Development of potential biomarkers to forecast treatment response and clinical relapses of multiple sclerosis by investigating the CNS-specific proteome fingerprint of experimental autoimmune encephalomyelitis

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dc.contributor.advisorForsthuber, Thomas G.
dc.contributor.authorRaphael, Itay
dc.contributor.committeeMemberHaskins, William E.
dc.contributor.committeeMemberGuentzel, M. Neal
dc.contributor.committeeMemberCardona, Astrid E.
dc.contributor.committeeMemberWang, Yufeng
dc.date.accessioned2024-02-12T19:52:43Z
dc.date.available2018-08-19
dc.date.available2024-02-12T19:52:43Z
dc.date.issued2016
dc.descriptionThis item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID.
dc.description.abstractDespite extensive research, multiple sclerosis (MS) remains a disease that lacks a definitive prognostic test to predict imminent disease relapses. Thus, patients may undergo years of unnecessary treatments. To address these issues, we developed a high-throughput quantitative proteomics method designated M2-proteomics to measure changes in proteome expression over the course of the preclinical experimental autoimmune encephalomyelitis (EAE) model of MS. Our studies revealed characteristic CNS-specific protein expression waves prior to the onset of clinical symptoms in EAE. Bioinformatics and statistical analyses revealed candidate predicative biomarkers to forecast the onset of clinical symptoms, and thereby onset of clinical relapses of MS. Importantly, we detected these proteins in serum and expression trajectories analysis identified a strong correlation of the CNS proteome to their levels in serum. Prospective studies in the EAE model showed the effectiveness of these proteins in predicting clinical disease. Our studies suggest the utility for establishing homologous protein biomarkers in human MS patients. Finally, our work investigating the CNS proteome over the course of EAE provides us with unique insights and novel molecular targets for disease mechanisms and treatments of MS.
dc.description.departmentIntegrative Biology
dc.format.extent182 pages
dc.format.mimetypeapplication/pdf
dc.identifier.isbn9781369059434
dc.identifier.urihttps://hdl.handle.net/20.500.12588/5241
dc.languageen
dc.subjectBiomarker
dc.subjectEAE
dc.subjectMultiple Sclerosis
dc.subjectProteomics
dc.subject.classificationImmunology
dc.subject.classificationBiochemistry
dc.subject.classificationBioinformatics
dc.subject.classificationchemistry
dc.titleDevelopment of potential biomarkers to forecast treatment response and clinical relapses of multiple sclerosis by investigating the CNS-specific proteome fingerprint of experimental autoimmune encephalomyelitis
dc.typeThesis
dc.type.dcmiText
dcterms.accessRightspq_closed
thesis.degree.departmentIntegrative Biology
thesis.degree.grantorUniversity of Texas at San Antonio
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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