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O'Connell GC, Smothers CG, Wang J, Ruksakulpiwat S, Armentrout BL. Brain Expression Levels of Commonly Measured Blood Biomarkers of Neurological Damage Differ with Respect to Sex, Race, and Age. Neuroscience 2024; 551:79-93. [PMID: 38762083 DOI: 10.1016/j.neuroscience.2024.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 04/30/2024] [Accepted: 05/13/2024] [Indexed: 05/20/2024]
Abstract
It is increasingly evident that blood biomarkers have potential to improve the diagnosis and management of both acute and chronic neurological conditions. The most well-studied candidates, and arguably those with the broadest utility, are proteins that are highly enriched in neural tissues and released into circulation upon cellular damage. It is currently unknown how the brain expression levels of these proteins is influenced by demographic factors such as sex, race, and age. Given that source tissue abundance is likely a key determinant of the levels observed in the blood during neurological pathology, understanding such influences is important in terms of identifying potential clinical scenarios that could produce diagnostic bias. In this study, we leveraged existing mRNA sequencing data originating from 2,642 normal brain specimens harvested from 382 human donors to examine potential demographic variability in the expression levels of genes which code for 28 candidate blood biomarkers of neurological damage. Existing mass spectrometry data originating from 26 additional normal brain specimens harvested from 26 separate human donors was subsequently used to tentatively assess whether observed transcriptional variance was likely to produce corresponding variance in terms of protein abundance. Genes associated with several well-studied or emerging candidate biomarkers including neurofilament light chain (NfL), ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCH-L1), neuron-specific enolase (NSE), and synaptosomal-associated protein 25 (SNAP-25) exhibited significant differences in expression with respect to sex, race, and age. In many instances, these differences in brain expression align well with and provide a mechanistic explanation for previously reported differences in blood levels.
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Affiliation(s)
- Grant C O'Connell
- Molecular Biomarker Core, Case Western Reserve University, Cleveland, OH, USA; School of Nursing, Case Western Reserve University, Cleveland, OH, USA.
| | | | - Jing Wang
- Molecular Biomarker Core, Case Western Reserve University, Cleveland, OH, USA; School of Nursing, Case Western Reserve University, Cleveland, OH, USA
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Hossain I, Marklund N, Czeiter E, Hutchinson P, Buki A. Blood biomarkers for traumatic brain injury: A narrative review of current evidence. BRAIN & SPINE 2023; 4:102735. [PMID: 38510630 PMCID: PMC10951700 DOI: 10.1016/j.bas.2023.102735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/05/2023] [Accepted: 12/11/2023] [Indexed: 03/22/2024]
Abstract
Introduction A blood-based biomarker (BBBM) test could help to better stratify patients with traumatic brain injury (TBI), reduce unnecessary imaging, to detect and treat secondary insults, predict outcomes, and monitor treatment effects and quality of care. Research question What evidence is available for clinical applications of BBBMs in TBI and how to advance this field? Material and methods This narrative review discusses the potential clinical applications of core BBBMs in TBI. A literature search in PubMed, Scopus, and ISI Web of Knowledge focused on articles in English with the words "traumatic brain injury" together with the words "blood biomarkers", "diagnostics", "outcome prediction", "extracranial injury" and "assay method" alone-, or in combination. Results Glial fibrillary acidic protein (GFAP) combined with Ubiquitin C-terminal hydrolase-L1(UCH-L1) has received FDA clearance to aid computed tomography (CT)-detection of brain lesions in mild (m) TBI. Application of S100B led to reduction of head CT scans. GFAP may also predict magnetic resonance imaging (MRI) abnormalities in CT-negative cases of TBI. Further, UCH-L1, S100B, Neurofilament light (NF-L), and total tau showed value for predicting mortality or unfavourable outcome. Nevertheless, biomarkers have less role in outcome prediction in mTBI. S100B could serve as a tool in the multimodality monitoring of patients in the neurointensive care unit. Discussion and conclusion Largescale systematic studies are required to explore the kinetics of BBBMs and their use in multiple clinical groups. Assay development/cross validation should advance the generalizability of those results which implicated GFAP, S100B and NF-L as most promising biomarkers in the diagnostics of TBI.
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Affiliation(s)
- Iftakher Hossain
- Neurocenter, Department of Neurosurgery, Turku University Hospital, Turku, Finland
- Department of Clinical Neurosciences, Neurosurgery Unit, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Niklas Marklund
- Department of Clinical Sciences Lund, Neurosurgery, Lund University, Department of Neurosurgery, Skåne University Hospital, Lund, Sweden
| | - Endre Czeiter
- Department of Neurosurgery, Medical School, Neurotrauma Research Group, Szentagothai Research Centre, And HUN-REN-PTE Clinical Neuroscience MR Research Group, University of Pecs, Pecs, Hungary
| | - Peter Hutchinson
- Department of Clinical Neurosciences, Neurosurgery Unit, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
| | - Andras Buki
- Department of Neurosurgery, University of Örebro, Örebro, Sweden
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3
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Mok TH, Nihat A, Majbour N, Sequeira D, Holm-Mercer L, Coysh T, Darwent L, Batchelor M, Groveman BR, Orr CD, Hughson AG, Heslegrave A, Laban R, Veleva E, Paterson RW, Keshavan A, Schott JM, Swift IJ, Heller C, Rohrer JD, Gerhard A, Butler C, Rowe JB, Masellis M, Chapman M, Lunn MP, Bieschke J, Jackson GS, Zetterberg H, Caughey B, Rudge P, Collinge J, Mead S. Seed amplification and neurodegeneration marker trajectories in individuals at risk of prion disease. Brain 2023; 146:2570-2583. [PMID: 36975162 PMCID: PMC10232278 DOI: 10.1093/brain/awad101] [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: 11/09/2022] [Revised: 02/17/2023] [Accepted: 03/13/2023] [Indexed: 03/29/2023] Open
Abstract
Human prion diseases are remarkable for long incubation times followed typically by rapid clinical decline. Seed amplification assays and neurodegeneration biofluid biomarkers are remarkably useful in the clinical phase, but their potential to predict clinical onset in healthy people remains unclear. This is relevant not only to the design of preventive strategies in those at-risk of prion diseases, but more broadly, because prion-like mechanisms are thought to underpin many neurodegenerative disorders. Here, we report the accrual of a longitudinal biofluid resource in patients, controls and healthy people at risk of prion diseases, to which ultrasensitive techniques such as real-time quaking-induced conversion (RT-QuIC) and single molecule array (Simoa) digital immunoassays were applied for preclinical biomarker discovery. We studied 648 CSF and plasma samples, including 16 people who had samples taken when healthy but later developed inherited prion disease (IPD) ('converters'; range from 9.9 prior to, and 7.4 years after onset). Symptomatic IPD CSF samples were screened by RT-QuIC assay variations, before testing the entire collection of at-risk samples using the most sensitive assay. Glial fibrillary acidic protein (GFAP), neurofilament light (NfL), tau and UCH-L1 levels were measured in plasma and CSF. Second generation (IQ-CSF) RT-QuIC proved 100% sensitive and specific for sporadic Creutzfeldt-Jakob disease (CJD), iatrogenic and familial CJD phenotypes, and subsequently detected seeding activity in four presymptomatic CSF samples from three E200K carriers; one converted in under 2 months while two remain asymptomatic after at least 3 years' follow-up. A bespoke HuPrP P102L RT-QuIC showed partial sensitivity for P102L disease. No compatible RT-QuIC assay was discovered for classical 6-OPRI, A117V and D178N, and these at-risk samples tested negative with bank vole RT-QuIC. Plasma GFAP and NfL, and CSF NfL levels emerged as proximity markers of neurodegeneration in the typically slow IPDs (e.g. P102L), with significant differences in mean values segregating healthy control from IPD carriers (within 2 years to onset) and symptomatic IPD cohorts; plasma GFAP appears to change before NfL, and before clinical conversion. In conclusion, we show distinct biomarker trajectories in fast and slow IPDs. Specifically, we identify several years of presymptomatic seeding positivity in E200K, a new proximity marker (plasma GFAP) and sequential neurodegenerative marker evolution (plasma GFAP followed by NfL) in slow IPDs. We suggest a new preclinical staging system featuring clinical, seeding and neurodegeneration aspects, for validation with larger prion at-risk cohorts, and with potential application to other neurodegenerative proteopathies.
