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Mapping cell-specific changes and interactions in subcortical multiple sclerosis lesions through paired transcriptomics

Lerma Martin, Celia

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Abstract

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, characterized by complex interactions between immune and glial cells. Despite advancements in understanding MS pathology, the molecular mechanisms that drive lesion formation, progression and resolution remain unknown. In my thesis, I want to explore the disease progression and tissue changes happening in control of subcortical white matter compared to subcortical MS lesions. Specifically, I focused on inflamed chronic active (CA) and non-inflamed chronic inactive (CI) lesions with an emphasis on the lesion rim. My aim is to characterize the molecular and cellular drivers underlying progression of these MS lesions using advanced transcriptomic techniques and properly validating them through several methods, such as single-molecule fluorescence in situ hybridization or immunofluorescence.

To achieve this, I opted for a combined approach, creating a paired single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics (ST) dataset to generate a high-resolution transcriptomic atlas. This approach provides a high cellular resolution based on gene expression, which allowed the identification of cell communities, as well as the study of cell type-specific drivers of inflammation and cell-cell communication in lesion and non-lesion areas. Among these findings, I discovered a previously unidentified astrocyte subtype localized at the lesion core, characterized by the presence of enlarged, motile-like cilia.

These findings provide new insight into the cellular drivers and mechanisms involved in MS lesion progression and cell-cell communication at the lesion rim, which could help identify potential therapeutic targets for halting the disease. Additionally, the methodological approaches that I have used, offer a valuable accessible framework for other scientists to apply to their own data, potentially uncovering therapeutic targets beyond MS.

Document type: Dissertation
Supervisor: Martin-Villalba, Prof. Dr. Ana
Place of Publication: Heidelberg
Date of thesis defense: 6 February 2025
Date Deposited: 05 Mar 2025 14:10
Date: 2025
Faculties / Institutes: The Faculty of Bio Sciences > Dean's Office of the Faculty of Bio Sciences
DDC-classification: 004 Data processing Computer science
500 Natural sciences and mathematics
Uncontrolled Keywords: Neuroimmunology
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