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Bettcher BM, de Oliveira FF, Willette AA, Michalowska MM, Machado LS, Rajbanshi B, Borelli WV, Tansey MG, Rocha A, Suryadevara V, Hu WT. Analysis and interpretation of inflammatory fluid markers in Alzheimer's disease: a roadmap for standardization. J Neuroinflammation 2025; 22:105. [PMID: 40234920 PMCID: PMC11998147 DOI: 10.1186/s12974-025-03432-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2025] [Accepted: 03/31/2025] [Indexed: 04/17/2025] Open
Abstract
Growing interest in the role of the immune response in Alzheimer's Disease and related dementias (ADRD) has led to widespread use of fluid inflammatory markers in research studies. To standardize the use and interpretation of inflammatory markers in AD research, we build upon prior guidelines to develop consensus statements and recommendations to advance application and interpretation of these markers. In this roadmap paper, we propose a glossary of terms related to the immune response in the context of biomarker discovery/validation, discuss current conceptualizations of inflammatory markers in research, and recommend best practices to address key knowledge gaps. We also provide consensus principles to summarize primary conceptual, methodological, and interpretative issues facing the field: (1) a single inflammatory marker is likely insufficient to describe an entire biological cascade, and multiple markers with similar or distinct functions should be simultaneously measured in a panel; (2) association studies in humans are insufficient to infer causal relationships or mechanisms; (3) neuroinflammation displays time-dependent and disease context-dependent patterns; (4) neuroinflammatory mechanisms should not be inferred based solely on blood inflammatory marker changes; and (5) standardized reporting of CSF inflammatory marker assay validation and performance will improve incorporation of inflammatory markers into the biological AD criteria.
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Affiliation(s)
- Brianne M Bettcher
- Department of Neurology, University of Colorado Anschutz Medical Campus, 12469 East 17th Place, Room 217- Campus Box F429, Aurora, CO, 80045, USA.
| | | | - Auriel A Willette
- Department of Neurology, Rutgers-Robert Wood Johnson Medical School and Center for Healthy Aging Research, Rutgers Institute for Health, Health Care Policy, and Aging Research, Rutgers Health, New Brunswick, USA
| | - Malgorzata M Michalowska
- Department of Clinical Neuroscience, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Luiza Santos Machado
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Binita Rajbanshi
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California - San Francisco, San Francisco, USA
| | - Wyllians V Borelli
- Department of Morphological Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Malú Gámez Tansey
- Department of Neurology, Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, USA
| | - Andréia Rocha
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | | | - William T Hu
- Department of Neurology, Rutgers-Robert Wood Johnson Medical School and Center for Healthy Aging Research, Rutgers Institute for Health, Health Care Policy, and Aging Research, Rutgers Health, New Brunswick, USA
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2
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Wang G, Li Y, Xiong C, Cao Y, Schindler SE, McDade E, Blennow K, Hansson O, Dage JL, Jack CR, Teunissen CE, Shaw LM, Zetterberg H, Ibanez L, Timsina J, Carlos C, Bateman RJ. The CentiMarker project: Standardizing quantitative Alzheimer's disease fluid biomarkers for biologic interpretation. Alzheimers Dement 2025; 21:e14587. [PMID: 40235082 PMCID: PMC12000244 DOI: 10.1002/alz.14587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 12/09/2024] [Accepted: 01/12/2025] [Indexed: 04/17/2025]
Abstract
INTRODUCTION Biomarkers play a crucial role in understanding Alzheimer's disease (AD) pathogenesis and treatment effects. However, comparing biomarker measures without standardization and appreciating their magnitude relative to the disease can be challenging. METHODS To address this issue, we propose the CentiMarker approach, similar to Centiloid, which provides a standardized scale between normal (0) and nearly maximum abnormal AD (100) ranges. We applied this scale to cerebrospinal fluid (CSF) biomarkers in dominantly inherited AD and sporadic AD cohorts. RESULTS CentiMarkers facilitated the interpretation of disease abnormality, demonstrating comparable changes and distributions of AD biomarkers across disease stages. CentiMarkers make the treatment effect more comparable than their original scales across various biomarkers. DISCUSSION The versatility of CentiMarkers makes it a valuable tool for standardized biomarker comparison in AD research, enabling informed cross-study comparisons and contributing to accelerated therapeutic development. Adoption of the CentiMarker scale could enhance biomarker reporting and advance our understanding of AD. HIGHLIGHTS Comparing fluid biomarkers without appreciating their magnitude relative to the disease can be challenging. We propose a CentiMarker metric to standardize biomarker measures from normal (0) and nearly maximum abnormal AD (100) ranges. CentiMarkers make the treatment effect more comparable across various biomarkers than when using the original scales.
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Affiliation(s)
- Guoqiao Wang
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
- Division of BiostatisticsWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Yan Li
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Chengjie Xiong
- Division of BiostatisticsWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Yuchen Cao
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Suzanne E. Schindler
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Eric McDade
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Kaj Blennow
- Institute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Paris Brain InstituteICMPitié‐Salpêtrière HospitalSorbonne UniversityParisFrance
| | - Oskar Hansson
- Clinical Memory Research UnitDepartment of Clinical Sciences MalmöFaculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University HospitalMalmöSweden
| | - Jeffrey L. Dage
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryAmsterdam University Medical CentersVrije Universiteit, Amsterdam NeuroscienceAmsterdamNetherlands
| | - Leslie M Shaw
- Department of Pathology & Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Henrik Zetterberg
- Institute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of Neurology, Queen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Laura Ibanez
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
| | - Jigyasha Timsina
- Department of PsychiatryWashington UniversitySt. LouisMissouriUSA
- Neuro Genomics and InformaticsWashington UniversitySt. LouisMissouriUSA
| | - Cruchaga Carlos
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
- Department of PsychiatryWashington UniversitySt. LouisMissouriUSA
- Neuro Genomics and InformaticsWashington UniversitySt. LouisMissouriUSA
| | | | - Randall J. Bateman
- Department of NeurologyWashington UniversitySchool of MedicineSt. LouisMissouriUSA
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3
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Abuwarda H, Trainer A, Horien C, Shen X, Ju S, Constable RT, Fredericks C. Whole-brain functional connectivity predicts regional tau PET in preclinical Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.04.02.587791. [PMID: 38617320 PMCID: PMC11014551 DOI: 10.1101/2024.04.02.587791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Preclinical Alzheimer's disease (AD), characterized by the abnormal accumulation of amyloid prior to cognitive symptoms, presents a critical opportunity for early intervention. Past work has described functional connectivity changes in preclinical disease, yet the interplay between AD pathology and the functional connectome during this window remains unexplored. We applied connectome-based predictive modeling to investigate the ability of resting-state whole-brain functional connectivity to predict tau (18F-flortaucipir) and amyloid (18F-florbetapir) PET binding in a preclinical AD cohort (A4, n =342, age 65-85). Separate predictive models were developed for each of 14 regions, and model performance was assessed using a Spearman's correlation between predicted and observed PET binding standard uptake value ratios. We assessed the validity of significant models by applying them to an external dataset, and visualized the underlying connectivity that was positively and negatively correlated to posterior cingulate tau binding, the most successful model. We found that whole brain functional connectivity predicts regional tau PET, outperforming amyloid PET models. The best performing tau models were for regions affected in Braak stage IV-V regions (posterior cingulate, precuneus, lateral occipital cortex, middle temporal, inferior temporal, and Bank STS), while models for regions of earlier tau pathology (entorhinal, parahippocampal, fusiform, and amygdala) performed poorly. Importantly, tau models generalized to a symptomatic AD cohort (ADNI; amyloid positive, n = 211, age 55-90), in tau-elevated but not tau-negative individuals. For the posterior cingulate A4 tau model, the most successful model, the predictive edges positively correlated with posterior cingulate tau predominantly came from nodes within temporal, limbic, and cerebellar regions. The most predictive edges negatively associated to tau were from nodes of heteromodal association areas, particularly within the prefrontal and parietal cortices. These findings reveal that whole-brain functional connectivity predicts tau PET in preclinical AD and generalizes to a clinical dataset specifically in individuals with abnormal tau PET, highlighting the relevance of the functional connectome for the early detection and monitoring of AD pathology.
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4
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Hoost SS, Honig LS, Kang MS, Bahl A, Lee AJ, Sanchez D, Reyes-Dumeyer D, Lantigua RA, Dage JL, Brickman AM, Manly JJ, Mayeux R, Gu Y. Association of dietary fatty acids with longitudinal change in plasma-based biomarkers of Alzheimer's disease. J Prev Alzheimers Dis 2025:100117. [PMID: 40107919 DOI: 10.1016/j.tjpad.2025.100117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 01/29/2025] [Accepted: 02/27/2025] [Indexed: 03/22/2025]
Abstract
BACKGROUND Elevated intake of omega-3 polyunsaturated fatty acids is linked to a reduced risk of dementia in some prospective studies. However, few studies have examined the relationship between nutrient intake and plasma biomarkers of Alzheimer's disease. OBJECTIVES We explored whether omega-3, omega-6, and monounsaturated fat intakes were associated with changes in plasma biomarkers of Alzheimer's disease over time. DESIGN The Washington Heights-Inwood Columbia Aging Project is a prospective cohort study (1994-2021); the data set used here includes a mean follow-up of 7.0 years. SETTING Community-based in New York City. PARTICIPANTS 599 dementia-free individuals at baseline who completed a 61-item food frequency questionnaire and had biomarkers measured in plasma from at least two different time points. MEASUREMENTS Fatty acid intake tertiles were computed from participant-completed 61-item Willett semi-quantitative food frequency questionnaires (Channing Laboratory, Cambridge, Massachusetts) obtained once at their baseline visit. Plasma-based biomarker assays were performed, using the single molecule array technology Quanterix Simoa HD-X platform, at baseline and follow-up visits. Generalized Estimating Equations (GEE) models were used to evaluate the association between baseline nutrient intake tertile and changes in biomarkers including phospho-tau181, amyloid-beta 42/40 ratio, phospho-tau181/amyloid-beta42 ratio, glial fibrillary acidic protein, neurofilament light chain, and two biomarker patterns derived from Principal Component Analysis (PCA1 and PCA2), with higher scores indicating a high level of neurodegeneration and low level of Alzheimer's disease burden, respectively). Models were adjusted for age, sex, race/ethnicity, education, and calculated total energy intake initially, and additionally for cerebrovascular risk factors. RESULTS Higher baseline omega-3 intake tertile was associated with lesser decline in PCA2 (β = 0.221, p < 0.001) and amyloid-beta 42/40 ratio (β = 0.022, p = 0.003), and a lesser rise in phospho-tau181 (β = -0.037, p = 0.001). Higher omega-6 intake tertile was linked to a lesser rise in phospho-tau181 (β = -0.050, p < 0.001) and glial fibrillary acidic protein (β = -0.028, p = 0.002). Most associations persisted after adjusting for cardiovascular risk factors. CONCLUSIONS Higher relative baseline intake of omega-3 and omega-6 fatty acids is associated with lesser progression of blood-based biomarkers of Alzheimer's disease. Consuming healthy fatty acids may help prevent accumulation of Alzheimer's disease-related pathological changes.
