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Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis
University of Skövde, School of Bioscience. University of Skövde, Systems Biology Research Environment. Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Sweden. (Translationell bioinformatik, Translational bioinformatics)ORCID iD: 0000-0002-9276-0546
Division of Inflammation and Infection, Department of Biomedical and Clinical Sciences, Linköping University, Sweden.
Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Sweden ; Division of Inflammation and Infection, Department of Biomedical and Clinical Sciences, Linköping University, Sweden.
Division of Inflammation and Infection, Department of Biomedical and Clinical Sciences, Linköping University, Sweden.ORCID iD: 0000-0001-8871-2560
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2023 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 14, no 1, article id 6903Article in journal (Refereed) Published
Abstract [en]

Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts, we identify CSF proteins that consistently predicted both short- and long-term disease progression. Lower levels of neurofilament light chain (NfL) in CSF is superior in predicting the absence of disease activity two years after sampling (replication AUC = 0.77) compared to all other tested proteins. Importantly, we also identify a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B and NfL) that predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). The identification of these proteins may help elucidate pathogenetic processes and might aid decisions on treatment strategies for persons with MS.

Place, publisher, year, edition, pages
Springer Nature, 2023. Vol. 14, no 1, article id 6903
National Category
Neurosciences Rheumatology and Autoimmunity Bioinformatics and Systems Biology Bioinformatics (Computational Biology)
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:his:diva-23344DOI: 10.1038/s41467-023-42682-9ISI: 001129872400021PubMedID: 37903821Scopus ID: 2-s2.0-85175444895OAI: oai:DiVA.org:his-23344DiVA, id: diva2:1810642
Funder
Swedish Foundation for Strategic Research, SB16-0011The Swedish Brain FoundationKnut and Alice Wallenberg FoundationSwedish Research Council, 2019-04193Swedish Research Council, 2018-02776Swedish Research Council, 2020-02700Swedish Research Council, 2020-00014Swedish Research Council, 2021-03092Medical Research Council of Southeast Sweden (FORSS), FORSS-315121Swedish Association of Persons with Neurological Disabilities, F2018-0052
Note

CC BY 4.0

e-mail: mika.gustafsson@liu.se

The study was funded by the Swedish Foundation for Strategic Research (SB16-0011 [M.G., J.E.]), the Swedish Brain Foundation, Knut and Alice Wallenberg Foundation, and Margareth AF Ugglas Foundation, Swedish Research Council (2019-04193 [M.G.], 2018-02776 [J.E.], 2020-02700 [F.P.], 2020-00014 [Z.L.P.], 2021-03092 [J.E.]), the Medical Research Council of Southeast Sweden (FORSS-315121 [J.E.]), NEURO Sweden (F2018-0052 [J.E.]), ALF grants, Region Östergötland, the Swedish Foundation for MS Research and the European Union’s Marie Sklodowska-Curie (813863 [J.E.]). The authors would like to acknowledge support of the Clinical biomarker facility at SciLifeLab Sweden for providing assistance in protein analyses.

Open access funding provided by Linköping University.

Available from: 2023-11-08 Created: 2023-11-08 Last updated: 2024-05-20Bibliographically approved

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Åkesson, JuliaLubovac-Pilav, Zelmina

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Åkesson, JuliaRaffetseder, JohannaKhademi, MohsenKockum, IngridAltafini, ClaudioLubovac-Pilav, ZelminaMellergård, JohanJenmalm, Maria C.Piehl, FredrikErnerudh, JanGustafsson, Mika
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