CSF proteome in multiple sclerosis subtypes related to brain lesion transcriptomes.

Maria L Elkjaer, Arkadiusz Nawrocki, Tim Kacprowski, Pernille Lassen, Anja Hviid Simonsen, Romain Marignier, Tobias Sejbaek, Helle H Nielsen, Lene Wermuth, Alyaa Yakut Rashid, Peter Høgh, Finn Sellebjerg, Richard Reynolds, Jan Baumbach, Martin R Larsen, Zsolt Illes

Journal: Scientific reports 2021;11(1):4132

PMID: 33603109

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Abstract

To identify markers in the CSF of multiple sclerosis (MS) subtypes, we used a two-step proteomic approach: (i) Discovery proteomics compared 169 pooled CSF from MS subtypes and inflammatory/degenerative CNS diseases (NMO spectrum and Alzheimer disease) and healthy controls. (ii) Next, 299 proteins selected by comprehensive statistics were quantified in 170 individual CSF samples. (iii) Genes of the identified proteins were also screened among transcripts in 73 MS brain lesions compared to 25 control brains. F-test based feature selection resulted in 8 proteins differentiating the MS subtypes, and secondary progressive (SP)MS was the most different also from controls. Genes of 7 out these 8 proteins were present in MS brain lesions: GOLM was significantly differentially expressed in active, chronic active, inactive and remyelinating lesions, FRZB in active and chronic active lesions, and SELENBP1 in inactive lesions. Volcano maps of normalized proteins in the different disease groups also indicated the highest amount of altered proteins in SPMS. Apolipoprotein C-I, apolipoprotein A-II, augurin, receptor-type tyrosine-protein phosphatase gamma, and trypsin-1 were upregulated in the CSF of MS subtypes compared to controls. This CSF profile and associated brain lesion spectrum highlight non-inflammatory mechanisms in differentiating CNS diseases and MS subtypes and the uniqueness of SPMS.

Address: Department of Neurology, Odense University Hospital, J.B. Winslowsvej 4, 5000, Odense C, Denmark.; Institute of Clinical Research, University of Southern Denmark, Odense, Denmark.; Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark.; Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark.; Research Group Computational Systems Medicine, Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.; Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Medical School Hannover, Brunswick, Germany.; Danish Dementia Research Centre, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.; Service de Neurologie, Sclérose en Plaques, Lyon Neuroscience Research Center, Lyon, France.; Department of Neurology, Hospital South West Jutland, University Hospital of Southern Denmark, Esbjerg, Denmark.; Regional Dementia Research Centre, Department of Neurology, Zealand University Hospital, Roskilde, Denmark.; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.; Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Glostrup, Denmark., Copenhagen, Denmark.; Department of Brain Sciences, Imperial College, London, UK.; Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.; Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.; Department of Neurology, Odense University Hospital, J.B. Winslowsvej 4, 5000, Odense C, Denmark. [email protected].; Institute of Clinical Research, University of Southern Denmark, Odense, Denmark. [email protected].; Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark. [email protected].

DOI: 10.1038/s41598-021-83591-5

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MeSH Terms: Adult, Biomarkers, Brain, Cerebrospinal Fluid, Female, Humans, Male, Multiple Sclerosis, Chronic Progressive, Proteome, Proteomics, Remyelination, Selenium-Binding Proteins, Transcriptome