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Affiliation(s)
- Tze How Mok
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Akin Nihat
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Nour Majbour
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Danielle Sequeira
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Leah Holm-Mercer
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Thomas Coysh
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Lee Darwent
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Mark Batchelor
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Bradley R Groveman
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Christina D Orr
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Andrew G Hughson
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Amanda Heslegrave
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
| | - Rhiannon Laban
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
| | - Elena Veleva
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
| | - Ross W Paterson
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Ashvini Keshavan
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Jonathan M Schott
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Imogen J Swift
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Carolin Heller
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Jonathan D Rohrer
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester M13 9PL, UK
- Department of Geriatric Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, 45147 Essen, Germany
- Department of Nuclear Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, 45147 Essen, Germany
| | - Christopher Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, UK
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Miles Chapman
- Neuroimmunology and CSF Laboratory, University College London Hospitals NHS Trust National Hospital of Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Michael P Lunn
- Neuroimmunology and CSF Laboratory, University College London Hospitals NHS Trust National Hospital of Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Jan Bieschke
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Graham S Jackson
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, S-43180 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- 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 53792-2420, USA
| | - Byron Caughey
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Peter Rudge
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - John Collinge
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Simon Mead
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
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Xu Y, Vasiljevic E, Deming YK, Jonaitis EM, Koscik RL, Van Hulle CA, Lu Q, Carboni M, Kollmorgen G, Wild N, Carlsson CM, Johnson SC, Zetterberg H, Blennow K, Engelman CD. Effect of Pathway-specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-related Biomarkers among Asymptomatic Individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.30.23285142. [PMID: 36778431 PMCID: PMC9915839 DOI: 10.1101/2023.01.30.23285142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Background Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan. Objective In this study, we leveraged 10 years of longitudinal data from initially cognitively unimpaired individuals in the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways. Methods PRS and p-PRSs with and without apolipoprotein E ( APOE ) were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and global/domain-specific cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers for beta-amyloid 42 (Aβ42), Aβ42/40 ratio, total tau, and phosphorylated tau in a subset. Replication analyses were performed in an independent sample. Results We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of p-PRSs/PRS on rate of change in cognition, beta-amyloid, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded. Conclusion In addition to APOE , the p-PRSs can predict age-dependent changes in beta-amyloid, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating beta-amyloid and tau, long before the onset of clinical symptoms.
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Affiliation(s)
- Yuexuan Xu
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
| | - Eva Vasiljevic
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, WI, USA
| | - Yuetiva K. Deming
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, WI, USA
| | - Erin M. Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, WI, USA
| | - Rebecca L. Koscik
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
| | - Carol A. Van Hulle
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
| | | | | | | | - Cynthia M. Carlsson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Memorial VA Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Corinne D. Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
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5
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Xu Y, Vasiljevic E, Deming YK, Jonaitis EM, Koscik RL, Van Hulle CA, Lu Q, Carboni M, Kollmorgen G, Wild N, Carlsson CM, Johnson SC, Zetterberg H, Blennow K, Engelman CD. Effect of Pathway-Specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-Related Biomarkers Among Asymptomatic Individuals. J Alzheimers Dis 2023; 94:1587-1605. [PMID: 37482996 PMCID: PMC10468904 DOI: 10.3233/jad-230097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
BACKGROUND Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan. OBJECTIVE In this study, we leveraged longitudinal data from the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways. METHODS PRS and p-PRSs with and without APOE were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers in a subset. Replication analyses were performed in an independent sample. RESULTS We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of PRS/p-PRSs on rate of change in cognition, amyloid-β, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded. CONCLUSION In addition to APOE, the p-PRSs can predict age-dependent changes in amyloid-β, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating amyloid-β and tau, long before the onset of clinical symptoms.