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Affiliation(s)
- Serena S Hoost
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Lawrence S Honig
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, New York, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Min Suk Kang
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Aanya Bahl
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
| | - Annie J Lee
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Danurys Sanchez
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Rafael A Lantigua
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 630 West 168th Street, New York, New York, 10032, USA
| | - Jeffrey L Dage
- Stark Neurosciences Research Institute, Suite 414, Indiana University School of Medicine, 320 West 15th Street, Indianapolis, Indiana, 46202, USA
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, New York, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Jennifer J Manly
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, New York, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, New York, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA; Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, New York, 10032, USA
| | - Yian Gu
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY, 10032, USA; G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, New York, 10032, USA; Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, 710 West 168th Street, New York, New York, 10032, USA; Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, New York, 10032, USA.
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5
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Leuzy A, Bollack A, Pellegrino D, Teunissen CE, La Joie R, Rabinovici GD, Franzmeier N, Johnson K, Barkhof F, Shaw LM, Arkhipenko A, Schindler SE, Honig LS, Moscoso Rial A, Schöll M, Zetterberg H, Blennow K, Hansson O, Farrar G. Considerations in the clinical use of amyloid PET and CSF biomarkers for Alzheimer's disease. Alzheimers Dement 2025; 21:e14528. [PMID: 40042435 PMCID: PMC11881640 DOI: 10.1002/alz.14528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2024] [Revised: 11/21/2024] [Accepted: 12/06/2024] [Indexed: 03/09/2025]
Abstract
Amyloid-β (Aβ) positron emission tomography (PET) imaging and cerebrospinal fluid (CSF) biomarkers are now established tools in the diagnostic workup of patients with Alzheimer's disease (AD), and their use is anticipated to increase with the introduction of new disease-modifying therapies. Although these biomarkers are comparable alternatives in research settings to determine Aβ status, biomarker testing in clinical practice requires careful consideration of the strengths and limitations of each modality, as well as the specific clinical context, to identify which test is best suited for each patient. This article provides a comprehensive review of the pathologic processes reflected by Aβ-PET and CSF biomarkers, their performance, and their current and future applications and contexts of use. The primary aim is to assist clinicians in making better-informed decisions about the suitability of each biomarker in different clinical situations, thereby reducing the risk of misdiagnosis or incorrect interpretation of biomarker results. HIGHLIGHTS: Recent advances have positioned Aβ PET and CSF biomarkers as pivotal in AD diagnosis. It is crucial to understand the differences in the clinical use of these biomarkers. A team of experts reviewed the state of Aβ PET and CSF markers in clinical settings. Differential features in the clinical application of these biomarkers were reviewed. We discussed the role of Aβ PET and CSF in the context of novel plasma biomarkers.
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Grants
- AF-930351 Neurodegenerative Disease Research
- 101053962 National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre
- R01 AG066107 NIA NIH HHS
- FO2022-0270 Bluefield Project, Olav Thon Foundation, Erling-Persson Family Foundation
- 101112145 European Union's Horizon Europe
- Alzheimer Netherlands
- ZEN-21-848495 Alzheimer's Association 2021 Zenith Award
- 2022-0231 Knut and Alice Wallenberg foundation
- KAW 2023.0371 Knut and Alice Wallenberg Foundation
- U19 ADNI4 Harvard Aging Brain Study
- R01 AG081394 NIA NIH HHS
- ADRC P30-AG-072979 Harvard Aging Brain Study
- 2022-1259 Regionalt Forskningsstöd
- Shanendoah Foundation
- 2020-O000028 Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, Skåne University Hospital Foundation
- The Selfridges Group Foundation
- R56 AG057195 NIA NIH HHS
- U01 NS100600 NINDS NIH HHS
- ALZ2022-0006 Hjärnfonden, Sweden
- U01 AG057195 NIA NIH HHS
- Dutch National Dementia Strategy
- ZEN24-1069572 Alzheimer's Association
- R01AG072474 Harvard Aging Brain Study
- 860197 Marie Curie International Training Network
- AF-939721 Neurodegenerative Disease Research
- R01 AG070941 NIA NIH HHS
- P01 AG036694 NIA NIH HHS
- JPND2021-00694 Neurodegenerative Disease Research
- ADSF-21-831376-C AD Strategic Fund, and Alzheimer's Association
- AF-994900 Swedish Alzheimer Foundation
- NIH
- ALFGBG-813971 County Councils, the ALF-agreement
- FO2021-0293 Swedish Brain Foundation
- U19AG063893 NINDS NIH HHS
- 2022-01018 National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre
- 201809-2016862 National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre
- 831434 Innovative Medicines Initiatives 3TR
- 101132933 European Union's Horizon Europe
- European Union Joint Programme
- Cure Alzheimer's fund, Rönström Family Foundation
- ID 390857198 Munich Cluster for Systems Neurology
- U01-AG057195 NIA NIH HHS
- Deutsche Forschungsgemeinschaft
- 2021-06545 Swedish Research Council
- Sahlgrenska Academy at the University of Gothenburg
- U19 AG024904 NIA NIH HHS
- GE Healthcare
- JPND2019-466-236 European Union Joint Program for Neurodegenerative Disorders
- P30 AG062422 NIA NIH HHS
- ADG-101096455 European Research Council
- 2022-00732 Neurodegenerative Disease Research
- 860197 Marie Skłodowska-Curie
- P01 AG019724 NIA NIH HHS
- U01NS100600 NINDS NIH HHS
- AF-980907 Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson's disease) at Lund University, Swedish Alzheimer Foundation
- P30 AG066462 NIA NIH HHS
- 2022-00775 GHR Foundation, Swedish Research Council
- R44 AG071388 NIA NIH HHS
- FO2017-0243 Hjärnfonden, Sweden
- AF-968270 Neurodegenerative Disease Research
- KAW2014.0363 Knut and Alice Wallenberg Foundation
- SG-23-1061717 Alzheimer's Association
- 2021-02678 Swedish Research Council
- R01 AG059013 NIA NIH HHS
- R35 AG072362 NIA NIH HHS
- VGFOUREG-995510 Västra Götaland Region R&D
- American College of Radiology
- R01 AG081394-01 European Union's Horizon Europe
- R21 AG070768 NIA NIH HHS
- U19 AG063893 NIA NIH HHS
- 2022-Projekt0080 Swedish Federal Government under the ALF agreement
- ALFGBG-965326 County Councils, the ALF-agreement
- Alzheimer Drug Discovery Foundation
- Rainwater Charitable Foundation
- Research of the European Commission
- R01AG083740 National Institute of Aging
- ADSF-21-831381-C AD Strategic Fund, and Alzheimer's Association
- SG-23-1038904 Alzheimer's Association 2022-2025
- RS-2023-00263612 National Research Foundation of Korea
- P30-AG062422 NIA NIH HHS
- R21AG070768 Harvard Aging Brain Study
- 2017-02869 Swedish Research Council
- 101034344 Joint Undertaking
- ALFGBG-715986 Swedish state under the agreement between the Swedish government and the County Councils, ALF-agreement
- ERAPERMED2021-184 ERA PerMed
- U19AG024904 Harvard Aging Brain Study
- R01 AG072474 NIA NIH HHS
- UKDRI-1003 Neurodegenerative Disease Research
- 10510032120003 Health Holland, the Dutch Research Council
- 2019-02397 National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre
- EXC 2145 SyNergy Munich Cluster for Systems Neurology
- 1412/22 Parkinson foundation of Sweden
- R01 AG046396 NIA NIH HHS
- ALFGBG-71320 National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre
- P01-AG019724 NIA NIH HHS
- ALFGBG-965240 Swedish state under the agreement between the Swedish government and the County Councils, ALF-agreement
- Deutsche Parkinson Gesellschaft
- ADSF-21-831377-C AD Strategic Fund, and Alzheimer's Association
- National MS Society
- R01 AG083740 NIA NIH HHS
- 2017-00915 Neurodegenerative Disease Research
- 2023-06188 Swedish Research Council
- Alzheimer Association
- National MS Society
- Alzheimer Netherlands
- NIH
- NIA
- National Institute of Neurological Disorders and Stroke
- American College of Radiology
- Rainwater Charitable Foundation
- Deutsche Forschungsgemeinschaft
- NINDS
- Knut and Alice Wallenberg Foundation
- Swedish Research Council
- National Research Foundation of Korea
- Swedish Brain Foundation
- European Research Council
- Alzheimer's Association
- GE Healthcare
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Wallenberg Centre for Molecular and Translational MedicineUniversity of GothenburgGothenburgSweden
- The Sahlgrenska AcademyInstitute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryUniversity of GothenburgGothenburgSweden
- Department of NeuropsychiatrySahlgrenska University HospitalRegion Västra GötalandGothenburgSweden
| | - Ariane Bollack
- The Grove CentreWhite Lion Road BuckinghamshireGE HealthCareAmershamUK
- Department of Medical Physics and BioengineeringCentre for Medical Image Computing (CMIC)University College LondonLondonUK
| | | | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Laboratory MedicineAmsterdam NeuroscienceNeurodegenerationAmsterdam UMC Vrije UniversiteitAmsterdamThe Netherlands
| | - Renaud La Joie
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Gil D. Rabinovici
- Department of NeurologyMemory and Aging CenterWeill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Nicolai Franzmeier
- The Sahlgrenska AcademyInstitute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryUniversity of GothenburgGothenburgSweden
- Institute for Stroke and Dementia Research (ISD)University HospitalLMU MunichMunichGermany
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
| | - Keith Johnson
- Gordon Center for Medical ImagingDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentBrigham and Women's HospitalBostonMassachusettsUSA
| | - Frederik Barkhof
- Department of Radiology and Nuclear MedicineVrije Universiteit AmsterdamAmsterdam University Medical CenterAmsterdamThe Netherlands
- Amsterdam NeuroscienceBrain imagingAmsterdamThe Netherlands
- UCL Queen Square Institute of Neurology and Center for Medical Image ComputingUniversity College LondonLondonUK
