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Data for: Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Immunology and Transfusion Medicine.ORCID iD: 0000-0001-9456-2044
Department of Clinical Neuroscience, Karolinska Institute.ORCID iD: 0000-0002-2938-1877
2023 (English)Data set
Physical description [en]

Raw data: supplementary information to publication

Abstract [en]

Protein levels were measured in cerebrospinal fluid samples (CSF; n = 186) and plasma samples (n = 165) from persons with multiple sclerosis and healthy controls. CSF samples and plasma samples were taken from 92 persons with CIS or RRMS at Linköping University Hospital, Sweden and 51 persons with CIS or RRMS at the Karolinska University Hospital, Sweden. Everyone fulfilled the revised McDonald criteria from 2010 and 2017 for CIS or Multiple sclerosis (MS). Age-matched healthy controls (HC) were recruited from healthy blood donors (23 at the Linköping University hospital and 20 at the Karolinska University Hospital). The concentration of 1463 proteins were measured using the Olink Explore platform which uses Proximity Extension Assay (PEA) technology. The proteins were preselected from four Olink panels: Explore 384 Cardiometabolic, Explore 384 Inflammation, Explore 384 Neurology, and Explore 384 Oncology. The protein concentrations are given as Olink’s relative protein quantification unit on log2 scale: Normalized Protein Expression (NPX). The NPX values were intensity normalized by Olink.

Place, publisher, year
2023.
Keywords [en]
multiple sclerosis, proteomics
National Category
Neurology Bioinformatics and Systems Biology Bioinformatics (Computational Biology) Rheumatology and Autoimmunity
Identifiers
URN: urn:nbn:se:liu:diva-198043DOI: 10.48360/jcps-gw67OAI: oai:DiVA.org:liu-198043DiVA, id: diva2:1799625
Note

For access to dataset, please contact mika.gustafsson@liu.se for further information.

Research funders:

Swedish Foundation for Strategic Research (SB16-0011)

Swedish Brain Foundation

Knut and Alice Wallenberg Foundation

Margareth AF Ugglas Foundation

Swedish Research Council (2019-04193, 2018-02776, 2020-02700, 2021-03092)

Swedish Knowledge Foundation (2020-0014)

Medical Research Council of Southeast Sweden (FORSS-315121)

NEURO Sweden (F2018-0052)

ALF grants

Region Östergötland

Swedish Foundation for MS Research

European Union's  Marie Sklodowska-Curie (813863)

Available from: 2023-09-22 Created: 2023-09-22 Last updated: 2024-05-03

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Gustafsson, MikaErnerudh, Jan

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Gustafsson, MikaErnerudh, JanOlsson, Tomas
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BioinformaticsFaculty of Science & EngineeringDivision of Inflammation and InfectionFaculty of Medicine and Health SciencesDepartment of Clinical Immunology and Transfusion Medicine
NeurologyBioinformatics and Systems BiologyBioinformatics (Computational Biology)Rheumatology and Autoimmunity
Åkesson, J., Hojjati, S., Hellberg, S., Raffetseder, J., Khademi, M., Rynkowski, R., . . . Gustafsson, M. (2023). Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis. Nature Communications, 14(1), Article ID 6903.

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