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Affiliation(s)
- Yuexuan Xu
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
| | - Eva Vasiljevic
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, WI, USA
| | - Yuetiva K. Deming
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, WI, USA
| | - Erin M. Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, WI, USA
| | - Rebecca L. Koscik
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
| | - Carol A. Van Hulle
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
| | | | | | | | - Cynthia M. Carlsson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Memorial VA Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, WI, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Corinne D. Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, WI, USA
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Hier DB, Azizi S, Thimgan MS, Wunsch DC. Tau kinetics in Alzheimer's disease. Front Aging Neurosci 2022; 14:1055170. [PMID: 36437992 PMCID: PMC9682289 DOI: 10.3389/fnagi.2022.1055170] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 10/27/2022] [Indexed: 07/20/2023] Open
Abstract
The cytoskeletal protein tau is implicated in the pathogenesis of Alzheimer's disease which is characterized by intra-neuronal neurofibrillary tangles containing abnormally phosphorylated insoluble tau. Levels of soluble tau are elevated in the brain, the CSF, and the plasma of patients with Alzheimer's disease. To better understand the causes of these elevated levels of tau, we propose a three-compartment kinetic model (brain, CSF, and plasma). The model assumes that the synthesis of tau follows zero-order kinetics (uncorrelated with compartmental tau levels) and that the release, absorption, and clearance of tau is governed by first-order kinetics (linearly related to compartmental tau levels). Tau that is synthesized in the brain compartment can be released into the interstitial fluid, catabolized, or retained in neurofibrillary tangles. Tau released into the interstitial fluid can mix with the CSF and eventually drain to the plasma compartment. However, losses of tau in the drainage pathways may be significant. The kinetic model estimates half-life of tau in each compartment (552 h in the brain, 9.9 h in the CSF, and 10 h in the plasma). The kinetic model predicts that an increase in the neuronal tau synthesis rate or a decrease in tau catabolism rate best accounts for observed increases in tau levels in the brain, CSF, and plasma found in Alzheimer's disease. Furthermore, the model predicts that increases in brain half-life of tau in Alzheimer's disease should be attributed to decreased tau catabolism and not to increased tau synthesis. Most clearance of tau in the neuron occurs through catabolism rather than release to the CSF compartment. Additional experimental data would make ascertainment of the model parameters more precise.
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Affiliation(s)
- Daniel B. Hier
- Applied Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, Missouri University of Science & Technology, Rolla, MO, United States
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, United States
| | - Sima Azizi
- Applied Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, Missouri University of Science & Technology, Rolla, MO, United States
| | - Matthew S. Thimgan
- Department of Biological Sciences, Missouri University of Science & Technology, Rolla, MO, United States
| | - Donald C. Wunsch
- Applied Computational Intelligence Laboratory, Department of Electrical & Computer Engineering, Missouri University of Science & Technology, Rolla, MO, United States
- ECCS Division, National Science Foundation, Alexandria, VA, United States
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Hossain I, Blennow K, Posti JP, Zetterberg H. Tau as a fluid biomarker of concussion and neurodegeneration. CONCUSSION (LONDON, ENGLAND) 2022; 7:CNC98. [PMID: 36687115 PMCID: PMC9841393 DOI: 10.2217/cnc-2022-0004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 11/16/2022] [Indexed: 12/12/2022]
Abstract
Concussion is predominant among the vast number of traumatic brain injuries that occur worldwide. Difficulties in timely identification, whether concussion led to neuronal injury or not, diagnosis and the lack of prognostic tools for adequate management could lead this type of brain injury to progressive neurodegenerative diseases. Tau has been extensively studied in recent years, particularly in repetitive mild traumatic brain injuries and sports-related concussions. Tauopathies, the group of neurodegenerative diseases, have also been studied with advanced functional imaging. Nevertheless, neurodegenerative diseases, such as chronic traumatic encephalopathy, are still conclusively diagnosed at autopsy. Here, we discuss the diagnostic dilemma and the relationship between concussion and neurodegenerative diseases and review the literature on tau as a promising biomarker for concussion.
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Affiliation(s)
- Iftakher Hossain
- Department of Neurosurgery, Neurocenter, Turku University Hospital, Finland,Turku Brain Injury Center, Turku University Hospital, Finland,Department of Clinical Neurosciences, University of Turku, Finland,Department of Clinical Neurosciences, Neurosurgery Unit, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK,Author for correspondence: Tel.: +358 2 313 0282;
| | - Kaj Blennow
- Institute of Neuroscience & Physiology, Department of Psychiatry & Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jussi P Posti
- Department of Neurosurgery, Neurocenter, Turku University Hospital, Finland,Turku Brain Injury Center, Turku University Hospital, Finland,Department of Clinical Neurosciences, University of Turku, Finland
| | - Henrik Zetterberg
- Institute of Neuroscience & Physiology, Department of Psychiatry & 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, Queen Square, London, UK,UK Dementia Research Institute at UCL, University College London, London, UK,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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8
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Tau isoform-specific enhancement of L-type calcium current and augmentation of afterhyperpolarization in rat hippocampal neurons. Sci Rep 2022; 12:15231. [PMID: 36075936 PMCID: PMC9458744 DOI: 10.1038/s41598-022-18648-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/17/2022] [Indexed: 11/08/2022] Open
Abstract
Accumulation of tau is observed in dementia, with human tau displaying 6 isoforms grouped by whether they display either 3 or 4 C-terminal repeat domains (3R or 4R) and exhibit no (0N), one (1N) or two (2N) N terminal repeats. Overexpression of 4R0N-tau in rat hippocampal slices enhanced the L-type calcium (Ca2+) current-dependent components of the medium and slow afterhyperpolarizations (AHPs). Overexpression of both 4R0N-tau and 4R2N-tau augmented CaV1.2-mediated L-type currents when expressed in tsA-201 cells, an effect not observed with the third 4R isoform, 4R1N-tau. Current enhancement was only observed when the pore-forming subunit was co-expressed with CaVβ3 and not CaVβ2a subunits. Non-stationary noise analysis indicated that enhanced Ca2+ channel current arose from a larger number of functional channels. 4R0N-tau and CaVβ3 were found to be physically associated by co-immunoprecipitation. In contrast, the 4R1N-tau isoform that did not augment expressed macroscopic L-type Ca2+ current exhibited greatly reduced binding to CaVβ3. These data suggest that physical association between tau and the CaVβ3 subunit stabilises functional L-type channels in the membrane, increasing channel number and Ca2+ influx. Enhancing the Ca2+-dependent component of AHPs would produce cognitive impairment that underlie those seen in the early phases of tauopathies.
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9
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Aquino Nunez W, Combs B, Gamblin TC, Ackley BD. Age-dependent accumulation of tau aggregation in Caenorhabditis elegans. FRONTIERS IN AGING 2022; 3:928574. [PMID: 36062211 PMCID: PMC9437221 DOI: 10.3389/fragi.2022.928574] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/25/2022] [Indexed: 06/15/2023]
Abstract
Aging is the primary risk factor for Alzheimer's disease (AD) and related disorders (ADRDs). Tau aggregation is a hallmark of AD and other tauopathies. Even in normal aging, tau aggregation is found in brains, but in disease states, significantly more aggregated tau is present in brain regions demonstrating synaptic degeneration and neuronal loss. It is unclear how tau aggregation and aging interact to give rise to the phenotypes observed in disease states. Most AD/ADRD animal models have focused on late stages, after significant tau aggregation has occurred. There are fewer where we can observe the early aggregation events and progression during aging. In an attempt to address this gap, we created C. elegans models expressing a GFP-tagged version of the human tau protein. Here we examined how tau-gfp behaved during aging, comparing wild-type tau (hTau40), a disease-associated mutation (P301S), and an aggregation-prone variant (3PO). We measured age-dependent changes in GFP intensity and correlated those changes to normal aging in the nematode. We found differences in tau stability and accumulation depending on the tau variant expressed. hTau40GFP and P301SGFP were localized to axons and cell bodies, while 3POGFP was more concentrated within cell bodies. Expression of 3POGFP resulted in decreased lifespan and variations in locomotor rate, consistent with a pathological effect. Finally, we found that the human tau interacted genetically with the C. elegans ortholog of human tau, ptl-1, where the loss of ptl-1 significantly accelerated the time to death in animals expressing 3PO.
