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van Amerongen S, Das S, Kamps S, Goossens J, Bongers B, Pijnenburg YAL, Vanmechelen E, Vijverberg EGB, Teunissen CE, Verberk IMW. Cerebrospinal fluid biomarkers and cognitive trajectories in patients with Alzheimer's disease and a history of traumatic brain injury. Neurobiol Aging 2024; 141:121-128. [PMID: 38908030 DOI: 10.1016/j.neurobiolaging.2024.06.001] [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: 02/28/2024] [Revised: 06/07/2024] [Accepted: 06/13/2024] [Indexed: 06/24/2024]
Abstract
Traumatic brain injury (TBI) and Alzheimer's disease (AD) have overlapping mechanisms but it remains unknown if pathophysiological characteristics and cognitive trajectories in AD patients are influenced by TBI history. Here, we studied AD patients (stage MCI or dementia) with TBI history (ADTBI+, n=110), or without (ADTBI-, n=110) and compared baseline CSF concentrations of amyloid beta 1-42 (Aβ42), phosphorylated tau181 (pTau181), total tau, neurofilament light chain (NfL), synaptosomal associated protein-25kDa (SNAP25), neurogranin (Ng), neuronal pentraxin-2 (NPTX2) and glutamate receptor-4 (GluR4), as well as differences in cognitive trajectories using linear mixed models. Explorative, analyses were repeated within stratified TBI groups by TBI characteristics (timing, severity, number). We found no differences in baseline CSF biomarker concentrations nor in cognitive trajectories between ADTBI+ and ADTBI- patients. TBI >5 years ago was associated with higher NPTX2 and a tendency for higher SNAP25 concentrations compared to TBI ≤ 5 years ago, suggesting that TBI may be associated with long-term synaptic dysfunction only when occurring before onset or in a pre-clinical disease stage of AD.
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Affiliation(s)
- Suzan van Amerongen
- Amsterdam Neuroscience, Neurodegeneration, De Boelelaan 1085, Amsterdam 1081 HV, the Netherlands; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, Amsterdam 1081 HV, the Netherlands.
| | - Shreyasee Das
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Boelelaan 1117, Amsterdam 1081 HV, the Netherlands; ADx NeuroSciences, Technologiepark-Zwijnaarde 6, Gent 9052, Belgium
| | - Suzie Kamps
- Amsterdam Neuroscience, Neurodegeneration, De Boelelaan 1085, Amsterdam 1081 HV, the Netherlands; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, Amsterdam 1081 HV, the Netherlands
| | - Julie Goossens
- ADx NeuroSciences, Technologiepark-Zwijnaarde 6, Gent 9052, Belgium
| | - Bram Bongers
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Boelelaan 1117, Amsterdam 1081 HV, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam Neuroscience, Neurodegeneration, De Boelelaan 1085, Amsterdam 1081 HV, the Netherlands; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, Amsterdam 1081 HV, the Netherlands
| | | | - Everard G B Vijverberg
- Amsterdam Neuroscience, Neurodegeneration, De Boelelaan 1085, Amsterdam 1081 HV, the Netherlands; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, Amsterdam 1081 HV, the Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, De Boelelaan 1085, Amsterdam 1081 HV, the Netherlands; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, Amsterdam 1081 HV, the Netherlands; Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Boelelaan 1117, Amsterdam 1081 HV, the Netherlands
| | - Inge M W Verberk
- Amsterdam Neuroscience, Neurodegeneration, De Boelelaan 1085, Amsterdam 1081 HV, the Netherlands; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, Amsterdam 1081 HV, the Netherlands; Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Boelelaan 1117, Amsterdam 1081 HV, the Netherlands
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2
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Wagemann O, Liu H, Wang G, Shi X, Bittner T, Scelsi MA, Farlow MR, Clifford DB, Supnet-Bell C, Santacruz AM, Aschenbrenner AJ, Hassenstab JJ, Benzinger TLS, Gordon BA, Coalier KA, Cruchaga C, Ibanez L, Perrin RJ, Xiong C, Li Y, Morris JC, Lah JJ, Berman SB, Roberson ED, van Dyck CH, Galasko D, Gauthier S, Hsiung GYR, Brooks WS, Pariente J, Mummery CJ, Day GS, Ringman JM, Mendez PC, St. George-Hyslop P, Fox NC, Suzuki K, Okhravi HR, Chhatwal J, Levin J, Jucker M, Sims JR, Holdridge KC, Proctor NK, Yaari R, Andersen SW, Mancini M, Llibre-Guerra J, Bateman RJ, McDade E. Downstream Biomarker Effects of Gantenerumab or Solanezumab in Dominantly Inherited Alzheimer Disease: The DIAN-TU-001 Randomized Clinical Trial. JAMA Neurol 2024; 81:582-593. [PMID: 38683602 PMCID: PMC11059071 DOI: 10.1001/jamaneurol.2024.0991] [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: 10/18/2023] [Accepted: 02/01/2024] [Indexed: 05/01/2024]
Abstract
Importance Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD). Objective To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment. Design, Setting, and Participants From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed. Interventions In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks. Main Outcomes and Measures Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL. Results Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] β = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] β = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] β = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] β = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] β = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] β = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] β = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo. Conclusions and Relevance This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification. Trial Registration ClinicalTrials.gov Identifier: NCT04623242.
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Affiliation(s)
- Olivia Wagemann
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Haiyan Liu
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | - Xinyu Shi
- Department of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | | | - Marzia A. Scelsi
- F. Hoffmann-La Roche Products Ltd, Welwyn Garden City, United Kingdom
| | - Martin R. Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis
| | - David B. Clifford
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Charlene Supnet-Bell
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Anna M. Santacruz
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | | | - Jason J. Hassenstab
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | | | - Brian A. Gordon
- Department of Radiology, Washington University in St Louis, St Louis, Missouri
| | | | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Laura Ibanez
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Richard J. Perrin
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, Missouri
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - James J. Lah
- Department of Neurology, School of Medicine Emory University, Atlanta, Georgia
| | - Sarah B. Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Erik D. Roberson
- Department of Neurology, University of Alabama at Birmingham, Birmingham
| | | | - Douglas Galasko
- Department of Neurology, University of California, San Diego
| | - Serge Gauthier
- Department of Neurology & Psychiatry, McGill University, Montréal, Québec, Canada
| | - Ging-Yuek R. Hsiung
- Department of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - William S. Brooks
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Clinical Medicine, University of New South Wales, Randwick, New South Wales, Australia
| | - Jérémie Pariente
- Department of Neurology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Catherine J. Mummery
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville
| | - John M. Ringman
- Department of Neurology, University of Southern California, Los Angeles
| | - Patricio Chrem Mendez
- Fundación Para la Lucha Contra las Enfermedades Neurológicas de la Infancia (FLENI), Buenos Aires, Argentina
| | | | - Nick C. Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | | | - Hamid R. Okhravi
- Department of Geriatrics, Eastern Virginia Medical School, Norfolk
| | - Jasmeer Chhatwal
- Department of Neurology, Massachusetts General and Brigham & Women’s Hospitals, Harvard Medical School, Boston
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | | | | | | | - Roy Yaari
- Eli Lilly and Company, Indianapolis, Indiana
| | | | | | - Jorge Llibre-Guerra
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
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Mohammadi H, Ariaei A, Ghobadi Z, Gorgich EAC, Rustamzadeh A. Which neuroimaging and fluid biomarkers method is better in theranostic of Alzheimer's disease? An umbrella review. IBRO Neurosci Rep 2024; 16:403-417. [PMID: 38497046 PMCID: PMC10940808 DOI: 10.1016/j.ibneur.2024.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/24/2024] [Indexed: 03/19/2024] Open
Abstract
Biomarkers are measured to evaluate physiological and pathological processes as well as responses to a therapeutic intervention. Biomarkers can be classified as diagnostic, prognostic, predictor, clinical, and therapeutic. In Alzheimer's disease (AD), multiple biomarkers have been reported so far. Nevertheless, finding a specific biomarker in AD remains a major challenge. Three databases, including PubMed, Web of Science, and Scopus were selected with the keywords of Alzheimer's disease, neuroimaging, biomarker, and blood. The results were finalized with 49 potential CSF/blood and 35 neuroimaging biomarkers. To distinguish normal from AD patients, amyloid-beta42 (Aβ42), plasma glial fibrillary acidic protein (GFAP), and neurofilament light (NFL) as potential biomarkers in cerebrospinal fluid (CSF) as well as the serum could be detected. Nevertheless, most of the biomarkers fairly change in the CSF during AD, listed as kallikrein 6, virus-like particles (VLP-1), galectin-3 (Gal-3), and synaptotagmin-1 (Syt-1). From the neuroimaging aspect, atrophy is an accepted biomarker for the neuropathologic progression of AD. In addition, Magnetic resonance spectroscopy (MRS), diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), tractography (DTT), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI), can be used to detect AD. Using neuroimaging and CSF/blood biomarkers, in combination with artificial intelligence, it is possible to obtain information on prognosis and follow-up on the different stages of AD. Hence physicians could select the suitable therapy to attenuate disease symptoms and follow up on the efficiency of the prescribed drug.
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Affiliation(s)
- Hossein Mohammadi
- Department of Bioimaging, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences (MUI), Isfahan, Islamic Republic of Iran
| | - Armin Ariaei
- Student Research Committee, School of Medicine, Iran University of Medical Sciences, Tehran, Islamic Republic of Iran
| | - Zahra Ghobadi
- Advanced Medical Imaging Ward, Pars Darman Medical Imaging Center, Karaj, Islamic Republic of Iran
| | - Enam Alhagh Charkhat Gorgich
- Department of Anatomy, School of Medicine, Iranshahr University of Medical Sciences, Iranshahr, Islamic Republic of Iran
| | - Auob Rustamzadeh
- Cellular and Molecular Research Center, Research Institute for Non-communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran
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Gouilly D, Vrillon A, Bertrand E, Goubeaud M, Catala H, Germain J, Ainaoui N, Rafiq M, Nogueira L, Mouton-Liger F, Planton M, Salabert AS, Hitzel A, Méligne D, Jasse L, Sarton B, Silva S, Lemesle B, Péran P, Payoux P, Thalamas C, Paquet C, Pariente J. Translocator protein (TSPO) genotype does not change cerebrospinal fluid levels of glial activation, axonal and synaptic damage markers in early Alzheimer's disease. Neuroimage Clin 2024; 43:103626. [PMID: 38850834 PMCID: PMC11201347 DOI: 10.1016/j.nicl.2024.103626] [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: 02/29/2024] [Revised: 05/10/2024] [Accepted: 05/29/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND PET imaging of the translocator protein (TSPO) is used to assess in vivo brain inflammation. One of the main methodological issues with this method is the allelic dependence of the radiotracer affinity. In Alzheimer's disease (AD), previous studies have shown similar clinical and patho-biological profiles between TSPO genetic subgroups. However, there is no evidence regarding the effect of the TSPO genotype on cerebrospinal-fluid biomarkers of glial activation, and synaptic and axonal damage. METHOD We performed a trans-sectional study in early AD to compare cerebrospinal-fluid levels of GFAP, YKL-40, sTREM2, IL-6, IL-10, NfL and neurogranin between TSPO genetic subgroups. RESULTS We recruited 33 patients with early AD including 16 (48%) high affinity binders, 13 (39%) mixed affinity binders, and 4/33 (12%) low affinity binders. No difference was observed in terms of demographics, and cerebrospinal fluid levels of each biomarker for the different subgroups. CONCLUSION TSPO genotype is not associated with a change in glial activation, synaptic and axonal damage in early AD. Further studies with larger numbers of participants will be needed to confirm that the inclusion of specific TSPO genetic subgroups does not introduce selection bias in studies and trials of AD that combine TSPO imaging with cerebrospinal fluid biomarkers.
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Affiliation(s)
- Dominique Gouilly
- Department of Cognitive Neurology, Epilepsy, Sleep and Movement Disorders, CHU Toulouse Purpan, Toulouse, France.
| | - Agathe Vrillon
- Université de Paris, Cognitive Neurology Center, GHU Nord, APHP, Hospital Lariboisière Fernand Widal, Paris, France; Université de Paris, Inserm UMRS11-44 Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Elsa Bertrand
- Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France
| | - Marie Goubeaud
- Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France
| | - Hélène Catala
- Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France
| | - Johanne Germain
- Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France
| | - Nadéra Ainaoui
- Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France
| | - Marie Rafiq
- Department of Cognitive Neurology, Epilepsy, Sleep and Movement Disorders, CHU Toulouse Purpan, Toulouse, France; Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France
| | - Leonor Nogueira
- Laboratory of Cell Biology and Cytology, CHU Toulouse Purpan, Toulouse, France
| | - François Mouton-Liger
- Université de Paris, Inserm UMRS11-44 Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Mélanie Planton
- Department of Cognitive Neurology, Epilepsy, Sleep and Movement Disorders, CHU Toulouse Purpan, Toulouse, France; Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France
| | - Anne-Sophie Salabert
- Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, Toulouse, France
| | - Anne Hitzel
- Department of Nuclear Medicine, CHU Toulouse Purpan, Toulouse, France
| | - Déborah Méligne
- Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France
| | - Laurence Jasse
- Department of Cognitive Neurology, Epilepsy, Sleep and Movement Disorders, CHU Toulouse Purpan, Toulouse, France
| | - Benjamine Sarton
- Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France; Critical Care Unit, CHU Toulouse Purpan, Toulouse, France
| | - Stein Silva
- Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France; Critical Care Unit, CHU Toulouse Purpan, Toulouse, France
| | - Béatrice Lemesle
- Department of Cognitive Neurology, Epilepsy, Sleep and Movement Disorders, CHU Toulouse Purpan, Toulouse, France
| | - Patrice Péran
- Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France
| | - Pierre Payoux
- Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, Toulouse, France
| | - Claire Thalamas
- Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France
| | - Claire Paquet
- Université de Paris, Cognitive Neurology Center, GHU Nord, APHP, Hospital Lariboisière Fernand Widal, Paris, France; Université de Paris, Inserm UMRS11-44 Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Jérémie Pariente
- Department of Cognitive Neurology, Epilepsy, Sleep and Movement Disorders, CHU Toulouse Purpan, Toulouse, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC 1436), Toulouse, France; Toulouse Neuroimaging Center, UMR 1214, Inserm/UPS, Toulouse, France
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5
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Knudtzon SL, Nordengen K, Grøntvedt GR, Jarholm J, Eliassen IV, Selnes P, Pålhaugen L, Espenes J, Gísladóttir B, Waterloo K, Fladby T, Kirsebom BE. Age-adjusted CSF t-tau and NfL do not improve diagnostic accuracy for prodromal Alzheimer's disease. Neurobiol Aging 2024; 141:74-84. [PMID: 38838442 DOI: 10.1016/j.neurobiolaging.2024.05.016] [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: 12/20/2023] [Revised: 05/01/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
Cerebrospinal fluid total-tau (t-tau) and neurofilament light chain (NfL) are biomarkers of neurodegeneration and are increased in Alzheimer's disease (AD). In order to adjust for age-related increases in t-tau and NfL, cross-sectional age-adjusted norms were developed based on amyloid negative cognitively normal (CN) adults aged 41-78 years (CN, n = 137). The age-adjusted norms for t-tau and NfL did not improve receiver operating curve based diagnostic accuracies in individuals with mild cognitive impairment (MCI) due to AD (AD-MCI, n = 144). Furthermore, while NfL was correlated with higher age in AD-MCI, no significant correlation was found for t-tau. The cox proportional hazard models, applied in 429 participants with baseline t-tau and NfL, showed higher hazard ratio of progression to MCI or dementia without age-adjustments (HR = 3.39 for t-tau and HR = 3.17 for NfL), as compared to using our norms (HR = 2.29 for t-tau and HR = 1.89 for NfL). Our results indicate that utilizing normative reference data could obscure significant age-related increases in these markers associated with neurodegeneration and AD leading to a potential loss of overall diagnostic accuracy.