| | - Leslie M. Shaw
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Suzanne E. Schindler
- Department of NeurologyKnight Alzheimer's Disease Research CenterWashington University School of MedicineSt. LouisMissouriUSA
| | - Lawrence S. Honig
- Department of NeurologyTaub Institute for Research on Alzheimer's Disease and Aging BrainColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alexis Moscoso Rial
- Wallenberg Centre for Molecular and Translational MedicineUniversity of GothenburgGothenburgSweden
- The Sahlgrenska AcademyInstitute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryUniversity of GothenburgGothenburgSweden
- Nuclear Medicine Department and Molecular Imaging GroupInstituto de Investigación Sanitaria de Santiago de CompostelaSantiago de CompostelaSpain
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational MedicineUniversity of GothenburgGothenburgSweden
- The Sahlgrenska AcademyInstitute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryUniversity of GothenburgGothenburgSweden
- Department of NeuropsychiatrySahlgrenska University HospitalRegion Västra GötalandGothenburgSweden
- Dementia Research CentreInstitute of NeurologyUniversity College LondonLondonUK
| | - Henrik Zetterberg
- The Sahlgrenska AcademyInstitute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryUniversity of GothenburgGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseQueen Square Institute of NeurologyUniversity College LondonLondonUK
- UK Dementia Research InstituteUniversity College LondonLondonUK
- Hong Kong Center for Neurodegenerative DiseasesScience ParkHong KongChina
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of WisconsinUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Kaj Blennow
- The Sahlgrenska AcademyInstitute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryUniversity of GothenburgGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Paris Brain InstituteICMPitié‐Salpêtrière HospitalSorbonne UniversityParisFrance
- Neurodegenerative Disorder Research CenterDivision of Life Sciences and Medicineand Department of NeurologyInstitute on Aging and Brain DisordersUniversity of Science and Technology of China and First Affiliated Hospital of USTCHefeiChina
| | - Oskar Hansson
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalMalmöSweden
| | - Gill Farrar
- The Grove CentreWhite Lion Road BuckinghamshireGE HealthCareAmershamUK
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6
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Kim BH, Kim S, Nam Y, Park YH, Shin SM, Moon M. Second-generation anti-amyloid monoclonal antibodies for Alzheimer's disease: current landscape and future perspectives. Transl Neurodegener 2025; 14:6. [PMID: 39865265 PMCID: PMC11771116 DOI: 10.1186/s40035-025-00465-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 12/20/2024] [Indexed: 01/28/2025] Open
Abstract
Alzheimer's disease (AD) is the most common type of dementia. Monoclonal antibodies (MABs) serve as a promising therapeutic approach for AD by selectively targeting key pathogenic factors, such as amyloid-β (Aβ) peptide, tau protein, and neuroinflammation. Specifically, based on their efficacy in removing Aβ plaques from the brains of patients with AD, the U.S. Food and Drug Administration has approved three anti-amyloid MABs, aducanumab (Aduhelm®), lecanemab (Leqembi®), and donanemab (Kisunla™). Notably, lecanemab received traditional approval after demonstrating clinical benefit, supporting the Aβ cascade hypothesis. These MABs targeting Aβ are categorized based on their affinity to diverse conformational features of Aβ, including monomer, fibril, protofibril, and plaque forms of Aβ as well as pyroglutamate Aβ. First-generation MABs targeting the non-toxic monomeric Aβ, such as solanezumab, bapineuzumab, and crenezumab, failed to demonstrate clinical benefit for AD in clinical trials. In contrast, second-generation MABs, including aducanumab, lecanemab, donanemab, and gantenerumab directed against pathogenic Aβ species and aggregates have shown that reducing Aβ deposition can be an effective strategy to slow cognitive impairment in AD. In this review, we provide a comprehensive overview of the current status, mechanisms, outcomes, and limitations of second-generation MABs for the clinical treatment of AD. Moreover, we discuss the perspectives and future directions of anti-amyloid MABs in the treatment of AD.
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Affiliation(s)
- Byeong-Hyeon Kim
- Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea
| | - Sujin Kim
- Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea
- Research Institute for Dementia Science, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea
| | - Yunkwon Nam
- Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea
| | - Yong Ho Park
- Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea
| | - Seong Min Shin
- Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea
| | - Minho Moon
- Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea.
- Research Institute for Dementia Science, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea.
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7
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Jutten RJ, Soberanes D, Molinare CP, Hsieh S, Farrell ME, Schultz AS, Rentz DM, Marshall GA, Johnson KA, Sperling RA, Amariglio RE, Papp KV. Detecting early cognitive deficits in preclinical Alzheimer's disease using a remote digital multi-day learning paradigm. NPJ Digit Med 2025; 8:24. [PMID: 39806194 PMCID: PMC11729905 DOI: 10.1038/s41746-024-01347-7] [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: 05/09/2024] [Accepted: 11/15/2024] [Indexed: 01/16/2025] Open
Abstract
Remote, digital cognitive testing on an individual's own device provides the opportunity to deploy previously understudied but promising cognitive paradigms in preclinical Alzheimer's disease (AD). The Boston Remote Assessment for NeuroCognitive Health (BRANCH) captures a personalized learning curve for the same information presented over seven consecutive days. Here, we examined BRANCH multi-day learning curves (MDLCs) in 167 cognitively unimpaired older adults (age = 74.3 ± 7.5, 63% female) with different amyloid-β (A) and tau (T) biomarker profiles on positron emission tomography. MDLC scores decreased across ascending biomarker groups, with the A + T- group performing numerically worse (β = -0.24, 95%CI[-0.55,0.07], p = 0.128) and the A + T+ group performing significantly worse (β = -0.58, 95%CI[-1.06,-0.10], p = 0.018) than the A-T- group. Further, lower MDLC scores were associated with greater cortical thinning (β = 0.18, 95%CI[0.04,0.34], p = 0.013). Our results suggest that diminished MDLCs track with advanced AD pathophysiology, and demonstrate how a digital multi-day learning paradigm can provide novel insights about cognitive decline during preclinical AD.
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Affiliation(s)
- Roos J Jutten
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA.
| | - Daniel Soberanes
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Cassidy P Molinare
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Stephanie Hsieh
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Michelle E Farrell
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
| | - Aaron S Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
| | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Gad A Marshall
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Keith A Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Rebecca E Amariglio
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Kathryn V Papp
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA.
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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Tsering W, de la Rosa A, Ruan IY, Philips JL, Bathe T, Villareal JA, Prokop S. Preferential clustering of microglia and astrocytes around neuritic plaques during progression of Alzheimer's disease neuropathological changes. J Neurochem 2025; 169:e16275. [PMID: 39655787 PMCID: PMC11629606 DOI: 10.1111/jnc.16275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Revised: 10/28/2024] [Accepted: 11/17/2024] [Indexed: 12/13/2024]
Abstract
Neuroinflammation plays an important role in the pathological cascade of Alzheimer's disease (AD) along with aggregation of extracellular amyloid-β (Aβ) plaques and intracellular aggregates of tau protein. In animal models of amyloidosis, local immune activation is centered around Aβ plaques, which are usually of uniform morphology, dependent on the transgenic model used. In postmortem human brains a diversity of Aβ plaque morphologies is seen including diffuse plaques (non-neuritic plaques, non-NP), dense-core plaques, cotton-wool plaques, and NP. In a recent study, we demonstrated that during the progression of Alzheimer's disease neuropathologic changes (ADNC), a transformation of non-NP into NP occurs which is tightly linked to the emergence of cortical, but not hippocampal neurofibrillary tangle (NFT) pathology. This highlights the central role of NP in AD pathogenesis as well as brain region-specific differences in NP formation. In order to correlate the transformation of plaque types with local immune activation, we quantified the clustering and phenotype of microglia and accumulation of astrocytes around non-NP and NP during the progression of ADNC. We hypothesize that glial clustering occurs in response to formation of neuritic dystrophy around NP. First, we show that Iba1-positive microglia preferentially cluster around NP. Utilizing microglia phenotypic markers, we furthermore demonstrate that CD68-positive phagocytic microglia show a strong preference to cluster around NP in both the hippocampus and frontal cortex. A similar preferential clustering is observed for CD11c and ferritin-positive microglia in the frontal cortex, while this preference is less pronounced in the hippocampus, highlighting differences between hippocampal and cortical Aβ plaques. Glial fibrillary acidic protein-positive astrocytes showed a clear preference for clustering around NP in both the frontal cortex and hippocampus. These data support the notion that NP are intimately associated with the neuroimmune response in AD and underscore the importance of the interplay of protein deposits and the immune system in the pathophysiology of AD.
