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Project

Approaching multiple sclerosis from a computational perspective through bioinformatic analysis of the T-cell repertoire.

Recent developments in the field of sequencing technology allow for the characterization of adaptive immune receptor repertoires with unprecedented detail. T-cell receptor (TCR) sequencing holds tremendous promise for understanding the involvement and dynamics of adaptive immune components in autoimmune disorders. As the field is rapidly evolving from pre-processing of TCR-seq data to functional analysis of adaptive immune repertoires, new opportunities emerge for the development of comprehensive approaches for the post-analysis of immune receptor profiles. These approaches can offer comprehensive solutions to address clinical questions in the research on autoimmune disorders. An important example is multiple sclerosis (MS), a neuroinflammatory disease of the central nervous system, for which very little is known about the specific T-cell clones involved in its pathogenesis. By analysing the adaptive immune repertoire of MS patients, we postulate it is possible to uncover key drivers of the MS disease process. The identified T-cell clones will present themselves as highly specific biomarkers and therapeutic targets. This translational research project will lead to novel approaches for the identification of condition-associated T-cell clones, to new monitoring tools to evaluate the efficacy of MS-therapies and to a model to predict the disease course of MS.
Date:1 Nov 2020 →  Today
Keywords:MULTIPLE SCLEROSIS, BIOINFORMATICS
Disciplines:Data mining, Bioinformatics of disease, Computational biomodelling and machine learning, Single-cell data analysis, Adaptive immunology