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Affiliation(s)
- Stephanie Lindgård Knudtzon
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway; Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.
| | - Kaja Nordengen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gøril Rolfseng Grøntvedt
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Jonas Jarholm
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingvild Vøllo Eliassen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Lene Pålhaugen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jacob Espenes
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway; Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Berglind Gísladóttir
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Clinical Molecular Biology (EpiGen), Medical Division, Akershus University Hospital and University of Oslo, Oslo, Norway
| | - Knut Waterloo
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway; Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Bjørn-Eivind Kirsebom
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway; Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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6
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Zeng X, Chen Y, Sehrawat A, Lee J, Lafferty TK, Kofler J, Berman SB, Sweet RA, Tudorascu DL, Klunk WE, Ikonomovic MD, Pfister A, Zetterberg H, Snitz BE, Cohen AD, Villemagne VL, Pascoal TA, Kamboh ML, Lopez OI, Blennow K, Karikari TK. Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting. Mol Neurodegener 2024; 19:40. [PMID: 38750570 PMCID: PMC11095038 DOI: 10.1186/s13024-024-00711-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 02/13/2024] [Indexed: 05/19/2024] Open
Abstract
Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.
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Affiliation(s)
- Xuemei Zeng
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Yijun Chen
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Anuradha Sehrawat
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Jihui Lee
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Tara K Lafferty
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Julia Kofler
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Sarah B Berman
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Robert A Sweet
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dana L Tudorascu
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - William E Klunk
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Milos D Ikonomovic
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | - Anna Pfister
- 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
| | - 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 Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Anne D Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Victor L Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - M Llyas Kamboh
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Oscar I Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, 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
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.
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7
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Wang S, Xie S, Zheng Q, Zhang Z, Wang T, Zhang G. Biofluid biomarkers for Alzheimer's disease. Front Aging Neurosci 2024; 16:1380237. [PMID: 38659704 PMCID: PMC11039951 DOI: 10.3389/fnagi.2024.1380237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 03/27/2024] [Indexed: 04/26/2024] Open
Abstract
Alzheimer's disease (AD) is a multifactorial neurodegenerative disease, with a complex pathogenesis and an irreversible course. Therefore, the early diagnosis of AD is particularly important for the intervention, prevention, and treatment of the disease. Based on the different pathophysiological mechanisms of AD, the research progress of biofluid biomarkers are classified and reviewed. In the end, the challenges and perspectives of future research are proposed.
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Affiliation(s)
- Sensen Wang
- Shandong Yinfeng Academy of Life Science, Jinan, Shandong, China
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, Shandong, China
| | - Sitan Xie
- Shandong Yinfeng Academy of Life Science, Jinan, Shandong, China
| | - Qinpin Zheng
- Shandong Yinfeng Academy of Life Science, Jinan, Shandong, China
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, Shandong, China
| | - Zhihui Zhang
- Shandong Yinfeng Academy of Life Science, Jinan, Shandong, China
| | - Tian Wang
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, Shandong, China
| | - Guirong Zhang
- Shandong Yinfeng Academy of Life Science, Jinan, Shandong, China
- School of Pharmacy, Key Laboratory of Molecular Pharmacology and Drug Evaluation, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, Shandong, China
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8
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Gonzalez-Ortiz F, Kirsebom BE, Contador J, Tanley JE, Selnes P, Gísladóttir B, Pålhaugen L, Suhr Hemminghyth M, Jarholm J, Skogseth R, Bråthen G, Grøndtvedt G, Bjørnerud A, Tecelao S, Waterloo K, Aarsland D, Fernández-Lebrero A, García-Escobar G, Navalpotro-Gómez I, Turton M, Hesthamar A, Kac PR, Nilsson J, Luchsinger J, Hayden KM, Harrison P, Puig-Pijoan A, Zetterberg H, Hughes TM, Suárez-Calvet M, Karikari TK, Fladby T, Blennow K. Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease. Nat Commun 2024; 15:2908. [PMID: 38575616 PMCID: PMC10995141 DOI: 10.1038/s41467-024-47286-5] [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: 08/09/2023] [Accepted: 03/26/2024] [Indexed: 04/06/2024] Open
Abstract
Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.
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Affiliation(s)
- Fernando Gonzalez-Ortiz
- 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.
| | - Bjørn-Eivind Kirsebom
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway
- Department of Psychology, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - José Contador
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
| | - Jordan E Tanley
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | | | - Lene Pålhaugen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Mathilde Suhr Hemminghyth
- Research Group for Age-Related Medicine, Haugesund Hospital, Haugesund, Norway
- Department of Neuropsychology, Haugesund Hospital, Haugesund, Norway
- Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway
| | - Jonas Jarholm
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Ragnhild Skogseth
- Department of Geriatric Medicine, Haraldsplass Deaconess Hospital, Bergen, Norway
- Department of Clinical Sciences, Faculty of Medicine, University of Bergen, Bergen, Norway
| | - Geir Bråthen
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Gøril Grøndtvedt
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Atle Bjørnerud
- Department of Physics, University of Oslo, Oslo, Norway
- Unit for Computational Radiology and Artificial Intelligence, Oslo University hospital, Oslo, Norway
- Department of Psychology, Faculty for Social Sciences, University of Oslo, Oslo, Norway
| | - Sandra Tecelao
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Knut Waterloo
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway
- Department of Psychology, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
| | - Dag Aarsland
- Department of Old Age Psychiatry. Institute of psychiatry, Psychology and Neuroscience King's College London, London, UK
- Centre for Age-Related Diseases, University Hospital Stavanger, Stavanger, Norway
| | - Aida Fernández-Lebrero
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, 08003, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
| | - Greta García-Escobar
- Hospital del Mar Research Institute, Barcelona, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
| | - Irene Navalpotro-Gómez
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
| | - Michael Turton
- Bioventix Plc, 7 Romans Business Park, East Street, Farnham, Surrey, GU9 7SX, UK
| | - Agnes Hesthamar
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Przemyslaw R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Johanna Nilsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Jose Luchsinger
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Kathleen M Hayden
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Peter Harrison
- Bioventix Plc, 7 Romans Business Park, East Street, Farnham, Surrey, GU9 7SX, UK
| | - Albert Puig-Pijoan
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
- Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - 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
| | - Timothy M Hughes
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tormod Fladby
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - 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
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9
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Jagadeesan N, Roules GC, Chandrashekar DV, Yang J, Kolluru S, Sumbria RK. Modulation of hippocampal protein expression by a brain penetrant biologic TNF-α inhibitor in the 3xTg Alzheimer's disease mice. J Transl Med 2024; 22:291. [PMID: 38500108 PMCID: PMC10946165 DOI: 10.1186/s12967-024-05008-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: 09/29/2023] [Accepted: 02/19/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Biologic TNF-α inhibitors (bTNFIs) can block cerebral TNF-α in Alzheimer's disease (AD) if these macromolecules can cross the blood-brain barrier (BBB). Thus, a model bTNFI, the extracellular domain of type II TNF-α receptor (TNFR), which can bind to and sequester TNF-α, was fused with a mouse transferrin receptor antibody (TfRMAb) to enable brain delivery via BBB TfR-mediated transcytosis. Previously, we found TfRMAb-TNFR to be protective in a mouse model of amyloidosis (APP/PS1) and tauopathy (PS19), and herein we investigated its effects in mice that combine both amyloidosis and tauopathy (3xTg-AD). METHODS Eight-month-old female 3xTg-AD mice were injected intraperitoneally with saline (n = 11) or TfRMAb-TNFR (3 mg/kg; n = 11) three days per week for 12 weeks. Age-matched wild-type (WT) mice (n = 9) were treated similarly with saline. Brains were processed for immunostaining and high-resolution multiplex NanoString GeoMx spatial proteomics. RESULTS We observed regional differences in proteins relevant to Aβ, tau, and neuroinflammation in the hippocampus of 3xTg-AD mice compared with WT mice. From 64 target proteins studied using spatial proteomics, a comparison of the Aβ-plaque bearing vs. plaque-free regions in the 3xTg-AD mice yielded 39 differentially expressed proteins (DEP) largely related to neuroinflammation (39% of DEP) and Aβ and tau pathology combined (31% of DEP). Hippocampal spatial proteomics revealed that the majority of the proteins modulated by TfRMAb-TNFR in the 3xTg-AD mice were relevant to microglial function (⁓ 33%). TfRMAb-TNFR significantly reduced mature Aβ plaques and increased Aβ-associated microglia around larger Aβ deposits in the 3xTg-AD mice. Further, TfRMAb-TNFR increased mature Aβ plaque-associated microglial TREM2 in 3xTg-AD mice. CONCLUSION Overall, despite the low visual Aβ load in the 11-month-old female 3xTg-AD mice, our results highlight region-specific AD-relevant DEP in the hippocampus of these mice. Chronic TfRMAb-TNFR dosing modulated several DEP involved in AD pathology and showed a largely microglia-centric mechanism of action in the 3xTg-AD mice.
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Affiliation(s)
- Nataraj Jagadeesan
- Department of Biomedical and Pharmaceutical Sciences, School of Pharmacy, Chapman University, Irvine, CA, 92618, USA
| | - G Chuli Roules
- Department of Biomedical and Pharmaceutical Sciences, School of Pharmacy, Chapman University, Irvine, CA, 92618, USA
| | - Devaraj V Chandrashekar
- Department of Biomedical and Pharmaceutical Sciences, School of Pharmacy, Chapman University, Irvine, CA, 92618, USA
| | - Joshua Yang
- Department of Biomedical and Pharmaceutical Sciences, School of Pharmacy, Chapman University, Irvine, CA, 92618, USA
| | - Sanjana Kolluru
- Rancho Cucamonga High School, 11801 Lark Dr, Rancho Cucamonga, CA, 91701, USA
| | - Rachita K Sumbria
- Department of Biomedical and Pharmaceutical Sciences, School of Pharmacy, Chapman University, Irvine, CA, 92618, USA.
- Department of Neurology, University of California, Irvine, CA, 92697, USA.
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10
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Meeker KL, Luckett PH, Barthélemy NR, Hobbs DA, Chen C, Bollinger J, Ovod V, Flores S, Keefe S, Henson RL, Herries EM, McDade E, Hassenstab JJ, Xiong C, Cruchaga C, Benzinger TLS, Holtzman DM, Schindler SE, Bateman RJ, Morris JC, Gordon BA, Ances BM. Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease. Brain Commun 2024; 6:fcae081. [PMID: 38505230 PMCID: PMC10950051 DOI: 10.1093/braincomms/fcae081] [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: 10/05/2023] [Revised: 02/01/2024] [Accepted: 03/14/2024] [Indexed: 03/21/2024] Open
Abstract
Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.
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Affiliation(s)
- Karin L Meeker
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Patrick H Luckett
- Department of Neurosurgery, Washington University in St Louis, St Louis, MO 63110, USA
| | - Nicolas R Barthélemy
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Diana A Hobbs
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Charles Chen
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - James Bollinger
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Vitaliy Ovod
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Shaney Flores
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Sarah Keefe
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Rachel L Henson
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Elizabeth M Herries
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Eric McDade
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Jason J Hassenstab
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Carlos Cruchaga
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - David M Holtzman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
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11
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Hemminghyth MS, Chwiszczuk LJ, Breitve MH, Gísladóttir B, Grøntvedt GR, Nakling A, Rongve A, Fladby T, Kirsebom BE. Cerebrospinal fluid neurofilament light chain mediates age-associated lower learning and memory in healthy adults. Neurobiol Aging 2024; 135:39-47. [PMID: 38159464 DOI: 10.1016/j.neurobiolaging.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 12/15/2023] [Accepted: 12/21/2023] [Indexed: 01/03/2024]
Abstract
Multiple cognitive domains, including learning, memory, and psychomotor speed, show significant reductions with age. Likewise, several cerebrospinal fluid (CSF) neurodegenerative biomarkers, including total tau (t-tau, a marker of neuronal body injury) and neurofilament light chain (NfL, a marker of axonal injury) show age-related increases in normal aging. In the current study, we aimed to investigate whether the age-effect within different cognitive domains was mediated by age-associated CSF markers for neurodegenerative changes. We fitted 10 mediation models using structural equation modeling to investigate this in a cohort of 137 healthy adults, aged 40-80 years, from the Norwegian Dementia Disease Initiation (DDI) study. Here, t-tau and NfL were defined as mediators between age and different cognitive tests. The models showed that NfL mediated the age-effect for CERAD learning and memory recall (learning: β = -0.395, p < 0.05; recall: β = -0.261, p < 0.01). No such effect was found in the other models. Our findings suggest that the age-related lower performance in verbal learning and memory may be linked to NfL-associated neurodegenerative changes in cognitively healthy adults.
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Affiliation(s)
- Mathilde Suhr Hemminghyth
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Neuropsychology, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway.
| | - Luiza Jadwiga Chwiszczuk
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Age-related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Monica Haraldseid Breitve
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Neuropsychology, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Age-related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Berglind Gísladóttir
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Clinical Molecular Biology (EpiGen), Medical Division, Akershus University Hospital and University of Oslo, Norway
| | - Gøril Rolfseng Grøntvedt
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Arne Nakling
- Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway
| | - Arvid Rongve
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway; Department of Age-related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Bjørn-Eivind Kirsebom
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway; Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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12
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Guise AJ, Misal SA, Carson R, Chu JH, Boekweg H, Van Der Watt D, Welsh NC, Truong T, Liang Y, Xu S, Benedetto G, Gagnon J, Payne SH, Plowey ED, Kelly RT. TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis. Cell Rep 2024; 43:113636. [PMID: 38183652 PMCID: PMC10926001 DOI: 10.1016/j.celrep.2023.113636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 11/02/2023] [Accepted: 12/14/2023] [Indexed: 01/08/2024] Open
Abstract
A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.
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Affiliation(s)
| | - Santosh A Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | - Richard Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | | | - Hannah Boekweg
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | | | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | | | | | | | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA.
