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Liu K, Tao Y, Zhao Q, Xia W, Li X, Zhang S, Yao Y, Xiang H, Han C, Tan L, Sun B, Li D, Li A, Liu C. Binding adaptability of chemical ligands to polymorphic α-synuclein amyloid fibrils. Proc Natl Acad Sci U S A 2024; 121:e2321633121. [PMID: 39172784 DOI: 10.1073/pnas.2321633121] [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: 12/08/2023] [Accepted: 07/17/2024] [Indexed: 08/24/2024] Open
Abstract
α-synuclein (α-syn) assembles into structurally distinct fibril polymorphs seen in different synucleinopathies, such as Parkinson's disease and multiple system atrophy. Targeting these unique fibril structures using chemical ligands holds diagnostic significance for different disease subtypes. However, the molecular mechanisms governing small molecules interacting with different fibril polymorphs remain unclear. Here, we investigated the interactions of small molecules belonging to four distinct scaffolds, with different α-syn fibril polymorphs. Using cryo-electron microscopy, we determined the structures of these molecules when bound to the fibrils formed by E46K mutant α-syn and compared them to those bound with wild-type α-syn fibrils. Notably, we observed that these ligands exhibit remarkable binding adaptability, as they engage distinct binding sites across different fibril polymorphs. While the molecular scaffold primarily steered the binding locations and geometries on specific sites, the conjugated functional groups further refined this adaptable binding by fine-tuning the geometries and binding sites. Overall, our finding elucidates the adaptability of small molecules binding to different fibril structures, which sheds light on the diagnostic tracer and drug developments tailored to specific pathological fibril polymorphs.
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Affiliation(s)
- Kaien Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Youqi Tao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Qinyue Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Wencheng Xia
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Xiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Shenqing Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yuxuan Yao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Huaijiang Xiang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Chao Han
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Li Tan
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Bo Sun
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Dan Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ang Li
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
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Islam MR, Rabbi MA, Hossain T, Sultana S, Uddin S. Mechanistic Approach to Immunity and Immunotherapy of Alzheimer's Disease: A Review. ACS Chem Neurosci 2024. [PMID: 39173186 DOI: 10.1021/acschemneuro.4c00360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2024] Open
Abstract
Alzheimer's disease (AD) is a debilitating neurodegenerative condition characterized by progressive cognitive decline and memory loss, affecting millions of people worldwide. Traditional treatments, such as cholinesterase inhibitors and NMDA receptor antagonists, offer limited symptomatic relief without addressing the underlying disease mechanisms. These limitations have driven the development of more potent and effective therapies. Recent advances in immunotherapy present promising avenues for AD treatment. Immunotherapy strategies, including both active and passive approaches, harness the immune system to target and mitigate AD-related pathology. Active immunotherapy stimulates the patient's immune response to produce antibodies against AD-specific antigens, while passive immunotherapy involves administering preformed antibodies or immune cells that specifically target amyloid-β (Aβ) or tau proteins. Monoclonal antibodies, such as aducanumab and lecanemab, have shown potential in reducing Aβ plaques and slowing cognitive decline in clinical trials, despite challenges related to adverse immune responses and the need for precise targeting. This comprehensive review explores the role of the immune system in AD, evaluates the current successes and limitations of immunotherapeutic approaches, and discusses future directions for enhancing the treatment efficacy.
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Affiliation(s)
- Md Rubiath Islam
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
| | - Md Afser Rabbi
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
| | - Tanbir Hossain
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
| | - Sadia Sultana
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
| | - Shihab Uddin
- Department of Bioengineering, King Fahad University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
- Interdisciplinary Research Center for Bio Systems and Machines, King Fahad University of Petroleum & Minerals, Dhahran-31261, Saudi Arabia
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Dyer AH, Dolphin H, O'Connor A, Morrison L, Sedgwick G, Young C, Killeen E, Gallagher C, McFeely A, Connolly E, Davey N, Claffey P, Doyle P, Lyons S, Gaffney C, Ennis R, McHale C, Joseph J, Knight G, Kelly E, O'Farrelly C, Fallon A, O'Dowd S, Bourke NM, Kennelly SP. Performance of plasma p-tau217 for the detection of amyloid-β positivity in a memory clinic cohort using an electrochemiluminescence immunoassay. Alzheimers Res Ther 2024; 16:186. [PMID: 39160628 PMCID: PMC11331802 DOI: 10.1186/s13195-024-01555-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 08/11/2024] [Indexed: 08/21/2024]
Abstract
BACKGROUND Plasma p-tau217 has emerged as the most promising blood-based marker (BBM) for the detection of Alzheimer Disease (AD) pathology, yet few studies have evaluated plasma p-tau217 performance in memory clinic settings. We examined the performance of plasma p-tau217 for the detection of AD using a high-sensitivity immunoassay in individuals undergoing diagnostic lumbar puncture (LP). METHODS Paired plasma and cerebrospinal fluid (CSF) samples were analysed from the TIMC-BRAiN cohort. Amyloid (Aβ) and Tau (T) pathology were classified based on established cut-offs for CSF Aβ42 and CSF p-tau181 respectively. High-sensitivity electrochemiluminescence (ECL) immunoassays were performed on paired plasma/CSF samples for p-tau217, p-tau181, Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light (NfL) and total tau (t-tau). Biomarker performance was evaluated using Receiver-Operating Curve (ROC) and Area-Under-the-Curve (AUC) analysis. RESULTS Of 108 participants (age: 69 ± 6.5 years; 54.6% female) with paired samples obtained at time of LP, 64.8% (n = 70/108) had Aβ pathology detected (35 with Mild Cognitive Impairment and 35 with mild dementia). Plasma p-tau217 was over three-fold higher in Aβ + (12.4 pg/mL; 7.3-19.2 pg/mL) vs. Aβ- participants (3.7 pg/mL; 2.8-4.1 pg/mL; Mann-Whitney U = 230, p < 0.001). Plasma p-tau217 exhibited excellent performance for the detection of Aβ pathology (AUC: 0.91; 95% Confidence Interval [95% CI]: 0.86-0.97)-greater than for T pathology (AUC: 0.83; 95% CI: 0.75-0.90; z = 1.75, p = 0.04). Plasma p-tau217 outperformed plasma p-tau181 for the detection of Aβ pathology (z = 3.24, p < 0.001). Of the other BBMs, only plasma GFAP significantly differed by Aβ status which significantly correlated with plasma p-tau217 in Aβ + (but not in Aβ-) individuals. Application of a two-point threshold at 95% and 97.5% sensitivities & specificities may have enabled avoidance of LP in 58-68% of cases. CONCLUSIONS Plasma p-tau217 measured using a high-sensitivity ECL immunoassay demonstrated excellent performance for detection of Aβ pathology in a real-world memory clinic cohort. Moving forward, clinical use of plasma p-tau217 to detect AD pathology may substantially reduce need for confirmatory diagnostic testing for AD pathology with diagnostic LP in specialist memory services.
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Affiliation(s)
- Adam H Dyer
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland.
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland.
| | - Helena Dolphin
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Laura Morrison
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Gavin Sedgwick
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Conor Young
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Emily Killeen
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Conal Gallagher
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Aoife McFeely
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Eimear Connolly
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Naomi Davey
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Paul Claffey
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Paddy Doyle
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Shane Lyons
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Christine Gaffney
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Ruth Ennis
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Cathy McHale
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Jasmine Joseph
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Graham Knight
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Emmet Kelly
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Cliona O'Farrelly
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Aoife Fallon
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean O'Dowd
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Nollaig M Bourke
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean P Kennelly
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
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Martinez-Murcia FJ, Arco JE, Jimenez-Mesa C, Segovia F, Illan IA, Ramirez J, Gorriz JM. Bridging Imaging and Clinical Scores in Parkinson's Progression via Multimodal Self-Supervised Deep Learning. Int J Neural Syst 2024; 34:2450043. [PMID: 38770651 DOI: 10.1142/s0129065724500436] [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: 05/22/2024]
Abstract
Neurodegenerative diseases pose a formidable challenge to medical research, demanding a nuanced understanding of their progressive nature. In this regard, latent generative models can effectively be used in a data-driven modeling of different dimensions of neurodegeneration, framed within the context of the manifold hypothesis. This paper proposes a joint framework for a multi-modal, common latent generative model to address the need for a more comprehensive understanding of the neurodegenerative landscape in the context of Parkinson's disease (PD). The proposed architecture uses coupled variational autoencoders (VAEs) to joint model a common latent space to both neuroimaging and clinical data from the Parkinson's Progression Markers Initiative (PPMI). Alternative loss functions, different normalization procedures, and the interpretability and explainability of latent generative models are addressed, leading to a model that was able to predict clinical symptomatology in the test set, as measured by the unified Parkinson's disease rating scale (UPDRS), with R2 up to 0.86 for same-modality and 0.441 cross-modality (using solely neuroimaging). The findings provide a foundation for further advancements in the field of clinical research and practice, with potential applications in decision-making processes for PD. The study also highlights the limitations and capabilities of the proposed model, emphasizing its direct interpretability and potential impact on understanding and interpreting neuroimaging patterns associated with PD symptomatology.
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Affiliation(s)
- Francisco J Martinez-Murcia
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Center for Advanced Studies, Ludwig-Maximilien Universität München, München, Germany
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
| | - Juan Eloy Arco
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
| | - Carmen Jimenez-Mesa
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
| | - Fermin Segovia
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
| | - Ignacio A Illan
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
| | - Javier Ramirez
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
| | - Juan Manuel Gorriz
- Department of Signal Processing, Networking and Communications, University of Granada, Granada, Spain
- Center for Advanced Studies, Ludwig-Maximilien Universität München, München, Germany
- Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
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5
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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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6
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Klug S, Murgaš M, Godbersen GM, Hacker M, Lanzenberger R, Hahn A. Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain. Neuroimage 2024; 295:120658. [PMID: 38810891 DOI: 10.1016/j.neuroimage.2024.120658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/22/2024] [Accepted: 05/27/2024] [Indexed: 05/31/2024] Open
Abstract
PURPOSE The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach. METHODS 51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions. RESULTS Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning. CONCLUSIONS Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.
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Affiliation(s)
- Sebastian Klug
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Matej Murgaš
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Godber M Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria.
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7
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Warmenhoven N, Salvadó G, Janelidze S, Mattsson-Carlgren N, Bali D, Dolado AO, Kolb H, Triana-Baltzer G, Barthélemy NR, Schindler SE, Aschenbrenner AJ, Raji CA, Benzinger TL, Morris JC, Ibanez L, Timsina J, Cruchaga C, Bateman RJ, Ashton N, Arslan B, Zetterberg H, Blennow K, Pichet Binette A, Hansson O. A Comprehensive Head-to-Head Comparison of Key Plasma Phosphorylated Tau 217 Biomarker Tests. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.02.24309629. [PMID: 39006421 PMCID: PMC11245081 DOI: 10.1101/2024.07.02.24309629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarkers for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU]and ptau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, and the FDA-approved p-tau181/Aβ42Elecsys and p-tau181Elecsys. All plasma p-tau217 tests exhibited high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (P diff<0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (P diff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (P diff=0.025). Plasma %p-tau217WashU exhibited higher associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more strongly associated with Aβ-PET load than plasma p-tau217Janssen (P diff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all P diff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; P diff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217Nulisa showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test.
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Affiliation(s)
- Noëlle Warmenhoven
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Anna Orduña Dolado
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, USA
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, USA
| | - Nicolas R. Barthélemy
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Cyrus A. Raji
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University St. Louis, MO, USA
| | - Randall J. Bateman
- The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicholas Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund University, Lund, Sweden
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8
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Langley J, Bennett IJ, Hu XP. Examining iron-related off-target binding effects of 18F-AV1451 PET in the cortex of Aβ+ individuals. Eur J Neurosci 2024; 60:3614-3628. [PMID: 38722153 DOI: 10.1111/ejn.16362] [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: 02/10/2023] [Revised: 12/22/2023] [Accepted: 04/01/2024] [Indexed: 07/06/2024]
Abstract
The presence of neurofibrillary tangles containing hyper-phosphorylated tau is a characteristic of Alzheimer's disease (AD) pathology. The positron emission tomography (PET) radioligand sensitive to tau neurofibrillary tangles (18F-AV1451) also binds with iron. This off-target binding effect may be enhanced in older adults on the AD spectrum, particularly those with amyloid-positive biomarkers. Here, we examined group differences in 18F-AV1451 PET after controlling for iron-sensitive measures from magnetic resonance imaging (MRI) and its relationships to tissue microstructure and cognition in 40 amyloid beta positive (Aβ+) individuals, 20 amyloid beta negative (Aβ-) with MCI and 31 Aβ- control participants. After controlling for iron, increased 18F-AV1451 PET uptake was found in the temporal lobe and hippocampus of Aβ+ participants compared to Aβ- MCI and control participants. Within the Aβ+ group, significant correlations were seen between 18F-AV1451 PET uptake and tissue microstructure and these correlations remained significant after controlling for iron. These findings indicate that off-target binding of iron to the 18F-AV1451 ligand may not affect its sensitivity to Aβ status or cognition in early-stage AD.