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Affiliation(s)
- Wangchen Tsering
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- Department of Neuroscience, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- McKnight Brain Institute, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Ana de la Rosa
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Isabelle Y. Ruan
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Jennifer L. Philips
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- Department of Pathology, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Tim Bathe
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- Department of Pathology, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Jonathan A. Villareal
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- Department of Pathology, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Stefan Prokop
- Center for Translational Research in Neurodegenerative Disease, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- McKnight Brain Institute, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- Department of Pathology, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
- Norman Fixel Institute for Neurological DiseasesUniversity of FloridaGainesvilleFloridaUSA
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9
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Shaw LM, Korecka M, Lee EB, Cousins KAQ, Vanderstichele H, Schindler SE, Tosun D, DeMarco ML, Brylska M, Wan Y, Burnham S, Sciulli A, Vulaj A, Tropea TF, Chen‐Plotkin A, Wolk DA. ADNI Biomarker Core: A review of progress since 2004 and future challenges. Alzheimers Dement 2025; 21:e14264. [PMID: 39614747 PMCID: PMC11773510 DOI: 10.1002/alz.14264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 08/21/2024] [Accepted: 08/22/2024] [Indexed: 01/29/2025]
Abstract
BACKGROUND We describe the Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core major activities from October 2004 to March 2024, including biobanking ADNI cerebrospinal fluid (CSF), plasma, and serum biofluid samples, biofluid analyses for Alzheimer's disease (AD) biomarkers in the Biomarker Core and various non-ADNI laboratories, and continuous assessments of pre-analytics. RESULTS Validated immunoassay and mass spectrometry-based assays were performed in CSF with a shift to plasma, a more accessible biofluid, as qualified assays became available. Performance comparisons across different CSF and plasma AD biomarker measurement platforms have enriched substantially the ADNI participant database enabling method performance determinations for AD pathology detection and longitudinal assessments of disease progression. DISCUSSION Close collaboration with academic and industrial partners in the validation and implementation of AD biomarkers for early detection of disease pathology in treatment trials and ultimately in clinical practice is a key factor for the success of the work done in the Biomarker Core. HIGHLIGHTS Describe ADNI Biomarker Core biobanking and sample distribution from 2007 to 2024. Discuss validated mass spectrometry and immunoassay methods for ADNI biofluid analyses. Review collaborations with academic and industrial partners to detect AD and progression. Discuss major challenges, and progress to date, for co-pathology detection. Implementation in the ATN scheme: co-pathology and modeling disease progression.
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Affiliation(s)
- Leslie M. Shaw
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Magdalena Korecka
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Edward B. Lee
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Katheryn A Q Cousins
- Neurology DepartmentUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | | | - Suzanne E. Schindler
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMissouriUSA
| | - Duygu Tosun
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Mari L. DeMarco
- Department of Pathology and Laboratory MedicineUniversity of British ColumbiaVan CouverCanada
| | - Magdalena Brylska
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Yang Wan
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | | | - Alexandria Sciulli
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Amberley Vulaj
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Thomas F. Tropea
- Neurology DepartmentUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alice Chen‐Plotkin
- Neurology DepartmentUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Neurology DepartmentUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
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10
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Vanderlip CR, Stark CEL. APOE4 Increases Susceptibility to Amyloid, Accelerating Episodic Memory Decline. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.23.630203. [PMID: 39763904 PMCID: PMC11703168 DOI: 10.1101/2024.12.23.630203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2025]
Abstract
Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Individuals with one copy of APOE4 exhibit greater amyloid-beta (Aβ) deposition compared to noncarriers, an effect that is even more pronounced in APOE4 homozygotes. Interestingly, APOE4 carriers not only show more AD pathology but also experience more rapid cognitive decline, particularly in episodic memory. The underlying mechanisms driving this domain-specific vulnerability, however, remain unclear. In this study, we examined whether the accelerated decline in episodic memory among APOE4 carriers is due to increased Aβ deposition or heightened susceptibility to Aβ-related effects. Using data from the Alzheimer's Disease Research Initiative, we modeled amyloid duration, the estimated number of years an individual has been amyloid-positive, and its impact on cognitive trajectories. Our findings reveal that APOE4 is associated with more rapid episodic memory decline as a function of amyloid duration. This decline was dose-dependent, with APOE4 homozygotes declining more rapidly than heterozygotes, and it was consistently observed across multiple episodic memory tasks and measures. Importantly, this pattern was not observed in other cognitive domains, such as processing speed, executive function, visuospatial skills, language, or crystallized intelligence. These results suggest that cognitive trajectories in AD differ by APOE genotype, with APOE4 conferring increased vulnerability to hippocampal dysfunction early in the disease course. Future research should investigate whether these cognitive differences stem from distinct pathological cascades in APOE4 carriers.
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Affiliation(s)
- Casey R Vanderlip
- Department of Neurobiology and Behavior, University of California Irvine
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California Irvine
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11
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Schindler SE, Petersen KK, Saef B, Tosun D, Shaw LM, Zetterberg H, Dage JL, Ferber K, Triana‐Baltzer G, Du‐Cuny L, Li Y, Coomaraswamy J, Baratta M, Mordashova Y, Saad ZS, Raunig DL, Ashton NJ, Meyers EA, Rubel CE, Rosenbaugh EG, Bannon AW, Potter WZ. Head-to-head comparison of leading blood tests for Alzheimer's disease pathology. Alzheimers Dement 2024; 20:8074-8096. [PMID: 39394841 PMCID: PMC11567821 DOI: 10.1002/alz.14315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 09/10/2024] [Accepted: 09/11/2024] [Indexed: 10/14/2024]
Abstract
INTRODUCTION Blood tests have the potential to improve the accuracy of Alzheimer's disease (AD) clinical diagnosis, which will enable greater access to AD-specific treatments. This study compared leading commercial blood tests for amyloid pathology and other AD-related outcomes. METHODS Plasma samples from the Alzheimer's Disease Neuroimaging Initiative were assayed with AD blood tests from C2N Diagnostics, Fujirebio Diagnostics, ALZPath, Janssen, Roche Diagnostics, and Quanterix. Outcomes measures were amyloid positron emission tomography (PET), tau PET, cortical thickness, and dementia severity. Logistic regression models assessed the classification accuracies of individual or combined plasma biomarkers for binarized outcomes, and Spearman correlations evaluated continuous relationships between individual plasma biomarkers and continuous outcomes. RESULTS Measures of plasma p-tau217, either individually or in combination with other plasma biomarkers, had the strongest relationships with all AD outcomes. DISCUSSION This study identified the plasma biomarker analytes and assays that most accurately classified amyloid pathology and other AD-related outcomes. HIGHLIGHTS Plasma p-tau217 measures most accurately classified amyloid and tau status. Plasma Aβ42/Aβ40 had relatively low accuracy in classification of amyloid status. Plasma p-tau217 measures had higher correlations with cortical thickness than NfL. Correlations of plasma biomarkers with dementia symptoms were relatively low.
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Affiliation(s)
| | - Kellen K. Petersen
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Benjamin Saef
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Duygu Tosun
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Henrik Zetterberg
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCLLondonUK
- Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyQueen SquareLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Jeffrey L. Dage
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
- Stark Neurosciences Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - Kyle Ferber
- Biogen, Biomarkers GroupCambridgeMassachusettsUSA
| | - Gallen Triana‐Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative MedicineSan DiegoCaliforniaUSA
| | - Lei Du‐Cuny
- AbbVieLudwigshafen am RheinRheinland‐PfalzGermany
| | - Yan Li
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | | | | | | | - Ziad S. Saad
- Neuroscience Biomarkers, Johnson and Johnson Innovative MedicineSan DiegoCaliforniaUSA
| | | | - Nicholas J. Ashton
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Banner Alzheimer's InstitutePhoenixArizonaUSA
- Banner Sun Health Research InstituteSun CityArizonaUSA
| | | | | | - Erin G. Rosenbaugh
- The Foundation for the National Institutes of HealthNorth BethesdaMarylandUSA
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12
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He B, Wu R, Sangani N, Pugalenthi PV, Patania A, Risacher SL, Nho K, Apostolova LG, Shen L, Saykin AJ, Yan J. Integrating amyloid imaging and genetics for early risk stratification of Alzheimer's disease. Alzheimers Dement 2024; 20:7819-7830. [PMID: 39285750 PMCID: PMC11567859 DOI: 10.1002/alz.14244] [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: 05/02/2024] [Revised: 07/24/2024] [Accepted: 08/15/2024] [Indexed: 09/21/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment. METHODS Given the genetic susceptibility of AD, a multi-factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk-stratified groups, focusing on patients with mild cognitive impairment (MCI). RESULTS Our risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI, APOE ε4- MCI, and amyloid+ MCI. DISCUSSION Our risk score holds great potential to improve the precision of early risk assessment. HIGHLIGHTS Accurate early risk assessment is critical for the success of clinical trials. A new risk score was built from integrating amyloid imaging and genetic data. Our risk score demonstrated improved capability in early risk stratification.
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Affiliation(s)
- Bing He
- Department of Biomedical Engineering and InformaticsIndiana University Luddy School of Informatics, Computing and EngineeringIndianapolisIndianaUSA
| | - Ruiming Wu
- Department of Biomedical Engineering and Informatics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Neel Sangani
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Pradeep Varathan Pugalenthi
- Department of Biomedical Engineering and InformaticsIndiana University Luddy School of Informatics, Computing and EngineeringIndianapolisIndianaUSA
| | - Alice Patania
- Department of Mathematics StatisticsUniversity of VermontBurlingtonVermontUSA
| | - Shannon L. Risacher
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Kwangsik Nho
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Liana G. Apostolova
- Department of Biomedical Engineering and Informatics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Li Shen
- Department of Biomedical Engineering and Informatics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Andrew J. Saykin
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Jingwen Yan
- Department of Biomedical Engineering and InformaticsIndiana University Luddy School of Informatics, Computing and EngineeringIndianapolisIndianaUSA
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13
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Hu Y, Cho M, Sachdev P, Dage J, Hendrix S, Hansson O, Bateman RJ, Hampel H. Fluid biomarkers in the context of amyloid-targeting disease-modifying treatments in Alzheimer's disease. MED 2024; 5:1206-1226. [PMID: 39255800 DOI: 10.1016/j.medj.2024.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 07/26/2024] [Accepted: 08/16/2024] [Indexed: 09/12/2024]
Abstract
Clinical management and therapeutics development for Alzheimer's disease (AD) have entered a new era, with recent approvals of monoclonal antibody therapies targeting the underlying pathophysiology of the disease and modifying its trajectory. Imaging and fluid biomarkers are becoming increasingly important in the clinical development of AD therapeutics. This review focuses on the evidence of fluid biomarkers from recent amyloid-β-targeting clinical trials, summarizing biomarker data across 12 trials. It further proposes a simple framework to put biomarker guidance in the context of amyloid-pathway-targeted disease modification, delineates factors that impact biomarker data in clinical trials, and highlights knowledge gaps and future directions. Increased knowledge and data on biomarkers in the context of disease progression and disease modification will help to better design future AD trials and guide the clinical management of patients on AD-modifying therapies, bringing us closer to the implementation of precision medicine in AD.