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Affiliation(s)
- Wendy Aquino Nunez
- Laboratory Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, United States
| | - Benjamin Combs
- Department of Translational Neuroscience, Michigan State University, Grand Rapids, MI, United States
| | - T. Chris Gamblin
- Department of Neuroscience, Developmental and Regenerative Biology, University of Texas San Antonio, San Antonio, TX, United States
| | - Brian D. Ackley
- Laboratory Department of Molecular Biosciences, The University of Kansas, Lawrence, KS, United States
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10
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Posti JP, Tenovuo O. Blood-based biomarkers and traumatic brain injury-A clinical perspective. Acta Neurol Scand 2022; 146:389-399. [PMID: 35383879 DOI: 10.1111/ane.13620] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/08/2022] [Accepted: 03/27/2022] [Indexed: 12/19/2022]
Abstract
Blood-based biomarkers are promising tools to complement clinical variables and imaging findings in the diagnosis, monitoring and outcome prediction of traumatic brain injury (TBI). Several promising biomarker candidates have been found for various clinical questions, but the translation of TBI biomarkers into clinical applications has been negligible. Measured biomarker levels are influenced by patient-related variables such as age, blood-brain barrier integrity and renal and liver function. It is not yet fully understood how biomarkers enter the bloodstream from the interstitial fluid of the brain. In addition, the diagnostic performance of TBI biomarkers is affected by sampling timing and analytical methods. In this focused review, the clinical aspects of glial fibrillary acidic protein, neurofilament light, S100 calcium-binding protein B, tau and ubiquitin C-terminal hydrolase-L1 are examined. Current findings and clinical caveats are addressed.
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Affiliation(s)
- Jussi P. Posti
- Neurocenter Department of Neurosurgery and Turku Brain Injury Center Turku University Hospital and University of Turku Turku Finland
| | - Olli Tenovuo
- Neurocenter Turku Brain Injury Center Turku University Hospital and University of Turku Turku Finland
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11
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Drouin SM, McFall GP, Potvin O, Bellec P, Masellis M, Duchesne S, Dixon RA. Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes. J Alzheimers Dis 2022; 88:97-115. [PMID: 35570482 PMCID: PMC9277685 DOI: 10.3233/jad-215289] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/11/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer's disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses. OBJECTIVE To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors/biomarkers. METHODS We used biomarker/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class. RESULTS For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma Aβ1-42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and Aβ1-40, higher depressive symptomology, and lower body mass index. CONCLUSION Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers/risk factors discriminating the higher and lower LHC/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers/risk factors from multiple modalities.
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Affiliation(s)
- Shannon M. Drouin
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
| | - G. Peggy McFall
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | | | - Pierre Bellec
- Département de Psychologie, Université de Montréal, Montreal, QC, Canada
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada
| | - Simon Duchesne
- CERVO Brain Research Centre, Quebec, QC, Canada
- Radiology and Nuclear Medicine Department, Université Laval, Quebec, QC, Canada
| | - Roger A. Dixon
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
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12
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Hazan J, Alston D, Fox NC, Howard R. Practical application of Alzheimer's Disease Neuroimaging Initiative plasma P-tau181 reference data to support diagnosis of Alzheimer's disease. Int J Geriatr Psychiatry 2021; 37. [PMID: 34997780 DOI: 10.1002/gps.5670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 12/18/2021] [Indexed: 11/10/2022]
Abstract
OBJECTIVES To assess plasma phosphorylated tau181 (p-tau181) levels in Alzheimer's disease (AD), cognitively impaired non-AD participants (CI non-AD) and Control participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset that could potentially act as reference data for clinic diagnoses of AD. METHODS Data from 1558 participants (649 AD participants, 445 CI non-AD participants and 464 controls) were examined, comparing p-tau181 levels between Controls, AD and other dementias, stratified by age. RESULTS There were significant differences in plasma p-tau181 values between Controls and those with AD at all ages up to 85 years. There were also significant differences between AD and CI non-AD participants up to the age of 85 years. CONCLUSIONS Plasma P-tau181 may be a useful tool in the diagnosis of AD in those clinical settings where biomarkers have traditionally been less used. P-tau181 may be less useful as an aid to diagnosis in the very oldest-old. Further work is needed to establish the feasibility and utility of this biomarker within dementia diagnosis services not led by Neurologists, such as UK National Health Service Memory Services.
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Affiliation(s)
- Jemma Hazan
- Division of Psychiatry, University College London, London, UK
| | - Duncan Alston
- Institute of Neurology, University College London, London, UK
| | - Nick C Fox
- Institute of Neurology, University College London, London, UK
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
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13
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Hier DB, Obafemi-Ajayi T, Thimgan MS, Olbricht GR, Azizi S, Allen B, Hadi BA, Wunsch DC. Blood biomarkers for mild traumatic brain injury: a selective review of unresolved issues. Biomark Res 2021; 9:70. [PMID: 34530937 PMCID: PMC8447604 DOI: 10.1186/s40364-021-00325-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 08/26/2021] [Indexed: 01/03/2023] Open
Abstract
Background The use of blood biomarkers after mild traumatic brain injury (mTBI) has been widely studied. We have identified eight unresolved issues related to the use of five commonly investigated blood biomarkers: neurofilament light chain, ubiquitin carboxy-terminal hydrolase-L1, tau, S100B, and glial acidic fibrillary protein. We conducted a focused literature review of unresolved issues in three areas: mode of entry into and exit from the blood, kinetics of blood biomarkers in the blood, and predictive capacity of the blood biomarkers after mTBI. Findings Although a disruption of the blood brain barrier has been demonstrated in mild and severe traumatic brain injury, biomarkers can enter the blood through pathways that do not require a breach in this barrier. A definitive accounting for the pathways that biomarkers follow from the brain to the blood after mTBI has not been performed. Although preliminary investigations of blood biomarkers kinetics after TBI are available, our current knowledge is incomplete and definitive studies are needed. Optimal sampling times for biomarkers after mTBI have not been established. Kinetic models of blood biomarkers can be informative, but more precise estimates of kinetic parameters are needed. Confounding factors for blood biomarker levels have been identified, but corrections for these factors are not routinely made. Little evidence has emerged to date to suggest that blood biomarker levels correlate with clinical measures of mTBI severity. The significance of elevated biomarker levels thirty or more days following mTBI is uncertain. Blood biomarkers have shown a modest but not definitive ability to distinguish concussed from non-concussed subjects, to detect sub-concussive hits to the head, and to predict recovery from mTBI. Blood biomarkers have performed best at distinguishing CT scan positive from CT scan negative subjects after mTBI.