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13
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Jung Y, Damoiseaux JS. The potential of blood neurofilament light as a marker of neurodegeneration for Alzheimer's disease. Brain 2024; 147:12-25. [PMID: 37540027 DOI: 10.1093/brain/awad267] [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: 03/01/2023] [Revised: 07/22/2023] [Accepted: 07/28/2023] [Indexed: 08/05/2023] Open
Abstract
Over the past several years, there has been a surge in blood biomarker studies examining the value of plasma or serum neurofilament light (NfL) as a biomarker of neurodegeneration for Alzheimer's disease. However, there have been limited efforts to combine existing findings to assess the utility of blood NfL as a biomarker of neurodegeneration for Alzheimer's disease. In addition, we still need better insight into the specific aspects of neurodegeneration that are reflected by the elevated plasma or serum concentration of NfL. In this review, we survey the literature on the cross-sectional and longitudinal relationships between blood-based NfL levels and other, neuroimaging-based, indices of neurodegeneration in individuals on the Alzheimer's continuum. Then, based on the biomarker classification established by the FDA-NIH Biomarker Working group, we determine the utility of blood-based NfL as a marker for monitoring the disease status (i.e. monitoring biomarker) and predicting the severity of neurodegeneration in older adults with and without cognitive decline (i.e. a prognostic or a risk/susceptibility biomarker). The current findings suggest that blood NfL exhibits great promise as a monitoring biomarker because an increased NfL level in plasma or serum appears to reflect the current severity of atrophy, hypometabolism and the decline of white matter integrity, particularly in the brain regions typically affected by Alzheimer's disease. Longitudinal evidence indicates that blood NfL can be useful not only as a prognostic biomarker for predicting the progression of neurodegeneration in patients with Alzheimer's disease but also as a susceptibility/risk biomarker predicting the likelihood of abnormal alterations in brain structure and function in cognitively unimpaired individuals with a higher risk of developing Alzheimer's disease (e.g. those with a higher amyloid-β). There are still limitations to current research, as discussed in this review. Nevertheless, the extant literature strongly suggests that blood NfL can serve as a valuable prognostic and susceptibility biomarker for Alzheimer's disease-related neurodegeneration in clinical settings, as well as in research settings.
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Affiliation(s)
- Youjin Jung
- Department of Psychology, Wayne State University, Detroit, MI 48202, USA
- Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Jessica S Damoiseaux
- Department of Psychology, Wayne State University, Detroit, MI 48202, USA
- Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
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14
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Trieu C, van Harten AC, Leeuwis AE, Exalto LG, Hooghiemstra AM, Verberk IMW, Allaart CP, Brunner-La Rocca HP, Kappelle LJ, van Oostenbrugge RJ, Biessels GJ, Teunissen CE, van der Flier WM. Alzheimer's Disease and Cognitive Decline in Patients with Cardiovascular Diseases Along the Heart-Brain Axis. J Alzheimers Dis 2024; 98:987-1000. [PMID: 38489178 DOI: 10.3233/jad-231096] [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: 03/17/2024]
Abstract
Background We hypothesize that Alzheimer's disease (AD)-related pathology may accelerate cognitive decline in patients with cardiovascular diseases. Objective To investigate the association between blood-based biomarkers of AD, astrocyte activation, and neurodegeneration and cognitive decline. Methods From the multi-center Heart-Brain study, we included 412 patients with heart failure, carotid occlusive disease or vascular cognitive impairment (age:68.6±9.0) and 128 reference participants (65.7±7.5). Baseline amyloid-β42/40 (Aβ42/40), phosphorylated-tau181 (pTau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) were determined using SiMoA (Quanterix). Memory, attention, language, and executive functioning were evaluated (follow-up:2.1±0.3 years). We applied linear mixed models with terms for biomarker, time and biomarker*time interactions, adjusted for age, sex, education, and site, to assess associations between biomarkers and cognitive decline. Results Among patients, Aβ42/40 was not associated with cognitive performance at baseline. However, lower Aβ42/40 was associated with steeper decline in global cognition (β±SE:0.04±0.02). Higher pTau181 was associated with worse baseline performance on global cognition (-0.14±0.04) and memory (-0.31±0.09) and with steeper decline in global cognition (-0.07±0.02), memory (-0.09±0.04), attention (-0.05±0.02), and language (-0.10±0.03). Higher GFAP was associated with worse baseline performance on global cognition (-0.22±0.05), memory (-0.43±0.10), attention (-0.14±0.06), language (-0.15±0.05), and executive functioning (-0.15±0.05) and steeper decline in global cognition (-0.05±0.01). Higher NfL was associated with worse baseline performance on global cognition (-0.16±0.04), memory (-0.28±0.09), attention (-0.20±0.06), and executive functioning (-0.10±0.04), but was not associated with performance over time. In reference participants, no associations were found. Conclusions Our findings suggest that blood-based biomarkers of AD-related pathology predict cognitive decline in patients with cardiovascular diseases.
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Affiliation(s)
- Calvin Trieu
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam, The Netherlands
- Department of Laboratory Medicine, Neurochemistry Laboratory, Amsterdam Neuroscience, Program Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam, The Netherlands
| | - Anna E Leeuwis
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam, The Netherlands
| | - Lieza G Exalto
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Brain Research Center, Zwolle, The Netherlands
- Julius Clinical, Zeist, The Netherlands
| | - Astrid M Hooghiemstra
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam, The Netherlands
| | - Inge M W Verberk
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam, The Netherlands
- Department of Laboratory Medicine, Neurochemistry Laboratory, Amsterdam Neuroscience, Program Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
| | - Cor P Allaart
- Department of Cardiology, Institute for Cardiovascular Research, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
| | | | - L Jaap Kappelle
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Geert-Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Charlotte E Teunissen
- Department of Laboratory Medicine, Neurochemistry Laboratory, Amsterdam Neuroscience, Program Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam, The Netherlands
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15
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Seidu NM, Kern S, Sacuiu S, Sterner TR, Blennow K, Zetterberg H, Lindberg O, Ferreira D, Westman E, Zettergren A, Skoog I. Association of CSF biomarkers with MRI brain changes in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12556. [PMID: 38406609 PMCID: PMC10884990 DOI: 10.1002/dad2.12556] [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: 09/15/2023] [Accepted: 01/24/2024] [Indexed: 02/27/2024]
Abstract
The relation between cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and magnetic resonance imaging (MRI) measures is poorly understood in cognitively healthy individuals from the general population. Participants' (n = 226) mean age was 70.9 years (SD = 0.4). CSF concentrations of amyloid beta (Aβ)1-42, total tau (t-tau), phosphorylated tau (p-tau), neurogranin, and neurofilament light, and volumes of hippocampus, amygdala, total basal forebrain (TBF), and cortical thickness were measured. Linear associations between CSF biomarkers and MRI measures were investigated. In Aβ1-42 positives, higher t-tau and p-tau were associated with smaller hippocampus (P = 0.001 and P = 0.003) and amygdala (P = 0.005 and P = 0.01). In Aβ1-42 negatives, higher t-tau, p-tau, and neurogranin were associated with larger TBF volume (P = 0.001, P = 0.001, and P = 0.01). No associations were observed between the CSF biomarkers and an AD signature score of cortical thickness. AD-specific biomarkers in cognitively healthy 70-year-olds may be related to TBF, hippocampus, and amygdala. Lack of association with cortical thickness might be due to early stage of disease.
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Affiliation(s)
- Nazib M Seidu
- Neuropsychiatric Epidemiology (EPINEP)Centre for Ageing and Health (AGECAP)Institute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Silke Kern
- Neuropsychiatric Epidemiology (EPINEP)Centre for Ageing and Health (AGECAP)Institute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Psychiatry Cognition and Old Age PsychiatrySahlgrenska University Hospital, Region Västra GötalandGothenburgSweden
| | - Simona Sacuiu
- Neuropsychiatric Epidemiology (EPINEP)Centre for Ageing and Health (AGECAP)Institute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Psychiatry Cognition and Old Age PsychiatrySahlgrenska University Hospital, Region Västra GötalandGothenburgSweden
- Division of Clinical GeriatricsDepartment of NeurobiologyCare Sciences and SocietyCenter for Alzheimer ResearchKarolinska InstitutetStockholmSweden
- Cognitive Disorders ClinicTheme Inflammation and AgingKarolinska University HospitalStockholmSweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology (EPINEP)Centre for Ageing and Health (AGECAP)Institute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Aging Research CenterDepartment of NeurobiologyCare Sciences and SocietyKarolinska Institutet and Stockholm UniversityStockholmSweden
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University Hospital, Region Västra GötalandGothenburgSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University Hospital, Region Västra GötalandGothenburgSweden
- UK Dementia Research Institute at UCLLondonUK
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- UW Department of MedicineSchool of Medicine and Public HealthMadisonWisconsinUSA
| | - Olof Lindberg
- Division of Clinical GeriatricsDepartment of NeurobiologyCare Sciences and SocietyCenter for Alzheimer ResearchKarolinska InstitutetStockholmSweden
| | - Daniel Ferreira
- Division of Clinical GeriatricsDepartment of NeurobiologyCare Sciences and SocietyCenter for Alzheimer ResearchKarolinska InstitutetStockholmSweden
- Facultad de Ciencias de la SaludUniversidad Fernando Pessoa CanariasLas PalmasSpain
| | - Eric Westman
- Division of Clinical GeriatricsDepartment of NeurobiologyCare Sciences and SocietyCenter for Alzheimer ResearchKarolinska InstitutetStockholmSweden
- Department of NeuroimagingCentre for Neuroimaging SciencesInstitute of PsychiatryPsychology and NeuroscienceKing's College LondonLondonUK
| | - Anna Zettergren
- Neuropsychiatric Epidemiology (EPINEP)Centre for Ageing and Health (AGECAP)Institute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology (EPINEP)Centre for Ageing and Health (AGECAP)Institute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Department of Psychiatry Cognition and Old Age PsychiatrySahlgrenska University Hospital, Region Västra GötalandGothenburgSweden
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16
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Dage JL, Eloyan A, Thangarajah M, Hammers DB, Fagan AM, Gray JD, Schindler SE, Snoddy C, Nudelman KNH, Faber KM, Foroud T, Aisen P, Griffin P, Grinberg LT, Iaccarino L, Kirby K, Kramer J, Koeppe R, Kukull WA, Joie RL, Mundada NS, Murray ME, Rumbaugh M, Soleimani-Meigooni DN, Toga AW, Touroutoglou A, Vemuri P, Atri A, Beckett LA, Day GS, Graff-Radford NR, Duara R, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha SJ, Turner RS, Wingo TS, Wolk DA, Womack KB, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG. Cerebrospinal fluid biomarkers in the Longitudinal Early-onset Alzheimer's Disease Study. Alzheimers Dement 2023; 19 Suppl 9:S115-S125. [PMID: 37491668 PMCID: PMC10877673 DOI: 10.1002/alz.13399] [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: 03/08/2023] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 07/27/2023]
Abstract
INTRODUCTION One goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early-onset Alzheimer's disease (EOAD). METHODS Cerebrospinal fluid (CSF) concentrations of Aβ1-40, Aβ1-42, total tau (tTau), pTau181, VILIP-1, SNAP-25, neurogranin (Ng), neurofilament light chain (NfL), and YKL-40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated. RESULTS Biomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP-25, and Ng in EOAD differed significantly from cognitively normal and early-onset non-AD dementia; NfL, YKL-40, and VILIP-1 did not. Across groups, all biomarkers except SNAP-25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP-25 were correlated with at least one cognitive measure. DISCUSSION This study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design.
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Affiliation(s)
- Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Maryanne Thangarajah
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Anne M. Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Julia D. Gray
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Casey Snoddy
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kelly N. H. Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kelley M. Faber
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Lea T. Grinberg
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
- Department of Pathology, University of California – San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Joel Kramer
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Renaud La Joie
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Nidhi S Mundada
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | | | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Arthur W. Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Laurel A. Beckett
- Department of Public Health Sciences, University of California-Davis, Davis, California, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | | | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C. Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon J. Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - Raymond S. Turner
- Department of Neurology, Georgetown University, Washington, D.C., USA
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyle B. Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D. Rabinovici
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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17
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Cai Y, Fan X, Zhao L, Liu W, Luo Y, Lau AYL, Au LWC, Shi L, Lam BYK, Ko H, Mok VCT. Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD. Alzheimers Dement 2023; 19:4987-4998. [PMID: 37087687 DOI: 10.1002/alz.13083] [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: 12/21/2022] [Revised: 03/13/2023] [Accepted: 03/20/2023] [Indexed: 04/24/2023]
Abstract
INTRODUCTION We compared the machine learning-derived, MRI-based Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) with plasma neurofilament light chain (NfL) level in predicting conversion of early AD among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects. METHODS We recruited participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had the following data: clinical features (age, gender, education, Montreal Cognitive Assessment [MoCA]), structural MRI, plasma biomarkers (p-tau181 , NfL), cerebrospinal fluid biomarkers (CSF) (Aβ42, p-tau181 ), and apolipoprotein E (APOE) ε4 genotype. We defined AD using CSF Aβ42 (A+) and p-tau181 (T+). We defined conversion (C+) if a subject progressed to the next syndromal stage within 4 years. RESULTS Of 589 participants, 96 (16.3%) were A+T+C+. AD-RAI performed better than plasma NfL when added on top of clinical features, plasma p-tau181 , and APOE ε4 genotype (area under the curve [AUC] = 0.832 vs. AUC = 0.650 among CU, AUC = 0.853 vs. AUC = 0.805 among MCI) in predicting A+T+C+. DISCUSSION AD-RAI outperformed plasma NfL in predicting syndromal conversion of early AD. HIGHLIGHTS AD-RAI outperformed plasma NfL in predicting syndromal conversion among early AD. AD-RAI showed better metrics than volumetric hippocampal measures in predicting syndromal conversion. Combining clinical features, plasma p-tau181 and apolipoprotein E (APOE) with AD-RAI is the best model for predicting syndromal conversion.
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Affiliation(s)
- Yuan Cai
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Xiang Fan
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Lei Zhao
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong SAR, China
| | - Wanting Liu
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Yishan Luo
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong SAR, China
| | - Alexander Yuk Lun Lau
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Lisa Wing Chi Au
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Lin Shi
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong SAR, China
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Bonnie Y K Lam
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Ho Ko
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Vincent Chung Tong Mok
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
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18
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Salvioli S, Basile MS, Bencivenga L, Carrino S, Conte M, Damanti S, De Lorenzo R, Fiorenzato E, Gialluisi A, Ingannato A, Antonini A, Baldini N, Capri M, Cenci S, Iacoviello L, Nacmias B, Olivieri F, Rengo G, Querini PR, Lattanzio F. Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective. Ageing Res Rev 2023; 91:102044. [PMID: 37647997 DOI: 10.1016/j.arr.2023.102044] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/24/2023] [Accepted: 08/25/2023] [Indexed: 09/01/2023]
Abstract
According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.