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Affiliation(s)
- Yan Hu
- Eisai Inc., Nutley, NJ, USA
| | | | | | - Jeffrey Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - 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
| | - Randall J Bateman
- Department of Neurology, Washington University of St. Louis, St. Louis, MO, USA; The Tracy Family SILQ Center, Washington University School of Medicine, Saint Louis, MO, USA
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14
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Vanderlip CR, Lee MD, Stark CEL. Cognitive modeling of the Mnemonic Similarity Task as a digital biomarker for Alzheimer's disease. Alzheimers Dement 2024; 20:6935-6947. [PMID: 39239893 PMCID: PMC11485396 DOI: 10.1002/alz.14163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND The Mnemonic Similarity Task (MST) is a popular memory task designed to assess hippocampal integrity. We assessed whether analyzing MST performance using a multinomial processing tree (MPT) cognitive model could detect individuals with elevated Alzheimer's disease (AD) biomarker status prior to cognitive decline. METHOD We analyzed MST data from >200 individuals (young, cognitively healthy older adults and individuals with mild cognitive impairment [MCI]), a subset of which also had existing cerebrospinal fluid (CSF) amyloid beta (Aβ) and phosphorylated tau (pTau) data using both traditional and model-derived approaches. We assessed how well each could predict age group, memory ability, MCI status, Aβ, and pTau status using receiver operating characteristic analyses. RESULTS Both approaches predicted age group membership equally, but MPT-derived metrics exceeded traditional metrics in all other comparisons. DISCUSSION A MPT model of the MST can detect individuals with AD prior to cognitive decline, making it a potentially useful tool for screening and monitoring older adults during the asymptomatic phase of AD. HIGHLIGHTS The MST, along with cognitive modeling, identifies individuals with memory deficits and cognitive impairment. Cognitive modeling of the MST identifies individuals with increased AD biomarkers prior to changes in cognitive function. The MST is a digital biomarker that identifies individuals at high risk of AD.
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Affiliation(s)
- Casey R. Vanderlip
- Department of Neurobiology and Behavior1424 Biological Sciences IIIUniversity of California, IrvineIrvineCaliforniaUSA
| | - Michael D. Lee
- Department of Cognitive Science3151 Social Sciences Plaza AUniversity of California, IrvineIrvineCaliforniaUSA
| | - Craig E. L. Stark
- Department of Neurobiology and Behavior1424 Biological Sciences IIIUniversity of California, IrvineIrvineCaliforniaUSA
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15
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Belder CRS, Boche D, Nicoll JAR, Jaunmuktane Z, Zetterberg H, Schott JM, Barkhof F, Fox NC. Brain volume change following anti-amyloid β immunotherapy for Alzheimer's disease: amyloid-removal-related pseudo-atrophy. Lancet Neurol 2024; 23:1025-1034. [PMID: 39304242 DOI: 10.1016/s1474-4422(24)00335-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/26/2024] [Accepted: 07/30/2024] [Indexed: 09/22/2024]
Abstract
Progressive cerebral volume loss on MRI is a hallmark of Alzheimer's disease and has been widely used as an outcome measure in clinical trials, with the prediction that disease-modifying treatments would slow loss. However, in trials of anti-amyloid immunotherapy, the participants who received treatment had excess volume loss. Explanations for this observation range from reduction of amyloid β plaque burden and related inflammatory changes through to treatment-induced toxicity. The excess volume changes are characteristic of only those immunotherapies that achieve amyloid β lowering; are compatible with plaque removal; and evidence to date does not suggest an association with harmful effects. Based on the current evidence, we suggest that these changes can be described as amyloid-removal-related pseudo-atrophy. Better understanding of the causes and consequences of these changes is important to enable informed decisions about treatments. Patient-level analyses of data from the trials are urgently needed, along with longitudinal follow-up and neuroimaging data, to determine the long-term trajectory of these volume changes and their clinical correlates. Post-mortem examination of cerebral tissue from treated patients and evaluation of potential correlation with antemortem neuroimaging findings are key priorities.
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Affiliation(s)
- Christopher R S Belder
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK; Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia
| | - Delphine Boche
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - James A R Nicoll
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Zane Jaunmuktane
- Department of Clinical and Movement Neurosciences, Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, University College London, London, UK; 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 Queen Square Institute of Neurology, University College London, London, UK; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong Special Administrative Region, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK.
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16
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Krizan I, Solingapuram Sai KK, Damuka N, Macauley SL, Maria Thurman B, Long M, Kavanagh K. Exploratory Dual PET imaging of [ 18F] fluorodeoxyglucose and [ 11C]acetoacetate in type 2 diabetic nonhuman primates. Bioorg Med Chem Lett 2024; 111:129906. [PMID: 39059565 PMCID: PMC11403582 DOI: 10.1016/j.bmcl.2024.129906] [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: 05/01/2024] [Revised: 07/20/2024] [Accepted: 07/23/2024] [Indexed: 07/28/2024]
Abstract
Despite recent advancements in imaging (amyloid-PET & tau-PET) and fluid (Aβ42/Aβ40 & Aβ42/ptau) biomarkers, the current standard for in vivo assessment of AD, diagnosis and prediction of Alzheimer's disease (AD) remains challenging. We demonstrated in nonhuman primates (NHP) that increased plasma and cerebrospinal fluid (CSF) glucose correlated with decreased CSF Aβ42 and CSF Aβ40, a hallmark of plaque promoting pathogenesis. Together, our findings demonstrate that altered glucose homeostasis and insulin resistance are associated with Aβ and amyloid in rodent and NHP models. This warranted further exploration into the dynamics of altered brain metabolism in the NHP model of T2D, cross referenced with CSF and blood-based AD markers. Preliminary dual PET ([11C]acetoacetate ([11C]AcAc) and [18F]fluorodeoxyglucose ([18F]FDG) imaging studies were conducted in an aged cohort of NHPs classified as T2D (n = 5) and pre-diabetic (n = 1) along with corresponding plasma and CSF samples for metabolite analysis. [11C]AcAc and [18F]FDG PET brain standard uptake values (SUV) were highly positively associated (r = 0.88, p = 0.02) in the T2D and pre-diabetic NHPs. Age was not significantly associated with brain SUV (age range 16.5-23.5 years old). Metabolic measures were positively correlated with brain [18F]FDG and CSF Aβ42:40 was positively correlated to fasting glucose values. Although our findings suggest moderate correlations, this study further elucidates that peripheral insulin resistance and poor glycemia control alter AD-related pathology, illustrating how T2D is a risk factor for AD.
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Affiliation(s)
- Ivan Krizan
- Department of Radiology, Wake Forest University School of Medicine, USA
| | | | - Naresh Damuka
- Department of Radiology, Wake Forest University School of Medicine, USA
| | - Shannon L Macauley
- Department of Physiology, University of Kentucky College of Medicine, USA
| | | | - Masha Long
- Department of Physiology, University of Kentucky College of Medicine, USA
| | - Kylie Kavanagh
- Department of Physiology, University of Kentucky College of Medicine, USA; College of Health and Medicine, University of Tasmania, Australia.
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17
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Vanderlip CR, Stark CEL. Digital cognitive assessments as low-burden markers for predicting future cognitive decline and tau accumulation across the Alzheimer's spectrum. Alzheimers Dement 2024; 20:6881-6895. [PMID: 39239892 PMCID: PMC11485398 DOI: 10.1002/alz.14154] [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: 05/09/2024] [Revised: 06/30/2024] [Accepted: 07/02/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND Digital cognitive assessments, particularly those that can be done at home, present as low-burden biomarkers for participants and patients alike, but their effectiveness in the diagnosis of Alzheimer's disease (AD) or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk of cognitive decline. METHODS We analyzed >500 Alzheimer's Disease Neuroimaging Initiative participants who underwent a brief digital cognitive assessment and amyloid beta (Aβ)/tau positron emission tomography scans, examining their ability to distinguish cognitive status and predict cognitive decline. RESULTS Performance on the digital cognitive assessment was superior to both cortical Aβ and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation. DISCUSSION Digital assessments are effective at identifying at-risk individuals, supporting their utility as low-burden tools for early AD detection and monitoring. HIGHLIGHTS Performance on digital cognitive assessments predicts progression to mild cognitive impairment at a higher proficiency compared to amyloid beta and tau. Deficits in mnemonic discrimination are indicative of future cognitive decline. Impaired mnemonic discrimination predicts future entorhinal and inferior temporal tau.
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Affiliation(s)
- Casey R. Vanderlip
- Department of Neurobiology and Behavior1424 Biological Sciences III Irvine, University of California IrvineIrvineCaliforniaUSA
| | - Craig E. L. Stark
- Department of Neurobiology and Behavior1424 Biological Sciences III Irvine, University of California IrvineIrvineCaliforniaUSA
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18
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Walker LC, Jucker M. The prion principle and Alzheimer's disease. Science 2024; 385:1278-1279. [PMID: 39298592 PMCID: PMC11492928 DOI: 10.1126/science.adq5252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Similarities to molecular mechanisms underlying prion diseases may help to refine Alzheimer's disease therapies.