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Affiliation(s)
- Daniel B Hier
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65401, USA.
| | - Tayo Obafemi-Ajayi
- Cooperative Engineering Program, Missouri State University, Springfield, MO 65897, United States
| | - Matthew S Thimgan
- Department of Biological Sciences, Missouri University of Science and Technology, Rolla, MO 65409, United States
| | - Gayla R Olbricht
- Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO 65409, United States
| | - Sima Azizi
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65401, USA
| | - Blaine Allen
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65401, USA
| | - Bassam A Hadi
- Department of Surgery, Mercy Hospital, St. Louis MO, Missouri, MO 63141, United States
| | - Donald C Wunsch
- Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO 65401, USA.,National Science Foundation, ECCS Division, Virginia, 22314, USA
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14
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Mielke MM. Consideration of Sex Differences in the Measurement and Interpretation of Alzheimer Disease-Related Biofluid-Based Biomarkers. J Appl Lab Med 2021; 5:158-169. [PMID: 31811073 DOI: 10.1373/jalm.2019.030023] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 10/23/2019] [Indexed: 12/26/2022]
Abstract
BACKGROUND The development of cerebrospinal fluid and blood-based biomarkers for Alzheimer disease (AD) and related disorders is rapidly progressing. Such biomarkers may be used clinically to screen the population, to enhance diagnosis, or to help determine prognosis. Although the use of precision medicine methods has contributed to enhanced understanding of the AD pathophysiological changes and development of assays, one aspect not commonly considered is sex differences. CONTENT There are several ways in which sex can affect the concentration or interpretation of biofluid biomarkers. For some markers, concentrations will vary by sex. For others, the concentrations might not vary by sex, but the impact or interpretation may vary by sex depending on the context of use (e.g., diagnostic vs prognostic). Finally, for others, there will be no sex differences in concentrations or their interpretation. This review will first provide a basis for sex differences, including differences in brain structure and function, and the means by which these differences could contribute to sex differences in biomarker concentrations. Next, the current state of sex differences in AD-related biofluid markers (i.e., amyloid-β, phosphorylated τ, total τ, neurofilament light chain, and neurogranin) will be reviewed. Lastly, factors that can lead to the misinterpretation of observed sex differences in biomarkers (either providing evidence for or against) will be considered. SUMMARY This review is intended to provide an impetus to consider sex differences in the measurement and interpretation of AD-related biofluid-based biomarkers.
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Affiliation(s)
- Michelle M Mielke
- Departments of Health Sciences Research and Neurology, Mayo Clinic, Rochester, MN
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15
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Chiu MJ, Yang SY, Chen TF, Lin CH, Yang FC, Chen WP, Zetterberg H, Blennow K. Synergistic Association between Plasma Aβ 1-42 and p-tau in Alzheimer's Disease but Not in Parkinson's Disease or Frontotemporal Dementia. ACS Chem Neurosci 2021; 12:1376-1383. [PMID: 33825443 PMCID: PMC9278807 DOI: 10.1021/acschemneuro.1c00010] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
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Beta-amyloid (Aβ1–42) triggers the phosphorylation
of tau protein in Alzheimer’s disease (AD), but the relationship
between phosphorylated tau (p-tau) and Aβ1–42 in the blood is not elucidated. We investigated the association
in individuals with AD (n = 62, including amnesic
mild cognitive impairment and dementia), Parkinson’s disease
(n = 30), frontotemporal dementia (n = 25), and cognitively unimpaired controls (n =
41) using immunomagnetic reduction assays to measure plasma Aβ1–42 and p-tau181 concentrations. Correlation and regression
analyses were performed to examine the relation between plasma levels,
demographic factors, and clinical severity. Both plasma Aβ1–42 and p-tau concentrations were significantly higher
in AD and frontotemporal dementia than in the controls and Parkinson’s
disease. A significant positive association was found between plasma
p-tau and Aβ1–42 in controls (r = 0.579, P < 0.001) and AD (r = 0.699, P < 0.001) but not in frontotemporal
dementia or Parkinson’s disease. Plasma p-tau was significantly
associated with clinical severity in the AD in terms of scores of
clinical dementia rating (r = 0.288, P = 0.025) and mini-mental state examination (r =
−0.253, P = 0.049). Regression analysis showed
that plasma Aβ1–42 levels explain approximately
47.7% of the plasma p-tau levels in the AD after controlling age,
gender, and clinical severity. While in non-AD participants, the clinical
dementia rating explained about 47.5% of the plasma p-tau levels.
The disease-specific association between plasma Aβ1–42 and p-tau levels in AD implies a possible synergic effect in mechanisms
involving these two pathological proteins’ genesis.
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Affiliation(s)
- Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei 100, Taiwan
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei 100, Taiwan
- Department of Psychology, National Taiwan University, Taipei 100, Taiwan
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 116, Taiwan
| | - Shieh-Yueh Yang
- MagQu Co., Ltd., New Taipei City 231, Taiwan
- MagQu LLC, Surprise, Arizona 85378, United States
| | - Ta-Fu Chen
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Chin-Hsien Lin
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Fu-Chi Yang
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan
| | | | - 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 405 30, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
- UK Dementia Research Institute at UCL, London WC1E 6BT, United Kingdom
| | - 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 405 30, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
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Ding X, Zhang S, Jiang L, Wang L, Li T, Lei P. Ultrasensitive assays for detection of plasma tau and phosphorylated tau 181 in Alzheimer's disease: a systematic review and meta-analysis. Transl Neurodegener 2021; 10:10. [PMID: 33712071 PMCID: PMC7953695 DOI: 10.1186/s40035-021-00234-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/24/2021] [Indexed: 02/08/2023] Open
Abstract
A lack of convenient and reliable biomarkers for diagnosis and prognosis is a common challenge for neurodegenerative diseases such as Alzheimer's disease (AD). Recent advancement in ultrasensitive protein assays has allowed the quantification of tau and phosphorylated tau proteins in peripheral plasma. Here we identified 66 eligible studies reporting quantification of plasma tau and phosphorylated tau 181 (ptau181) using four ultrasensitive methods. Meta-analysis of these studies confirmed that the AD patients had significantly higher plasma tau and ptau181 levels compared with controls, and that the plasma tau and ptau181 could predict AD with high-accuracy area under curve of the Receiver Operating Characteristic. Therefore, plasma tau and plasma ptau181 can be considered as biomarkers for AD diagnosis.