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Affiliation(s)
- Stefano Salvioli
- Department of Medical and Surgical Science, University of Bologna, Bologna, Italy; IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
| | | | - Leonardo Bencivenga
- Department of Translational Medical Sciences, University of Naples Federico II, Napoli, Italy
| | - Sara Carrino
- Department of Medical and Surgical Science, University of Bologna, Bologna, Italy
| | - Maria Conte
- Department of Medical and Surgical Science, University of Bologna, Bologna, Italy
| | - Sarah Damanti
- IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy
| | - Rebecca De Lorenzo
- IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy
| | - Eleonora Fiorenzato
- Parkinson's Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), Department of Neurosciences, University of Padova, Padova, Italy
| | - Alessandro Gialluisi
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy; EPIMED Research Center, Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Angelo Antonini
- Parkinson's Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), Department of Neurosciences, University of Padova, Padova, Italy; Center for Neurodegenerative Disease Research (CESNE), Department of Neurosciences, University of Padova, Padova, Italy
| | - Nicola Baldini
- IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Miriam Capri
- Department of Medical and Surgical Science, University of Bologna, Bologna, Italy
| | - Simone Cenci
- IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy; EPIMED Research Center, Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, Università Politecnica Delle Marche, Ancona, Italy; Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy
| | - Giuseppe Rengo
- Department of Translational Medical Sciences, University of Naples Federico II, Napoli, Italy; Istituti Clinici Scientifici Maugeri IRCCS, Scientific Institute of Telese Terme, Telese Terme, Italy
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19
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Stojanovic M, Schindler SE, Morris JC, Head D. Effect of exercise engagement and cardiovascular risk on neuronal injury. Alzheimers Dement 2023; 19:4454-4462. [PMID: 37534906 PMCID: PMC10592382 DOI: 10.1002/alz.13400] [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: 03/28/2023] [Revised: 06/26/2023] [Accepted: 06/28/2023] [Indexed: 08/04/2023]
Abstract
INTRODUCTION Neuronal health as a potential underlying mechanism of the beneficial effects of exercise has been understudied in humans. Furthermore, there has been limited consideration of potential moderators (e.g., cardiovascular health) on the effects of exercise. METHODS Clinically normal middle-aged and older adults completed a validated questionnaire about exercise engagement over a 10-year period (n = 75; age 63 ± 8 years). A composite estimate of neuronal injury was formulated that included cerebrospinal fluid-based measures of visinin-like protein-1, neurogranin, synaptosomal-associated protein 25, and neurofilament light chain. Cardiovascular risk was estimated using the Framingham Risk Score. RESULTS Cross-sectional analyses showed that greater exercise engagement was associated with less neuronal injury in the group with lower cardiovascular risk (p = 0.008), but not the group with higher cardiovascular risk (p = 0.209). DISCUSSION Cardiovascular risk is an important moderator to consider when examining the effects of exercise on cognitive and neural health, and may be relevant to personalized exercise recommendations. HIGHLIGHTS We examined the association between exercise engagement and neuronal injury. Vascular risk moderated the association between exercise and neuronal injury. Cardiovascular risk may be relevant to personalized exercise recommendations.
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Affiliation(s)
- Marta Stojanovic
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, 63105
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63110
| | - Suzanne E. Schindler
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63110
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, 63110
| | - John C. Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, 63110
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, 63110
| | - Denise Head
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, 63105
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, 63110
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, 63110
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20
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Juganavar A, Joshi A, Shegekar T. Navigating Early Alzheimer's Diagnosis: A Comprehensive Review of Diagnostic Innovations. Cureus 2023; 15:e44937. [PMID: 37818489 PMCID: PMC10561010 DOI: 10.7759/cureus.44937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 09/09/2023] [Indexed: 10/12/2023] Open
Abstract
The hunt for early Alzheimer's disease detection has created cutting-edge diagnostic instruments with enormous promise. This article examines the many facets of these developments, focusing on how they have revolutionised diagnosis and patient outcomes. These tools make it possible to detect tiny brain changes even before they give birth to clinical symptoms by combining cutting-edge biomarkers, neuroimaging methods, and machine-learning algorithms. A significant opportunity for therapies that can slow the course of the disease exists during this early detection stage. Additionally, these cutting-edge techniques improve diagnostic precision, objectivity, and accessibility. Liquid biopsies and blood-based biomarkers provide non-invasive alternatives, filling accessibility gaps in diagnosis. While issues with standardisation, ethics, and data integration continue, collaboration within research, clinical practice, and policy realms fuels positive developments. As technology advances, the way towards better Alzheimer's diagnosis becomes more evident, giving patients and families dealing with this difficult illness fresh hope. The synergy between scientific advancement and compassionate treatment is crucial for improving Alzheimer's disease diagnosis, as this paper emphasises.
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Affiliation(s)
- Anup Juganavar
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Abhishek Joshi
- Community Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Tejas Shegekar
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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21
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Elmers J, Colzato LS, Akgün K, Ziemssen T, Beste C. Neurofilaments - Small proteins of physiological significance and predictive power for future neurodegeneration and cognitive decline across the life span. Ageing Res Rev 2023; 90:102037. [PMID: 37619618 DOI: 10.1016/j.arr.2023.102037] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/15/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023]
Abstract
Neurofilaments (NFs) are not only important for axonal integrity and nerve conduction in large myelinated axons but they are also thought to be crucial for receptor and synaptic functioning. Therefore, NFs may play a critical role in cognitive functions, as cognitive processes are known to depend on synaptic integrity and are modulated by dopaminergic signaling. Here, we present a theory-driven interdisciplinary approach that NFs may link inflammation, neurodegeneration, and cognitive functions. We base our hypothesis on a wealth of evidence suggesting a causal link between inflammation and neurodegeneration and between these two and cognitive decline (see Fig. 1), also taking dopaminergic signaling into account. We conclude that NFs may not only serve as biomarkers for inflammatory, neurodegenerative, and cognitive processes but also represent a potential mechanical hinge between them, moreover, they may even have predictive power regarding future cognitive decline. In addition, we advocate the use of both NFs and MRI parameters, as their synthesis offers the opportunity to individualize medical treatment by providing a comprehensive view of underlying disease activity in neurological diseases. Since our society will become significantly older in the upcoming years and decades, maintaining cognitive functions and healthy aging will play an important role. Thanks to technological advances in recent decades, NFs could serve as a rapid, noninvasive, and relatively inexpensive early warning system to identify individuals at increased risk for cognitive decline and could facilitate the management of cognitive dysfunctions across the lifespan.
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Affiliation(s)
- Julia Elmers
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany; Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, TU Dresden, Germany
| | - Lorenza S Colzato
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany; Cognitive Psychology, Faculty of Psychology, Shandong Normal University, Jinan, China.
| | - Katja Akgün
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, TU Dresden, Germany
| | - Tjalf Ziemssen
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, TU Dresden, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany; Cognitive Psychology, Faculty of Psychology, Shandong Normal University, Jinan, China.
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22
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Saloner R, Paolillo EW, Wojta KJ, Fonseca C, Gontrum EQ, Lario-Lago A, Rabinovici GD, Yokoyama JS, Rexach JE, Kramer JH, Casaletto KB. Sex-specific effects of SNAP-25 genotype on verbal memory and Alzheimer's disease biomarkers in clinically normal older adults. Alzheimers Dement 2023; 19:3448-3457. [PMID: 36807763 PMCID: PMC10435666 DOI: 10.1002/alz.12989] [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: 02/20/2023]
Abstract
INTRODUCTION We tested sex-dependent associations of variation in the SNAP-25 gene, which encodes a presynaptic protein involved in hippocampal plasticity and memory, on cognitive and Alzheimer's disease (AD) neuroimaging outcomes in clinically normal adults. METHODS Participants were genotyped for SNAP-25 rs1051312 (T > C; SNAP-25 expression: C-allele > T/T). In a discovery cohort (N = 311), we tested the sex by SNAP-25 variant interaction on cognition, Aβ-PET positivity, and temporal lobe volumes. Cognitive models were replicated in an independent cohort (N = 82). RESULTS In the discovery cohort, C-allele carriers exhibited better verbal memory and language, lower Aβ-PET positivity rates, and larger temporal volumes than T/T homozygotes among females, but not males. Larger temporal volumes related to better verbal memory only in C-carrier females. The female-specific C-allele verbal memory advantage was evidenced in the replication cohort. CONCLUSIONS In females, genetic variation in SNAP-25 is associated with resistance to amyloid plaque formation and may support verbal memory through fortification of temporal lobe architecture. HIGHLIGHTS The SNAP-25 rs1051312 (T > C) C-allele results in higher basal SNAP-25 expression. C-allele carriers had better verbal memory in clinically normal women, but not men. Female C-carriers had higher temporal lobe volumes, which predicted verbal memory. Female C-carriers also exhibited the lowest rates of amyloid-beta PET positivity. The SNAP-25 gene may influence female-specific resistance to Alzheimer's disease (AD).
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Affiliation(s)
- Rowan Saloner
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Emily W. Paolillo
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Kevin J. Wojta
- Neurogenetics Program, Department of Neurology, University of California, Los Angeles, California, USA
| | - Corrina Fonseca
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
| | - Eva Q. Gontrum
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Argentina Lario-Lago
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jennifer S. Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jessica E. Rexach
- Neurogenetics Program, Department of Neurology, University of California, Los Angeles, California, USA
| | - Joel H. Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Kaitlin B. Casaletto
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
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23
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Shaji S, Palanisamy R, Swaminathan R. Structural irregularities in MR corpus callosal images and their association with cerebrospinal fluid biomarkers in Mild Cognitive Impairments. Neurosci Lett 2023; 810:137329. [PMID: 37301466 DOI: 10.1016/j.neulet.2023.137329] [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: 01/14/2023] [Revised: 05/15/2023] [Accepted: 06/05/2023] [Indexed: 06/12/2023]
Abstract
In this study, irregularity measures from MR images of corpus callosal brain structures in healthy and Mild Cognitive Impairment (MCI) conditions are extracted and their association with Cerebrospinal Fluid (CSF) biomarkers are analyzed. For this, MR images of healthy controls, Early MCI (EMCI) and Late MCI (LMCI) subjects are considered from a public database. The considered images are preprocessed and corpus callosal structure is segmented. Structural irregularity measures are extracted from the segmented regions using Fourier analysis. Statistical tests are performed to identify the significant features which can characterize the MCI stages. Association of these measures with CSF amyloid beta and tau concentrations are further investigated. Results demonstrate that Fourier spectral analysis is able to characterize the non-periodic variations in the corpus callosal structures of healthy, EMCI and LMCI MR images. The callosal irregularity measures increase as the disease progresses from healthy to LMCI. Phosphorylated tau concentrations in CSF demonstrate a positive correlation with irregularity measures across the diagnostic groups. Significant association of callosal measures and amyloid beta levels are found to be absent in MCI stages. As corpus callosal structural irregularities due to early MCI condition and their association with CSF markers remain uncharacterized in the literature, this study seems to be clinically significant for the timely intervention of pre-symptomatic MCI stages.
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Affiliation(s)
- Sreelakshmi Shaji
- Non-Invasive Imaging and Diagnostic Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.
| | - Rohini Palanisamy
- Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, Chennai, India.
| | - Ramakrishnan Swaminathan
- Non-Invasive Imaging and Diagnostic Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.
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24
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Gaetani L, Chiasserini D, Paolini Paoletti F, Bellomo G, Parnetti L. Required improvements for cerebrospinal fluid-based biomarker tests of Alzheimer's disease. Expert Rev Mol Diagn 2023; 23:1195-1207. [PMID: 37902844 DOI: 10.1080/14737159.2023.2276918] [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: 04/26/2023] [Accepted: 10/25/2023] [Indexed: 11/01/2023]
Abstract
INTRODUCTION Cerebrospinal fluid (CSF) biomarkers represent a well-established tool for diagnosing Alzheimer's disease (AD), independently from the clinical stage, by reflecting the presence of brain amyloidosis (A+) and tauopathy (T+). In front of this important achievement, so far, (i) CSF AD biomarkers have not yet been adopted for routine clinical use in all Centers dedicated to AD, mainly due to inter-lab variation and lack of internationally accepted cutoff values; (ii) we do need to add other biomarkers more suitable to correlate with the clinical stage and disease monitoring; (iii) we also need to detect the co-presence of other 'non-AD' pathologies. AREAS COVERED Efforts to establish standardized cutoff values based on large-scale multi-center studies are discussed. The influence of aging and comorbidities on CSF biomarker levels is also analyzed, and possible solutions are presented, i.e. complementing the A/T/(N) system with markers of axonal damage and synaptic derangement. EXPERT OPINION The first, mandatory need is to reach common cutoff values and defined (automated) methodologies for CSF AD biomarkers. To properly select subjects deserving CSF analysis, blood tests might represent the first-line approach. In those subjects undergoing CSF analysis, multiple biomarkers, able to give a comprehensive and personalized pathophysiological/prognostic information, should be included.
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Affiliation(s)
- Lorenzo Gaetani
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Davide Chiasserini
- Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | | | - Giovanni Bellomo
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Lucilla Parnetti
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
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25
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Papaliagkas V, Kalinderi K, Vareltzis P, Moraitou D, Papamitsou T, Chatzidimitriou M. CSF Biomarkers in the Early Diagnosis of Mild Cognitive Impairment and Alzheimer's Disease. Int J Mol Sci 2023; 24:ijms24108976. [PMID: 37240322 DOI: 10.3390/ijms24108976] [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: 03/23/2023] [Revised: 05/09/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
Alzheimer's disease (AD) is a rapidly growing disease that affects millions of people worldwide, therefore there is an urgent need for its early diagnosis and treatment. A huge amount of research studies are performed on possible accurate and reliable diagnostic biomarkers of AD. Due to its direct contact with extracellular space of the brain, cerebrospinal fluid (CSF) is the most useful biological fluid reflecting molecular events in the brain. Proteins and molecules that reflect the pathogenesis of the disease, e.g., neurodegeneration, accumulation of Abeta, hyperphosphorylation of tau protein and apoptosis may be used as biomarkers. The aim of the current manuscript is to present the most commonly used CSF biomarkers for AD as well as novel biomarkers. Three CSF biomarkers, namely total tau, phospho-tau and Abeta42, are believed to have the highest diagnostic accuracy for early AD diagnosis and the ability to predict AD development in mild cognitive impairment (MCI) patients. Moreover, other biomarkers such as soluble amyloid precursor protein (APP), apoptotic proteins, secretases and inflammatory and oxidation markers are believed to have increased future prospects.