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Affiliation(s)
- Lary C Walker
- Department of Neurology, Emory University, Atlanta, GA, USA
- Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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19
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Nixon RA. Autophagy-lysosomal-associated neuronal death in neurodegenerative disease. Acta Neuropathol 2024; 148:42. [PMID: 39259382 PMCID: PMC11418399 DOI: 10.1007/s00401-024-02799-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 08/30/2024] [Accepted: 08/31/2024] [Indexed: 09/13/2024]
Abstract
Autophagy, the major lysosomal pathway for degrading damaged or obsolete constituents, protects neurons by eliminating toxic organelles and peptides, restoring nutrient and energy homeostasis, and inhibiting apoptosis. These functions are especially vital in neurons, which are postmitotic and must survive for many decades while confronting mounting challenges of cell aging. Autophagy failure, especially related to the declining lysosomal ("phagy") functions, heightens the neuron's vulnerability to genetic and environmental factors underlying Alzheimer's disease (AD) and other late-age onset neurodegenerative diseases. Components of the global autophagy-lysosomal pathway and the closely integrated endolysosomal system are increasingly implicated as primary targets of these disorders. In AD, an imbalance between heightened autophagy induction and diminished lysosomal function in highly vulnerable pyramidal neuron populations yields an intracellular lysosomal build-up of undegraded substrates, including APP-βCTF, an inhibitor of lysosomal acidification, and membrane-damaging Aβ peptide. In the most compromised of these neurons, β-amyloid accumulates intraneuronally in plaque-like aggregates that become extracellular senile plaques when these neurons die, reflecting an "inside-out" origin of amyloid plaques seen in human AD brain and in mouse models of AD pathology. In this review, the author describes the importance of lysosomal-dependent neuronal cell death in AD associated with uniquely extreme autophagy pathology (PANTHOS) which is described as triggered by lysosomal membrane permeability during the earliest "intraneuronal" stage of AD. Effectors of other cell death cascades, notably calcium-activated calpains and protein kinases, contribute to lysosomal injury that induces leakage of cathepsins and activation of additional death cascades. Subsequent events in AD, such as microglial invasion and neuroinflammation, induce further cytotoxicity. In major neurodegenerative disease models, neuronal death and ensuing neuropathologies are substantially remediable by reversing underlying primary lysosomal deficits, thus implicating lysosomal failure and autophagy dysfunction as primary triggers of lysosomal-dependent cell death and AD pathogenesis and as promising therapeutic targets.
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Affiliation(s)
- Ralph A Nixon
- Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, 10962, USA.
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Department of Cell Biology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Neuroscience Institute, New York University, New York, NY, 10012, USA.
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20
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Paterno G, Moore BD, Bell BM, Gorion KMM, Ran Y, Prokop S, Golde TE, Giasson BI. Novel Monoclonal Antibody Specific toward Amyloid-β Binds to a Unique Epitope within the N-Terminal Region. Antibodies (Basel) 2024; 13:68. [PMID: 39189239 PMCID: PMC11348109 DOI: 10.3390/antib13030068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 08/04/2024] [Accepted: 08/06/2024] [Indexed: 08/28/2024] Open
Abstract
Amyloid-β (Aβ) deposition throughout the neuroaxis is a classical hallmark of several neurodegenerative diseases, most notably Alzheimer's disease (AD). Aβ peptides of varied length and diverse structural conformations are deposited within the parenchyma and vasculature in the brains of individuals with AD. Neuropathologically, Aβ pathology can be assessed using antibodies to label and characterize their features, which in turn leads to a more extensive understanding of the pathological process. In the present study, we generated a novel monoclonal antibody, which we found to be specific for the N-terminal region of Aβ. This antibody reacted to amyloid precursor protein expressed in cultured cells and labels Aβ plaques and cerebral amyloid angiopathy in brain tissue from a mouse model of amyloidosis as well as post-mortem brain tissue from patients diagnosed with AD. This highly specific novel antibody will serve as a unique tool for future studies investigating Aβ deposition in novel mouse models and cross-sectional studies using post-mortem human tissue.
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Affiliation(s)
- Giavanna Paterno
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA; (G.P.); (B.M.B.); (K.-M.M.G.)
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL 32610, USA;
| | - Brenda D. Moore
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA 30322, USA; (B.D.M.); (Y.R.); (T.E.G.)
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Brach M. Bell
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA; (G.P.); (B.M.B.); (K.-M.M.G.)
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL 32610, USA;
| | - Kimberly-Marie M. Gorion
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA; (G.P.); (B.M.B.); (K.-M.M.G.)
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL 32610, USA;
| | - Yong Ran
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA 30322, USA; (B.D.M.); (Y.R.); (T.E.G.)
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Stefan Prokop
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL 32610, USA;
- McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32610, USA
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Todd E. Golde
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA 30322, USA; (B.D.M.); (Y.R.); (T.E.G.)
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Benoit I. Giasson
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA; (G.P.); (B.M.B.); (K.-M.M.G.)
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL 32610, USA;
- McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL 32610, USA
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21
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Li M, Guan M, Lin J, Zhu K, Zhu J, Guo M, Li Y, Chen Y, Chen Y, Zou Y, Wu D, Xu J, Yi W, Fan Y, Ma S, Chen Y, Xu J, Yang L, Dai J, Ye T, Lu Z, Chen Y. Early blood immune molecular alterations in cynomolgus monkeys with a PSEN1 mutation causing familial Alzheimer's disease. Alzheimers Dement 2024; 20:5492-5510. [PMID: 38973166 PMCID: PMC11350033 DOI: 10.1002/alz.14046] [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: 10/21/2023] [Revised: 05/04/2024] [Accepted: 05/14/2024] [Indexed: 07/09/2024]
Abstract
INTRODUCTION More robust non-human primate models of Alzheimer's disease (AD) will provide new opportunities to better understand the pathogenesis and progression of AD. METHODS We designed a CRISPR/Cas9 system to achieve precise genomic deletion of exon 9 in cynomolgus monkeys using two guide RNAs targeting the 3' and 5' intron sequences of PSEN1 exon 9. We performed biochemical, transcriptome, proteome, and biomarker analyses to characterize the cellular and molecular dysregulations of this non-human primate model. RESULTS We observed early changes of AD-related pathological proteins (cerebrospinal fluid Aβ42 and phosphorylated tau) in PSEN1 mutant (ie, PSEN1-ΔE9) monkeys. Blood transcriptome and proteome profiling revealed early changes in inflammatory and immune molecules in juvenile PSEN1-ΔE9 cynomolgus monkeys. DISCUSSION PSEN1 mutant cynomolgus monkeys recapitulate AD-related pathological protein changes, and reveal early alterations in blood immune signaling. Thus, this model might mimic AD-associated pathogenesis and has potential utility for developing early diagnostic and therapeutic interventions. HIGHLIGHTS A dual-guide CRISPR/Cas9 system successfully mimics AD PSEN1-ΔE9 mutation by genomic excision of exon 9. PSEN1 mutant cynomolgus monkey-derived fibroblasts exhibit disrupted PSEN1 endoproteolysis and increased Aβ secretion. Blood transcriptome and proteome profiling implicate early inflammatory and immune molecular dysregulation in juvenile PSEN1 mutant cynomolgus monkeys. Cerebrospinal fluid from juvenile PSEN1 mutant monkeys recapitulates early changes of AD-related pathological proteins (increased Aβ42 and phosphorylated tau).
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Affiliation(s)
- Mengqi Li
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
| | - Mingfeng Guan
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
| | - Jianbang Lin
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
| | - Kaichuan Zhu
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
| | - Jiayi Zhu
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
| | - Ming Guo
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
| | - Yinhu Li
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
| | - Yefei Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
| | - Yijing Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
| | - Ying Zou
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
| | - Daiqiang Wu
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
| | - Junxin Xu
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
| | - Wanying Yi
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
| | - Yingying Fan
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
| | - Shuangshuang Ma
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
| | - Yuewen Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
| | - Jun Xu
- Department of NeurologyBeijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Lixin Yang
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
| | - Ji Dai
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
| | - Tao Ye
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zhonghua Lu
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Shenzhen Technological Research Center for Primate Translational MedicineShenzhen Key Laboratory for Molecular Biology of Neural DevelopmentShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
- The Key Laboratory of Biomedical Imaging Science and SystemChinese Academy of SciencesShenzhenChina
| | - Yu Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and ManipulationShenzhen Key Laboratory of Translational Research for Brain Diseasesthe Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of Sciences, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug DevelopmentHKUST Shenzhen Research Institute, Shenzhen‐Hong Kong Institute of Brain Science—Shenzhen Fundamental Research InstitutionsShenzhenChina
- SIAT‐HKUST Joint Laboratory for Brain ScienceChinese Academy of SciencesShenzhenChina
- University of Chinese Academy of SciencesBeijingChina
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22
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Jack CR, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, Molinuevo JL, Okonkwo OC, Pani L, Rafii MS, Scheltens P, Siemers E, Snyder HM, Sperling R, Teunissen CE, Carrillo MC. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement 2024; 20:5143-5169. [PMID: 38934362 PMCID: PMC11350039 DOI: 10.1002/alz.13859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/21/2024] [Accepted: 04/04/2024] [Indexed: 06/28/2024]
Abstract
The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.