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Affiliation(s)
- Xulong Ding
- Department of Neurology and State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Shuting Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lijun Jiang
- Mental Health Center and West China Brain Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lu Wang
- Department of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Tao Li
- Mental Health Center and West China Brain Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Peng Lei
- Department of Neurology and State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, China.
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17
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Cantero JL, Atienza M, Ramos-Cejudo J, Fossati S, Wisniewski T, Osorio RS. Plasma tau predicts cerebral vulnerability in aging. Aging (Albany NY) 2020; 12:21004-21022. [PMID: 33147571 PMCID: PMC7695405 DOI: 10.18632/aging.104057] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Accepted: 08/25/2020] [Indexed: 12/11/2022]
Abstract
Identifying cerebral vulnerability in late life may help prevent or slow the progression of aging-related chronic diseases. However, non-invasive biomarkers aimed at detecting subclinical cerebral changes in the elderly are lacking. Here, we have examined the potential of plasma total tau (t-tau) for identifying cerebral and cognitive deficits in normal elderly subjects. Patterns of cortical thickness and cortical glucose metabolism were used as outcomes of cerebral vulnerability. We found that increased plasma t-tau levels were associated with widespread reductions of cortical glucose uptake, thinning of the temporal lobe, and memory deficits. Importantly, tau-related reductions of glucose consumption in the orbitofrontal cortex emerged as a determining factor of the relationship between cortical thinning and memory loss. Together, these results support the view that plasma t-tau may serve to identify subclinical cerebral and cognitive deficits in normal aging, allowing detection of individuals at risk for developing aging-related neurodegenerative conditions.
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Affiliation(s)
- Jose L. Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
| | - Jaime Ramos-Cejudo
- Division of Brain Aging, Department of Psychiatry, New York University School of Medicine, New York, NY 10016, USA
| | - Silvia Fossati
- Alzheimer's Center at Temple, Lewis Katz School of Medicine, Temple University, Philadelphia, PA 19140, USA
| | - Thomas Wisniewski
- Departments of Neurology, Pathology and Psychiatry, Center for Cognitive Neurology, New York University School of Medicine, New York, NY 10016, USA
| | - Ricardo S. Osorio
- Division of Brain Aging, Department of Psychiatry, New York University School of Medicine, New York, NY 10016, USA
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18
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Houben S, de Fisenne MA, Ando K, Vanden Dries V, Poncelet L, Yilmaz Z, Mansour S, De Decker R, Brion JP, Leroy K. Intravenous Injection of PHF-Tau Proteins From Alzheimer Brain Exacerbates Neuroinflammation, Amyloid Beta, and Tau Pathologies in 5XFAD Transgenic Mice. Front Mol Neurosci 2020; 13:106. [PMID: 32765217 PMCID: PMC7381181 DOI: 10.3389/fnmol.2020.00106] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 05/20/2020] [Indexed: 02/01/2023] Open
Abstract
Alzheimer's disease (AD) is characterized by the accumulation in the brain of intraneuronal aggregates of abnormally and hyperphosphorylated tau proteins and of extracellular deposits of amyloid-β surrounded by dystrophic neurites. Numerous experimental models have shown that tau pathology develops in the brain after intracerebral injection of brain homogenates or pathological tau [paired helical filaments (PHF)-tau)] from AD brains. Further investigations are however necessary to identify or exclude potential extracerebral routes of tau pathology transmission, e.g., through the intravascular route. In this study, we have analyzed the effect of intravenous injection of PHF-tau proteins from AD brains on the formation of tau and amyloid pathologies in the brain of wild-type (WT) mice and of 5XFAD mice (an amyloid model). We observed that 5XFAD mice with a disrupted blood-brain barrier showed increased plaque-associated astrogliosis, microgliosis, and increased deposits of Aβ40 and Aβ42 after intravenous injection of PHF-tau proteins. In addition, an increased phosphotau immunoreactivity was observed in plaque-associated dystrophic neurites. These results suggest that blood products contaminated by PHF-tau proteins could potentially induce an exacerbation of neuroinflammation and AD pathologies.
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Affiliation(s)
- Sarah Houben
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Marie-Ange de Fisenne
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Kunie Ando
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Virginie Vanden Dries
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Luc Poncelet
- Laboratory of Anatomy, Biomechanics and Organogenesis, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Zehra Yilmaz
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Salwa Mansour
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Robert De Decker
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Jean-Pierre Brion
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Karelle Leroy
- Laboratory of Histology, Neuroanatomy and Neuropathology, Faculty of Medicine, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
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19
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Kuo CY, Lee PL, Hung SC, Liu LK, Lee WJ, Chung CP, Yang AC, Tsai SJ, Wang PN, Chen LK, Chou KH, Lin CP. Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker. Cereb Cortex 2020; 30:5844-5862. [PMID: 32572452 DOI: 10.1093/cercor/bhaa161] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/05/2020] [Accepted: 05/21/2020] [Indexed: 12/31/2022] Open
Abstract
The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing individual brain health and for identifying neurodegenerative and neuropsychiatric diseases. Using a large-scale structural covariance network (SCN)-based framework with machine learning algorithms, we demonstrate this framework's ability to predict individual brain age in a large sample of middle-to-late age adults, and highlight its clinical specificity for several disease populations from a network perspective. A proposed estimator with 40 SCNs could predict individual brain age, balancing between model complexity and prediction accuracy. Notably, we found that the most significant SCN for predicting brain age included the caudate nucleus, putamen, hippocampus, amygdala, and cerebellar regions. Furthermore, our data indicate a larger brain age disparity in patients with schizophrenia and Alzheimer's disease than in healthy controls, while this metric did not differ significantly in patients with major depressive disorder. These findings provide empirical evidence supporting the estimation of brain age from a brain network perspective, and demonstrate the clinical feasibility of evaluating neurological diseases hypothesized to be associated with accelerated brain aging.