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Affiliation(s)
- Vasileios Papaliagkas
- Department of Biomedical Sciences, School of Health Sciences, International Hellenic University, Alexandrion University Campus, 57400 Sindos, Greece
| | - Kallirhoe Kalinderi
- Laboratory of Medical Biology-Genetics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Patroklos Vareltzis
- Department of Chemical Engineering, School of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Despoina Moraitou
- Laboratory of Psychology, School of Psychology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Theodora Papamitsou
- Histology and Embryology Department, Faculty of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Maria Chatzidimitriou
- Department of Biomedical Sciences, School of Health Sciences, International Hellenic University, Alexandrion University Campus, 57400 Sindos, Greece
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26
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Rogatzki MJ, Szeghy RE, Stute NL, Province VM, Augenreich MA, Stickford JL, Stickford AS, Hanson ED, Ratchford SM. Plasma UCHL1, GFAP, Tau, and NfL Are Not Different in Young Healthy Persons With Mild COVID-19 Symptoms Early in the Pandemic: A Pilot Study. Neurotrauma Rep 2023; 4:330-341. [PMID: 37284701 PMCID: PMC10240333 DOI: 10.1089/neur.2023.0014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023] Open
Abstract
Elevated levels of brain injury biomarkers have been found primarily in middle-aged or older persons experiencing moderate-to-severe COVID-19 symptoms. However, there is little research in young adults, and there is concern that COVID-19 causes brain injury even in the absence of moderate-to-severe symptoms. Therefore, the purpose of our study was to investigate whether neurofilament light (NfL), glial fibrillary acidic protein (GFAP), tau, or ubiquitin carboxyl-terminal esterase L1 (UCHL1) are elevated in the plasma of young adults with mild COVID-19 symptoms. Twelve participants diagnosed with COVID-19 had plasma collected 1, 2, 3, and 4 months after diagnosis to determine whether NfL, GFAP, tau, and UCHL1 concentrations increased over time or whether plasma concentrations were elevated compared with COVID-19-naïve participants. We also compared plasma NfL, GFAP, tau, and UCHL1 concentrations between sexes. Our results showed no difference between NfL, GFAP, tau, and UCHL1 concentrations in COVID-19-naïve participants and COVID-19-positive participants at any of the four time points (p = 0.771). Within the COVID-19-positive participants, UCHL1 levels were higher at month 3 after diagnosis compared to month 1 or month 2 (p = 0.027). Between sexes, females were found to have higher UCHL1 (p = 0.003) and NfL (p = 0.037) plasma concentrations compared to males, whereas males had higher plasma tau concentrations than females (p = 0.024). Based on our data, it appears that mild COVID-19 in young adults does not increase plasma NfL, GFAP, tau, or UCHL1.
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Affiliation(s)
- Matthew J. Rogatzki
- Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, USA
| | - Rachel E. Szeghy
- Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, USA
| | - Nina L. Stute
- School of Kinesiology, Auburn University, Auburn, Alabama, USA
| | - Valesha M. Province
- Department of Cardiovascular and Metabolic Sciences, The Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Marc A. Augenreich
- Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, Missouri, USA
| | - Jonathon L. Stickford
- Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, USA
| | - Abigail S.L. Stickford
- Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, USA
| | - Erik D. Hanson
- Department of Exercise and Sport Science, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Stephen M. Ratchford
- Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, USA
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27
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Wang L, Western D, Timsina J, Repaci C, Song WM, Norton J, Kohlfeld P, Budde J, Climer S, Butt OH, Jacobson D, Garvin M, Templeton AR, Campagna S, O’Halloran J, Presti R, Goss CW, Mudd PA, Ances BM, Zhang B, Sung YJ, Cruchaga C. Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways. iScience 2023; 26:106408. [PMID: 36974157 PMCID: PMC10010831 DOI: 10.1016/j.isci.2023.106408] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/21/2023] [Accepted: 03/10/2023] [Indexed: 03/14/2023] Open
Abstract
Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
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Affiliation(s)
- Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Charlie Repaci
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Won-Min Song
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Sharlee Climer
- Department of Computer Science, University of Missouri-St. Louis, St. Louis, MO, USA
| | - Omar H. Butt
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Michael Garvin
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Alan R. Templeton
- Department of Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Shawn Campagna
- Department of Chemistry, University of Tennessee, Knoxville, TN, USA
| | - Jane O’Halloran
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Rachel Presti
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Charles W. Goss
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip A. Mudd
- Department of Emergency Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Beau M. Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, 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: 27] [Impact Index Per Article: 27.0] [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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Arvidsson Rådestig M, Skoog I, Skillbäck T, Zetterberg H, Kern J, Zettergren A, Andreasson U, Wetterberg H, Kern S, Blennow K. Cerebrospinal fluid biomarkers of axonal and synaptic degeneration in a population-based sample. Alzheimers Res Ther 2023; 15:44. [PMID: 36869347 PMCID: PMC9983206 DOI: 10.1186/s13195-023-01193-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/14/2023] [Indexed: 03/05/2023]
Abstract
BACKGROUND Neurofilament light (NfL) and neurogranin (Ng) are promising candidate AD biomarkers, reflecting axonal and synaptic damage, respectively. Since there is a need to understand the synaptic and axonal damage in preclinical Alzheimer's disease (AD), we aimed to determine the cerebrospinal fluid (CSF) levels of NfL and Ng in cognitively unimpaired elderly from the Gothenburg H70 Birth Cohort Studies classified according to the amyloid/tau/neurodegeneration (A/T/N) system. METHODS The sample consisted of 258 cognitively unimpaired older adults (age 70, 129 women and 129 men) from the Gothenburg Birth Cohort Studies. We compared CSF NfL and Ng concentrations in A/T/N groups using Student's T-test and ANCOVA. RESULTS CSF NfL concentration was higher in the A-T-N+ group (p=0.001) and the A-T+N+ group (p=0.006) compared with A-T-N-. CSF Ng concentration was higher in the A-T-N+, A-T+N+, A+T-N+, and A+T+N+ groups (p<0.0001) compared with A-T-N-. We found no difference in NfL or Ng concentration in A+ compared with A- (disregarding T- and N- status), whereas those with N+ had higher concentrations of NfL and Ng compared with N- (p<0.0001) (disregarding A- and T- status). CONCLUSIONS CSF NfL and Ng concentrations are increased in cognitively normal older adults with biomarker evidence of tau pathology and neurodegeneration.
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Affiliation(s)
- Maya Arvidsson Rådestig
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Ingmar Skoog
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry, Cognition and Old Age Psychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Tobias Skillbäck
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden. .,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at UCL, London, WC1N 3BG, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Jürgen Kern
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Anna Zettergren
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Hanna Wetterberg
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Silke Kern
- Department of Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry, Cognition and Old Age Psychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
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Kasuga K, Tsukie T, Kikuchi M, Tokutake T, Washiyama K, Simizu S, Yoshizawa H, Kuroha Y, Yajima R, Mori H, Arakawa Y, Onda K, Miyashita A, Onodera O, Iwatsubo T, Ikeuchi T. The Clinical Application of Optimized AT(N) Classification in Alzheimer’s Clinical Syndrome (ACS) and non-ACS Conditions. Neurobiol Aging 2023; 127:23-32. [PMID: 37030016 DOI: 10.1016/j.neurobiolaging.2023.03.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/10/2023] [Accepted: 03/11/2023] [Indexed: 03/18/2023]
Abstract
We aimed to assess the utility of AT(N) classification in clinical practice. We measured the cerebrospinal fluid levels of amyloid-β (Aβ) 42, Aβ40, phosphorylated tau, total tau, and neurofilament light chain (NfL) in samples from 230 patients with Alzheimer's clinical syndrome (ACS) and 328 patients with non-ACS. The concordance of two A-markers (i.e., Aβ42 alone and the Aβ42/Aβ40 ratio) was not significantly different between the ACS (87.4%) and non-ACS (74.1%) groups. However, the frequency of discordant cases with AAβ42-alone+/AAβ-ratio- was significantly higher in the non-ACS (23.8%) than in the ACS group (7.4%). The concordance of two N-markers (i.e., total tau and NfL) was 40.4% in the ACS group and 24.4% in the non-ACS group. In the ACS samples, the frequency of biological Alzheimer's disease (i.e., A+T+) in Ntau+ cases was 95% while that in NNfL+ cases was 65%. Reflecting Aβ deposition and neurodegeneration more accurately, we recommend the use of AT(N) classification defined by cerebrospinal fluid AAβ-ratioTNNfL in clinical practice.
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Guo Y, Shen XN, Wang HF, Chen SD, Zhang YR, Chen SF, Cui M, Cheng W, Dong Q, Ma T, Yu JT. The dynamics of plasma biomarkers across the Alzheimer's continuum. Alzheimers Res Ther 2023; 15:31. [PMID: 36750875 PMCID: PMC9906840 DOI: 10.1186/s13195-023-01174-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/18/2023] [Indexed: 02/09/2023]
Abstract
BACKGROUND Failures in drug trials strengthen the necessity to further determine the neuropathological events during the development of Alzheimer's disease (AD). We sought to investigate the dynamic changes and performance of plasma biomarkers across the entire Alzheimer's continuum in the Chinese population. METHODS Plasma amyloid-β (Αβ)42, Aβ40, Aβ42/Aβ40, phosphorylated tau (p-tau)181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured utilizing the ultrasensitive single-molecule array technology across the AD continuum (n=206), wherein Aβ status was defined by the values of cerebrospinal fluid (CSF) Aβ42 or Aβ positron emission tomography (PET). Their trajectories were compared with those of putative CSF biomarkers. RESULTS Plasma GFAP and p-tau181 increased only in Aβ-positive individuals throughout aging, whereas NfL increased with aging regardless of Aβ status. Among the plasma biomarkers studied, GFAP was the one that changed first. It had a prominent elevation early in the cognitively unimpaired (CU) A+T- phase (CU A+T- phase: 97.10±41.29 pg/ml; CU A-T- phase: 49.18±14.39 pg/ml; p<0.001). From preclinical to symptomatic stages of AD, plasma GFAP started to rise sharply as soon as CSF Aβ became abnormal and continued to increase until reaching its highest level during the AD dementia phase. The greatest slope of change was seen in plasma GFAP. This is followed by CSF p-tau181 and total-tau, and, to a lesser extent, then plasma p-tau181. In contrast, the changes in plasma NfL, Aβ42/Aβ40, Aβ42, and Aβ40 were less pronounced. Of note, these plasma biomarkers exhibited smaller dynamic ranges than their CSF counterparts, except for GFAP which was the opposite. Plasma GFAP and p-tau181 were tightly associated with AD pathologies and amyloid tracer uptake in widespread brain areas. Plasma GFAP could accurately identify CSF Aβ42 (area under the curve (AUC)=0.911) and Aβ PET (AUC=0.971) positivity. Plasma p-tau181 also performed well in discriminating Aβ PET status (AUC=0.916), whereas the discriminative accuracy was relatively low for other plasma biomarkers. CONCLUSIONS This study is the first to delineate the trajectories of plasma biomarkers throughout the Alzheimer's continuum in the Chinese population, providing important implications for future trials targeting plasma GFAP to facilitate AD prevention and treatment.
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Affiliation(s)
- Yu Guo
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Xue-Ning Shen
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Hui-Fu Wang
- grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Ya-Ru Zhang
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Shu-Fen Chen
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Mei Cui
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Wei Cheng
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China ,grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China ,grid.8547.e0000 0001 0125 2443Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China ,grid.453534.00000 0001 2219 2654Fudan ISTBI—ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Qiang Dong
- grid.11841.3d0000 0004 0619 8943Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Tao Ma
- Department of Neurology, Wuxi Second People Hospital, Jiangnan University Medical Center, Wuxi, China.
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
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Rådestig MA, Skoog J, Zetterberg H, Skillbäck T, Zettergren A, Sterner TR, Fässberg MM, Sacuiu S, Waern M, Wetterberg H, Blennow K, Skoog I, Kern S. Subtle Differences in Cognition in 70-Year-Olds with Elevated Cerebrospinal Fluid Neurofilament Light and Neurogranin: A H70 Cross-Sectional Study. J Alzheimers Dis 2023; 91:291-303. [PMID: 36617786 PMCID: PMC9881027 DOI: 10.3233/jad-220452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/19/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND Most research on cerebrospinal fluid (CSF) neurofilament light protein (NfL) as a marker for neurodegeneration and neurogranin (Ng) for synaptic dysfunction has largely focused on clinical cohorts rather than population-based samples. OBJECTIVE We hypothesized that increased CSF levels of NfL and Ng are associated with subtle cognitive deficits in cognitively unimpaired (CU) older adults. METHODS The sample was derived from the Gothenburg H70 Birth Cohort Studies and comprised 258 CU 70-year-olds, with a Clinical Dementia Rating score of zero. All participants underwent extensive cognitive testing. CSF levels of NfL and Ng, as well as amyloid β1 - 42, total tau, and phosphorylated tau, were measured. RESULTS Participants with high CSF NfL performed worse in one memory-based test (Immediate recall, p = 0.013) and a language test (FAS, p = 0.016). Individuals with high CSF Ng performed worse on the memory-based test Supra Span (p = 0.035). When stratified according to CSF tau and Aβ42 concentrations, participants with high NfL and increased tau performed worse on a memory test than participants normal tau concentrations (Delayed recall, p = 0.003). In participants with high NfL, those with pathologic Aβ42 concentrations performed worse on the Delayed recall memory (p = 0.044). In the high Ng group, participants with pathological Aβ42 concentrations had lower MMSE scores (p = 0.027). However, in regression analysis we found no linear correlations between CSF NfL or CSF Ng in relation to cognitive tests when controlled for important co-variates. CONCLUSION Markers of neurodegeneration and synaptic pathology might be associated with subtle signs of cognitive decline in a population-based sample of 70-year-olds.