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Affiliation(s)
| | - J. Scott Andrews
- Global Evidence & OutcomesTakeda Pharmaceuticals Company LimitedCambridgeMassachusettsUSA
| | - Thomas G. Beach
- Civin Laboratory for NeuropathologyBanner Sun Health Research InstituteSun CityArizonaUSA
| | - Teresa Buracchio
- Office of NeuroscienceU.S. Food and Drug AdministrationSilver SpringMarylandUSA
| | - Billy Dunn
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Ana Graf
- NovartisNeuroscience Global Drug DevelopmentBaselSwitzerland
| | - Oskar Hansson
- Department of Clinical Sciences Malmö, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, MalmöLundSweden
| | - Carole Ho
- DevelopmentDenali TherapeuticsSouth San FranciscoCaliforniaUSA
| | - William Jagust
- School of Public Health and Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Eric McDade
- Department of NeurologyWashington University St. Louis School of MedicineSt. LouisMissouriUSA
| | - Jose Luis Molinuevo
- Department of Global Clinical Development H. Lundbeck A/SExperimental MedicineCopenhagenDenmark
| | - Ozioma C. Okonkwo
- Department of Medicine, Division of Geriatrics and GerontologyUniversity of Wisconsin School of MedicineMadisonWisconsinUSA
| | - Luca Pani
- University of MiamiMiller School of MedicineMiamiFloridaUSA
| | - Michael S. Rafii
- Alzheimer's Therapeutic Research Institute (ATRI)Keck School of Medicine at the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Philip Scheltens
- Amsterdam University Medical Center (Emeritus)NeurologyAmsterdamthe Netherlands
| | - Eric Siemers
- Clinical ResearchAcumen PharmaceuticalsZionsvilleIndianaUSA
| | - Heather M. Snyder
- Medical & Scientific Relations DivisionAlzheimer's AssociationChicagoIllinoisUSA
| | - Reisa Sperling
- Department of Neurology, Brigham and Women's HospitalMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Charlotte E. Teunissen
- Department of Laboratory MedicineAmsterdam UMC, Neurochemistry LaboratoryAmsterdamthe Netherlands
| | - Maria C. Carrillo
- Medical & Scientific Relations DivisionAlzheimer's AssociationChicagoIllinoisUSA
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Wang G, Li Y, Xiong C, Cao Y, Schindler SE, McDade E, Blennow K, Hansson O, Dage JL, Jack CR, Teunissen CE, Shaw LM, Zetterberg H, Laura I, Timsina J, Carlos C, Bateman RJ. The CentiMarker Project: Standardizing Quantitative Alzheimer's disease Fluid Biomarkers for Biologic Interpretation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.25.24311002. [PMID: 39108526 PMCID: PMC11302716 DOI: 10.1101/2024.07.25.24311002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Introduction Biomarkers have been essential to understanding Alzheimer's disease (AD) pathogenesis, pathophysiology, progression, and treatment effects. However, each biomarker measure is a representation of the biological target, the assay used to measure it, and the variance of the assay. Thus, biomarker measures are difficult to compare without standardization, and the units and magnitude of effect relative to the disease are difficult to appreciate, even for experts. To facilitate quantitative comparisons of AD biomarkers in the context of biologic and treatment effects, we propose a biomarker standardization approach between normal ranges and maximum abnormal AD ranges, which we refer to as CentiMarker, similar to the Centiloid approach used in PET. Methods We developed a standardization scale that creates percentile values ranging from 0 for a normal population to 100 for the most abnormal measures across disease stages. We applied this scale to CSF and plasma biomarkers in autosomal dominant AD, assessing the distribution by estimated years from symptom onset, between biomarkers, and across cohorts. We then validated this approach in a large national sporadic AD cohort. Results We found the CentiMarker scale provided an easily interpretable metric of disease abnormality. The biologic changes, range, and distribution of several AD fluid biomarkers including amyloid-β, phospho-tau and other biomarkers, were comparable across disease stages in both early onset autosomal dominant and sporadic late onset AD. Discussion The CentiMarker scale offers a robust and versatile framework for the standardized biological comparison of AD biomarkers. Its broader adoption could facilitate biomarker reporting, allowing for more informed cross-study comparisons and contributing to accelerated therapeutic development.
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Affiliation(s)
- Guoqiao Wang
- Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University, School of Medicine, St. Louis, MO, USA
| | - Yan Li
- Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University, School of Medicine, St. Louis, MO, USA
| | - Yuchen Cao
- 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
| | - Eric McDade
- Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
| | - 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
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Leslie M Shaw
- Department of Pathology & Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, 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
| | - Ibanez Laura
- Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University, St. Louis, 63110, MO, USA
- Neuro Genomics and Informatics. Washington University, St. Louis, 63110, MO, USA
| | - Cruchaga Carlos
- Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
- Department of Psychiatry, Washington University, St. Louis, 63110, MO, USA
- Neuro Genomics and Informatics. Washington University, St. Louis, 63110, MO, USA
| | | | - Randall J. Bateman
- Department of Neurology, Washington University, School of Medicine, St. Louis, MO, USA
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Wang Y, Ye M, Ji Q, Liu Q, Xu X, Zhan Y. The longitudinal trajectory of CSF sTREM2: the alzheimer's disease neuroimaging initiative. Alzheimers Res Ther 2024; 16:138. [PMID: 38926894 PMCID: PMC11202383 DOI: 10.1186/s13195-024-01506-8] [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: 01/03/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND The soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) is considered a biomarker of microglia activity. The objective of this study was to investigate the trajectory of CSF sTREM2 levels over time and examine its association with sex. METHODS A total of 1,017 participants from the Alzheimer's Disease Neuroimaging Initiative Study (ADNI) with at least one CSF sTREM2 record were included. The trajectory of CSF sTREM2 was analyzed using a growth curve model. The association between CSF sTREM2 levels and sex was assessed using linear mixed-effect models. RESULTS CSF sTREM2 levels were increased with age over time (P < 0.0001). No significant sex difference was observed in sTREM2 levels across the entire sample; however, among the APOE ε4 allele carriers, women exhibited significantly higher sTREM2 levels than men (β = 0.146, P = 0.002). CONCLUSION Our findings highlight the association between CSF sTREM2 levels and age-related increments, underscoring the potential influence of aging on sTREM2 dynamics. Furthermore, our observations indicate a noteworthy association between sex and CSF sTREM2 levels, particularly in individuals carrying the APOE ε4 allele.
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Affiliation(s)
- Yu Wang
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
| | - Meijie Ye
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
| | - Qianqian Ji
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
| | - Qi Liu
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
| | - Xiaowei Xu
- Department of Neurology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China.
| | - Yiqiang Zhan
- Department of Epidemiology, School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China.
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
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25
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Lin C, Kong Y, Chen Q, Zeng J, Pan X, Miao J. Decoding sTREM2: its impact on Alzheimer's disease - a comprehensive review of mechanisms and implications. Front Aging Neurosci 2024; 16:1420731. [PMID: 38912524 PMCID: PMC11190086 DOI: 10.3389/fnagi.2024.1420731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Accepted: 05/30/2024] [Indexed: 06/25/2024] Open
Abstract
Soluble Triggering Receptor Expressed on Myeloid Cells 2 (sTREM2) plays a crucial role in the pathogenesis of Alzheimer's disease (AD). This review comprehensively examines sTREM2's involvement in AD, focusing on its regulatory functions in microglial responses, neuroinflammation, and interactions with key pathological processes. We discuss the dynamic changes in sTREM2 levels in cerebrospinal fluid and plasma throughout AD progression, highlighting its potential as a therapeutic target. Furthermore, we explore the impact of genetic variants on sTREM2 expression and its interplay with other AD risk genes. The evidence presented in this review suggests that modulating sTREM2 activity could influence AD trajectory, making it a promising avenue for future research and drug development. By providing a holistic understanding of sTREM2's multifaceted role in AD, this review aims to guide future studies and inspire novel therapeutic strategies.
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Affiliation(s)
- Cui Lin
- Shenzhen Bao’an District Hospital of Traditional Chinese Medicine, Shenzhen, Guangdong, China
| | - Yu Kong
- Shenzhen Bao’an District Hospital of Traditional Chinese Medicine, Shenzhen, Guangdong, China
| | - Qian Chen
- Shenzhen Bao’an District Hospital of Traditional Chinese Medicine, Shenzhen, Guangdong, China
| | - Jixiang Zeng
- Shenzhen Bao’an Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Xiaojin Pan
- Shenzhen Bao’an District Hospital of Traditional Chinese Medicine, Shenzhen, Guangdong, China
| | - Jifei Miao
- Shenzhen Bao’an District Hospital of Traditional Chinese Medicine, Shenzhen, Guangdong, China
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26
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Hansen N, Wiltfang J. Fluid biomarkers unveil signatures of pathological aging. Seizure 2024:S1059-1311(24)00158-4. [PMID: 38871529 DOI: 10.1016/j.seizure.2024.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 05/29/2024] [Accepted: 05/30/2024] [Indexed: 06/15/2024] Open
Abstract
Aging is a multifaceted and highly varied process in the brain. Identifying aging biomarkers is one means of distinguishing pathological from physiological aging. The aim of this narrative review is to focus on two new developments in the field of fluid biomarkers and draw attention to this excellent tool for the early detection of potential brain pathologies that delay, alter, or enable physiological aging to become pathological. Pathological aging can lower the threshold for the development of specific diseases such as late-onset epilepsy. Fluid biomarkers can reveal pathological levels at an early stage and thus indicate disease processes in the brain that begin before symptoms develop; they thus differ from physiological aging.
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Affiliation(s)
- Niels Hansen
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Von-Siebold-Str. 5, 37075 Göttingen, Germany.
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Von-Siebold-Str. 5, 37075 Göttingen, Germany; German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075, Göttingen, Germany; Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
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27
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Vanderlip CR, Stark CE. Digital cognitive assessments as low-burden markers for predicting future cognitive decline and tau accumulation across the Alzheimer's spectrum. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595638. [PMID: 38826456 PMCID: PMC11142177 DOI: 10.1101/2024.05.23.595638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Digital cognitive assessments, particularly those that can be done at home, present as low burden biomarkers for participants and patients alike, but their effectiveness in diagnosis of Alzheimer's or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk for cognitive decline. We analyzed >500 ADNI participants who underwent a brief digital cognitive assessment and Aβ/tau PET scans, examining their ability to distinguish cognitive status and predict cognitive decline. Performance on the digital cognitive assessment were superior to both cortical Aβ and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation. Digital assessments are effective in identifying at-risk individuals, supporting their utility as low-burden tools for early Alzheimer's detection and monitoring.
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Affiliation(s)
- Casey R. Vanderlip
- Department of Neurobiology and Behavior, 1424 Biological Sciences III Irvine, University of California Irvine, Irvine, CA, 92697 USA
| | - Craig E.L. Stark
- Department of Neurobiology and Behavior, 1424 Biological Sciences III Irvine, University of California Irvine, Irvine, CA, 92697 USA
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Vanderlip C, Lee MD, Stark CE. Cognitive modeling of the Mnemonic Similarity Task as a digital biomarker for Alzheimer's Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.07.584012. [PMID: 38559159 PMCID: PMC10979889 DOI: 10.1101/2024.03.07.584012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
AD related pathologies, such as beta-amyloid (Aβ) and phosphorylated tau (pTau), are evident decades before any noticeable decline in memory occurs. Identifying individuals during this asymptomatic phase is crucial for timely intervention. The Mnemonic Similarity Task (MST), a modified recognition memory task, is especially relevant for early AD screening, as it assesses hippocampal integrity, a region affected (both directly and indirectly) early in the progression of the disease. Further, strong inferences on the underlying cognitive mechanisms that support performance on this task can be made using Bayesian cognitive modeling. We assessed whether analyzing MST performance using a cognitive model could detect subtle changes in cognitive function and AD biomarker status prior to overt cognitive decline. We analyzed MST data from >200 individuals (young, cognitively healthy older adults, and individuals with MCI), a subset of which also had existing CSF Aβ and pTau data. Traditional performance scores and cognitive modeling using multinomial processing trees was applied to each participants MST data using Bayesian approaches. We assessed how well each could predict age group, memory ability, MCI status, Aβ/pTau status using ROC analyses. Both approaches predicted age group membership equally, but cognitive modeling approaches exceeded traditional metrics in all other comparisons. This work establishes that cognitive modeling of the MST can detect individuals with AD prior to cognitive decline, making it a potentially useful tool for both screening and monitoring older adults during the asymptomatic phase of AD.