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Affiliation(s)
- Chen-Yuan Kuo
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming University, Taipei 11221, Taiwan
| | - Pei-Lin Lee
- Institute of Neuroscience, National Yang Ming University, Taipei 11221, Taiwan
| | - Sheng-Che Hung
- Department of Radiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Li-Kuo Liu
- Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Wei-Ju Lee
- Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Department of Family Medicine, Yuanshan Branch, Taipei Veterans General Hospital, Yi-Lan 264, Taiwan
| | - Chih-Ping Chung
- Department of Neurology, School of Medicine, National Yang Ming University, Taipei 11221, Taiwan.,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Albert C Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, School of Medicine, National Yang Ming University, Taipei 11221, Taiwan.,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan.,Brain Research Center, National Yang Ming University, Taipei 11221, Taiwan
| | - Liang-Kung Chen
- Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Kun-Hsien Chou
- Institute of Neuroscience, National Yang Ming University, Taipei 11221, Taiwan.,Brain Research Center, National Yang Ming University, Taipei 11221, Taiwan
| | - Ching-Po Lin
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming University, Taipei 11221, Taiwan.,Institute of Neuroscience, National Yang Ming University, Taipei 11221, Taiwan.,Aging and Health Research Center, National Yang Ming University, Taipei 11221, Taiwan.,Brain Research Center, National Yang Ming University, Taipei 11221, Taiwan
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20
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Sonuç Karaboga MN, Sezgintürk MK. Analysis of Tau-441 protein in clinical samples using rGO/AuNP nanocomposite-supported disposable impedimetric neuro-biosensing platform: Towards Alzheimer's disease detection. Talanta 2020; 219:121257. [PMID: 32887148 DOI: 10.1016/j.talanta.2020.121257] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 05/29/2020] [Accepted: 05/31/2020] [Indexed: 12/18/2022]
Abstract
Changes in isoforms of Tau protein, which are critical for microtubule functioning, are accepted as being responsible for diseases characterized by dementia, in particular Alzheimer's disease (AD). In this comprehensive study, a single-use neuro-biosensing probe for the determination of Tau-441 protein was developed by utilizing the power of nanocomposites consisting of reduced graphene oxide (rGO) and gold nanoparticles (AuNP) using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The nanocomposite surface (rGO-AuNP) was modified with 11-mercaptoundecanoic acid (11-MUA) act as covalent anchorer to increase the sensitivity of the assay. Surface coverage value and pinhole ratio were calculated using EIS data. Kramers-kronig data, which helps to interpret instrumental errors, are also calculated. The immunoreaction of Tau-441 with anti-Tau was monitored simultaneously with Single Frequency Impedance (SFI). The changes in surface morphology were evaluated with scanning electron microscopy (SEM), atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR). The designed immunosensor showed a linear response within the concentration range of 1-500 pg/mL for the target analyte Tau-441 and the limit of detection was found to be 0.091 pg/mL. The promising point of the study is that this neuro-biosensor system can capture the Tau-441 target protein in both serum fluid and cerebrospinal fluid (CSF) samples with recoveries ranging from 96% to 108%.
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21
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From the prion-like propagation hypothesis to therapeutic strategies of anti-tau immunotherapy. Acta Neuropathol 2020; 139:3-25. [PMID: 31686182 PMCID: PMC6942016 DOI: 10.1007/s00401-019-02087-9] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 10/18/2019] [Accepted: 10/19/2019] [Indexed: 12/15/2022]
Abstract
The term “propagon” is used to define proteins that may transmit misfolding in vitro, in tissues or in organisms. Among propagons, misfolded tau is thought to be involved in the pathogenic mechanisms of various “tauopathies” that include Alzheimer's disease, progressive supranuclear palsy, and argyrophilic grain disease. Here, we review the available data in the literature and point out how the prion-like tau propagation has been extended from Alzheimer's disease to tauopathies. First, in Alzheimer’s disease, the progression of tau aggregation follows stereotypical anatomical stages which may be considered as spreading. The mechanisms of the propagation are now subject to intensive and controversial research. It has been shown that tau may be secreted in the interstitial fluid in an active manner as reflected by high and constant concentration of extracellular tau during Alzheimer’s pathology. Animal and cell models have been devised to mimic tau seeding and propagation, and despite their limitations, they have further supported to the prion-like propagation hypothesis. Finally, such new ways of thinking have led to different therapeutic strategies in anti-tau immunotherapy among tauopathies and have stimulated new clinical trials. However, it appears that the prion-like propagation hypothesis mainly relies on data obtained in Alzheimer’s disease. From this review, it appears that further studies are needed (1) to characterize extracellular tau species, (2) to find the right pathological tau species to target, (3) to follow in vivo tau pathology by brain imaging and biomarkers and (4) to interpret current clinical trial results aimed at reducing the progression of these pathologies. Such inputs will be essential to have a comprehensive view of these promising therapeutic strategies in tauopathies.
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22
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Lue LF, Pai MC, Chen TF, Hu CJ, Huang LK, Lin WC, Wu CC, Jeng JS, Blennow K, Sabbagh MN, Yan SH, Wang PN, Yang SY, Hatsuta H, Morimoto S, Takeda A, Itoh Y, Liu J, Xie H, Chiu MJ. Age-Dependent Relationship Between Plasma Aβ40 and Aβ42 and Total Tau Levels in Cognitively Normal Subjects. Front Aging Neurosci 2019; 11:222. [PMID: 31551751 PMCID: PMC6734161 DOI: 10.3389/fnagi.2019.00222] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 08/06/2019] [Indexed: 12/21/2022] Open
Abstract
Both amyloid plaques and neurofibrillary tangles are pathological hallmarks in the brains of patients with Alzheimer’s disease (AD). However, the constituents of these hallmarks, amyloid beta (Aβ) 40, Aβ42, and total Tau (t-Tau), have been detected in the blood of cognitively normal subjects by using an immunomagnetic reduction (IMR) assay. Whether these levels are age-dependent is not known, and their interrelation remains undefined. We determined the levels of these biomarkers in cognitively normal subjects of different age groups. A total of 391 cognitively normal subjects aged 23–91 were enrolled from hospitals in Asia, Europe, and North America. Healthy cognition was evaluated by NIA-AA guidelines to exclude subjects with mild cognitive impairment (MCI) and AD and by cognitive assessment using the Mini Mental State Examination and Clinical Dementia Rating (CDR). We examined the effect of age on plasma levels of Aβ40, Aβ42, and t-Tau and the relationship between these biomarkers during aging. Additionally, we explored age-related reference intervals for each biomarker. Plasma t-Tau and Aβ42 levels had modest but significant correlations with chronological age (r = 0.127, p = 0.0120 for t-Tau; r = −0.126, p = 0.0128 for Aβ42), ranging from ages 23 to 91. Significant positive correlations were detected between Aβ42 and t-Tau in the groups aged 50 years and older, with Rho values ranging from 0.249 to 0.474. Significant negative correlations were detected between Aβ40 and t-Tau from age 40 to 91 (r ranged from −0.293 to −0.582) and between Aβ40 and Aβ42 in the age groups of 30–39 (r = −0.562, p = 0.0235), 50–59 (r = −0.261, p = 0.0142), 60–69 (r = −0.303, p = 0.0004), and 80–91 (r = 0.459, p = 0.0083). We also provided age-related reference intervals for each biomarker. In this multicenter study, age had weak but significant effects on the levels of Aβ42 and t-Tau in plasma. However, the age group defined by decade revealed the emergence of a relationship between Aβ40, Aβ42, and t-Tau in the 6th and 7th decades. Validation of our findings in a large-scale and longitudinal study is warranted.