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Affiliation(s)
- Maya Arvidsson Rådestig
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Johan Skoog
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Psychiatry/Cognition and Old Age Psychiatry Clinic, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - 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
- UCL Institute of Neurology, Queen Square, London, UK
- The UK Dementia Research Institute, UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Tobias Skillbäck
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Anna Zettergren
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Therese Rydberg Sterner
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Madeleine Mellqvist Fässberg
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Simona Sacuiu
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Psychiatry/Cognition and Old Age Psychiatry Clinic, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
- Memory Disorders Clinic, Theme Inflammation and Aging, Karolinska University Hospital, Region Stockholm, Stockholm, Sweden
- Department of Neurobiology, Care Sciences and Society (NVS), Clinical Geriatric, Karolinska Institute, Stockholm, Sweden
| | - Margda Waern
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Psychosis Clinic, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - Hanna Wetterberg
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - 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
| | - Ingmar Skoog
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Psychiatry/Cognition and Old Age Psychiatry Clinic, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - Silke Kern
- Center for Ageing and Health (AgeCap), University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Psychiatry/Cognition and Old Age Psychiatry Clinic, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
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Wesenhagen KEJ, Tijms BM, Boonkamp L, Hoede PL, Goossens J, Dewit N, Scheltens P, Vanmechelen E, Visser PJ, Teunissen CE. P-tau subgroups in AD relate to distinct amyloid production and synaptic integrity profiles. Alzheimers Res Ther 2022; 14:95. [PMID: 35841015 PMCID: PMC9288016 DOI: 10.1186/s13195-022-01038-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022]
Abstract
Background We previously identified four Alzheimer’s disease (AD) subgroups with increasingly higher cerebrospinal fluid (CSF) levels of tau phosphorylated at threonine 181 (p-tau). These subgroups included individuals across the cognitive spectrum, suggesting p-tau subgroups could reflect distinct biological changes in AD, rather than disease severity. Therefore, in the current study, we further investigated which potential processes may be related with p-tau subgroups, by comparing individuals on CSF markers for presynaptic structure [vesicle-associated membrane protein 2 (VAMP2)], postsynaptic structure [neurogranin (NRGN)], axonal damage [neurofilament light (NfL)], and amyloid production [beta-secretase 1 (BACE1) and amyloid-beta 1–40 (Aβ40)]. Methods We selected 348 amyloid-positive (A+) individuals (53 preclinical, 102 prodromal, 193 AD dementia) and 112 amyloid-negative (A−) cognitively normal (CN) individuals from the Amsterdam Dementia Cohort (ADC). Individuals were labeled according to their p-tau subgroup (subgroup 1: p-tau ≤ 56 pg/ml; subgroup 2: 57–96 pg/ml; subgroup 3: 97–159 pg/ml; subgroup 4: > 159 pg/ml). CSF protein levels were measured with ELISA (NRGN, BACE1, Aβ40, NfL) or single-molecule array (Simoa) (VAMP2). We tested whether protein levels differed between the p-tau subgroups within A+ individuals with linear models corrected for age and sex and whether disease stage influenced these relationships. Results Among A+ individuals, higher p-tau subgroups showed a higher percentage of AD dementia [subgroup 1: n = 41/94 (44%); subgroup 2: n = 81/147 (55%); subgroup 3: n = 59/89 (66%); subgroup 4: n = 7/11 (64%)]. Relative to controls, subgroup 1 showed reduced CSF levels of BACE1, Aβ40, and VAMP2 and higher levels of NfL. Subgroups 2 to 4 showed gradually increased CSF levels of all measured proteins, either across the first three (NfL and Aβ40) or across all subgroups (VAMP2, NRGN, BACE1). The associations did not depend on the clinical stage (interaction p-values ranging between 0.19 and 0.87). Conclusions The results suggest that biological heterogeneity in p-tau levels in AD is related to amyloid metabolism and synaptic integrity independent of clinical stage. Biomarkers reflecting amyloid metabolism and synaptic integrity may be useful outcome measures in clinical trials targeting tau pathology.
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Saloner R, Fonseca C, Paolillo EW, Asken BM, Djukic NA, Lee S, Nilsson J, Brinkmalm A, Blennow K, Zetterberg H, Kramer JH, Casaletto KB. Combined Effects of Synaptic and Axonal Integrity on Longitudinal Gray Matter Atrophy in Cognitively Unimpaired Adults. Neurology 2022; 99:e2285-e2293. [PMID: 36041868 PMCID: PMC9694840 DOI: 10.1212/wnl.0000000000201165] [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: 02/17/2022] [Accepted: 07/11/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Synaptic dysfunction and degeneration is a predominant feature of brain aging, and synaptic preservation buffers against Alzheimer disease (AD) protein-related brain atrophy. We tested whether CSF synaptic protein concentrations similarly moderate the effects of axonal injury, indexed by CSF neurofilament light [NfL]), on brain atrophy in clinically normal adults. METHODS Clinically normal older adults enrolled in the observational Hillblom Aging Network study at the UCSF Memory and Aging Center completed baseline lumbar puncture and longitudinal brain MRI (mean scan [follow-up] = 2.6 [3.7 years]). CSF was assayed for synaptic proteins (synaptotagmin-1, synaptosomal-associated protein 25 [SNAP-25], neurogranin, growth-associated protein 43 [GAP-43]), axonal injury (NfL), and core AD biomarkers (ptau181/Aβ42 ratio; reflecting AD proteinopathy). Ten bilateral temporoparietal gray matter region of interest (ROIs) shown to be sensitive to clinical AD were summed to generate a composite temporoparietal ROI. Linear mixed-effects models tested statistical moderation of baseline synaptic proteins on baseline NfL-related temporoparietal trajectories, controlling for ptau181/Aβ42 ratios. RESULTS Forty-six clinically normal older adults (mean age = 70 years; 43% female) were included. Synaptic proteins exhibited small to medium correlations with NfL (r range: 0.10-0.36). Higher baseline NfL, but not ptau181/Aβ42 ratios, predicted steeper temporoparietal atrophy (NfL × time: β = -0.08, p < 0.001; ptau181/Aβ42 × time: β = -0.02, p = 0.31). SNAP-25, neurogranin, and GAP-43 significantly moderated NfL-related atrophy trajectories (-0.07 ≤ β's ≥ -0.06, p's < 0.05) such that NfL was associated with temporoparietal atrophy at high (more abnormal) but not low (more normal) synaptic protein concentrations. At high NfL concentrations, atrophy trajectories were 1.5-4.5 times weaker when synaptic protein concentrations were low (β range: -0.21 to -0.07) than high (β range: -0.33 to -0.30). DISCUSSION The association between baseline CSF NfL and longitudinal temporoparietal atrophy is accelerated by synaptic dysfunction and buffered by synaptic integrity. Beyond AD proteins, concurrent examination of in vivo axonal and synaptic biomarkers may improve detection of neural alterations that precede overt structural changes in AD-sensitive brain regions.
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Affiliation(s)
- Rowan Saloner
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China.
| | - Corrina Fonseca
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Emily W Paolillo
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Breton M Asken
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Nina A Djukic
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Shannon Lee
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Johanna Nilsson
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Ann Brinkmalm
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Kaj Blennow
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Henrik Zetterberg
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Joel H Kramer
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
| | - Kaitlin B Casaletto
- From the Department of Neurology (R.S., E.W.P., B.M.A., N.A.D., S.L., J.H.K., K.B.C.), Memory and Aging CenterWeill Institute for Neurosciences, University of California, San Francisco; Helen Wills Neuroscience Institute (C.F.), University of California, Berkeley; Department of Psychiatry and Neurochemistry (J.N., A.B., K.B., H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory (A.B., K.B., H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z.), UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL (H.Z.), London; and Hong Kong Center for Neurodegenerative Diseases (H.Z.), China
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Aschenbrenner AJ, Li Y, Henson RL, Volluz K, Hassenstab J, Verghese P, West T, Meyer MR, Kirmess KM, Fagan AM, Xiong C, Holtzman D, Morris JC, Bateman RJ, Schindler SE. Comparison of plasma and CSF biomarkers in predicting cognitive decline. Ann Clin Transl Neurol 2022; 9:1739-1751. [PMID: 36183195 PMCID: PMC9639639 DOI: 10.1002/acn3.51670] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/07/2022] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVES Concentrations of amyloid-β peptides (Aβ42/Aβ40) and neurofilament light (NfL) can be measured in plasma or cerebrospinal fluid (CSF) and are associated with Alzheimer's disease brain pathology and cognitive impairment. This study directly compared plasma and CSF measures of Aβ42/Aβ40 and NfL as predictors of cognitive decline. METHODS Participants were 65 years or older and cognitively normal at baseline with at least one follow-up cognitive assessment. Analytes were measured with the following types of assays: plasma Aβ42/Aβ40, immunoprecipitation-mass spectrometry; plasma NfL, Simoa; CSF Aβ42/Aβ40, automated immunoassay; CSF NfL plate-based immunoassay. Mixed effects models evaluated the global cognitive composite score over a maximum of 6 years as predicted by the fluid biomarkers. RESULTS Analyses included 371 cognitively normal participants, aged 72.7 ± 5.2 years (mean ± standard deviation) with an average length of follow-up of 3.9 ± 1.6 years. Standardized concentrations of biomarkers were associated with annualized cognitive change: plasma Aβ42/Aβ40, 0.014 standard deviations (95% confidence intervals 0.002 to 0.026); CSF Aβ42/Aβ40, 0.020 (0.008 to 0.032); plasma Nfl, -0.018 (-0.030 to -0.005); and CSF NfL, -0.024 (-0.036 to -0.012). Power analyses estimated that 266 individuals in each treatment arm would be needed to detect a 50% slowing of decline if identified by abnormal plasma measures versus 229 for CSF measures. INTERPRETATION Both plasma and CSF measures of Aβ42/Aβ40 and NfL predicted cognitive decline. A clinical trial that enrolled individuals based on abnormal plasma Aβ42/Aβ40 and NfL levels would require only a marginally larger cohort than if CSF measures were used.
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Affiliation(s)
- Andrew J. Aschenbrenner
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | - Yan Li
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Division of BiostatisticsWashington University School of MedicineSt. LouisMOUSA
| | - Rachel L. Henson
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | - Katherine Volluz
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | - Jason Hassenstab
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | | | | | | | | | - Anne M. Fagan
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - Chengjie Xiong
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Division of BiostatisticsWashington University School of MedicineSt. LouisMOUSA
| | - David Holtzman
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - John C. Morris
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - Randall J. Bateman
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - Suzanne E. Schindler
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
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Saunders TS, Gadd DA, Spires‐Jones TL, King D, Ritchie C, Muniz‐Terrera G. Associations between cerebrospinal fluid markers and cognition in ageing and dementia: A systematic review. Eur J Neurosci 2022; 56:5650-5713. [PMID: 35338546 PMCID: PMC9790745 DOI: 10.1111/ejn.15656] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/08/2022] [Accepted: 03/13/2022] [Indexed: 12/30/2022]
Abstract
A biomarker associated with cognition in neurodegenerative dementias would aid in the early detection of disease progression, complement clinical staging and act as a surrogate endpoint in clinical trials. The current systematic review evaluates the association between cerebrospinal fluid protein markers of synapse loss and neuronal injury and cognition. We performed a systematic search which revealed 67 studies reporting an association between cerebrospinal fluid markers of interest and neuropsychological performance. Despite the substantial heterogeneity between studies, we found some evidence for an association between neurofilament-light and worse cognition in Alzheimer's diseases, frontotemporal dementia and typical cognitive ageing. Moreover, there was an association between cerebrospinal fluid neurogranin and cognition in those with an Alzheimer's-like cerebrospinal fluid biomarker profile. Some evidence was found for cerebrospinal fluid neuronal pentraxin-2 as a correlate of cognition across dementia syndromes. Due to the substantial heterogeneity of the field, no firm conclusions can be drawn from this review. Future research should focus on improving standardization and reporting as well as establishing the importance of novel markers such as neuronal pentraxin-2 and whether such markers can predict longitudinal cognitive decline.
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Affiliation(s)
- Tyler S. Saunders
- UK Dementia Research InstituteThe University of EdinburghEdinburghUK,Center for Discovery Brain SciencesThe University of EdinburghEdinburghUK,Center for Clinical Brain SciencesThe University of EdinburghEdinburghUK,Center for Dementia PreventionThe University of EdinburghEdinburghUK
| | - Danni A. Gadd
- Center for Genomic and Experimental Medicine, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
| | - Tara L. Spires‐Jones
- UK Dementia Research InstituteThe University of EdinburghEdinburghUK,Center for Discovery Brain SciencesThe University of EdinburghEdinburghUK
| | - Declan King
- UK Dementia Research InstituteThe University of EdinburghEdinburghUK,Center for Discovery Brain SciencesThe University of EdinburghEdinburghUK
| | - Craig Ritchie
- Center for Clinical Brain SciencesThe University of EdinburghEdinburghUK,Center for Dementia PreventionThe University of EdinburghEdinburghUK
| | - Graciela Muniz‐Terrera
- Center for Clinical Brain SciencesThe University of EdinburghEdinburghUK,Center for Dementia PreventionThe University of EdinburghEdinburghUK
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Svenningsson AL, Stomrud E, Palmqvist S, Hansson O, Ossenkoppele R. Axonal degeneration and amyloid pathology predict cognitive decline beyond cortical atrophy. Alzheimers Res Ther 2022; 14:144. [PMID: 36192766 PMCID: PMC9531524 DOI: 10.1186/s13195-022-01081-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 09/11/2022] [Indexed: 12/02/2022]
Abstract
BACKGROUND Cortical atrophy is associated with cognitive decline, but the association is not perfect. We aimed to identify factors explaining the discrepancy between the degree of cortical atrophy and cognitive decline in cognitively unimpaired elderly. METHODS The discrepancy between atrophy and cognitive decline was measured using the residuals from a linear regression analysis between change in whole brain cortical thickness over time and change in a cognitive composite measure over time in 395 cognitively unimpaired participants from the Swedish BioFINDER study. We tested for bivariate associations of this residual measure with demographic, imaging, and fluid biomarker variables using Pearson correlations and independent-samples t-tests, and for multivariate associations using linear regression models. Mediation analyses were performed to explore possible paths between the included variables. RESULTS In bivariate analyses, older age (r = -0.11, p = 0.029), male sex (t = -3.00, p = 0.003), larger intracranial volume (r = -0.17, p < 0.001), carrying an APOEe4 allele (t = -2.71, p = 0.007), larger white matter lesion volume (r = -0.16, p = 0.002), lower cerebrospinal fluid (CSF) β-amyloid (Aβ) 42/40 ratio (t = -4.05, p < 0.001), and higher CSF levels of phosphorylated tau (p-tau) 181 (r = -0.22, p < 0.001), glial fibrillary acidic protein (GFAP; r = -0.15, p = 0.003), and neurofilament light (NfL; r = -0.34, p < 0.001) were negatively associated with the residual measure, i.e., associated with worse than expected cognitive trajectory given the level of atrophy. In a multivariate analysis, only lower CSF Aβ42/40 ratio and higher CSF NfL levels explained cognition beyond brain atrophy. Mediation analyses showed that associations between the residual measure and APOEe4 allele, CSF Aβ42/40 ratio, and CSF GFAP and p-tau181 levels were mediated by levels of CSF NfL, as were the associations with the residual measure for age, sex, and WML volume. CONCLUSIONS Our results suggest that axonal degeneration and amyloid pathology independently affect the rate of cognitive decline beyond the degree of cortical atrophy. Furthermore, axonal degeneration mediated the negative effects of old age, male sex, and white matter lesions, and in part also amyloid and tau pathology, on cognition over time when accounting for cortical atrophy.
