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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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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 2024:2821669. [PMID: 39068545 DOI: 10.1001/jama.2024.13855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [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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3
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Salloway S, Rowe C, Burns JM. Are Blood Tests for Alzheimer Disease Ready for Prime Time? JAMA 2024:2821671. [PMID: 39068544 DOI: 10.1001/jama.2024.12814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [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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4
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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. [PMID: 39030981 DOI: 10.1002/alz.14140] [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: 05/06/2024] [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 Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael Griswold
- The MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Joshua A Bornhorst
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
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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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7
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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. [PMID: 38940656 DOI: 10.1002/alz.14073] [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: 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. 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 Generation, Nutley, New Jersey, USA
- Department of Mathematics, Statistics and Computer Science, University of Illinois Chicago, Chicago, Illinois, USA
| | | | - Arnaud Charil
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | - Pallavi Sachdev
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | - Yuanqing Ye
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | | | - Daniel A Llano
- Carle Illinois College of Medicine, Urbana, Illinois, USA
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
- Beckman Institute for Advanced Science and Technology, Urbana, Illinois, USA
| | - Jin Zhou
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | - Larisa Reyderman
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | - Harald Hampel
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | - Lynn D Kramer
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
| | - Shobha Dhadda
- Eisai Inc., Clinical Evidence Generation, Nutley, New Jersey, USA
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8
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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. [PMID: 38934362 DOI: 10.1002/alz.13859] [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: 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)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - J Scott Andrews
- Global Evidence & Outcomes, Takeda Pharmaceuticals Company Limited, Cambridge, Massachusetts, USA
| | - Thomas G Beach
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Teresa Buracchio
- Office of Neuroscience, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Billy Dunn
- The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA
| | - Ana Graf
- Novartis, Neuroscience Global Drug Development, Basel, Switzerland
| | - Oskar Hansson
- Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Lund, Sweden
| | - Carole Ho
- Development, Denali Therapeutics, South San Francisco, California, USA
| | - William Jagust
- School of Public Health and Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA
| | - Eric McDade
- Department of Neurology, Washington University St. Louis School of Medicine, St. Louis, Missouri, USA
| | - Jose Luis Molinuevo
- Department of Global Clinical Development H. Lundbeck A/S, Experimental Medicine, Copenhagen, Denmark
| | - Ozioma C Okonkwo
- Department of Medicine, Division of Geriatrics and Gerontology, University of Wisconsin School of Medicine, Madison, Wisconsin, USA
| | - Luca Pani
- University of Miami, Miller School of Medicine, Miami, Florida, USA
| | - Michael S Rafii
- Alzheimer's Therapeutic Research Institute (ATRI), Keck School of Medicine at the University of Southern California, San Diego, California, USA
| | - Philip Scheltens
- Amsterdam University Medical Center (Emeritus), Neurology, Amsterdam, the Netherlands
| | - Eric Siemers
- Clinical Research, Acumen Pharmaceuticals, Zionsville, Indiana, USA
| | - Heather M Snyder
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Reisa Sperling
- Department of Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Charlotte E Teunissen
- Department of Laboratory Medicine, Amsterdam UMC, Neurochemistry Laboratory, Amsterdam, the Netherlands
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
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9
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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 2024:2820395. [PMID: 38913396 PMCID: PMC11197458 DOI: 10.1001/jamaneurol.2024.1755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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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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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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, La Joie R, 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 outcomes 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 highly 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 reveals 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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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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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:jnnp-2024-333467. [PMID: 38658136 DOI: 10.1136/jnnp-2024-333467] [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: 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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16
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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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18
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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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