOI: 10.1186/s13024-024-00707-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 01/30/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Novel phosphorylated-tau (p-tau) blood biomarkers (e.g., p-tau181, p-tau217 or p-tau231), are highly specific for Alzheimer's disease (AD), and can track amyloid-β (Aβ) and tau pathology. However, because these biomarkers are strongly associated with the emergence of Aβ pathology, it is difficult to determine the contribution of insoluble tau aggregates to the plasma p-tau signal in blood. Therefore, there remains a need for a biomarker capable of specifically tracking insoluble tau accumulation in brain. METHODS NTA is a novel ultrasensitive assay targeting N-terminal containing tau fragments (NTA-tau) in cerebrospinal fluid (CSF) and plasma, which is elevated in AD. Using two well-characterized research cohorts (BioFINDER-2, n = 1,294, and BioFINDER-1, n = 932), we investigated the association between plasma NTA-tau levels and disease progression in AD, including tau accumulation, brain atrophy and cognitive decline. RESULTS We demonstrate that plasma NTA-tau increases across the AD continuum¸ especially during late stages, and displays a moderate-to-strong association with tau-PET (β = 0.54, p < 0.001) in Aβ-positive participants, while weak with Aβ-PET (β = 0.28, p < 0.001). Unlike plasma p-tau181, GFAP, NfL and t-tau, tau pathology determined with tau-PET is the most prominent contributor to NTA-tau variance (52.5% of total R2), while having very low contribution from Aβ pathology measured with CSF Aβ42/40 (4.3%). High baseline NTA-tau levels are predictive of tau-PET accumulation (R2 = 0.27), steeper atrophy (R2 ≥ 0.18) and steeper cognitive decline (R2 ≥ 0.27) in participants within the AD continuum. Plasma NTA-tau levels significantly increase over time in Aβ positive cognitively unimpaired (βstd = 0.16) and impaired (βstd = 0.18) at baseline compared to their Aβ negative counterparts. Finally, longitudinal increases in plasma NTA-tau levels were associated with steeper longitudinal decreases in cortical thickness (R2 = 0.21) and cognition (R2 = 0.20). CONCLUSION Our results indicate that plasma NTA-tau levels increase across the AD continuum, especially during mid-to-late AD stages, and it is closely associated with in vivo tau tangle deposition in AD and its downstream effects. Moreover, this novel biomarker has potential as a cost-effective and easily accessible tool for monitoring disease progression and cognitive decline in clinical settings, and as an outcome measure in clinical trials which also need to assess the downstream effects of successful Aβ removal.
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Affiliation(s)
- Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden.
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Anniina Snellman
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Turku PET Centre, University of Turku, Turku University Hospital, Turku, Finland
| | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul (UFRGS), Porto Alegre, Brazil
| | - Andrea L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Pontus Tideman
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- 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
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, 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-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden.
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Error in Open Access Status. JAMA Neurol 2024:2814787. [PMID: 38345800 PMCID: PMC10862263 DOI: 10.1001/jamaneurol.2024.0033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
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Wood H. Tau aids selection of anti-amyloid drug recipients. Nat Rev Neurol 2024; 20:63. [PMID: 38167677 DOI: 10.1038/s41582-023-00925-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
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Giuffrè GM, Quaranta D, Citro S, Morganti TG, Martellacci N, Vita MG, Rossini PM, Calabresi P, Marra C. Associations Between Free and Cued Selective Reminding Test and Cerebrospinal Fluid Biomarkers in Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2024; 100:713-723. [PMID: 38905044 DOI: 10.3233/jad-240150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
Background The Free and Cued Selective Reminding Test (FCSRT), assessing verbal episodic memory with controlled learning and semantic cueing, has been recommended for detecting the genuine encoding and storage deficits characterizing AD-related memory disorders. Objective The present study aims at investigating the ability of FCSRT in predicting cerebrospinal fluid (CSF) evidence of amyloid-β positivity in subjects with amnestic mild cognitive impairment (aMCI) and exploring its associations with amyloidopathy, tauopathy and neurodegeneration biomarkers. Methods 120 aMCI subjects underwent comprehensive neurological and neuropsychological examinations, including the FCSRT assessment, and CSF collection; CSF Aβ42/40 ratio, p-tau181, and total-tau quantification were conducted by an automated CLEIA method on Lumipulse G1200. Based on the Aβ42/40 ratio value, subjects were classified as either A+ or A-. Results All FCSRT subitem scores were significantly lower in A+ group and significantly predicted the amyloid-β status, with Immediate Total Recall (ITR) being the best predictor. No significant correlations were found between FCSRT and CSF biomarkers in the A- aMCI group, while in the A+ aMCI group, all FCSRT subitem scores were negatively correlated with CSF p-tau181 and total-tau, but not with the Aβ42/40 ratio. Conclusions FCSRT confirms its validity as a tool for the diagnosis of AD, being able to predict the presence of amyloid-β deposition with high specificity. The associations between FCSRT subitem scores and CSF p-tau-181 and total-tau levels in aMCI due to AD could further encourage the clinical use of this simple and cost-effective test in the evaluation of individuals with aMCI.