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Affiliation(s)
- Casey Vanderlip
- Department of Neurobiology and Behavior, University of California Irvine
| | - Michael D. Lee
- Department of Cognitive Science, University of California, Irvine
| | - Craig E.L. Stark
- Department of Neurobiology and Behavior, University of California Irvine
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Walter S, Langford O, Jimenez-Maggiora GA, Abdel-Latif S, Rissman RA, Grill JD, Karlawish J, Atri A, Bruschi S, Hussen K, Donohue MC, Marshall GA, Jicha G, Racke M, Turner RS, van Dyck CH, Venkatesh V, Yarasheski KE, Sperling R, Cummings J, Aisen PS, Raman R. The AlzMatch Pilot Study - Feasibility of Remote Blood Collection of Plasma Biomarkers for Preclinical Alzheimer's Disease Trials. J Prev Alzheimers Dis 2024; 11:1435-1444. [PMID: 39350391 PMCID: PMC11436450 DOI: 10.14283/jpad.2024.101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 04/30/2024] [Indexed: 10/04/2024]
Abstract
BACKGROUND Advances in plasma biomarkers to detect Alzheimer's disease (AD) biology allows researchers to improve the efficiency of participant recruitment into preclinical trials. Recently, protein levels of plasma amyloid-beta and tau proteins have been shown to be predictive of elevated amyloid in brain. Online registries, such as the Alzheimer's Prevention Trials (APT) Webstudy, include and follow participants using remote assessments to facilitate efficient screening and enrollment of large numbers of individuals who may be at higher risk for AD. OBJECTIVES The AlzMatch Pilot Study investigated the feasibility of recruiting individuals from an online registry for blood sample collection at community-based phlebotomy centers and plasma biomarker quantification to assess an individual's eligibility for AD preclinical trials. DESIGN Pilot feasibility study with co-primary outcomes. SETTING This pilot feasibility study included participants from the APT Webstudy, the remote assessment arm of the Trial-ready cohort for Preclinical and Prodromal AD (TRC-PAD) Platform. Novel design included collection of electronic consent, use of community laboratories for plasma collection, mass spectrometry-based biomarker assay, and telephone communication of plasma biomarker screening eligibility. PARTICIPANTS Participants invited to the AlzMatch pilot feasibility study were active in the APT Webstudy, 50 years of age or older, resided within 50 miles of both a Quest Diagnostics Patient Services Center (a national diagnostic laboratory with convenient locations for sample collection and processing) and one of six TRC-PAD vanguard clinical trial sites, had no self-reported dementia diagnosis, were able to communicate in English and engaged with the APT Webstudy within the prior 6 months. MEASUREMENTS Primary feasibility outcomes were completion of electronic consent (e-consent) for invited participants and collection of usable blood samples. Additional feasibility outcomes included invitation response rate, plasma biomarker eligibility status (based on amyloid beta-42/40 [Aβ42/40] concentration ratio), ApoE proteotype, and trial inclusion criterion), and completion of telephone contact to learn eligibility to screen for a study. RESULTS 300 APT Webstudy participants were invited to consent to the AlzMatch study. The AlzMatch e-consent rate was 39% (n=117) (95% CI of 33.5%-44.5%) overall, which was higher than the expected rate of 25%. Similar consent rates were observed across participants based on self-defined sex (41% Female (n=75), 37% Male (n=42)) and race and ethnicity (37% from underrepresented groups (URG) (n=36), 40% not from URG (n=79)). Among those that consented (n=117), plasma was successfully collected from 74% (n=87) (95% CI of 66%-82%), with similar rates across sex (76% Female (n=57), 71% Male (n=30)) and race and ethnicity (75% URG (n=27) and 75% not from URG (n=59)). 60% (n=51) of participants with plasma biomarker results were eligible to screen for future preclinical AD trials. CONCLUSION Electronic consent of participants through an online registry, blood sample collection at community-based centers, plasma biomarker quantification and reporting, and biomarker assessments for study eligibility were all feasible with similar engagement rates across demographic groups. Although this pilot was a small and selective sample, participants engaged and consented at higher than expected rates. We conclude that collecting blood at community laboratories for biomarker analyses may improve accessibility beyond research, and may facilitate broader access for clinical use of AD plasma biomarkers. Based on our results, an expanded version of the AlzMatch study is underway, which involves expanding invitations to additional APT Webstudy participants and clinical trial sites.
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Affiliation(s)
- S Walter
- Sarah Walter, Alzheimer's Therapeutic Research Institute, University of Southern California, USA,
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30
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Molina-Henry D, Langford O, Donohue MC, Raman R, Aisen P, Johnson KA, Rissman RA, Sperling R. Relationship between Plasma P-Tau217 and Amyloid PET in Racial and Ethnic Underrepresented Groups (RE-URG) Compared with Non RE-URG in LEARN and A4. J Prev Alzheimers Dis 2024; 11:831-837. [PMID: 39044491 PMCID: PMC11266219 DOI: 10.14283/jpad.2024.124] [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: 06/01/2024] [Accepted: 06/13/2024] [Indexed: 07/25/2024]
Abstract
BACKGROUND Individuals from diverse racial and ethnic groups are severely underrepresented in Alzheimer's disease trials in part due to disproportionate biomarker ineligibility. Evidence from recent studies support plasma phosphorylated tau 217 (P-tau217) as an early marker for brain Aβ pathology and a reliable marker in predicting elevated brain amyloid PET in cognitively unimpaired adults. OBJECTIVES To examine whether the relationship between P-tau217 and 18-F florbetapir PET standard uptake value ratios (SUVR) is influenced by race and ethnicity in the Anti-Amyloid treatment in Asymptomatic Alzheimer's disease (A4) preclinical AD studies. DESIGN We conducted a retrospective analysis of A4 clinical trial and the LEARN natural history companion study data to evaluate the relationship between baseline P-tau217 and PET SUVR concentration levels by race and ethnicity. SETTING The analysis was conducted on samples from participants enrolled across 65 study sites in the United States and Canada. PARTICIPANTS Cognitively unimpaired adults aged 65-85 enrolled at North American sites in the A4 preclinical AD trial, pre-dose, (N=1018), and the LEARN (N=480) study. Participants were grouped into 2 categories, racial and ethnic underrepresented group (RE-URG) and non-RE-URG (nRE-URG) based on self-identification. MEASUREMENTS A mixed-effects regression model was fit to determine differences in the relationship between P-tau217 and PET SUVR by race and ethnicity, adjusting for age, and APOE ε4 carrier status. RESULTS Results from the linear mixed-effects model support that there was no statistically significant effect of race and ethnicity on the relationship between P-tau217 and PET SUVR. CONCLUSION These findings suggest that the relationship between plasma P-tau217 and PET SUVR is the same across race and ethnicity. Future analyses should corroborate these findings in a larger sample and examine whether plasma P-tau217 reflects the differential amyloid prevalence previously reported for other biomarkers of amyloid.
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Affiliation(s)
- D Molina-Henry
- Doris Molina-Henry, PhD, Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, USA,
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31
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Aschenbrenner AJ, Hassenstab JJ, Schindler SE, Janelidze S, Hansson O, Morris JC, Grober E. Free Recall Outperforms Story Recall in Associations with Plasma Biomarkers in Preclinical Alzheimer Disease. J Prev Alzheimers Dis 2024; 11:1696-1702. [PMID: 39559880 PMCID: PMC11573877 DOI: 10.14283/jpad.2024.130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2024]
Abstract
BACKGROUND A decline in episodic memory is one of the earliest cognitive characteristics of Alzheimer disease and memory tests are heavily featured in cognitive composite endpoints that are used to demonstrate treatment efficacy. Assessments of episodic memory can take many forms including free recall, associate learning, and paragraph or story recall. Plasma biomarkers of Alzheimer disease are now widely available and will likely form the backbone of cohort enrichment strategies for future clinical trials. Thus, it is critical to evaluate which episodic memory measures are most sensitive to plasma markers of Alzheimer disease pathology. OBJECTIVES To compare the associations of common episodic memory tests with plasma biomarkers of Alzheimer disease. DESIGN Longitudinal cohort study. SETTING Academic medical center in the midwestern United States. PARTICIPANTS A total of 161 cognitively normal older adults with at least one plasma biomarker assessment and two or more annual clinical and cognitive assessments which included up to three different tests of episodic memory. MEASUREMENTS Episodic memory performance using free recall, paired associates recall or paragraph recall. Plasma Aβ42, Aβ40, ptau217, and neurofilament light chain were measured. RESULTS Free recall on the Free and Cued Selective Reminding Test with Immediate Recall (FCSRT + IR) was substantially more sensitive to longitudinal cognitive change associated with abnormal baseline plasma Aβ42/Aβ40 and ptau217 compared to other measures of episodic memory. A cognitive composite that included only free recall showed larger decline associated with baseline Aβ42/Aβ40 when compared to those that included paragraph recall. Differences in decline across composites were minimal when considering baseline ptau217 or NfL. CONCLUSION Episodic memory is a critical domain to assess in preclinical Alzheimer disease. Methods of assessing memory are not equal and longitudinal change in free recall substantially outperformed both paired associates and paragraph recall. Clinical trial results will depend critically on the episodic memory test(s) that are chosen for a composite endpoint and free recall from the FCSRT + IR is an optimal memory measure to include rather than paired associates or paragraph recall.
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Affiliation(s)
- A J Aschenbrenner
- Andrew Aschenbrenner, PhD, 4488 Forest Park Ave, STE 301, St. Louis, MO, 63108, , 314-273-1041
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