Gene-environment interactions in Multiple Sclerosis: from etiology to therapy, and prevention

This dissertation presents a body of research work investigating three distinct, yet interrelated research domains in multiple sclerosis (MS): (1) Genetics: mechanisms and pathophysiology, (2) Gene–environment interactions: etiology and therapy, and (3) Environmental factors and opportunities for prevention. Each domain is addressed using computational genomics and systems-biology methodologies, with the aim of contributing mechanistic insight and translational potential. In the first domain — Genetics: mechanisms and pathophysiology — genome-wide data, and network-modeling of monogenic-to-polygenic relationships were deployed to delineate latent pathophysiological axes of MS. Moreover, genomic analyses of MS severity were undertaken to genetic-driven biological determinants of long-term disability accumulation, identifying novel candidate genes and cell-specific mechanisms. In the second domain — Gene–environment interactions: etiology and therapy — the research examines how host genetic risk interfaces with viral exposure (particularly Epstein–Barr virus) and molecular-network perturbations. Host–virus interactome enrichment analyses, transient‐transcriptome colocalization, and functional mapping methods were employed to identify convergence points of inherited and environmental risk, and to elucidate mechanistic intersections pertinent to therapeutic modulation. In the third domain — Environmental factors and opportunities for prevention — the focus shifts to upstream, modifiable factors and their translational potential. Within this domain two main analytical streams are distinguished: (a) microbiome-strain-level association studies assessing specific gut microbial taxa as antecedent modulators of MS risk, and (b) epidemiological and genetic analyses quantifying the risk of infectious mononucleosis (IM) associated with vitamin D deficiency and evaluating vitamin D status as a modifiable precursor in the MS causal chain. The combined analysis addresses how these environmental exposures operate within gene–environment interaction hotspots and how their modulation may interrupt the trajectory from inherited susceptibility to disease emergence.