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Affiliation(s)
- Jason Langley
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, California, USA
| | - Ilana J Bennett
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Xiaoping P Hu
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, California, USA
- Department of Bioengineering, University of California Riverside, Riverside, California, USA
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9
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Earnest T, Bani A, Ha SM, Hobbs DA, Kothapalli D, Yang B, Lee JJ, Benzinger TLS, Gordon BA, Sotiras A. Data-driven decomposition and staging of flortaucipir uptake in Alzheimer's disease. Alzheimers Dement 2024; 20:4002-4019. [PMID: 38683905 PMCID: PMC11180875 DOI: 10.1002/alz.13769] [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: 10/10/2023] [Revised: 02/06/2024] [Accepted: 02/06/2024] [Indexed: 05/02/2024]
Abstract
INTRODUCTION Previous approaches pursuing in vivo staging of tau pathology in Alzheimer's disease (AD) have typically relied on neuropathologically defined criteria. In using predefined systems, these studies may miss spatial deposition patterns which are informative of disease progression. METHODS We selected discovery (n = 418) and replication (n = 132) cohorts with flortaucipir imaging. Non-negative matrix factorization (NMF) was applied to learn tau covariance patterns and develop a tau staging system. Flortaucipir components were also validated by comparison with amyloid burden, gray matter loss, and the expression of AD-related genes. RESULTS We found eight flortaucipir covariance patterns which were reproducible and overlapped with relevant gene expression maps. Tau stages were associated with AD severity as indexed by dementia status and neuropsychological performance. Comparisons of flortaucipir uptake with amyloid and atrophy also supported our model of tau progression. DISCUSSION Data-driven decomposition of flortaucipir uptake provides a novel framework for tau staging which complements existing systems. HIGHLIGHTS NMF reveals patterns of tau deposition in AD. Data-driven staging of flortaucipir tracks AD severity. Learned flortaucipir patterns overlap with AD-related gene expression.
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Affiliation(s)
- Tom Earnest
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Abdalla Bani
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Sung Min Ha
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Diana A. Hobbs
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Deydeep Kothapalli
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Braden Yang
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - John J. Lee
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Tammie L. S. Benzinger
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Brian A. Gordon
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
| | - Aristeidis Sotiras
- Mallinckrodt Institute of RadiologyWashington University School of Medicine in St LouisSaint LouisMissouriUSA
- Institute for Informatics, Data Science & BiostatisticsWashington University School of Medicine in St LouisSaint LouisMissouriUSA
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10
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Karlsson L, Vogel J, Arvidsson I, Åström K, Strandberg O, Seidlitz J, Bethlehem RAI, Stomrud E, Ossenkoppele R, Ashton NJ, Zetterberg H, Blennow K, Palmqvist S, Smith R, Janelidze S, La Joie R, Rabinovici GD, Binette AP, Mattsson-Carlgren N, Hansson O. A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.31.24308264. [PMID: 38853877 PMCID: PMC11160861 DOI: 10.1101/2024.05.31.24308264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.
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Affiliation(s)
- Linda Karlsson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Jacob Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Clinical Sciences, SciLifeLab, Lund University, Lund, Sweden
| | - Ida Arvidsson
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Kalle Åström
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Jakob Seidlitz
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104 USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104 USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Richard A. I. Bethlehem
- University of Cambridge, Department of Psychology, Cambridge Biomedical Campus, Cambridge, CB2 3EB, UK
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience, King’s College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D. Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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11
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Chen Y, Zeng X, Diaz JL, Sehrawat A, Lafferty TK, Boslett JJ, Klunk WE, Pascoal TA, Villemagne VL, Cohen AD, Lopez OI, Yates NA, Karikari TK. Effect of blood collection tube containing protease inhibitors on the pre-analytical stability of Alzheimer's disease plasma biomarkers. J Neurochem 2024. [PMID: 38814273 DOI: 10.1111/jnc.16130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 05/03/2024] [Accepted: 05/05/2024] [Indexed: 05/31/2024]
Abstract
The reliability of plasma biomarkers of Alzheimer's disease (AD) can be compromised by protease-induced degradation. This can limit the feasibility of conducting plasma biomarker studies in environments that lack the capacity for immediate processing and appropriate storage of blood samples. We hypothesized that blood collection tube supplementation with protease inhibitors can improve the stability of plasma biomarkers at room temperatures (RT). In this study, we conducted a comparative analysis of blood biomarker stability in traditional ethylenediaminetetraacetic acid (EDTA) tubes versus BD™ P100 collection tubes, the latter being coated with a protease inhibitor cocktail. The stability of six plasma AD biomarkers was evaluated over time under RT conditions. We evaluated three experimental approaches. In Approach 1, pooled plasma samples underwent storage at RT for up to 96 h. In Approach 2, plasma samples isolated upfront from whole blood collected into EDTA or P100 tubes were stored at RT for 0 h or 24 h before biomarker measurements. In Approach 3, whole blood samples were collected into paired EDTA and P100 tubes, followed by storage at RT for 0 h or 24 h before isolating the plasma for analyses. Biomarkers were measured with Single Molecule Array (Simoa) and immunoprecipitation-mass spectrometry (IP-MS) assays. Both the IP-MS and Simoa methods revealed that the use of P100 tubes significantly improves the stability of Aβ42 and Aβ40 across all approaches. However, the Aβ42/Aβ40 ratio levels were significantly stabilized only in the IP-MS assay in Approach 3. No significant differences were observed in the levels of plasma p-tau181, GFAP, and NfL for samples collected using either tube type in any of the approaches. Supplementation of blood collection tubes with protease inhibitors could reduce the protease-induced degradation of plasma Aβ42 and Aβ40, and the Aβ42/40 ratio for the IP-MS assay. These findings have crucial implications for preanalytical procedures, particularly in resource-limited settings.
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Affiliation(s)
- Yijun Chen
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Xuemei Zeng
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jihui L Diaz
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anuradha Sehrawat
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tara K Lafferty
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - James J Boslett
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - William E Klunk
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Victor L Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ann D Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Oscar I Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Nathan A Yates
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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12
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Wuestefeld A, Binette AP, van Westen D, Strandberg O, Stomrud E, Mattsson-Carlgren N, Janelidze S, Smith R, Palmqvist S, Baumeister H, Berron D, Yushkevich PA, Hansson O, Spotorno N, Wisse LEM. Medial temporal lobe atrophy patterns in early- versus late-onset amnestic Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.21.594976. [PMID: 38826333 PMCID: PMC11142072 DOI: 10.1101/2024.05.21.594976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer's disease (EOAD). Yet, detailed examination of MTL subfield volumes and drivers of atrophy in amnestic EOAD is lacking. Methods BioFINDER-2 participants with memory impairment, abnormal amyloid-β status and tau-PET were included. Forty-one EOAD individuals aged ≤65 years and, as comparison, late-onset AD (LOAD, ≥70 years, n=154) and Aβ-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. Results AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups, although LOAD showed thinner entorhinal cortices compared to EOAD. EOAD showed lower WMH compared to LOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity was found. Conclusions We found in vivo evidence for MTL atrophy in amnestic EOAD and overall similar levels to LOAD of MTL tau pathology and co-pathologies.
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Affiliation(s)
- Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Danielle van Westen
- Department of Diagnostic Radiology, Clinical Sciences, Lund University, 22242 Lund, Sweden
- Image and Function, Skåne University Hospital, 22242 Lund Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Department of Neurology, Skåne University Hospital, 22242 Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, 22184 Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Laura EM Wisse
- Department of Diagnostic Radiology, Clinical Sciences, Lund University, 22242 Lund, Sweden
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13
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Salvadó G, Horie K, Barthélemy NR, Vogel JW, Pichet Binette A, Chen CD, Aschenbrenner AJ, Gordon BA, Benzinger TLS, Holtzman DM, Morris JC, Palmqvist S, Stomrud E, Janelidze S, Ossenkoppele R, Schindler SE, Bateman RJ, Hansson O. Disease staging of Alzheimer's disease using a CSF-based biomarker model. NATURE AGING 2024; 4:694-708. [PMID: 38514824 PMCID: PMC11108782 DOI: 10.1038/s43587-024-00599-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 02/20/2024] [Indexed: 03/23/2024]
Abstract
Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aβ42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aβ-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
| | - Kanta Horie
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Eisai, Inc., Nutley, NJ, USA
| | - Nicolas R Barthélemy
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jacob W Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Clinical Science, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Charles D Chen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew J Aschenbrenner
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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Jarek DJ, Mizerka H, Nuszkiewicz J, Szewczyk-Golec K. Evaluating p-tau217 and p-tau231 as Biomarkers for Early Diagnosis and Differentiation of Alzheimer's Disease: A Narrative Review. Biomedicines 2024; 12:786. [PMID: 38672142 PMCID: PMC11048667 DOI: 10.3390/biomedicines12040786] [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: 02/15/2024] [Revised: 03/26/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
The escalating prevalence of Alzheimer's disease (AD) highlights the urgent need to develop reliable biomarkers for early diagnosis and intervention. AD is characterized by the pathological accumulation of amyloid-beta plaques and tau neurofibrillary tangles. Phosphorylated tau (p-tau) proteins, particularly p-tau217 and p-tau231, have been identified as promising biomarker candidates to differentiate the disease progression from preclinical stages. This narrative review is devoted to a critical evaluation of the diagnostic accuracy, sensitivity, and specificity of p-tau217 and p-tau231 levels in the detection of AD, measured in plasma, serum, and cerebrospinal fluid, compared to established biomarkers. Additionally, the efficacy of these markers in distinguishing AD from other neurodegenerative disorders is examined. The significant advances offered by p-tau217 and p-tau231 in AD diagnostics are highlighted, demonstrating their unique utility in early detection and differential diagnosis. This comprehensive analysis not only confirms the excellent diagnostic capabilities of these markers, but also deepens the understanding of the molecular dynamics of AD, contributing to the broader scientific discourse on neurodegenerative diseases. This review is aimed to provide key information for researchers and clinicians across disciplines, filling interdisciplinary gaps and highlighting the role of p-tau proteins in revolutionizing AD research and clinical practice.
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Affiliation(s)
- Dorian Julian Jarek
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Hubert Mizerka
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Jarosław Nuszkiewicz
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Karolina Szewczyk-Golec
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
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15
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Barthélemy NR, Salvadó G, Schindler SE, He Y, Janelidze S, Collij LE, Saef B, Henson RL, Chen CD, Gordon BA, Li Y, La Joie R, Benzinger TLS, Morris JC, Mattsson-Carlgren N, Palmqvist S, Ossenkoppele R, Rabinovici GD, Stomrud E, Bateman RJ, Hansson O. Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests. Nat Med 2024; 30:1085-1095. [PMID: 38382645 PMCID: PMC11031399 DOI: 10.1038/s41591-024-02869-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/12/2024] [Indexed: 02/23/2024]
Abstract
With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.
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Affiliation(s)
- Nicolas R Barthélemy
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, MO, USA
| | - Yingxin He
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | - Lyduine E Collij
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Benjamin Saef
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Rachel L Henson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Charles D Chen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, MO, USA
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, MO, 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.
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16
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Wei B, Xu Y, Du Y, Zhou J, Zhong F, Wu C, Lou Y. Feasibility of Using Magnetic Resonance Spectroscopy Test Biomarkers to Diagnose Alzheimer's Disease: Systematic Evaluation and Meta-Analysis. ACTAS ESPANOLAS DE PSIQUIATRIA 2024; 52:161-171. [PMID: 38622011 PMCID: PMC11016455 DOI: 10.62641/aep.v52i2.1552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia, resulting in impairments in memory, cognition, decision-making, and social skills. Thus, accurate preclinical diagnosis of Alzheimer's disease is paramount. The identification of biomarkers for Alzheimer's disease through magnetic resonance spectroscopy (MRS) represents a novel adjunctive diagnostic approach. OBJECTIVE This study conducted a meta-analysis of the diagnostic results of this technology to explore its feasibility and accuracy. METHODS PubMed, Cochrane Library, EMBASE, and Web of Science databases were searched without restrictions, with the search period extending up to July 31, 2022. The search strategy employed a combination of subject headings and keywords. All retrieved documents underwent screening by two researchers, who selected them for meta-analysis. The included literature was analyzed using Review Manager 5.4 software, with corresponding bias maps, forest plots, and summary receiver operating characteristic (SROC) curves generated and analyzed. RESULTS A total of 344 articles were retrieved initially, with 11 articles meeting the criteria for inclusion in the analysis. The analysis encompassed data from approximately 1766 patients. In the forest plot, both sensitivity (95% CI) and specificity (95% CI) approached 1. Examining the true positive rate, false positive rate, true negative rate, and false negative rate, all studies on the summary receiver operating characteristic (SROC) curve clustered in the upper left quadrant, suggesting a very high accuracy of biomarkers detected by MRS for diagnosing Alzheimer's disease. CONCLUSION The detection of biomarkers by MRS demonstrates feasibility and high accuracy in diagnosing AD. This technology holds promise for widespread adoption in the clinical diagnosis of AD in the future.
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Affiliation(s)
- Bo Wei
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Yiqin Xu
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Ye Du
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Jie Zhou
- Department of Radiology, Shaoxing Seventh People's Hospital (Affiliated Mental Health Center, Medical College of Shaoxing University), 312000 Shaoxing, Zhejiang, China
| | - Fangfang Zhong
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Chenglong Wu
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
| | - Yiping Lou
- Department of Neurology, Shaoxing People's Hospital, 312000 Shaoxing, Zhejiang, China
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17
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Therriault J, Schindler SE, Salvadó G, Pascoal TA, Benedet AL, Ashton NJ, Karikari TK, Apostolova L, Murray ME, Verberk I, Vogel JW, La Joie R, Gauthier S, Teunissen C, Rabinovici GD, Zetterberg H, Bateman RJ, Scheltens P, Blennow K, Sperling R, Hansson O, Jack CR, Rosa-Neto P. Biomarker-based staging of Alzheimer disease: rationale and clinical applications. Nat Rev Neurol 2024; 20:232-244. [PMID: 38429551 DOI: 10.1038/s41582-024-00942-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/05/2024] [Indexed: 03/03/2024]
Abstract
Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-β and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.
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Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, Quebec, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa Lessa Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- NIHR Biomedical Research Centre, South London and Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Liana Apostolova
- Department of Neurology, University of Indiana School of Medicine, Indianapolis, IN, USA
| | | | - Inge Verberk
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Jacob W Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Clinical Sciences, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Charlotte Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip Scheltens
- Alzheimer Centre Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Reisa Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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18
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Mendes AJ, Ribaldi F, Lathuiliere A, Ashton NJ, Janelidze S, Zetterberg H, Scheffler M, Assal F, Garibotto V, Blennow K, Hansson O, Frisoni GB. Head-to-head study of diagnostic accuracy of plasma and cerebrospinal fluid p-tau217 versus p-tau181 and p-tau231 in a memory clinic cohort. J Neurol 2024; 271:2053-2066. [PMID: 38195896 PMCID: PMC10972950 DOI: 10.1007/s00415-023-12148-5] [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: 10/27/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 01/11/2024]
Abstract
BACKGROUND AND OBJECTIVE Phosphorylated tau (p-tau) 217 has recently received attention because it seems more reliable than other p-tau variants for identifying Alzheimer's disease (AD) pathology. Thus, we aimed to compare the diagnostic accuracy of plasma and CSF p-tau217 with p-tau181 and p-tau231 in a memory clinic cohort. METHODS The study included 114 participants (CU = 33; MCI = 67; Dementia = 14). The p-tau variants were correlated versus continuous measures of amyloid (A) and tau (T)-PET. The p-tau phospho-epitopes were assessed through: (i) effect sizes (δ) between diagnostic and A ± and T ± groups; (ii) receiver operating characteristic (ROC) analyses in A-PET and T-PET. RESULTS The correlations between both plasma and CSF p-tau217 with A-PET and T-PET (r range 0.64-0.83) were stronger than those of p-tau181 (r range 0.44-0.79) and p-tau231 (r range 0.46-0.76). Plasma p-tau217 showed significantly higher diagnostic accuracy than p-tau181 and p-tau231 in (i) differences between diagnostic and biomarker groups (δrange: p-tau217 = 0.55-0.96; p-tau181 = 0.51-0.67; p-tau231 = 0.53-0.71); (ii) ROC curves to identify A-PET and T-PET positivity (AUCaverage: p-tau217 = 0.96; p-tau181 = 0.76; p-tau231 = 0.79). On the other hand, CSF p-tau217 (AUCaverage = 0.95) did not reveal significant differences in A-PET and T-PET AUC than p-tau181 (AUCaverage = 0.88) and p-tau231 (AUCaverage = 0.89). DISCUSSION Plasma p-tau217 demonstrated better performance in the identification of AD pathology and clinical phenotypes in comparison with other variants of p-tau in a memory clinic cohort. Furthermore, p-tau217 had comparable performance in plasma and CSF. Our findings suggest the potential of plasma p-tau217 in the diagnosis and screening for AD, which could allow for a decreased use of invasive biomarkers in the future.
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Affiliation(s)
- Augusto J Mendes
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland.
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Aurelien Lathuiliere
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Frédéric Assal
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, Geneva, Switzerland
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, People's Republic of China
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
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Chen Y, Zeng X, Lee J, Sehrawat A, Lafferty TK, Boslett JJ, Klunk WE, Pascoal TA, Villemagne VL, Cohen AD, Lopez O, Yates NA, Karikari TK. Effect of blood collection tube containing protease inhibitors on the pre-analytical stability of Alzheimer's disease plasma biomarkers. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.05.24303504. [PMID: 38496591 PMCID: PMC10942510 DOI: 10.1101/2024.03.05.24303504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
INTRODUCTION The reliability of plasma Alzheimer's disease (AD) biomarkers can be compromised by protease-induced degradation. This limits the feasibility of conducting plasma biomarker studies in environments that lack the capacity for immediate processing and appropriate storage of blood samples. We hypothesized that blood collection tube supplementation with protease inhibitors can improve the stability of plasma biomarkers at room temperatures (RT). This study conducted a comparative analysis of blood biomarker stability in traditional ethylenediaminetetraacetic acid (EDTA) tubes versus BD™ P100 collection tubes, the latter being coated with a protease inhibitor cocktail. The stability of six plasma AD biomarkers was evaluated over time under RT conditions. METHODS We evaluated three experimental approaches. In Approach 1, pooled plasma samples underwent storage at RT for up to 96 hours. In Approach 2, plasma samples isolated upfront from whole blood collected into EDTA or P100 tubes were stored at RT for 0h or 24h before biomarker measurements. In Approach 3, whole blood samples were collected into paired EDTA or P100 tubes, followed by storage at RT for 0h or 24h before isolating the plasma for analyses. Biomarkers were measured with Single Molecule Array (Simoa) and immunoprecipitation-mass spectrometry (IP-MS) assays. RESULTS Both the IP-MS and Simoa methods revealed that the use of P100 tubes significantly improved the stability of Aβ42 and Aβ40 across all approaches. Additionally, the Aβ42/Aβ40 ratio levels were significantly stabilized only in the IP-MS assay in Approach 3. No significant differences were observed in the levels of plasma p-tau181, GFAP, and NfL for samples collected using either tube type in any of the approaches. CONCLUSION Supplementation of blood collection tubes with protease inhibitors could reduce the protease-induced degradation of plasma Aβ42 and Aβ40, and the Aβ ratio for IP-MS assay. This has crucial implications for preanalytical procedures, particularly in resource-limited settings.
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20
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Watanabe Y, Miyazaki Y, Hata M, Fukuma R, Aoki Y, Kazui H, Araki T, Taomoto D, Satake Y, Suehiro T, Sato S, Kanemoto H, Yoshiyama K, Ishii R, Harada T, Kishima H, Ikeda M, Yanagisawa T. A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study. Neural Netw 2024; 171:242-250. [PMID: 38101292 DOI: 10.1016/j.neunet.2023.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 11/12/2023] [Accepted: 12/04/2023] [Indexed: 12/17/2023]
Abstract
Dementia and mild cognitive impairment (MCI) represent significant health challenges in an aging population. As the search for noninvasive, precise and accessible diagnostic methods continues, the efficacy of electroencephalography (EEG) combined with deep convolutional neural networks (DCNNs) in varied clinical settings remains unverified, particularly for pathologies underlying MCI such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and idiopathic normal-pressure hydrocephalus (iNPH). Addressing this gap, our study evaluates the generalizability of a DCNN trained on EEG data from a single hospital (Hospital #1). For data from Hospital #1, the DCNN achieved a balanced accuracy (bACC) of 0.927 in classifying individuals as healthy (n = 69) or as having AD, DLB, or iNPH (n = 188). The model demonstrated robustness across institutions, maintaining bACCs of 0.805 for data from Hospital #2 (n = 73) and 0.920 at Hospital #3 (n = 139). Additionally, the model could differentiate AD, DLB, and iNPH cases with bACCs of 0.572 for data from Hospital #1 (n = 188), 0.619 for Hospital #2 (n = 70), and 0.508 for Hospital #3 (n = 139). Notably, it also identified MCI pathologies with a bACC of 0.715 for Hospital #1 (n = 83), despite being trained on overt dementia cases instead of MCI cases. These outcomes confirm the DCNN's adaptability and scalability, representing a significant stride toward its clinical application. Additionally, our findings suggest a potential for identifying shared EEG signatures between MCI and dementia, contributing to the field's understanding of their common pathophysiological mechanisms.
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Affiliation(s)
- Yusuke Watanabe
- Institute for Advanced Co-creation Studies, Osaka University, Osaka, Japan
| | - Yuki Miyazaki
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Masahiro Hata
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ryohei Fukuma
- Institute for Advanced Co-creation Studies, Osaka University, Osaka, Japan; Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yasunori Aoki
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Psychiatry, Nippon Life Hospital, Osaka, Japan
| | - Hiroaki Kazui
- Department of Neuropsychiatry, Kochi Medical School, Kochi University, Kochi, Japan
| | - Toshihiko Araki
- Department of Medical Technology, Osaka University Hospital, Osaka, Japan
| | - Daiki Taomoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuto Satake
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Takashi Suehiro
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Shunsuke Sato
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hideki Kanemoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kenji Yoshiyama
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ryouhei Ishii
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Occupational Therapy, Graduate School of Rehabilitation Science, Osaka Metropolitan University, Habikino, Japan
| | - Tatsuya Harada
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan; RIKEN, Tokyo, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Takufumi Yanagisawa
- Institute for Advanced Co-creation Studies, Osaka University, Osaka, Japan; Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan.
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21
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Stouffer KM, Grande X, Düzel E, Johansson M, Creese B, Witter MP, Miller MI, Wisse LEM, Berron D. Amidst an amygdala renaissance in Alzheimer's disease. Brain 2024; 147:816-829. [PMID: 38109776 PMCID: PMC10907090 DOI: 10.1093/brain/awad411] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/03/2023] [Accepted: 11/27/2023] [Indexed: 12/20/2023] Open
Abstract
The amygdala was highlighted as an early site for neurofibrillary tau tangle pathology in Alzheimer's disease in the seminal 1991 article by Braak and Braak. This knowledge has, however, only received traction recently with advances in imaging and image analysis techniques. Here, we provide a cross-disciplinary overview of pathology and neuroimaging studies on the amygdala. These studies provide strong support for an early role of the amygdala in Alzheimer's disease and the utility of imaging biomarkers of the amygdala in detecting early changes and predicting decline in cognitive functions and neuropsychiatric symptoms in early stages. We summarize the animal literature on connectivity of the amygdala, demonstrating that amygdala nuclei that show the earliest and strongest accumulation of neurofibrillary tangle pathology are those that are connected to brain regions that also show early neurofibrillary tangle accumulation. Additionally, we propose an alternative pathway of neurofibrillary tangle spreading within the medial temporal lobe between the amygdala and the anterior hippocampus. The proposed existence of this pathway is strengthened by novel experimental data on human functional connectivity. Finally, we summarize the functional roles of the amygdala, highlighting the correspondence between neurofibrillary tangle accumulation and symptomatic profiles in Alzheimer's disease. In summary, these findings provide a new impetus for studying the amygdala in Alzheimer's disease and a unique perspective to guide further study on neurofibrillary tangle spreading and the occurrence of neuropsychiatric symptoms in Alzheimer's disease.
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Affiliation(s)
- Kaitlin M Stouffer
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21218, USA
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Xenia Grande
- German Center for Neurodegenerative Diseases (DZNE), 39120, Magdeburg, Germany
- Institute for Cognitive Neurology and Dementia Research, Otto-von-Guericke University, 39106, Magdeburg, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), 39120, Magdeburg, Germany
- Institute for Cognitive Neurology and Dementia Research, Otto-von-Guericke University, 39106, Magdeburg, Germany
| | - Maurits Johansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 205 02, Lund, Sweden
- Division of Clinical Sciences, Helsingborg, Department of Clinical Sciences Lund, Lund University, 221 84, Lund, Sweden
- Department of Psychiatry, Helsingborg Hospital, 252 23, Helsingborg, Sweden
| | - Byron Creese
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, EX4 4PY, Exeter, UK
- Division of Psychology, Department of Life Sciences, Brunel University London, UB8 3PH, Uxbridge, UK
| | - Menno P Witter
- Kavli Institute for Systems Neuroscience, NTNU Norwegian University of Science and Technology, 7491, Trondheim, Norway
- KG. Jebsen Centre for Alzheimer’s Disease, NTNU Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Michael I Miller
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, 21218, USA
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Laura E M Wisse
- Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, 211 84, Lund, Sweden
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), 39120, Magdeburg, Germany
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 205 02, Lund, Sweden
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22
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Lantero-Rodriguez J, Salvadó G, Snellman A, Montoliu-Gaya L, Brum WS, Benedet AL, Mattsson-Carlgren N, Tideman P, Janelidze S, Palmqvist S, Stomrud E, Ashton NJ, Zetterberg H, Blennow K, Hansson O. Plasma N-terminal containing tau fragments (NTA-tau): a biomarker of tau deposition in Alzheimer's Disease. Mol Neurodegener 2024; 19:19. [PMID: 38365825 PMCID: PMC10874032 DOI: 10.1186/s13024-024-00707-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 01/30/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Novel phosphorylated-tau (p-tau) blood biomarkers (e.g., p-tau181, p-tau217 or p-tau231), are highly specific for Alzheimer's disease (AD), and can track amyloid-β (Aβ) and tau pathology. However, because these biomarkers are strongly associated with the emergence of Aβ pathology, it is difficult to determine the contribution of insoluble tau aggregates to the plasma p-tau signal in blood. Therefore, there remains a need for a biomarker capable of specifically tracking insoluble tau accumulation in brain. METHODS NTA is a novel ultrasensitive assay targeting N-terminal containing tau fragments (NTA-tau) in cerebrospinal fluid (CSF) and plasma, which is elevated in AD. Using two well-characterized research cohorts (BioFINDER-2, n = 1,294, and BioFINDER-1, n = 932), we investigated the association between plasma NTA-tau levels and disease progression in AD, including tau accumulation, brain atrophy and cognitive decline. RESULTS We demonstrate that plasma NTA-tau increases across the AD continuum¸ especially during late stages, and displays a moderate-to-strong association with tau-PET (β = 0.54, p < 0.001) in Aβ-positive participants, while weak with Aβ-PET (β = 0.28, p < 0.001). Unlike plasma p-tau181, GFAP, NfL and t-tau, tau pathology determined with tau-PET is the most prominent contributor to NTA-tau variance (52.5% of total R2), while having very low contribution from Aβ pathology measured with CSF Aβ42/40 (4.3%). High baseline NTA-tau levels are predictive of tau-PET accumulation (R2 = 0.27), steeper atrophy (R2 ≥ 0.18) and steeper cognitive decline (R2 ≥ 0.27) in participants within the AD continuum. Plasma NTA-tau levels significantly increase over time in Aβ positive cognitively unimpaired (βstd = 0.16) and impaired (βstd = 0.18) at baseline compared to their Aβ negative counterparts. Finally, longitudinal increases in plasma NTA-tau levels were associated with steeper longitudinal decreases in cortical thickness (R2 = 0.21) and cognition (R2 = 0.20). CONCLUSION Our results indicate that plasma NTA-tau levels increase across the AD continuum, especially during mid-to-late AD stages, and it is closely associated with in vivo tau tangle deposition in AD and its downstream effects. Moreover, this novel biomarker has potential as a cost-effective and easily accessible tool for monitoring disease progression and cognitive decline in clinical settings, and as an outcome measure in clinical trials which also need to assess the downstream effects of successful Aβ removal.
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Affiliation(s)
- Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden.
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Anniina Snellman
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Turku PET Centre, University of Turku, Turku University Hospital, Turku, Finland
| | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul (UFRGS), Porto Alegre, Brazil
| | - Andrea L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Pontus Tideman
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Old Age Psychiatry, Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, House V3/SU, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden.
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23
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Bisi N, Pinzi L, Rastelli G, Tonali N. Early Diagnosis of Neurodegenerative Diseases: What Has Been Undertaken to Promote the Transition from PET to Fluorescence Tracers. Molecules 2024; 29:722. [PMID: 38338465 PMCID: PMC10856728 DOI: 10.3390/molecules29030722] [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: 01/04/2024] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/12/2024] Open
Abstract
Alzheimer's Disease (AD) and Parkinson's Disease (PD) represent two among the most frequent neurodegenerative diseases worldwide. A common hallmark of these pathologies is the misfolding and consequent aggregation of amyloid proteins into soluble oligomers and insoluble β-sheet-rich fibrils, which ultimately lead to neurotoxicity and cell death. After a hundred years of research on the subject, this is the only reliable histopathological feature in our hands. Since AD and PD are diagnosed only once neuronal death and the first symptoms have appeared, the early detection of these diseases is currently impossible. At present, there is no effective drug available, and patients are left with symptomatic and inconclusive therapies. Several reasons could be associated with the lack of effective therapeutic treatments. One of the most important factors is the lack of selective probes capable of detecting, as early as possible, the most toxic amyloid species involved in the onset of these pathologies. In this regard, chemical probes able to detect and distinguish among different amyloid aggregates are urgently needed. In this article, we will review and put into perspective results from ex vivo and in vivo studies performed on compounds specifically interacting with such early species. Following a general overview on the three different amyloid proteins leading to insoluble β-sheet-rich amyloid deposits (amyloid β1-42 peptide, Tau, and α-synuclein), a list of the advantages and disadvantages of the approaches employed to date is discussed, with particular attention paid to the translation of fluorescence imaging into clinical applications. Furthermore, we also discuss how the progress achieved in detecting the amyloids of one neurodegenerative disease could be leveraged for research into another amyloidosis. As evidenced by a critical analysis of the state of the art, substantial work still needs to be conducted. Indeed, the early diagnosis of neurodegenerative diseases is a priority, and we believe that this review could be a useful tool for better investigating this field.
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Affiliation(s)
- Nicolò Bisi
- Université Paris-Saclay, CNRS, BioCIS, Bat. Henri Moissan, 17, Av. des Sciences, 91400 Orsay, France
| | - Luca Pinzi
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125 Modena, Italy; (L.P.); (G.R.)
| | - Giulio Rastelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125 Modena, Italy; (L.P.); (G.R.)
| | - Nicolò Tonali
- Université Paris-Saclay, CNRS, BioCIS, Bat. Henri Moissan, 17, Av. des Sciences, 91400 Orsay, France
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24
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Young AL, Oxtoby NP, Garbarino S, Fox NC, Barkhof F, Schott JM, Alexander DC. Data-driven modelling of neurodegenerative disease progression: thinking outside the black box. Nat Rev Neurosci 2024; 25:111-130. [PMID: 38191721 DOI: 10.1038/s41583-023-00779-6] [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] [Accepted: 11/30/2023] [Indexed: 01/10/2024]
Abstract
Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.
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Affiliation(s)
- Alexandra L Young
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Neil P Oxtoby
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
| | - Sara Garbarino
- Life Science Computational Laboratory, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Daniel C Alexander
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
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25
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Rudisch DM, Krasko MN, Barnett DGS, Mueller KD, Russell JA, Connor NP, Ciucci MR. Early ultrasonic vocalization deficits and related thyroarytenoid muscle pathology in the transgenic TgF344-AD rat model of Alzheimer's disease. Front Behav Neurosci 2024; 17:1294648. [PMID: 38322496 PMCID: PMC10844490 DOI: 10.3389/fnbeh.2023.1294648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/01/2023] [Indexed: 02/08/2024] Open
Abstract
Background Alzheimer's disease (AD) is a progressive neurologic disease and the most common cause of dementia. Classic pathology in AD is characterized by inflammation, abnormal presence of tau protein, and aggregation of β-amyloid that disrupt normal neuronal function and lead to cell death. Deficits in communication also occur during disease progression and significantly reduce health, well-being, and quality of life. Because clinical diagnosis occurs in the mid-stage of the disease, characterizing the prodrome and early stages in humans is currently challenging. To overcome these challenges, we use the validated TgF344-AD (F344-Tg(Prp-APP, Prp-PS1)19/Rrrc) transgenic rat model that manifests cognitive, behavioral, and neuropathological dysfunction akin to AD in humans. Objectives The overarching goal of our work is to test the central hypothesis that pathology and related behavioral deficits such as communication dysfunction in part manifest in the peripheral nervous system and corresponding target tissues already in the early stages. The primary aims of this study are to test the hypotheses that: (1) changes in ultrasonic vocalizations (USV) occur in the prodromal stage at 6 months of age and worsen at 9 months of age, (2) inflammation as well as AD-related pathology can be found in the thyroarytenoid muscle (TA) at 12 months of age (experimental endpoint tissue harvest), and to (3) demonstrate that the TgF344-AD rat model is an appropriate model for preclinical investigations of early AD-related vocal deficits. Methods USVs were collected from male TgF344-AD (N = 19) and wildtype (WT) Fischer-344 rats (N = 19) at 6 months (N = 38; WT: n = 19; TgF344-AD: n = 19) and 9 months of age (N = 18; WT: n = 10; TgF344-AD: n = 8) and acoustically analyzed for duration, mean power, principal frequency, low frequency, high frequency, peak frequency, and call type. RT-qPCR was used to assay peripheral inflammation and AD-related pathology via gene expressions in the TA muscle of male TgF344-AD rats (n = 6) and WT rats (n = 6) at 12 months of age. Results This study revealed a significant reduction in mean power of ultrasonic calls from 6 to 9 months of age and increased peak frequency levels over time in TgF344-AD rats compared to WT controls. Additionally, significant downregulation of AD-related genes Uqcrc2, Bace2, Serpina3n, and Igf2, as well as downregulation of pro-inflammatory gene Myd88 was found in the TA muscle of TgF344-AD rats at 12 months of age. Discussion Our findings demonstrate early and progressive vocal deficits in the TgF344-AD rat model. We further provide evidence of dysregulation of AD-pathology-related genes as well as inflammatory genes in the TA muscles of TgF344-AD rats in the early stage of the disease, confirming this rat model for early-stage investigations of voice deficits and related pathology.
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Affiliation(s)
- Denis Michael Rudisch
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, United States
- Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- UW Institute for Clinical and Translational Research, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Maryann N Krasko
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, United States
- Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - David G S Barnett
- Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Kimberly D Mueller
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, United States
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - John A Russell
- Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Nadine P Connor
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, United States
- Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Michelle R Ciucci
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, United States
- Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, UW School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
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26
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Zammit MD, Betthauser TJ, McVea AK, Laymon CM, Tudorascu DL, Johnson SC, Hartley SL, Converse AK, Minhas DS, Zaman SH, Ances BM, Stone CK, Mathis CA, Cohen AD, Klunk WE, Handen BL, Christian BT. Characterizing the emergence of amyloid and tau burden in Down syndrome. Alzheimers Dement 2024; 20:388-398. [PMID: 37641577 PMCID: PMC10843570 DOI: 10.1002/alz.13444] [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: 05/17/2023] [Revised: 07/14/2023] [Accepted: 07/23/2023] [Indexed: 08/31/2023]
Abstract
INTRODUCTION Almost all individuals with Down syndrome (DS) will develop neuropathological features of Alzheimer's disease (AD). Understanding AD biomarker trajectories is necessary for DS-specific clinical interventions and interpretation of drug-related changes in the disease trajectory. METHODS A total of 177 adults with DS from the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) underwent positron emission tomography (PET) and MR imaging. Amyloid-beta (Aβ) trajectories were modeled to provide individual-level estimates of Aβ-positive (A+) chronicity, which were compared against longitudinal tau change. RESULTS Elevated tau was observed in all NFT regions following A+ and longitudinal tau increased with respect to A+ chronicity. Tau increases in NFT regions I-III was observed 0-2.5 years following A+. Nearly all A+ individuals had tau increases in the medial temporal lobe. DISCUSSION These findings highlight the rapid accumulation of amyloid and early onset of tau relative to amyloid in DS and provide a strategy for temporally characterizing AD neuropathology progression that is specific to the DS population and independent of chronological age. HIGHLIGHTS Longitudinal amyloid trajectories reveal rapid Aβ accumulation in Down syndrome NFT stage tau was strongly associated with A+ chronicity Early longitudinal tau increases were observed 2.5-5 years after reaching A.
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Affiliation(s)
| | - Tobey J. Betthauser
- University of Wisconsin‐Madison Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Andrew K. McVea
- University of Wisconsin‐Madison Waisman CenterMadisonWisconsinUSA
| | - Charles M. Laymon
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Dana L. Tudorascu
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Sterling C. Johnson
- University of Wisconsin‐Madison Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Sigan L. Hartley
- University of Wisconsin‐Madison Waisman CenterMadisonWisconsinUSA
| | | | - Davneet S. Minhas
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Shahid H. Zaman
- Cambridge Intellectual Disability Research GroupUniversity of CambridgeCambridgeUK
| | - Beau M. Ances
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Charles K. Stone
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Chester A. Mathis
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Annie D. Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - William E. Klunk
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Benjamin L. Handen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Bradley T. Christian
- University of Wisconsin‐Madison Waisman CenterMadisonWisconsinUSA
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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27
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Khaled M, Al-Jamal H, Tajer L, El-Mir R. Alzheimer's Disease in Lebanon: Exploring Genetic and Environmental Risk Factors-A Comprehensive Review. J Alzheimers Dis 2024; 99:21-40. [PMID: 38640157 DOI: 10.3233/jad-231432] [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: 04/21/2024]
Abstract
Alzheimer's disease (AD) is a neurodegenerative condition that displays a high prevalence in Lebanon causing a local burden in healthcare and socio-economic sectors. Unfortunately, the lack of prevalence studies and clinical trials in Lebanon minimizes the improvement of AD patient health status. In this review, we include over 155 articles to cover the different aspects of AD ranging from mechanisms to possible treatment and management tools. We highlight some important modifiable and non-modifiable risk factors of the disease including genetics, age, cardiovascular diseases, smoking, etc. Finally, we propose a hypothetical genetic synergy model between APOE4 and TREM2 genes which constitutes a potential early diagnostic tool that helps in reducing the risk of AD based on preventative measures decades before cognitive decline. The studies on AD in Lebanon and the Middle East are scarce. This review points out the importance of genetic mapping in the understanding of disease pathology which is crucial for the emergence of novel diagnostic tools. Hence, we establish a rigid basis for further research to identify the most influential genetic and environmental risk factors for the purpose of using more specific diagnostic tools and possibly adopting a local management protocol.
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Affiliation(s)
| | - Hadi Al-Jamal
- Faculty of Public Health III, Lebanese University, Tripoli, Lebanon
| | - Layla Tajer
- Faculty of Public Health III, Lebanese University, Tripoli, Lebanon
| | - Reem El-Mir
- Faculty of Public Health III, Lebanese University, Tripoli, Lebanon
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Asken BM, Wang W, McFarland K, Arias F, Fiala J, Velez‐Uribe I, Mayrand RP, Sawada LO, Freytes C, Adeyosoye M, Marsiske M, Rosselli M, Barker WW, Curiel Cid R, Loewenstein DA, DeKosky ST, Armstrong MJ, Smith GE, Adjouadi M, Vaillancourt DE, Duara R. Plasma Alzheimer's biomarkers and brain amyloid in Hispanic and non-Hispanic older adults. Alzheimers Dement 2024; 20:437-446. [PMID: 37671801 PMCID: PMC10865106 DOI: 10.1002/alz.13456] [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: 05/03/2023] [Revised: 08/01/2023] [Accepted: 08/04/2023] [Indexed: 09/07/2023]
Abstract
INTRODUCTION Alzheimer's disease studies often lack ethnic diversity. METHODS We evaluated associations between plasma biomarkers commonly studied in Alzheimer's (p-tau181, GFAP, and NfL), clinical diagnosis (clinically normal, amnestic MCI, amnestic dementia, or non-amnestic MCI/dementia), and Aβ-PET in Hispanic and non-Hispanic older adults. Hispanics were predominantly of Cuban or South American ancestry. RESULTS Three-hundred seventy nine participants underwent blood draw (71.9 ± 7.8 years old, 60.2% female, 57% Hispanic of which 88% were Cuban or South American) and 240 completed Aβ-PET. P-tau181 was higher in amnestic MCI (p = 0.004, d = 0.53) and dementia (p < 0.001, d = 0.97) than in clinically normal participants and discriminated Aβ-PET[+] and Aβ-PET[-] (AUC = 0.86). P-tau181 outperformed GFAP and NfL. There were no significant interactions with ethnicity. Among amnestic MCI, Hispanics had lower odds of elevated p-tau181 than non-Hispanic (OR = 0.41, p = 0.006). DISCUSSION Plasma p-tau181 informs etiological diagnosis of cognitively impaired Hispanic and non-Hispanic older adults. Hispanic ethnicity may relate to greater likelihood of non-Alzheimer's contributions to memory loss. HIGHLIGHTS Alzheimer's biomarkers were measured in Hispanic and non-Hispanic older adults. Plasma p-tau181 related to amnestic cognitive decline and brain amyloid burden. AD biomarker associations did not differ between Hispanic and non-Hispanic ethnicity. Hispanic individuals may be more likely to have non-Alzheimer causes of memory loss.
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Boccalini C, Ribaldi F, Hristovska I, Arnone A, Peretti DE, Mu L, Scheffler M, Perani D, Frisoni GB, Garibotto V. The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline. Alzheimers Dement 2024; 20:221-233. [PMID: 37555516 PMCID: PMC10916991 DOI: 10.1002/alz.13355] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/09/2023] [Accepted: 05/29/2023] [Indexed: 08/10/2023]
Abstract
INTRODUCTION Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified. METHODS We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose (FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values. RESULTS Metabolism had the strongest association with cognition (r = 0.712; p < 0.001), followed by tau (r = -0.682; p < 0.001). Neocortical tau showed the strongest association with cognitive decline (r = -0.677; p < 0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio = 32). DISCUSSION Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics. HIGHLIGHTS Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.
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Affiliation(s)
- Cecilia Boccalini
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Vita‐Salute San Raffaele UniversityMilanItaly
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Federica Ribaldi
- Geneva Memory CenterGeneva University HospitalsGenevaSwitzerland
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
| | - Ines Hristovska
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Annachiara Arnone
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Débora Elisa Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Linjing Mu
- Institute of Pharmaceutical SciencesETH ZurichZurichSwitzerland
| | - Max Scheffler
- Division of RadiologyGeneva University HospitalsGenevaSwitzerland
| | - Daniela Perani
- Vita‐Salute San Raffaele UniversityMilanItaly
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Nuclear Medicine UnitSan Raffaele HospitalMilanItaly
| | - Giovanni B. Frisoni
- Geneva Memory CenterGeneva University HospitalsGenevaSwitzerland
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Division of Nuclear Medicine and Molecular ImagingGeneva University HospitalsGenevaSwitzerland
- CIBM Center for Biomedical ImagingGeneva University HospitalsGenevaSwitzerland
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30
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Dyer AH, Dolphin H, O'Connor A, Morrison L, Sedgwick G, McFeely A, Killeen E, Gallagher C, Davey N, Connolly E, Lyons S, Young C, Gaffney C, Ennis R, McHale C, Joseph J, Knight G, Kelly E, O'Farrelly C, Bourke NM, Fallon A, O'Dowd S, Kennelly SP. Protocol for the Tallaght University Hospital Institute for Memory and Cognition-Biobank for Research in Ageing and Neurodegeneration. BMJ Open 2023; 13:e077772. [PMID: 38070888 PMCID: PMC10729202 DOI: 10.1136/bmjopen-2023-077772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/13/2023] [Indexed: 12/18/2023] Open
Abstract
INTRODUCTION Alzheimer's disease and other dementias affect >50 million individuals globally and are characterised by broad clinical and biological heterogeneity. Cohort and biobank studies have played a critical role in advancing the understanding of disease pathophysiology and in identifying novel diagnostic and treatment approaches. However, further discovery and validation cohorts are required to clarify the real-world utility of new biomarkers, facilitate research into the development of novel therapies and advance our understanding of the clinical heterogeneity and pathobiology of neurodegenerative diseases. METHODS AND ANALYSIS The Tallaght University Hospital Institute for Memory and Cognition Biobank for Research in Ageing and Neurodegeneration (TIMC-BRAiN) will recruit 1000 individuals over 5 years. Participants, who are undergoing diagnostic workup in the TIMC Memory Assessment and Support Service (TIMC-MASS), will opt to donate clinical data and biological samples to a biobank. All participants will complete a detailed clinical, neuropsychological and dementia severity assessment (including Addenbrooke's Cognitive Assessment, Repeatable Battery for Assessment of Neuropsychological Status, Clinical Dementia Rating Scale). Participants undergoing venepuncture/lumbar puncture as part of the clinical workup will be offered the opportunity to donate additional blood (serum/plasma/whole blood) and cerebrospinal fluid samples for longitudinal storage in the TIMC-BRAiN biobank. Participants are followed at 18-month intervals for repeat clinical and cognitive assessments. Anonymised clinical data and biological samples will be stored securely in a central repository and used to facilitate future studies concerned with advancing the diagnosis and treatment of neurodegenerative diseases. ETHICS AND DISSEMINATION Ethical approval has been granted by the St. James's Hospital/Tallaght University Hospital Joint Research Ethics Committee (Project ID: 2159), which operates in compliance with the European Communities (Clinical Trials on Medicinal Products for Human Use) Regulations 2004 and ICH Good Clinical Practice Guidelines. Findings using TIMC-BRAiN will be published in a timely and open-access fashion.
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Affiliation(s)
- Adam H Dyer
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Helena Dolphin
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | | | - Laura Morrison
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Gavin Sedgwick
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Aoife McFeely
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Emily Killeen
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Conal Gallagher
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Naomi Davey
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Eimear Connolly
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Shane Lyons
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Conor Young
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Christine Gaffney
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Ruth Ennis
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Cathy McHale
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Jasmine Joseph
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Graham Knight
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Emmet Kelly
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | | | - Nollaig M Bourke
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Aoife Fallon
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Sean O'Dowd
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
- Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
| | - Sean P Kennelly
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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Kang JH, Korecka M, Lee EB, Cousins KAQ, Tropea TF, Chen-Plotkin AA, Irwin DJ, Wolk D, Brylska M, Wan Y, Shaw LM. Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology. Clin Chem 2023; 69:1247-1259. [PMID: 37725909 PMCID: PMC10895336 DOI: 10.1093/clinchem/hvad139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 07/07/2023] [Indexed: 09/21/2023]
Abstract
BACKGROUND Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway. CONTENT Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers. SUMMARY CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.
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Affiliation(s)
- Ju Hee Kang
- Department of Pharmacology and Clinical Pharmacology, Research Center for Controlling Intercellular Communication, Inha University, Incheon, South Korea
| | - Magdalena Korecka
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A Q Cousins
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Thomas F Tropea
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Alice A Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Magdalena Brylska
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Yang Wan
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Zhao K, Chen P, Alexander-Bloch A, Wei Y, Dyrba M, Yang F, Kang X, Wang D, Fan D, Ye S, Tang Y, Yao H, Zhou B, Lu J, Yu C, Wang P, Liao Z, Chen Y, Huang L, Zhang X, Han Y, Li S, Liu Y. A neuroimaging biomarker for Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN): a cross-sectional study. EClinicalMedicine 2023; 65:102276. [PMID: 37954904 PMCID: PMC10632687 DOI: 10.1016/j.eclinm.2023.102276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 09/27/2023] [Accepted: 09/29/2023] [Indexed: 11/14/2023] Open
Abstract
Background Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that poses a worldwide public health challenge. A neuroimaging biomarker would significantly improve early diagnosis and intervention, ultimately enhancing the quality of life for affected individuals and reducing the burden on healthcare systems. Methods Cross-sectional and longitudinal data (10,099 participants with 13,380 scans) from 12 independent datasets were used in the present study (this study was performed between September 1, 2021 and February 15, 2023). The Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN) score was developed via integrated regional- and network-based measures under an ensemble machine learning model based on structural MRI data. We systematically assessed whether IBRAIN could be a neuroimaging biomarker for AD. Findings IBRAIN accurately differentiated individuals with AD from NCs (AUC = 0.92) and other neurodegenerative diseases, including Frontotemporal dementia (FTD), Parkinson's disease (PD), Vascular dementia (VaD) and Amyotrophic Lateral Sclerosis (ALS) (AUC = 0.92). IBRAIN was significantly correlated to clinical measures and gene expression, enriched in immune process and protein metabolism. The IBRAIN score exhibited a significant ability to reveal the distinct progression of prodromal AD (i.e., Mild cognitive impairment, MCI) (Hazard Ratio (HR) = 6.52 [95% CI: 4.42∼9.62], p < 1 × 10-16), which offers similar powerful performance with Cerebrospinal Fluid (CSF) Aβ (HR = 3.78 [95% CI: 2.63∼5.43], p = 2.13 × 10-14) and CSF Tau (HR = 3.77 [95% CI: 2.64∼5.39], p = 9.53 × 10-15) based on the COX and Log-rank test. Notably, the IBRAIN shows comparable sensitivity (beta = -0.70, p < 1 × 10-16) in capturing longitudinal changes in individuals with conversion to AD than CSF Aβ (beta = -0.26, p = 4.40 × 10-9) and CSF Tau (beta = 0.12, p = 1.02 × 10-5). Interpretation Our findings suggested that IBRAIN is a biologically relevant, specific, and sensitive neuroimaging biomarker that can serve as a clinical measure to uncover prodromal AD progression. It has strong potential for application in future clinical practice and treatment trials. Funding Science and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, Beijing Natural Science Funds, the Fundamental Research Funds for the CentralUniversity, and the Startup Funds for Talents at Beijing Normal University.