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Affiliation(s)
- Guido Maria Giuffrè
- Neurology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Memory Clinic Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | - Davide Quaranta
- Neurology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Memory Clinic Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | - Salvatore Citro
- Neurology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | - Tommaso Giuseppe Morganti
- Neurology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | - Noemi Martellacci
- Memory Clinic Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Maria Gabriella Vita
- Neurology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Paolo Maria Rossini
- Department of Neuroscience and Neurorehabilitation, Brain Connectivity Laboratory, IRCCS San Raffaele Roma, Rome, Italy
| | - Paolo Calabresi
- Neurology Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | - Camillo Marra
- Memory Clinic Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
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Korologou-Linden R, Kalsi J, Kafetsouli D, Olawale A, Iwata A, Wingfield D, Mummery D, Hayhoe B, Robinson O, Majeed A, Middleton LT. Novel Blood-Based Biomarkers and Disease Modifying Therapies for Alzheimer's Disease. Are We Ready for the New Era? J Prev Alzheimers Dis 2024; 11:897-902. [PMID: 39044500 PMCID: PMC11266440 DOI: 10.14283/jpad.2024.83] [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: 02/23/2024] [Accepted: 03/17/2024] [Indexed: 07/25/2024]
Abstract
Recent positive trials for novel disease modifying therapies of anti-amyloid monoclonal antibodies represent a paradigm shift in the prevention and management of Alzheimer's disease, a relentlessly progressive and debilitating disease of old age. The reported efficacy of these new agents when given early in the disease trajectory is dependent on an early and accurate disease diagnosis, which is currently based on cerebrospinal fluid tests or/and neuro-imaging studies such as positron emission tomography. These confirmatory tests provide in vivo evidence of the pathological signature of Alzheimer's disease, of increased cerebral amyloid and tau burden and neurodegeneration. The emergence of blood-based biomarkers represents another breakthrough, offering a less invasive and scalable diagnostic tool that could be applied in both primary and specialist care settings, potentially revolutionizing Alzheimer's disease clinical pathways. However, healthcare systems face challenges in the adoption of these new technologies and therapies due to diagnostic and treatment capacity constraints, as well as financial and infrastructure requirements.
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Affiliation(s)
- R Korologou-Linden
- Roxanna Korologou-Linden, Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, 11th Floor, Charing Cross Hospital Campus, W6 8RP, , Tel: +44 20 3311 0208
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Sperling RA, Donohue MC, Rissman RA, Johnson KA, Rentz DM, Grill JD, Heidebrink JL, Jenkins C, Jimenez-Maggiora G, Langford O, Liu A, Raman R, Yaari R, Holdridge KC, Sims JR, Aisen PS. Amyloid and Tau Prediction of Cognitive and Functional Decline in Unimpaired Older Individuals: Longitudinal Data from the A4 and LEARN Studies. J Prev Alzheimers Dis 2024; 11:802-813. [PMID: 39044488 PMCID: PMC11266444 DOI: 10.14283/jpad.2024.122] [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: 05/31/2024] [Accepted: 06/13/2024] [Indexed: 07/25/2024]
Abstract
BACKGROUND Converging evidence suggests that markers of Alzheimer's disease (AD) pathology in cognitively unimpaired older individuals are associated with high risk of cognitive decline and progression to functional impairment. The Anti-Amyloid Treatment in Asymptomatic Alzheimer's disease (A4) and Longitudinal Evaluation of Amyloid and Neurodegeneration Risk (LEARN) Studies enrolled a large cohort of cognitively normal older individuals across a range of baseline amyloid PET levels. Recent advances in AD blood-based biomarkers further enable the comparison of baseline markers in the prediction of longitudinal clinical outcomes. OBJECTIVES We sought to evaluate whether biomarker indicators of higher levels of AD pathology at baseline predicted greater cognitive and functional decline, and to compare the relative predictive power of amyloid PET imaging, tau PET imaging, and a plasma P-tau217 assay. DESIGN All participants underwent baseline amyloid PET scan, plasma P-tau217; longitudinal cognitive testing with the Primary Alzheimer Cognitive Composite (PACC) every 6 months; and annual functional assessments with the clinical dementia rating (CDR), cognitive functional index (CFI), and activities of daily living (ADL) scales. Baseline tau PET scans were obtained in a subset of participants. Participants with elevated amyloid (Aβ+) on screening PET who met inclusion/exclusion criteria were randomized to receive placebo or solanezumab in a double-blind phase of the A4 Study over 240+ weeks. Participants who did not have elevated amyloid (Aβ-) but were otherwise eligible for the A4 Study were referred to the companion observational LEARN Study with the same outcome assessments over 240+ weeks. SETTING The A4 and LEARN Studies were conducted at 67 clinical trial sites in the United States, Canada, Japan and Australia. PARTICIPANTS Older participants (ages 65-85) who were cognitively unimpaired at baseline (CDR-GS=0, MMSE 25-30 with educational adjustment, and Logical Memory scores within the normal range LMIIa 6-18) were eligible to continue in