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Affiliation(s)
- Lih-Fen Lue
- Civin Neuropathology Laboratory, Banner Sun Health Research Institute, Sun City, AZ, United States
| | - Ming-Chyi Pai
- Division of Behavioral Neurology, Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ta-Fu Chen
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chaur-Jong Hu
- Department of Neurology, Taipei Medical University, Taipei, Taiwan.,Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Li-Kai Huang
- Department of Neurology, Taipei Medical University, Taipei, Taiwan.,Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Wei-Che Lin
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chau-Chung Wu
- Department of Internal Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Jian-Shing Jeng
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
| | - Marwan N Sabbagh
- Lou Ruvo Center for Brain Health, Cleveland Clinic Nevada, Las Vegas, NV, United States
| | - Sui-Hing Yan
- Department of Neurology, Renai Branch, Taipei City Hospital, Taipei, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, National Yang-Ming University, Taipei, Taiwan.,Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Shieh-Yueh Yang
- MagQu Company Limited, New Taipei City, Taiwan.,MagQu LLC, Surprise, AZ, United States
| | - Hiroyuki Hatsuta
- Hatsuta Neurology Clinic, Osaka, Japan.,Department of Neurology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Satoru Morimoto
- Hatsuta Neurology Clinic, Osaka, Japan.,Department of Physiology, School of Medicine, Keio University, Tokyo, Japan
| | - Akitoshi Takeda
- Department of Neurology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Yoshiaki Itoh
- Department of Neurology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Jun Liu
- Departemnt of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Haiqun Xie
- Department of Neurology, Foshan Hospital of Sun Yat-Sen University, Foshan, China
| | - Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
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23
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Tau-Reactive Endogenous Antibodies: Origin, Functionality, and Implications for the Pathophysiology of Alzheimer's Disease. J Immunol Res 2019; 2019:7406810. [PMID: 31687413 PMCID: PMC6811779 DOI: 10.1155/2019/7406810] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Revised: 03/19/2019] [Accepted: 07/23/2019] [Indexed: 12/11/2022] Open
Abstract
In Alzheimer's disease (AD), tau pathology manifested by the accumulation of intraneuronal tangles and soluble toxic oligomers emerges as a promising therapeutic target. Multiple anti-tau antibodies inhibiting the formation and propagation of cytotoxic tau or promoting its clearance and degradation have been tested in clinical trials, albeit with the inconclusive outcome. Antibodies against tau protein have been documented both in the brain circulatory system and at the periphery, but their origin and role under normal conditions and in AD remain unclear. While it is tempting to assign them a protective role in regulating tau level and removal of toxic variants, the supportive evidence remains sporadic, requiring systematic analysis and critical evaluation. Herein, we review recent data showing the occurrence of tau-reactive antibodies in the brain and peripheral circulation and discuss their origin and significance in tau clearance. Based on the emerging evidence, we cautiously propose that impairments of tau clearance at the periphery by humoral immunity might aggravate the tau pathology in the central nervous system, with implication for the neurodegenerative process of AD.
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24
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Lin CH, Yang SY, Horng HE, Yang CC, Chieh JJ, Chen HH, Liu BH, Chiu MJ. Plasma Biomarkers Differentiate Parkinson's Disease From Atypical Parkinsonism Syndromes. Front Aging Neurosci 2018; 10:123. [PMID: 29755341 PMCID: PMC5934438 DOI: 10.3389/fnagi.2018.00123] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 04/11/2018] [Indexed: 12/13/2022] Open
Abstract
Objective: Parkinson’s disease (PD) has significant clinical overlaps with atypical parkinsonism syndromes (APS), which have a poorer treatment response and a more aggressive course than PD. We aimed to identify plasma biomarkers to differentiate PD from APS. Methods: Plasma samples (n = 204) were obtained from healthy controls and from patients with PD, dementia with Lewy bodies (DLB), multiple system atrophy, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), or frontotemporal dementia (FTD) with parkinsonism (FTD-P) or without parkinsonism. We measured plasma levels of α-synuclein, total tau, p-Tau181, and amyloid beta 42 (Aβ42) by immunomagnetic reduction-based immunoassay. Results: Plasma α-synuclein level was significantly increased in patients with PD and APS when compared with controls and FTD without parkinsonism (p < 0.01). Total tau and p-Tau181 were significantly increased in all disease groups compared to controls, especially in patients with FTD (p < 0.01). A multivariate and receiver operating characteristic curve analysis revealed that a cut-off value for Aβ42 multiplied by p-Tau181 for discriminating patients with FTD from patients with PD and APS was 92.66 (pg/ml)2, with an area under the curve (AUC) of 0.932. An α-synuclein cut-off of 0.1977 pg/ml could separate FTD-P from FTD without parkinsonism (AUC 0.947). In patients with predominant parkinsonism, an α-synuclein cut-off of 1.388 pg/ml differentiated patients with PD from those with APS (AUC 0.87). Conclusion: Our results suggest that integrated plasma biomarkers improve the differential diagnosis of PD from APS (PSP, CBD, DLB, and FTD-P).
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Affiliation(s)
- Chin-Hsien Lin
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | | | - Herng-Er Horng
- Graduate Institute of Electro-Optical Science and Technology, College of Science, National Taiwan Normal University, Taipei, Taiwan
| | | | - Jen-Jie Chieh
- Graduate Institute of Electro-Optical Science and Technology, College of Science, National Taiwan Normal University, Taipei, Taiwan
| | | | | | - Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Biomedical Engineering, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Psychology, National Taiwan University, Taipei, Taiwan
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