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Affiliation(s)
- Anna Linnéa Svenningsson
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Sebastian Palmqvist
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.484519.5Alzheimer Center Amsterdam, Department of Neurology, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
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Laudanski K, Liu D, Okeke T, Restrepo M, Szeto WY. Persistent Depletion of Neuroprotective Factors Accompanies Neuroinflammatory, Neurodegenerative, and Vascular Remodeling Spectra in Serum Three Months after Non-Emergent Cardiac Surgery. Biomedicines 2022; 10:biomedicines10102364. [PMID: 36289630 PMCID: PMC9598177 DOI: 10.3390/biomedicines10102364] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 11/24/2022] Open
Abstract
We hypothesized that the persistent depletion of neuroprotective markers accompanies neuroinflammation and neurodegeneration in patients after cardiac surgery. A total of 158 patients underwent elective heart surgery with their blood collected before surgery (tbaseline) and 24 h (t24hr), seven days (t7d), and three months (t3m) post-surgery. The patients’ serum was measured for markers of neurodegeneration (τau, τaup181–183, amyloid β1-40/β2-42, and S100), atypical neurodegeneration (KLK6 and NRGN), neuro-injury (neurofilament light/heavy, UC-HL, and GFAP), neuroinflammation (YKL-40 and TDP-43), peripheral nerve damage (NCAM-1), neuroprotection (apoE4, BDNF, fetuin, and clusterin), and vascular smoldering inflammation (C-reactive protein, CCL-28 IL-6, and IL-8). The mortality at 28 days, incidence of cerebrovascular accidents (CVA), and functional status were followed for three months. The levels of amyloid β1-40/β1-42 and NF-L were significantly elevated at all time points. The levels of τau, S100, KLK6, NRGN, and NCAM-1 were significantly elevated at 24 h. A cluster analysis demonstrated groupings around amyloids, KLK6, and NCAM-1. YKL-40, but not TDP-43, was significantly elevated across all time points. BDNF, apoE4, fetuin, and clusterin levels were significantly diminished long-term. IL-6 and IL-8 levles returned to baseline at t3m. The levels of CRP, CCL-28, and Hsp-70 remained elevated. At 3 months, 8.2% of the patients experienced a stroke, with transfusion volume being a significant variable. Cardiac-surgery patients exhibited persistent peripheral and neuronal inflammation, blood vessel remodeling, and the depletion of neuroprotective factors 3 months post-procedure.
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Affiliation(s)
- Krzysztof Laudanski
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence: ; Tel.: +1-215-662-8000
| | - Da Liu
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110055, China
| | - Tony Okeke
- Department of Bioengineering, Drexel University, Philadelphia, PA 19104, USA
| | - Mariana Restrepo
- College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Wilson Y. Szeto
- Division of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA 19104, USA
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Kasuga K, Kikuchi M, Tsukie T, Suzuki K, Ihara R, Iwata A, Hara N, Miyashita A, Kuwano R, Iwatsubo T, Ikeuchi T. Different AT(N) profiles and clinical progression classified by two different N markers using total tau and neurofilament light chain in cerebrospinal fluid. BMJ Neurol Open 2022; 4:e000321. [PMID: 36046332 PMCID: PMC9379489 DOI: 10.1136/bmjno-2022-000321] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/29/2022] [Indexed: 12/12/2022] Open
Abstract
Background The AT(N) classification was proposed for categorising individuals according to biomarkers. However, AT(N) profiles may vary depending on the markers chosen and the target population. Methods We stratified 177 individuals who participated in the Japanese Alzheimer's Disease Neuroimaging Initiative by AT(N) classification according to cerebrospinal fluid (CSF) biomarkers. We compared the frequency of AT(N) profiles between the classification using total tau and neurofilament light chain (NfL) as N markers (AT(N)tau and AT(N)NfL). Baseline characteristics, and longitudinal biological and clinical changes were examined between AT(N) profiles. Results We found that 9% of cognitively unimpaired subjects, 49% of subjects with mild cognitive impairment, and 61% of patients with Alzheimer's disease (AD) dementia had the biological AD profile (ie, A+T+) in the cohort. The frequency of AT(N) profiles substantially differed between the AT(N)tau and AT(N)NfL classifications. When we used t-tau as the N marker (AT(N)tau), those who had T- were more frequently assigned to (N)-, whereas those who had T+were more frequently assigned to (N)+ than when we used NfL as the N marker (AT(N)NfL). During a follow-up, the AD continuum group progressed clinically and biologically compared with the normal biomarker group in both the AT(N)tau and AT(N)NfL classifications. More frequent conversion to dementia was observed in the non-AD pathological change group in the AT(N)tau classification, but not in the AT(N)NfL classification. Conclusions AT(N)tau and AT(N)NfL in CSF may capture different aspects of neurodegeneration and provide a different prognostic value. The AT(N) classification aids in understanding the AD continuum biology in various populations.
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Affiliation(s)
- Kensaku Kasuga
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | - Masataka Kikuchi
- Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan.,Computational Biology and Medical Science, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Tamao Tsukie
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | - Kazushi Suzuki
- Neurology, National Defense Medical College, Tokorozawa, Japan
| | - Ryoko Ihara
- Neurology, Tokyo Metropolitan Geriatric Medical Center Hospital, Tokyo, Japan
| | - Atsushi Iwata
- Neurology, Tokyo Metropolitan Geriatric Medical Center Hospital, Tokyo, Japan
| | - Norikazu Hara
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | - Akinori Miyashita
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | | | - Takeshi Iwatsubo
- Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takeshi Ikeuchi
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
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Andrews EJ, Martini AC, Head E. Exploring the role of sex differences in Alzheimer's disease pathogenesis in Down syndrome. Front Neurosci 2022; 16:954999. [PMID: 36033603 PMCID: PMC9411995 DOI: 10.3389/fnins.2022.954999] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/25/2022] [Indexed: 11/14/2022] Open
Abstract
Women are disproportionately affected by Alzheimer's disease (AD), yet little is known about sex-specific effects on the development of AD in the Down syndrome (DS) population. DS is caused by a full or partial triplication of chromosome 21, which harbors the amyloid precursor protein (APP) gene, among others. The majority of people with DS in their early- to mid-40s will accumulate sufficient amyloid-beta (Aβ) in their brains along with neurofibrillary tangles (NFT) for a neuropathological diagnosis of AD, and the triplication of the APP gene is regarded as the main cause. Studies addressing sex differences with age and impact on dementia in people with DS are inconsistent. However, women with DS experience earlier age of onset of menopause, marked by a drop in estrogen, than women without DS. This review focuses on key sex differences observed with age and AD in people with DS and a discussion of possible underlying mechanisms that could be driving or protecting from AD development in DS. Understanding how biological sex influences the brain will lead to development of dedicated therapeutics and interventions to improve the quality of life for people with DS and AD.
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Affiliation(s)
- Elizabeth J. Andrews
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
| | - Alessandra C. Martini
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
| | - Elizabeth Head
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, United States
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41
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Nguyen AD, Malmstrom TK, Aggarwal G, Miller DK, Vellas B, Morley JE. Serum neurofilament light levels are predictive of all-cause mortality in late middle-aged individuals. EBioMedicine 2022; 82:104146. [PMID: 35830835 PMCID: PMC9284367 DOI: 10.1016/j.ebiom.2022.104146] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/13/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022] Open
Abstract
Background Blood biomarkers can offer valuable and easily accessible indicators of normal biological processes, pathogenic conditions, and responses to therapeutic interventions. Recent studies found that levels of neurofilament light chain (NfL) in the blood are associated with mortality in three European cohorts of older adults (median ages 73, 93, and 100 years). Whether similar associations exist in younger adults and in other ethnic groups is currently not known. Methods We utilized a cohort study that included 294 African Americans (baseline ages 49–65). Serum NfL levels were measured using a Meso Scale Discovery-based assay. Vital status was determined by matching through the National Death Index. Findings Seventy-two participants (24.5%) died during the 14–15 years of follow up (2000–2014). Baseline serum NfL levels were significantly higher in the decedent group (86.1±65.7 pg/ml vs. 50.1±28.0 pg/ml, p < 0·001). In binomial logistic regression models adjusted for age, gender, education, baseline smoking status, BMI, and total comorbidities (0–11), serum NfL levels remained a strong predictor of all-cause mortality, and sensitivity analyses employing multiple additional covariates did not substantively change the relationship. Further, Kaplan-Meier curves based on serum NfL quartiles showed reduced survival in groups with higher serum NfL levels. Interpretation This study found a positive association between serum NfL levels and mortality in late middle-aged and older individuals. While our findings support that serum NfL levels may be a useful biomarker for all-cause mortality, further studies are needed to understand the biological mechanisms underlying this association. Funding National Institute on Aging, Saint Louis University.
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Affiliation(s)
- Andrew D Nguyen
- Division of Geriatric Medicine, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA; Department of Pharmacology and Physiology, Saint Louis University School of Medicine, St. Louis, MO, USA; Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, USA.
| | - Theodore K Malmstrom
- Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, USA; Department of Psychiatry and Behavioral Neuroscience, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Geetika Aggarwal
- Division of Geriatric Medicine, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA; Department of Pharmacology and Physiology, Saint Louis University School of Medicine, St. Louis, MO, USA; Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, USA
| | | | - Bruno Vellas
- Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse, Toulouse, France; UMR 1295 INSERM, University of Toulouse III, Toulouse, France
| | - John E Morley
- Division of Geriatric Medicine, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA
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Wang L, Western D, Timsina J, Repaci C, Song WM, Norton J, Kohlfeld P, Budde J, Climer S, Butt OH, Jacobson D, Garvin M, Templeton AR, Campagna S, O’Halloran J, Presti R, Goss CW, Mudd PA, Ances BM, Zhang B, Sung YJ, Cruchaga C. Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.07.25.22278025. [PMID: 35923315 PMCID: PMC9347279 DOI: 10.1101/2022.07.25.22278025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10 -14 ), Alzheimer's disease (FDR ≤ 5.46×10 -10 ) and coronary artery disease (FDR ≤ 4.64×10 -2 ). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
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Affiliation(s)
- Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Dan Western
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Charlie Repaci
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Won-Min Song
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Sharlee Climer
- Department of Computer Science, University of Missouri-St. Louis, St. Louis, MO, USA
| | - Omar H. Butt
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Michael Garvin
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Alan R Templeton
- Department of Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Shawn Campagna
- Department of Chemistry, University of Tennessee, Knoxville, TN, USA
| | - Jane O’Halloran
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Rachel Presti
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Charles W. Goss
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip A. Mudd
- Department of Emergency Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Beau M. Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
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Non-Invasive Nasal Discharge Fluid and Other Body Fluid Biomarkers in Alzheimer’s Disease. Pharmaceutics 2022; 14:pharmaceutics14081532. [PMID: 35893788 PMCID: PMC9330777 DOI: 10.3390/pharmaceutics14081532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/12/2022] [Accepted: 07/19/2022] [Indexed: 02/04/2023] Open
Abstract
The key to current Alzheimer’s disease (AD) therapy is the early diagnosis for prompt intervention, since available treatments only slow the disease progression. Therefore, this lack of promising therapies has called for diagnostic screening tests to identify those likely to develop full-blown AD. Recent AD diagnosis guidelines incorporated core biomarker analyses into criteria, including amyloid-β (Aβ), total-tau (T-tau), and phosphorylated tau (P-tau). Though effective, the accessibility of screening tests involving conventional cerebrospinal fluid (CSF)- and blood-based analyses is often hindered by the invasiveness and high cost. In an attempt to overcome these shortcomings, biomarker profiling research using non-invasive body fluid has shown the potential to capture the pathological changes in the patients’ bodies. These novel non-invasive body fluid biomarkers for AD have emerged as diagnostic and pathological targets. Here, we review the potential peripheral biomarkers, including non-invasive peripheral body fluids of nasal discharge, tear, saliva, and urine for AD.
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Johansson M, Stomrud E, Johansson PM, Svenningsson A, Palmqvist S, Janelidze S, van Westen D, Mattsson-Carlgren N, Hansson O. Development of Apathy, Anxiety, and Depression in Cognitively Unimpaired Older Adults: Effects of Alzheimer's Disease Pathology and Cognitive Decline. Biol Psychiatry 2022; 92:34-43. [PMID: 35346458 DOI: 10.1016/j.biopsych.2022.01.012] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/12/2022] [Accepted: 01/16/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND The impact of Alzheimer's disease (AD) pathology and cognitive deficits on longitudinal neuropsychiatric symptoms is unclear, especially in early disease stages. METHODS Cognitively unimpaired older adults (N = 356) enrolled in the prospective Swedish BioFINDER study were examined. Neuropsychiatric assessments encompassed the Apathy Evaluation Scale and the Hospital Anxiety and Depression Scale, performed biennially (together with tests of global cognition) for up to 8 years. Biomarkers were measured in cerebrospinal fluid or plasma at baseline. Magnetic resonance imaging quantified white matter lesions. We used linear mixed-effect models to test associations between baseline AD biomarkers (for amyloid-β [Aβ], tau, and neurodegeneration) and white matter lesions with longitudinal neuropsychiatric symptoms (apathy, anxiety, and depressive symptoms). We also tested associations between changes in cognition and changes in neuropsychiatric symptoms. Finally, we tested if change in cognition mediated the effects of different brain pathologies on neuropsychiatric symptoms. RESULTS Aβ pathology at baseline was associated with increasing levels of apathy (β = -0.284, p = .005) and anxiety (β = -0.060, p = .011) longitudinally. More rapid decline of cognition over time was related to increasing levels of apathy. The effects of baseline Aβ pathology on longitudinal apathy were partly mediated by changes in cognitive performance (proportion mediated 23%). CONCLUSIONS Aβ pathology may drive the development of both apathy and anxiety in very early stages of AD, largely independent of cognitive change. The effect of Aβ on apathy is only partially conveyed by worse cognition. Together, these findings highlight certain neuropsychiatric symptoms as early manifestations of AD.
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Affiliation(s)
- Maurits Johansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Division of Clinical Sciences Helsingborg, Department of Clinical Sciences Lund, Lund University, Helsingborg, Sweden; Clinical Department of Psychiatry, Helsingborg Hospital, Helsingborg, Sweden.
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Per Mårten Johansson
- Division of Clinical Sciences Helsingborg, Department of Clinical Sciences Lund, Lund University, Helsingborg, Sweden; Department of Internal Medicine, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden
| | - Anna Svenningsson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Sebastian Palmqvist
- 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
| | - Danielle van Westen
- Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden; Image and Function, Skåne University Hospital Lund, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden; Department of Neurology, Skåne University Hospital Lund, Lund, Sweden
| | - 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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Delvenne A, Gobom J, Tijms B, Bos I, Reus LM, Dobricic V, Kate MT, Verhey F, Ramakers I, Scheltens P, Teunissen CE, Vandenberghe R, Schaeverbeke J, Gabel S, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, Vos SJB. Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology. Alzheimers Dement 2022; 19:807-820. [PMID: 35698882 DOI: 10.1002/alz.12713] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 04/06/2022] [Accepted: 05/12/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics. METHODS Individuals were classified based on CSF amyloid beta (Aβ)1-42 (A) and phosphorylated tau (T), as cognitively normal A-T- (CN), MCI A-T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed. RESULTS A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus. CONCLUSION The pathophysiology of MCI-SNAP (A-T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD.