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Affiliation(s)
- Kun Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Pindong Chen
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Centre, Chinese Academy of Sciences, Beijing, China
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, USA
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Martin Dyrba
- German Centre for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Fan Yang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Xiaopeng Kang
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Centre, Chinese Academy of Sciences, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Ji'nan, China
| | - Dongsheng Fan
- Department of Neurology, Peking University Third Hospital, Beijing, China
- Key Laboratory for Neuroscience, National Health Commission/Ministry of Education, Peking University, Beijing, China
- Beijing Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Shan Ye
- Department of Neurology, Peking University Third Hospital, Beijing, China
- Key Laboratory for Neuroscience, National Health Commission/Ministry of Education, Peking University, Beijing, China
- Beijing Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Yi Tang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Hongxiang Yao
- Department of Radiology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China
| | - Zhengluan Liao
- Department of Psychiatry, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Yan Chen
- Department of Psychiatry, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Longjian Huang
- Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
- National Clinical Research Centre for Geriatric Disorders, Beijing, China
- Centre of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
| | - Shuyu Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Centre, Chinese Academy of Sciences, Beijing, China
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Ding J, Shen C, Wang Z, Yang Y, El Fakhri G, Lu J, Liang D, Zheng H, Zhou Y, Sun T. Tau-PET abnormality as a biomarker for Alzheimer's disease staging and early detection: a topological perspective. Cereb Cortex 2023; 33:10649-10659. [PMID: 37653600 DOI: 10.1093/cercor/bhad312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 08/10/2023] [Accepted: 08/10/2023] [Indexed: 09/02/2023] Open
Abstract
Alzheimer's disease can be detected early through biomarkers such as tau positron emission tomography (PET) imaging, which shows abnormal protein accumulations in the brain. The standardized uptake value ratio (SUVR) is often used to quantify tau-PET imaging, but topological information from multiple brain regions is also linked to tau pathology. Here a new method was developed to investigate the correlations between brain regions using subject-level tau networks. Participants with cognitive normal (74), early mild cognitive impairment (35), late mild cognitive impairment (32), and Alzheimer's disease (40) were included. The abnormality network from each scan was constructed to extract topological features, and 7 functional clusters were further analyzed for connectivity strengths. Results showed that the proposed method performed better than conventional SUVR measures for disease staging and prodromal sign detection. For example, when to differ healthy subjects with and without amyloid deposition, topological biomarker is significant with P < 0.01, SUVR is not with P > 0.05. Functionally significant clusters, i.e. medial temporal lobe, default mode network, and visual-related regions, were identified as critical hubs vulnerable to early disease conversion before mild cognitive impairment. These findings were replicated in an independent data cohort, demonstrating the potential to monitor the early sign and progression of Alzheimer's disease from a topological perspective for individual.
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Affiliation(s)
- Jie Ding
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
| | - Chushu Shen
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
| | - Zhenguo Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
| | - Yongfeng Yang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, United States
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, People's Republic of China
| | - Dong Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
| | - Yun Zhou
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai 201807, People's Republic of China
- School of Biomedical Engineering, Shanghai Tech University, Shanghai 201210, People's Republic of China
| | - Tao Sun
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 100864, People's Republic of China
- United Imaging Research Institute of Innovative Medical Equipment, Shenzhen 518055, People's Republic of China
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Wagatsuma K, Miwa K, Akamatsu G, Yamao T, Kamitaka Y, Sakurai M, Fujita N, Hanaoka K, Matsuda H, Ishii K. Toward standardization of tau PET imaging corresponding to various tau PET tracers: a multicenter phantom study. Ann Nucl Med 2023; 37:494-503. [PMID: 37243882 DOI: 10.1007/s12149-023-01847-8] [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: 03/20/2023] [Accepted: 05/17/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE Tau positron emission tomography (PET) imaging is a recently developed non-invasive tool that can detect the density and extension of tau neurofibrillary tangles. Tau PET tracers have been validated to harmonize and accelerate their development and implementation in clinical practice. Whereas standard protocols including injected dose, uptake time, and duration have been determined for tau PET tracers, reconstruction parameters have not been standardized. The present study conducted phantom experiments based on tau pathology to standardize quantitative tau PET imaging parameters and optimize reconstruction conditions of PET scanners at four Japanese sites according to the results of phantom experiments. METHODS The activity of 4.0 and 2.0 kBq/mL for Hoffman 3D brain and cylindrical phantoms, respectively, was estimated from published studies of brain activity using [18F]flortaucipir, [18F]THK5351, and [18F]MK6240. We developed an original tau-specific volume of interest template for the brain based on pathophysiological tau distribution in the brain defined as Braak stages. We acquired brain and cylindrical phantom images using four PET scanners. Iteration numbers were determined as contrast and recover coefficients (RCs) in gray (GM) and white (WM) matter, and the magnitude of the Gaussian filter was determined from image noise. RESULTS Contrast and RC converged at ≥ 4 iterations, the error rates of RC for GM and WM were < 15% and 1%, respectively, and noise was < 10% in Gaussian filters of 2-4 mm in images acquired using the four scanners. Optimizing the reconstruction conditions for phantom tau PET images acquired by each scanner improved contrast and image noise. CONCLUSIONS The phantom activity was comprehensive for first- and second-generation tau PET tracers. The mid-range activity that we determined could be applied to later tau PET tracers. We propose an analytical tau-specific VOI template based on tau pathophysiological changes in patients with AD to standardize tau PET imaging. Phantom images reconstructed under the optimized conditions for tau PET imaging achieved excellent image quality and quantitative accuracy.
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Affiliation(s)
- Kei Wagatsuma
- School of Allied Health Sciences, Kitasato University, 1-15-1 Kitazato, Minami-Ku, Sagamihara, Kanagawa, 252-0373, Japan.
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2, Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan.
| | - Kenta Miwa
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima City, Fukushima, 960-1295, Japan
| | - Go Akamatsu
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology (QST), 4-9-1 Anagawa, Inage-Ku, Chiba, 263-8555, Japan
| | - Tensho Yamao
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima City, Fukushima, 960-1295, Japan
| | - Yuto Kamitaka
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2, Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan
| | - Minoru Sakurai
- Clinical Imaging Center for Healthcare, Nippon Medical School, 1-12-15, Sendagi, Bunkyo-Ku, Tokyo, 113-0022, Japan
| | - Naotoshi Fujita
- Department of Radiological Technology, Nagoya University Hospital, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Kohei Hanaoka
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, 377-2 Onohigashi, Osakasayama, Osaka, 589-8511, Japan
| | - Hiroshi Matsuda
- Department of Biofunctional Imaging, Fukushima Medical University, 1 Hikarigaoka, Fukushima City, Fukushima, 960-1295, Japan
- Drug Discovery and Cyclotron Research Center, Southern Tohoku Research Institute for Neuroscience, 7-115, Yatsuyamada, Koriyama, 963-8052, Japan
| | - Kenji Ishii
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2, Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan
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Salvadó G, Horie K, Barthélemy NR, Vogel JW, Binette AP, Chen CD, Aschenbrenner AJ, Gordon BA, Benzinger TL, Holtzman DM, Morris JC, Palmqvist S, Stomrud E, Janelidze S, Ossenkoppele R, Schindler SE, Bateman RJ, Hansson O. Novel CSF tau biomarkers can be used for disease staging of sporadic Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.14.23292650. [PMID: 37503281 PMCID: PMC10370223 DOI: 10.1101/2023.07.14.23292650] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic work-up of dementia in clinical practice and the design of clinical trials. Here, we created a staging model using the Subtype and Stage Inference (SuStaIn) algorithm by evaluating cerebrospinal fluid (CSF) amyloid-β (Aβ) and tau biomarkers in 426 participants from BioFINDER-2, that represent the entire spectrum of AD. The model composition and main analyses were replicated in 222 participants from the Knight ADRC cohort. SuStaIn revealed in the two cohorts that the data was best explained by a single biomarker sequence (one subtype), and that five CSF biomarkers (ordered: Aβ42/40, tau phosphorylation occupancies at the residues 217 and 205 [pT217/T217 and pT205/T205], microtubule-binding region of tau containing the residue 243 [MTBR-tau243], and total tau) were sufficient to create an accurate disease staging model. Increasing CSF stages (0-5) were associated with increased abnormality in other AD-related biomarkers, such as Aβ- and tau-PET, and aligned with different phases of longitudinal biomarker changes consistent with current models of AD progression. Higher CSF stages at baseline were associated with higher hazard ratio of clinical decline. Our findings indicate that a common pathophysiologic molecular pathway develops across all AD patients, and that a single CSF collection is sufficient to reliably indicate the presence of both AD pathologies and the degree and stage of disease progression.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Kanta Horie
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- Eisai Inc., Nutley, NJ, United States
| | - Nicolas R. Barthélemy
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Jacob W. Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Clinical Science, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Charles D. Chen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew J Aschenbrenner
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A. Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M. Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J. Bateman
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Visser D, Verfaillie SCJ, Bosch I, Brouwer I, Tuncel H, Coomans EM, Rikken RM, Mastenbroek SE, Golla SSV, Barkhof F, van de Giessen E, van Berckel BNM, van der Flier WM, Ossenkoppele R. Tau pathology as determinant of changes in atrophy and cerebral blood flow: a multi-modal longitudinal imaging study. Eur J Nucl Med Mol Imaging 2023; 50:2409-2419. [PMID: 36976303 PMCID: PMC10250461 DOI: 10.1007/s00259-023-06196-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/13/2023] [Indexed: 03/29/2023]
Abstract
PURPOSE Tau pathology is associated with concurrent atrophy and decreased cerebral blood flow (CBF) in Alzheimer's disease (AD), but less is known about their temporal relationships. Our aim was therefore to investigate the association of concurrent and longitudinal tau PET with longitudinal changes in atrophy and relative CBF. METHODS We included 61 individuals from the Amsterdam Dementia Cohort (mean age 65.1 ± 7.5 years, 44% female, 57% amyloid-β positive [Aβ +], 26 cognitively impaired [CI]) who underwent dynamic [18F]flortaucipir PET and structural MRI at baseline and 25 ± 5 months follow-up. In addition, we included 86 individuals (68 CI) who only underwent baseline dynamic [18F]flortaucipir PET and MRI scans to increase power in our statistical models. We obtained [18F]flortaucipir PET binding potential (BPND) and R1 values reflecting tau load and relative CBF, respectively, and computed cortical thickness from the structural MRI scans using FreeSurfer. We assessed the regional associations between i) baseline and ii) annual change in tau PET BPND in Braak I, III/IV, and V/VI regions and cortical thickness or R1 in cortical gray matter regions (spanning the whole brain) over time using linear mixed models with random intercepts adjusted for age, sex, time between baseline and follow-up assessments, and baseline BPND in case of analyses with annual change as determinant. All analyses were performed in Aβ- cognitively normal (CN) individuals and Aβ+ (CN and CI) individuals separately. RESULTS In Aβ+ individuals, greater baseline Braak III/IV and V/VI tau PET binding was associated with faster cortical thinning in primarily frontotemporal regions. Annual changes in tau PET were not associated with cortical thinning over time in either Aβ+ or Aβ- individuals. Baseline tau PET was not associated with longitudinal changes in relative CBF, but increases in Braak III/IV tau PET over time were associated with increases in parietal relative CBF over time in Aβ + individuals. CONCLUSION We showed that higher tau load was related to accelerated cortical thinning, but not to decreases in relative CBF. Moreover, tau PET load at baseline was a stronger predictor of cortical thinning than change of tau PET signal.
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Affiliation(s)
- Denise Visser
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands.
| | - Sander C J Verfaillie
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Medical Psychology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands
| | - Iris Bosch
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Iman Brouwer
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Hayel Tuncel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Emma M Coomans
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Roos M Rikken
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Sophie E Mastenbroek
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Sandeep S V Golla
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Elsmarieke van de Giessen
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
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Walker JM, Goette W, Farrell K, Iida MA, Karlovich E, White CL, Crary JF, Richardson TE. The relationship between hippocampal amyloid beta burden and spatial distribution of neurofibrillary degeneration. Alzheimers Dement 2023; 19:3158-3170. [PMID: 36738450 PMCID: PMC11100308 DOI: 10.1002/alz.12966] [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: 11/17/2022] [Revised: 12/30/2022] [Accepted: 01/04/2023] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Neurofibrillary degeneration in Alzheimer's disease (AD) typically involves the entorhinal cortex and CA1 subregion of the hippocampus early in the disease process, whereas in primary age-related tauopathy (PART), there is an early selective vulnerability of the CA2 subregion. METHODS Image analysis-based quantitative pixel assessments were used to objectively evaluate amyloid beta (Aβ) burden in the medial temporal lobe in relation to the distribution of hyperphosphorylated-tau (p-tau) in 142 cases of PART and AD. RESULTS Entorhinal, CA1, CA3, and CA4 p-tau deposition levels are significantly correlated with Aβ burden, while CA2 p-tau is not. Furthermore, the CA2/CA1 p-tau ratio is inversely correlated with Aβ burden and distribution. In addition, cognitive impairment is correlated with overall p-tau burden. DISCUSSION These data indicate that the presence and extent of medial temporal lobe Aβ may determine the distribution and spread of neurofibrillary degeneration. The resulting p-tau distribution patterns may discriminate between PART and AD. HIGHLIGHTS Subregional hyperphosphorylated-tau (p-tau) distribution is influenced by hippocampal amyloid beta burden. Higher CA2/CA1 p-tau ratio is predictive of primary age-related tauopathy-like neuropathology. Cognitive function is correlated with the overall hippocampal p-tau burden.