screening. Aβ+ participants were randomized to either placebo (n=583) or solanezumab (n=564) in the A4 Study. A subset of Aβ+ underwent tau PET imaging in A4 (n=350). Aβ- were enrolled into the LEARN Study (n=553). MEASUREMENTS Baseline 18-F Florbetapir amyloid PET, 18-F Flortaucipir tau PET in a subset and plasma P-tau217 with an electrochemiluminescence (ECL) immunoassay were evaluated as predictors of cognitive (PACC), and functional (CDR, CFI and ADL) change. Models were evaluated to explore the impact of baseline tertiles of amyloid PET and tertiles of plasma P-tau217 on cognitive and functional outcomes in the A4 Study compared to LEARN. Multivariable models were used to evaluate the unique and common variance explained in longitudinal outcomes based on baseline predictors, including effects for age, gender, education, race/ethnic group, APOEε4 carrier status, baseline PACC performance and treatment assignment in A4 participants (solanezumab vs placebo). RESULTS Higher baseline amyloid PET CL and P-tau217 levels were associated with faster rates of PACC decline, and increased likelihood of progression to functional impairment (CDR 0.5 or higher on two consecutive measurements), both across LEARN Aβ- and A4 Aβ+ (solanezumab and placebo arms). In analyses considering all baseline predictor variables, P-tau217 was the strongest predictor of PACC decline. Among participants in the highest tertiles of amyloid PET or P-tau217, >50% progressed to CDR 0.5 or greater. In the tau PET substudy, neocortical tau was the strongest predictor of PACC decline, but plasma P-tau217 contributed additional independent predictive variance in commonality variance models. CONCLUSIONS In a large cohort of cognitively unimpaired individuals enrolled in a Phase 3 clinical trial and companion observational study, these findings confirm that higher baseline levels of amyloid and tau markers are associated with increased rates of cognitive decline and progression to functional impairment. Interestingly, plasma P-tau217 was the best predictor of decline in the overall sample, superior to baseline amyloid PET. Neocortical tau was the strongest predictor of cognitive decline in the subgroup with tau PET, suggesting that tau deposition is most closely linked to clinical decline. These findings indicate that biomarkers of AD pathology are useful to predict decline in an older asymptomatic population and may prove valuable in the selection of individuals for disease-modifying treatments.
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Affiliation(s)
- R A Sperling
- Reisa A. Sperling, MD, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA 02115, 617-732-8472
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Aschenbrenner AJ, Hassenstab JJ, Schindler SE, Janelidze S, Hansson O, Morris JC, Grober E. Free Recall Outperforms Story Recall in Associations with Plasma Biomarkers in Preclinical Alzheimer Disease. J Prev Alzheimers Dis 2024; 11:1696-1702. [PMID: 39559880 PMCID: PMC11573877 DOI: 10.14283/jpad.2024.130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2024]
Abstract
BACKGROUND A decline in episodic memory is one of the earliest cognitive characteristics of Alzheimer disease and memory tests are heavily featured in cognitive composite endpoints that are used to demonstrate treatment efficacy. Assessments of episodic memory can take many forms including free recall, associate learning, and paragraph or story recall. Plasma biomarkers of Alzheimer disease are now widely available and will likely form the backbone of cohort enrichment strategies for future clinical trials. Thus, it is critical to evaluate which episodic memory measures are most sensitive to plasma markers of Alzheimer disease pathology. OBJECTIVES To compare the associations of common episodic memory tests with plasma biomarkers of Alzheimer disease. DESIGN Longitudinal cohort study. SETTING Academic medical center in the midwestern United States. PARTICIPANTS A total of 161 cognitively normal older adults with at least one plasma biomarker assessment and two or more annual clinical and cognitive assessments which included up to three different tests of episodic memory. MEASUREMENTS Episodic memory performance using free recall, paired associates recall or paragraph recall. Plasma Aβ42, Aβ40, ptau217, and neurofilament light chain were measured. RESULTS Free recall on the Free and Cued Selective Reminding Test with Immediate Recall (FCSRT + IR) was substantially more sensitive to longitudinal cognitive change associated with abnormal baseline plasma Aβ42/Aβ40 and ptau217 compared to other measures of episodic memory. A cognitive composite that included only free recall showed larger decline associated with baseline Aβ42/Aβ40 when compared to those that included paragraph recall. Differences in decline across composites were minimal when considering baseline ptau217 or NfL. CONCLUSION Episodic memory is a critical domain to assess in preclinical Alzheimer disease. Methods of assessing memory are not equal and longitudinal change in free recall substantially outperformed both paired associates and paragraph recall. Clinical trial results will depend critically on the episodic memory test(s) that are chosen for a composite endpoint and free recall from the FCSRT + IR is an optimal memory measure to include rather than paired associates or paragraph recall.
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Affiliation(s)
- A J Aschenbrenner
- Andrew Aschenbrenner, PhD, 4488 Forest Park Ave, STE 301, St. Louis, MO, 63108, , 314-273-1041
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