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Affiliation(s)
- Aurore Delvenne
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Johan Gobom
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Betty Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Isabelle Bos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Frans Verhey
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Inez Ramakers
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Centers (AUMC), Amsterdam Neuroscience, the Netherlands
| | - Rik Vandenberghe
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jolien Schaeverbeke
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Silvy Gabel
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Julius Popp
- Old Age Psychiatry, University Hospital Lausanne, Lausanne, Switzerland
- Department of Geriatric Psychiatry, Psychiatry University Hospital Zürich, Zürich, Switzerland
| | | | | | - Mikel Tainta
- Fundación CITA-Alzhéimer Fundazioa, San Sebastian, Spain
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Thessaloniki, Greece
| | - Yvonne Freund-Levi
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry in Region Örebro County and School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Old Age Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Simon Lovestone
- University of Oxford, Oxford, United Kingdom (currently at Johnson and Johnson Medical Ltd.), London, UK
| | - Johannes Streffer
- Institute Born-Bunge, Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Belgium
- UCB Biopharma SPRL, Brain-l'Alleud, Belgium
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Institutes of Neurology & Healthcare Engineering, UCL London, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Teitsdottir UD, Darreh-Shori T, Lund SH, Jonsdottir MK, Snaedal J, Petersen PH. Phenotypic Displays of Cholinergic Enzymes Associate With Markers of Inflammation, Neurofibrillary Tangles, and Neurodegeneration in Pre- and Early Symptomatic Dementia Subjects. Front Aging Neurosci 2022; 14:876019. [PMID: 35693340 PMCID: PMC9178195 DOI: 10.3389/fnagi.2022.876019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 05/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background Cholinergic drugs are the most commonly used drugs for the treatment of Alzheimer’s disease (AD). Therefore, a better understanding of the cholinergic system and its relation to both AD-related biomarkers and cognitive functions is of high importance. Objectives To evaluate the relationships of cerebrospinal fluid (CSF) cholinergic enzymes with markers of amyloidosis, neurodegeneration, neurofibrillary tangles, inflammation and performance on verbal episodic memory in a memory clinic cohort. Methods In this cross-sectional study, 46 cholinergic drug-free subjects (median age = 71, 54% female, median MMSE = 28) were recruited from an Icelandic memory clinic cohort targeting early stages of cognitive impairment. Enzyme activity of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) was measured in CSF as well as levels of amyloid-β1–42 (Aβ42), phosphorylated tau (P-tau), total-tau (T-tau), neurofilament light (NFL), YKL-40, S100 calcium-binding protein B (S100B), and glial fibrillary acidic protein (GFAP). Verbal episodic memory was assessed with the Rey Auditory Verbal Learning (RAVLT) and Story tests. Results No significant relationships were found between CSF Aβ42 levels and AChE or BuChE activity (p > 0.05). In contrast, T-tau (r = 0.46, p = 0.001) and P-tau (r = 0.45, p = 0.002) levels correlated significantly with AChE activity. Although neurodegeneration markers T-tau and NFL did correlate with each other (r = 0.59, p < 0.001), NFL did not correlate with AChE (r = 0.25, p = 0.09) or BuChE (r = 0.27, p = 0.06). Inflammation markers S100B and YKL-40 both correlated significantly with AChE (S100B: r = 0.43, p = 0.003; YKL-40: r = 0.32, p = 0.03) and BuChE (S100B: r = 0.47, p < 0.001; YKL-40: r = 0.38, p = 0.009) activity. A weak correlation was detected between AChE activity and the composite score reflecting verbal episodic memory (r = −0.34, p = 0.02). LASSO regression analyses with a stability approach were performed for the selection of a set of measures best predicting cholinergic activity and verbal episodic memory score. S100B was the predictor with the highest model selection frequency for both AChE (68%) and BuChE (73%) activity. Age (91%) was the most reliable predictor for verbal episodic memory, with selection frequency of both cholinergic enzymes below 10%. Conclusions Results indicate a relationship between higher activity of the ACh-degrading cholinergic enzymes with increased neurodegeneration, neurofibrillary tangles and inflammation in the stages of pre- and early symptomatic dementia, independent of CSF Aβ42 levels.
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Affiliation(s)
- Unnur D. Teitsdottir
- Faculty of Medicine, Department of Anatomy, Biomedical Center, University of Iceland, Reykjavik, Iceland
- *Correspondence: Unnur D. Teitsdottir
| | - Taher Darreh-Shori
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | | | - Maria K. Jonsdottir
- Department of Psychology, Reykjavik University, Reykjavik, Iceland
- Department of Psychiatry, Landspitali-National University Hospital, Reykjavik, Iceland
| | - Jon Snaedal
- Memory Clinic, Department of Geriatric Medicine, Landspitali-National University Hospital, Reykjavik, Iceland
| | - Petur H. Petersen
- Faculty of Medicine, Department of Anatomy, Biomedical Center, University of Iceland, Reykjavik, Iceland
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47
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Marutani N, Akamine S, Kanayama D, Gotoh S, Yanagida K, Maruyama R, Mori K, Miyamoto T, Adachi H, Sakagami Y, Yoshiyama K, Hotta M, Nagase A, Kozawa J, Maeda N, Otsuki M, Matsuoka T, Iwahashi H, Shimomura I, Murayama N, Watanabe H, Ikeda M, Mizuta I, Kudo T. Plasma NfL is associated with mild cognitive decline in patients with diabetes. Psychogeriatrics 2022; 22:353-359. [PMID: 35279914 DOI: 10.1111/psyg.12819] [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: 12/06/2021] [Revised: 01/27/2022] [Accepted: 02/01/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Patients with diabetes are at a higher risk for cognitive decline. Thus, biomarkers that can provide early and simple detection of cognitive decline are required. Neurofilament light chain (NfL) is a cytoskeletal protein that constitutes neural axons. Plasma NfL levels are elevated when neurodegeneration occurs. Here, we investigated whether plasma NfL levels were associated with cognitive decline in patients with type 2 diabetes. METHOD This study included 183 patients with type 2 diabetes who visited Osaka University Hospital. All participants were tested for cognitive function using the Mini-Mental State Examination (MMSE) and the Rivermead Behavioural Memory Test (RBMT). NfL levels were analysed in the plasma and the relationship between NfL and cognitive function was examined. RESULTS Lower RBMT-standardized profile scores (SPS) or MMSE scores correlated with higher plasma NfL levels (one-way analysis of variance: MMSE, P = 0.0237; RBMT-SPS, P = 0.0001). Furthermore, plasma NfL levels (β = -0.34, P = 0.0005) and age (β = -0.19, P = 0.016) were significantly associated with the RBMT score after multivariable regression adjustment. CONCLUSIONS Plasma NfL levels were correlated with mild cognitive decline which is detected by the RBMT but not the MMSE in patients with type 2 diabetes. This suggests that plasma NfL levels may provide a valuable clinical tool for identifying mild cognitive decline in patients with diabetes.
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Affiliation(s)
- Noriko Marutani
- Health and Counseling Center, Osaka University, Osaka, Japan
| | - Shoshin Akamine
- Health and Counseling Center, Osaka University, Osaka, Japan
| | - Daisuke Kanayama
- Health and Counseling Center, Osaka University, Osaka, Japan.,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Shiho Gotoh
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kanta Yanagida
- Health and Counseling Center, Osaka University, Osaka, Japan
| | | | - Kohji Mori
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Tesshin Miyamoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hiroyoshi Adachi
- Health and Counseling Center, Osaka University, Osaka, Japan.,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yukako Sakagami
- Health and Counseling Center, Osaka University, Osaka, Japan.,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kenji Yoshiyama
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Maki Hotta
- Department of Behavioral Neurology and Neuropsychiatry, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Aki Nagase
- Department of Behavioral Neurology and Neuropsychiatry, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Junji Kozawa
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, Osaka, Japan.,Department of Diabetes Care Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Norikazu Maeda
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, Osaka, Japan.,Department of Metabolism and Atherosclerosis, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Michio Otsuki
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Takaaki Matsuoka
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hiromi Iwahashi
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, Osaka, Japan.,Department of Diabetes Care Medicine, Osaka University Graduate School of Medicine, Osaka, Japan.,Department of Internal Medicine, Toyonaka Municipal Hospital, Osaka, Japan
| | - Iichiro Shimomura
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Norihito Murayama
- Research Institute, Suntory Global Innovation Center Limited, Suntory World Research Center, Tokyo, Japan
| | - Hiroshi Watanabe
- Research Institute, Suntory Global Innovation Center Limited, Suntory World Research Center, Tokyo, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ichiro Mizuta
- Health and Counseling Center, Osaka University, Osaka, Japan.,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Takashi Kudo
- Health and Counseling Center, Osaka University, Osaka, Japan.,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
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Meeker KL, Butt OH, Gordon BA, Fagan AM, Schindler SE, Morris JC, Benzinger TLS, Ances BM. Cerebrospinal fluid neurofilament light chain is a marker of aging and white matter damage. Neurobiol Dis 2022; 166:105662. [PMID: 35167933 PMCID: PMC9112943 DOI: 10.1016/j.nbd.2022.105662] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/09/2022] [Accepted: 02/10/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Cerebrospinal fluid (CSF) neurofilament light chain (NfL) reflects neuro-axonal damage and is increasingly used to evaluate disease progression across neurological conditions including Alzheimer disease (AD). However, it is unknown how NfL relates to specific types of brain tissue. We sought to determine whether CSF NfL is more strongly associated with total gray matter, white matter, or white matter hyperintensity (WMH) volume, and to quantify the relative importance of brain tissue volume, age, and AD marker status (i.e., APOE genotype, brain amyloidosis, tauopathy, and cognitive status) in predicting CSF NfL. METHODS 419 participants (Clinical Dementia Rating [CDR] Scale > 0, N = 71) had CSF, magnetic resonance imaging (MRI), and neuropsychological data. A subset had amyloid positron emission tomography (PET) and tau PET. Pearson correlation analysis was used to determine the association between CSF NfL and age. Multiple regression was used to determine which brain volume (i.e., gray, white, or WMH volume) most strongly associated with CSF NfL. Stepwise regression and dominance analyses were used to determine the individual contributions and relative importance of brain volume, age, and AD marker status in predicting CSF NfL. RESULTS CSF NfL increased with age (r = 0.59, p < 0.001). Elevated CSF NfL was associated with greater total WMH volume (p < 0.001), but not gray or white matter volume (p's > 0.05) when considered simultaneously. Age and WMH volume were consistently more important (i.e., have greater R2 values) than AD markers when predicting CSF NfL. CONCLUSIONS CSF NfL is a non-specific marker of aging and white matter integrity with limited sensitivity to specific markers of AD. CSF NfL likely reflects processes associated with cerebrovascular disease.
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Affiliation(s)
- Karin L Meeker
- Department of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
| | - Omar H Butt
- Department of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Suzanne E Schindler
- Department of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Beau M Ances
- Department of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
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49
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Cerebrospinal Fluid Neurofilament Light Predicts Risk of Dementia Onset in Cognitively Healthy Individuals and Rate of Cognitive Decline in Mild Cognitive Impairment: A Prospective Longitudinal Study. Biomedicines 2022; 10:biomedicines10051045. [PMID: 35625782 PMCID: PMC9138299 DOI: 10.3390/biomedicines10051045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 12/10/2022] Open
Abstract
Background: Biomarkers that are indicative of early biochemical aberrations are needed to predict the risk of dementia onset and progression in Alzheimer’s disease (AD). We assessed the utility of cerebrospinal fluid (CSF) neurofilament light (NfL) chain for screening preclinical AD, predicting dementia onset among cognitively healthy (CH) individuals, and the rate of cognitive decline amongst individuals with mild cognitive impairment (MCI). Methods: Neurofilament light levels were measured in CSF samples of participants (CH, n = 154 and MCI, n = 32) from the Australian Imaging, Biomarkers and Lifestyle study of ageing (AIBL). Cases of preclinical AD were identified using biomarker-guided classification (CH, amyloid-β [Aβ]+, phosphorylated-tau [P-tau]+ and total-tau [T-tau]±; A+T+/N±). The prediction of dementia onset (questionable dementia) among CH participants was assessed as the risk of conversion from Clinical Dementia Rating [CDR = 0] to CDR ≥ 0.5 over 6 years. Mixed linear models were used to assess the utility of baseline CSF NfL levels for predicting the rate of cognitive decline among participants with MCI over 4.5 years. Results: Neurofilament light levels were significantly higher in preclinical AD participants (CH, A+T+/N±) as compared to A-T-N- (p < 0.001). Baseline levels of CSF NfL were higher in CH participants who converted to CDR ≥ 0.5 over 6 years (p = 0.045) and the risk of conversion to CDR ≥ 0.5 was predicted (hazard ratio [HR] 1.60, CI 1.03−2.48, p = 0.038). CH participants with CSF NfL > cut-off were at a higher risk of developing dementia (HR 4.77, CI 1.31−17.29, p = 0.018). Participants with MCI and with higher baseline levels of CSF NfL (>median) had a higher rate of decline in cognition over 4.5 years. Conclusion: An assessment of CSF NfL levels can help to predict dementia onset among CH vulnerable individuals and cognitive decline among those with MCI.
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50
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Alawode DOT, Fox NC, Zetterberg H, Heslegrave AJ. Alzheimer’s Disease Biomarkers Revisited From the Amyloid Cascade Hypothesis Standpoint. Front Neurosci 2022; 16:837390. [PMID: 35573283 PMCID: PMC9091905 DOI: 10.3389/fnins.2022.837390] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 04/04/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common neurodegenerative disease worldwide. Amyloid beta (Aβ) is one of the proteins which aggregate in AD, and its key role in the disease pathogenesis is highlighted in the amyloid cascade hypothesis, which states that the deposition of Aβ in the brain parenchyma is a crucial initiating step in the future development of AD. The sensitivity of instruments used to measure proteins in blood and cerebrospinal fluid has significantly improved, such that Aβ can now successfully be measured in plasma. However, due to the peripheral production of Aβ, there is significant overlap between diagnostic groups. The presence of pathological Aβ within the AD brain has several effects on the cells and surrounding tissue. Therefore, there is a possibility that using markers of tissue responses to Aβ may reveal more information about Aβ pathology and pathogenesis than looking at plasma Aβ alone. In this manuscript, using the amyloid cascade hypothesis as a starting point, we will delve into how the effect of Aβ on the surrounding tissue can be monitored using biomarkers. In particular, we will consider whether glial fibrillary acidic protein, triggering receptor expressed on myeloid cells 2, phosphorylated tau, and neurofilament light chain could be used to phenotype and quantify the tissue response against Aβ pathology in AD.
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Affiliation(s)
- Deborah O. T. Alawode
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- *Correspondence: Deborah O. T. Alawode,
| | - Nick C. Fox
- UK Dementia Research Institute at UCL, London, United Kingdom
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Amanda J. Heslegrave
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Amanda J. Heslegrave,
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