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Affiliation(s)
- Jamie M. Walker
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - William Goette
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Kurt Farrell
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Megan A. Iida
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- School of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Esma Karlovich
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Pathology and Cell Biology, Columbia University, New York, New York, USA
| | - The PART Working Group
- The PART working group is a multi-institutional collaboration. PART working group investigators are listed in the acknowledgments section
| | - Charles L. White
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - John F. Crary
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Timothy E. Richardson
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Lu J, Ma X, Zhang H, Xiao Z, Li M, Wu J, Ju Z, Chen L, Zheng L, Ge J, Liang X, Bao W, Wu P, Ding D, Yen TC, Guan Y, Zuo C, Zhao Q. Head-to-head comparison of plasma and PET imaging ATN markers in subjects with cognitive complaints. Transl Neurodegener 2023; 12:34. [PMID: 37381042 PMCID: PMC10308642 DOI: 10.1186/s40035-023-00365-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023] Open
Abstract
BACKGROUND Gaining more information about the reciprocal associations between different biomarkers within the ATN (Amyloid/Tau/Neurodegeneration) framework across the Alzheimer's disease (AD) spectrum is clinically relevant. We aimed to conduct a comprehensive head-to-head comparison of plasma and positron emission tomography (PET) ATN biomarkers in subjects with cognitive complaints. METHODS A hospital-based cohort of subjects with cognitive complaints with a concurrent blood draw and ATN PET imaging (18F-florbetapir for A, 18F-Florzolotau for T, and 18F-fluorodeoxyglucose [18F-FDG] for N) was enrolled (n = 137). The β-amyloid (Aβ) status (positive versus negative) and the severity of cognitive impairment served as the main outcome measures for assessing biomarker performances. RESULTS Plasma phosphorylated tau 181 (p-tau181) level was found to be associated with PET imaging of ATN biomarkers in the entire cohort. Plasma p-tau181 level and PET standardized uptake value ratios of AT biomarkers showed a similarly excellent diagnostic performance for distinguishing between Aβ+ and Aβ- subjects. An increased tau burden and glucose hypometabolism were significantly associated with the severity of cognitive impairment in Aβ+ subjects. Additionally, glucose hypometabolism - along with elevated plasma neurofilament light chain level - was related to more severe cognitive impairment in Aβ- subjects. CONCLUSION Plasma p-tau181, as well as 18F-florbetapir and 18F-Florzolotau PET imaging can be considered as interchangeable biomarkers in the assessment of Aβ status in symptomatic stages of AD. 18F-Florzolotau and 18F-FDG PET imaging could serve as biomarkers for the severity of cognitive impairment. Our findings have implications for establishing a roadmap to identifying the most suitable ATN biomarkers for clinical use.
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Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoxi Ma
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhenxu Xiao
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming Li
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jie Wu
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zizhao Ju
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Chen
- Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Zheng
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoniu Liang
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Weiqi Bao
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ding Ding
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | | | - Yihui Guan
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
- Human Phenome Institute, Fudan University, Shanghai, China.
| | - Qianhua Zhao
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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Samudra N, Lane-Donovan C, VandeVrede L, Boxer AL. Tau pathology in neurodegenerative disease: disease mechanisms and therapeutic avenues. J Clin Invest 2023; 133:e168553. [PMID: 37317972 PMCID: PMC10266783 DOI: 10.1172/jci168553] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023] Open
Abstract
Tauopathies are disorders associated with tau protein dysfunction and insoluble tau accumulation in the brain at autopsy. Multiple lines of evidence from human disease, as well as nonclinical translational models, suggest that tau has a central pathologic role in these disorders, historically thought to be primarily related to tau gain of toxic function. However, a number of tau-targeting therapies with various mechanisms of action have shown little promise in clinical trials in different tauopathies. We review what is known about tau biology, genetics, and therapeutic mechanisms that have been tested in clinical trials to date. We discuss possible reasons for failures of these therapies, such as use of imperfect nonclinical models that do not predict human effects for drug development; heterogeneity of human tau pathologies which may lead to variable responses to therapy; and ineffective therapeutic mechanisms, such as targeting of the wrong tau species or protein epitope. Innovative approaches to human clinical trials can help address some of the difficulties that have plagued our field's development of tau-targeting therapies thus far. Despite limited clinical success to date, as we continue to refine our understanding of tau's pathogenic mechanism(s) in different neurodegenerative diseases, we remain optimistic that tau-targeting therapies will eventually play a central role in the treatment of tauopathies.
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Telser J, Grossmann K, Wohlwend N, Risch L, Saely CH, Werner P. Phosphorylated tau in Alzheimer's disease. Adv Clin Chem 2023; 116:31-111. [PMID: 37852722 DOI: 10.1016/bs.acc.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
There is a need for blood biomarkers to detect individuals at different Alzheimer's disease (AD) stages because obtaining cerebrospinal fluid-based biomarkers is invasive and costly. Plasma phosphorylated tau proteins (p-tau) have shown potential as such biomarkers. This systematic review was conducted according to the PRISMA guidelines and aimed to determine whether quantification of plasma tau phosphorylated at threonine 181 (p-tau181), threonine 217 (p-tau217) and threonine 231 (p-tau231) is informative in the diagnosis of AD. All p-tau isoforms increase as a function of Aβ-accumulation and discriminate healthy individuals from those at preclinical AD stages with high accuracy. P-tau231 increases earliest, followed by p-tau181 and p-tau217. In advanced stages, all p-tau isoforms are associated with the clinical classification of AD and increase with disease severity, with the greatest increase seen for p-tau217. This is also reflected by a better correlation of p-tau217 with Aβ scans, whereas both, p-tau217 and p-tau181 correlated equally with tau scans. However, at the very advanced stages, p-tau181 begins to plateau, which may mirror the trajectory of the Aβ pathology and indicate an association with a more intermediate risk of AD. Across the AD continuum, the incremental increase in all biomarkers is associated with structural changes in widespread brain regions and underlying cognitive decline. Furthermore, all isoforms differentiate AD from non-AD neurodegenerative disorders, making them specific for AD. Incorporating p-tau181, p-tau217 and p-tau231 in clinical use requires further studies to examine ideal cut-points and harmonize assays.
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Affiliation(s)
- Julia Telser
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Kirsten Grossmann
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Niklas Wohlwend
- Laboratory Dr. Risch, Vaduz, Liechtenstein; Department of Internal Medicine Spital Grabs, Spitalregion Rheintal Werdenberg Sarganserland, Grabs, Switzerland
| | - Lorenz Risch
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein; University Institute of Clinical Chemistry, University Hospital and University of Bern, Inselspital, Bern, Switzerland
| | - Christoph H Saely
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT), Feldkirch, Austria
| | - Philipp Werner
- Department of Neurology, State Hospital of Rankweil, Academic Teaching Hospital, Rankweil, Austria.
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Smith R, Cullen NC, Binette AP, Leuzy A, Blennow K, Zetterberg H, Klein G, Borroni E, Ossenkoppele R, Janelidze S, Palmqvist S, Mattsson-Carlgren N, Stomrud E, Hansson O. Tau-PET is superior to phospho-tau when predicting cognitive decline in symptomatic AD patients. Alzheimers Dement 2023; 19:2497-2507. [PMID: 36516028 PMCID: PMC10264552 DOI: 10.1002/alz.12875] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/15/2022] [Accepted: 10/21/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Biomarkers for the prediction of cognitive decline in patients with amnestic mild cognitive impairment (MCI) and amnestic mild dementia are needed for both clinical practice and clinical trials. METHODS We evaluated the ability of tau-PET (positron emission tomography), cortical atrophy on magnetic resonance imaging (MRI), baseline cognition, apolipoprotein E gene (APOE) status, plasma and cerebrospinal fluid (CSF) levels of phosphorylated tau-217, neurofilament light (NfL), and amyloid beta (Aβ)42/40 ratio (individually and in combination) to predict cognitive decline over 2 years in BioFINDER-2 and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS Baseline tau-PET and a composite baseline cognitive score were the strongest independent predictors of cognitive decline. Cortical thickness and NfL provided some additional information. Using a predictive algorithm to enrich patient selection in a theoretical clinical trial led to a significantly lower required sample size. DISCUSSION Models including baseline tau-PET and cognition consistently provided the best prediction of change in cognitive function over 2 years in patients with amnestic MCI or mild dementia.
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Affiliation(s)
- Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Nicholas C. Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | | | | | | | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Leuzy A, Binette AP, Vogel JW, Klein G, Borroni E, Tonietto M, Strandberg O, Mattsson-Carlgren N, Palmqvist S, Pontecorvo MJ, Iaccarino L, Stomrud E, Ossenkoppele R, Smith R, Hansson O. Comparison of Group-Level and Individualized Brain Regions for Measuring Change in Longitudinal Tau Positron Emission Tomography in Alzheimer Disease. JAMA Neurol 2023; 80:614-623. [PMID: 37155176 PMCID: PMC10167602 DOI: 10.1001/jamaneurol.2023.1067] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 02/15/2023] [Indexed: 05/10/2023]
Abstract
Importance Longitudinal tau positron emission tomography (PET) is a relevant outcome in clinical trials evaluating disease-modifying therapies in Alzheimer disease (AD). A key unanswered question is whether the use of participant-specific (individualized) regions of interest (ROIs) is superior to conventional approaches where the same ROI (group-level) is used for each participant. Objective To compare group- and participant-level ROIs in participants at different stages of the AD clinical continuum in terms of annual percentage change in tau-PET standardized uptake value ratio (SUVR) and sample size requirements. Design, Setting, and Participants This was a longitudinal cohort study with consecutive participant enrollment between September 18, 2017, and November 15, 2021. Included in the analysis were participants with mild cognitive impairment and AD dementia from the prospective and longitudinal Swedish Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably 2 (BioFINDER-2) study; in addition, a validation sample (the AVID 05e, Expedition-3, Alzheimer's Disease Neuroimaging Initiative [ADNI], and BioFINDER-1 study cohorts) was also included. Exposures Tau PET (BioFINDER-2, [18F]RO948; validation sample, [18F]flortaucipir), 7 group-level (5 data-driven stages, meta-temporal, whole brain), and 5 individualized ROIs. Main Outcomes and Measures Annual percentage change in tau-PET SUVR across ROIs. Sample size requirements in simulated clinical trials using tau PET as an outcome were also calculated. Results A total of 215 participants (mean [SD] age, 71.4 (7.5) years; 111 male [51.6%]) from the BioFINDER-2 study were included in this analysis: 97 amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals, 77 with Aβ-positive mild cognitive impairment (MCI), and 41 with AD dementia. In the validation sample were 137 Aβ-positive CU participants, 144 with Aβ-positive MCI, and 125 with AD dementia. Mean (SD) follow-up time was 1.8 (0.3) years. Using group-level ROIs, the largest annual percentage increase in tau-PET SUVR in Aβ-positive CU individuals was seen in a composite ROI combining the entorhinal cortex, hippocampus, and amygdala (4.29%; 95% CI, 3.42%-5.16%). In individuals with Aβ-positive MCI, the greatest change was seen in the temporal cortical regions (5.82%; 95% CI, 4.67%-6.97%), whereas in those with AD dementia, the greatest change was seen in the parietal regions (5.22%; 95% CI, 3.95%-6.49%). Significantly higher estimates of annual percentage change were found using several of the participant-specific ROIs. Importantly, the simplest participant-specific approach, where change in tau PET was calculated in an ROI that best matched the participant's data-driven disease stage, performed best in all 3 subgroups. For the power analysis, sample size reductions for the participant-specific ROIs ranged from 15.94% (95% CI, 8.14%-23.74%) to 72.10% (95% CI, 67.10%-77.20%) compared with the best-performing group-level ROIs. Findings were replicated using [18F]flortaucipir. Conclusions and Relevance Finding suggest that certain individualized ROIs carry an advantage over group-level ROIs for assessing longitudinal tau changes and increase the power to detect treatment effects in AD clinical trials using longitudinal tau PET as an outcome.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Jacob W. Vogel
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia
- Department of Psychiatry, University of Pennsylvania, Philadelphia
| | | | | | | | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Michael J. Pontecorvo
- Avid Radiopharmaceuticals, Philadelphia, Pennsylvania
- Eli Lilly and Company, Indianapolis, Indiana
| | - Leonardo Iaccarino
- Avid Radiopharmaceuticals, Philadelphia, Pennsylvania
- Eli Lilly and Company, Indianapolis, Indiana
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
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Aguillon D, Langella S, Chen Y, Sanchez J, Su Y, Vila-Castelar C, Vasquez D, Zetterberg H, Hansson O, Dage JL, Janelidze S, Chen K, Fox-Fuller JT, Aduen P, Martinez JE, Garcia G, Baena A, Guzman C, Johnson K, Sperling RA, Blennow K, Reiman EM, Lopera F, Quiroz YT. Plasma p-tau217 predicts in vivo brain pathology and cognition in autosomal dominant Alzheimer's disease. Alzheimers Dement 2023; 19:2585-2594. [PMID: 36571821 PMCID: PMC10271963 DOI: 10.1002/alz.12906] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 12/27/2022]
Abstract
INTRODUCTION Plasma-measured tau phosphorylated at threonine 217 (p-tau217) is a potential non-invasive biomarker of Alzheimer's disease (AD). We investigated whether plasma p-tau217 predicts subsequent cognition and positron emission tomography (PET) markers of pathology in autosomal dominant AD. METHODS We analyzed baseline levels of plasma p-tau217 and its associations with amyloid PET, tau PET, and word list delayed recall measured 7.61 years later in non-demented age- and education-matched presenilin-1 E280A carriers (n = 24) and non-carrier (n = 20) family members. RESULTS Carriers had higher plasma p-tau217 levels than non-carriers. Baseline plasma p-tau217 was associated with subsequent amyloid and tau PET pathology levels and cognitive function. DISCUSSION Our findings suggest that plasma p-tau217 predicts subsequent brain pathological burden and memory performance in presenilin-1 E280A carriers. These results provide support for plasma p-tau217 as a minimally invasive diagnostic and prognostic biomarker for AD, with potential utility in clinical practice and trials. HIGHLIGHTS Non-demented presenilin-1 E280A carriers have higher plasma tau phosphorylated at threonine 217 (p-tau217) than do age-matched non-carriers. Higher baseline p-tau217 is associated with greater future amyloid positron emission tomography (PET) pathology burden. Higher baseline p-tau217 is associated with greater future tau PET pathology burden. Higher baseline p-tau217 is associated with worse future memory performance.
