Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit

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• dc.contributor.author Johnson, Sterling C.
• dc.contributor.author Suárez-Calvet, Marc
• dc.contributor.author Suridjan, Ivonne
• dc.contributor.author Minguillón, Carolina
• dc.contributor.author Gispert López, Juan Domingo
• dc.contributor.author Jonaitis, Erin
• dc.contributor.author Michna, Agatha
• dc.contributor.author Carboni, Margherita
• dc.contributor.author Bittner, Tobias
• dc.contributor.author Rabe, Christina
• dc.contributor.author Kollmorgen, Gwendlyn
• dc.contributor.author Zetterberg, Henrik
• dc.contributor.author Blennow, Kaj
• dc.date.accessioned 2023-12-18T06:55:32Z
• dc.date.available 2023-12-18T06:55:32Z
• dc.date.issued 2023
• dc.description.abstract Background: Alzheimer's disease (AD) is a complex and heterogeneous disease, which requires reliable biomarkers for diagnosis and monitoring disease activity. Preanalytical protocol and technical variability associated with biomarker immunoassays makes comparability of biomarker data across multiple cohorts difficult. This study aimed to compare cerebrospinal fluid (CSF) biomarker results across independent cohorts, including participants spanning the AD continuum. Methods: Measured on the NeuroToolKit (NTK) prototype panel of immunoassays, 12 CSF biomarkers were evaluated from three cohorts (ALFA+, Wisconsin, and Abby/Blaze). A correction factor was applied to biomarkers found to be affected by preanalytical procedures (amyloid-β1-42, amyloid-β1-40, and alpha-synuclein), and results between cohorts for each disease stage were compared. The relationship between CSF biomarker concentration and cognitive scores was evaluated. Results: Biomarker distributions were comparable across cohorts following correction. Correlations of biomarker values were consistent across cohorts, regardless of disease stage. Disease stage differentiation was highest for neurofilament light (NfL), phosphorylated tau, and total tau, regardless of the cohort. Correlation between biomarker concentration and cognitive scores was comparable across cohorts, and strongest for NfL, chitinase-3-like protein-1 (YKL40), and glial fibrillary acidic protein. Discussion: The precision of the NTK enables merging of biomarker datasets, after correction for preanalytical confounders. Assessment of multiple cohorts is crucial to increase power in future studies into AD pathogenesis.
• dc.description.sponsorship The ALFA+ study receives funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004 and the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007). For the Wisconsin studies, CSF assay kits were provided by Roche Diagnostics GmbH. Data were collected under the following grants from the NIH National Institute of Aging: R01 AG027161, R01 AG037639, R01AG054059 UF1AG051216, P50 AG033514, and P30 AG062715. Support was also provided by the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR000427 (Clinical and Translational Sciences). MSC receives funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement No. 948677), the Instituto de Salud Carlos III (PI19/00155), and a fellowship from “la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie (grant agreement No. 847648; LCF/BQ/PR21/11840004). JDG is supported by the Spanish Ministry of Science and Innovation (RYC-2013-13054). JDG has also received research support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking AMYPAD (grant agreement 115952), EIT Digital (Grant 2021), and from Ministerio de Ciencia y Universidades (grant agreement RTI2018-102261). HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532); the European Research Council (#681712); Swedish State Support for Clinical Research (#ALFGBG-720931); the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862); the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C and #ADSF-21-831377-C); the Olav Thon Foundation; the Erling-Persson Family Foundation; Stiftelsen för Gamla Tjänarinnor; Hjärnfonden, Sweden (#FO2019-0228); the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE); and the UK Dementia Research Institute at UCL. KB is supported by the Swedish Research Council (#2017-00915); the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615); the Swedish Alzheimer Foundation (#AF-742881); Hjärnfonden, Sweden (#FO2017-0243); the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986); the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236); the National Institute of Health (NIH), USA (grant #1R01AG068398-01); and the Alzheimer’s Association 2021 Zenith Award (ZEN-21-848495).
• dc.format.mimetype application/pdf
• dc.identifier.citation Johnson SC, Suárez-Calvet M, Suridjan I, Minguillón C, Gispert JD, Jonaitis E, Michna A, Carboni M, Bittner T, Rabe C, Kollmorgen G, Zetterberg H, Blennow K. Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit. Alzheimers Res Ther. 2023 Jan 28;15(1):25. DOI: 10.1186/s13195-023-01168-y
• dc.identifier.doi http://dx.doi.org/10.1186/s13195-023-01168-y
• dc.identifier.issn 1758-9193
• dc.identifier.uri http://hdl.handle.net/10230/58552
• dc.language.iso eng
• dc.publisher BioMed Central
• dc.relation.ispartof Alzheimer's Research & Therapy. 2023 Jan 28;15(1):25
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/948677
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/847648
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/115952
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/RTI2018-102261
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/681712
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/860197
• dc.rights © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/publicdomain/zero/1.0/
• dc.subject.keyword Alzheimer’s disease
• dc.subject.keyword Amyloid-β
• dc.subject.keyword Cerebrospinal fluid biomarkers
• dc.subject.keyword Glial activation
• dc.subject.keyword Inflammation
• dc.subject.keyword Neurodegeneration
• dc.title Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion