CSF proteome in multiple sclerosis subtypes related to brain lesion transcriptomes

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作者
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
机构
[1] Odense University Hospital,Department of Neurology
[2] University of Southern Denmark,Institute of Clinical Research
[3] University of Southern Denmark,Institute of Molecular Medicine
[4] University of Southern Denmark,Department of Biochemistry and Molecular Biology
[5] TUM School of Life Sciences Weihenstephan,Research Group Computational Systems Medicine, Chair of Experimental Bioinformatics
[6] Technical University of Munich,Danish Dementia Research Centre
[7] Division Data Science in Biomedicine,Department of Neurology
[8] Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Medical School Hannover,Regional Dementia Research Centre, Department of Neurology
[9] Copenhagen University Hospital Rigshospitalet,Department of Clinical Medicine
[10] Service de Neurologie,Danish Multiple Sclerosis Center, Department of Neurology
[11] Sclérose en Plaques,Department of Brain Sciences
[12] Lyon Neuroscience Research Center,Department of Mathematics and Computer Science
[13] Hospital South West Jutland,Chair of Experimental Bioinformatics
[14] University Hospital of Southern Denmark,undefined
[15] Zealand University Hospital,undefined
[16] University of Copenhagen,undefined
[17] Copenhagen University Hospital – Rigshospitalet,undefined
[18] Glostrup,undefined
[19] Denmark.,undefined
[20] Imperial College,undefined
[21] University of Southern Denmark,undefined
[22] TUM School of Life Sciences Weihenstephan,undefined
[23] Technical University of Munich,undefined
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摘要
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.
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