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Affiliation(s)
- David Aguillon
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | | | | | - Justin Sanchez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | | | - Daniel Vasquez
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden
| | - Jeffrey L. Dage
- Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | - Joshua T. Fox-Fuller
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, USA
| | - Paula Aduen
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jairo E. Martinez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, USA
| | - Gloria Garcia
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Ana Baena
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Claudia Guzman
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Keith Johnson
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A. Sperling
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Yakeel T. Quiroz
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Hansson O, Blennow K, Zetterberg H, Dage J. Blood biomarkers for Alzheimer's disease in clinical practice and trials. NATURE AGING 2023; 3:506-519. [PMID: 37202517 PMCID: PMC10979350 DOI: 10.1038/s43587-023-00403-3] [Citation(s) in RCA: 66] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/21/2023] [Indexed: 05/20/2023]
Abstract
Blood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.
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Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Lund, Sweden.
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for 27 Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jeffrey Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
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Gonzalez-Ortiz F, Kac PR, Brum WS, Zetterberg H, Blennow K, Karikari TK. Plasma phospho-tau in Alzheimer's disease: towards diagnostic and therapeutic trial applications. Mol Neurodegener 2023; 18:18. [PMID: 36927491 PMCID: PMC10022272 DOI: 10.1186/s13024-023-00605-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 02/15/2023] [Indexed: 03/18/2023] Open
Abstract
As the leading cause of dementia, Alzheimer's disease (AD) is a major burden on affected individuals, their families and caregivers, and healthcare systems. Although AD can be identified and diagnosed by cerebrospinal fluid or neuroimaging biomarkers that concord with neuropathological evidence and clinical symptoms, challenges regarding practicality and accessibility hinder their widespread availability and implementation. Consequently, many people with suspected cognitive impairment due to AD do not receive a biomarker-supported diagnosis. Blood biomarkers have the capacity to help expand access to AD diagnostics worldwide. One such promising biomarker is plasma phosphorylated tau (p-tau), which has demonstrated specificity to AD versus non-AD neurodegenerative diseases, and will be extremely important to inform on clinical diagnosis and eligibility for therapies that have recently been approved. This review provides an update on the diagnostic and prognostic performances of plasma p-tau181, p-tau217 and p-tau231, and their associations with in vivo and autopsy-verified diagnosis and pathological hallmarks. Additionally, we discuss potential applications and unanswered questions of plasma p-tau for therapeutic trials, given their recent addition to the biomarker toolbox for participant screening, recruitment and during-trial monitoring. Outstanding questions include assay standardization, threshold generation and biomarker verification in diverse cohorts reflective of the wider community attending memory clinics and included in clinical trials.
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Affiliation(s)
- Fernando Gonzalez-Ortiz
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Przemysław R. Kac
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Wagner S. Brum
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.8532.c0000 0001 2200 7498Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul (UFRGS), Porto Alegre, Brazil
| | - Henrik Zetterberg
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- grid.83440.3b0000000121901201Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- grid.83440.3b0000000121901201UK Dementia Research Institute at UCL, London, UK
- grid.24515.370000 0004 1937 1450Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Thomas K. Karikari
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
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Singh P, Singh D, Srivastava P, Mishra G, Tiwari AK. Evaluation of advanced, pathophysiologic new targets for imaging of CNS. Drug Dev Res 2023; 84:484-513. [PMID: 36779375 DOI: 10.1002/ddr.22040] [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: 10/23/2022] [Revised: 12/12/2022] [Accepted: 12/31/2022] [Indexed: 02/14/2023]
Abstract
The inadequate information about the in vivo pathological, physiological, and neurological impairments, as well as the absence of in vivo tools for assessing brain penetrance and the efficiency of newly designed drugs, has hampered the development of new techniques for the treatment for variety of new central nervous system (CNS) diseases. The searching sites such as Science Direct and PubMed were used to find out the numerous distinct tracers across 16 CNS targets including tau, synaptic vesicle glycoprotein, the adenosine 2A receptor, the phosphodiesterase enzyme PDE10A, and the purinoceptor, among others. Among the most encouraging are [18 F]FIMX for mGluR imaging, [11 C]Martinostat for Histone deacetylase, [18 F]MNI-444 for adenosine 2A imaging, [11 C]ER176 for translocator protein, and [18 F]MK-6240 for tau imaging. We also reviewed the findings for each tracer's features and potential for application in CNS pathophysiology and therapeutic evaluation investigations, including target specificity, binding efficacy, and pharmacokinetic factors. This review aims to present a current evaluation of modern positron emission tomography tracers for CNS targets, with a focus on recent advances for targets that have newly emerged for imaging in humans.
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Affiliation(s)
- Priya Singh
- Department of Chemistry, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
| | - Deepika Singh
- Department of Chemistry, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
| | - Pooja Srivastava
- Division of Cyclotron and Radiopharmaceuticals Sciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Gauri Mishra
- Department of Zoology, Swami Shraddhananad College, University of Delhi, Alipur, Delhi, India
| | - Anjani K Tiwari
- Department of Chemistry, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India
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Insel PS, Young CB, Aisen PS, Johnson KA, Sperling RA, Mormino EC, Donohue MC. Tau positron emission tomography in preclinical Alzheimer's disease. Brain 2023; 146:700-711. [PMID: 35962782 PMCID: PMC10169284 DOI: 10.1093/brain/awac299] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 07/01/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Rates of tau accumulation in cognitively unimpaired older adults are subtle, with magnitude and spatial patterns varying in recent reports. Regional accumulation also likely varies in the degree to which accumulation is amyloid-β-dependent. Thus, there is a need to evaluate the pattern and consistency of tau accumulation across multiple cognitively unimpaired cohorts and how these patterns relate to amyloid burden, in order to design optimal tau end points for clinical trials. Using three large cohorts of cognitively unimpaired older adults, the Anti-Amyloid Treatment in Asymptomatic Alzheimer's and companion study, Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (n = 447), the Alzheimer's Disease Neuroimaging Initiative (n = 420) and the Harvard Aging Brain Study (n = 190), we attempted to identify regions with high rates of tau accumulation and estimate how these rates evolve over a continuous spectrum of baseline amyloid deposition. Optimal combinations of regions, tailored to multiple ranges of baseline amyloid burden as hypothetical clinical trial inclusion criteria, were tested and validated. The inferior temporal cortex, fusiform gyrus and middle temporal cortex had the largest effect sizes of accumulation in both longitudinal cohorts when considered individually. When tau regions of interest were combined to find composite weights to maximize the effect size of tau change over time, both longitudinal studies exhibited a similar pattern-inferior temporal cortex, almost exclusively, was optimal for participants with mildly elevated amyloid β levels. For participants with highly elevated baseline amyloid β levels, combined optimal composite weights were 53% inferior temporal cortex, 31% amygdala and 16% fusiform. At mildly elevated levels of baseline amyloid β, a sample size of 200/group required a treatment effect of 0.40-0.45 (40-45% slowing of tau accumulation) to power an 18-month trial using the optimized composite. Neither a temporal lobe composite nor a global composite reached 80% power with 200/group with an effect size under 0.5. The focus of early tau accumulation on the medial temporal lobe has resulted from the observation that the entorhinal cortex is the initial site to show abnormal levels of tau with age. However, these abnormal levels do not appear to be the result of a high rate of accumulation in the short term, but possibly a more moderate rate occurring early with respect to age. While the entorhinal cortex plays a central role in the early appearance of tau, it may be the inferior temporal cortex that is the critical region for rapid tau accumulation in preclinical Alzheimer's disease.
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Affiliation(s)
- Philip S Insel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Paul S Aisen
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
| | - Keith A Johnson
- Department of Neurology, Harvard Aging Brain Study, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Harvard Aging Brain Study, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Michael C Donohue
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
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49
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Mohammadi Z, Alizadeh H, Marton J, Cumming P. The Sensitivity of Tau Tracers for the Discrimination of Alzheimer's Disease Patients and Healthy Controls by PET. Biomolecules 2023; 13:290. [PMID: 36830659 PMCID: PMC9953528 DOI: 10.3390/biom13020290] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/12/2023] [Accepted: 01/25/2023] [Indexed: 02/09/2023] Open
Abstract
Hyperphosphorylated tau aggregates, also known as neurofibrillary tangles, are a hallmark neuropathological feature of Alzheimer's disease (AD). Molecular imaging of tau by positron emission tomography (PET) began with the development of [18F]FDDNP, an amyloid β tracer with off-target binding to tau, which obtained regional specificity through the differing distributions of amyloid β and tau in AD brains. A concerted search for more selective and affine tau PET tracers yielded compounds belonging to at least eight structural categories; 18F-flortaucipir, known variously as [18F]-T807, AV-1451, and Tauvid®, emerged as the first tau tracer approved by the American Food and Drug Administration. The various tau tracers differ concerning their selectivity over amyloid β, off-target binding at sites such as monoamine oxidase and neuromelanin, and degree of uptake in white matter. While there have been many reviews of molecular imaging of tau in AD and other conditions, there has been no systematic comparison of the fitness of the various tracers for discriminating between AD patient and healthy control (HC) groups. In this narrative review, we endeavored to compare the binding properties of the various tau tracers in vitro and the effect size (Cohen's d) for the contrast by PET between AD patients and age-matched HC groups. The available tracers all gave good discrimination, with Cohen's d generally in the range of two-three in culprit brain regions. Overall, Cohen's d was higher for AD patient groups with more severe illness. Second-generation tracers, while superior concerning off-target binding, do not have conspicuously higher sensitivity for the discrimination of AD and HC groups. We suppose that available pharmacophores may have converged on a maximal affinity for tau fibrils, which may limit the specific signal imparted in PET studies.
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Affiliation(s)
- Zohreh Mohammadi
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran
| | - Hadi Alizadeh
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz 5166/15731, Iran
| | - János Marton
- ABX Advanced Biochemical Compounds Biomedizinische Forschungsreagenzien GmbH, Heinrich-Glaeser-Straße 10-14, D-01454 Radeberg, Germany
| | - Paul Cumming
- Department of Nuclear Medicine, Bern University Hospital, Freiburgstraße 18, CH-3010 Bern, Switzerland
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD 4059, Australia
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50
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Hoenig MC, Drzezga A. Clear-headed into old age: Resilience and resistance against brain aging-A PET imaging perspective. J Neurochem 2023; 164:325-345. [PMID: 35226362 DOI: 10.1111/jnc.15598] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/18/2022] [Accepted: 02/22/2022] [Indexed: 11/28/2022]
Abstract
With the advances in modern medicine and the adaptation towards healthier lifestyles, the average life expectancy has doubled since the 1930s, with individuals born in the millennium years now carrying an estimated life expectancy of around 100 years. And even though many individuals around the globe manage to age successfully, the prevalence of aging-associated neurodegenerative diseases such as sporadic Alzheimer's disease has never been as high as nowadays. The prevalence of Alzheimer's disease is anticipated to triple by 2050, increasing the societal and economic burden tremendously. Despite all efforts, there is still no available treatment defeating the accelerated aging process as seen in this disease. Yet, given the advances in neuroimaging techniques that are discussed in the current Review article, such as in positron emission tomography (PET) or magnetic resonance imaging (MRI), pivotal insights into the heterogenous effects of aging-associated processes and the contribution of distinct lifestyle and risk factors already have and are still being gathered. In particular, the concepts of resilience (i.e. coping with brain pathology) and resistance (i.e. avoiding brain pathology) have more recently been discussed as they relate to mechanisms that are associated with the prolongation and/or even stop of the progressive brain aging process. Better understanding of the underlying mechanisms of resilience and resistance may one day, hopefully, support the identification of defeating mechanism against accelerating aging.
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Affiliation(s)
- Merle C Hoenig
- Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany.,Department of Nuclear Medicine, Faculty of Medicine, University Hospital Cologne, Cologne, Germany
| | - Alexander Drzezga
- Research Center Juelich, Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Juelich, Germany.,Department of Nuclear Medicine, Faculty of Medicine, University Hospital Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases, Bonn/Cologne, Germany
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