Identifying molecular factors that drive MS severity remains a major challenge. Although multi-omic profiling offers a powerful framework to study disease mechanisms, large-scale integrative analyses in MS remain limited. Leveraging comprehensive serum proteomic and metabolomic datasets enables unbiased identification of molecular signatures associated with disease severity and provides insight into processes contributing to MS progression.

Two distinct molecular groups were identified. The first group, associated with imaging outcomes, comprised metabolites related to mitochondrial and membrane metabolism (DHEA-S, phosphoethanolamine, taurine, sphingomyelins) and proteins involved in immune signaling, receptor activity, and axonal guidance, including TNFRSF1A, FZD2, FZD7, EPHA2, EFNA5, CD46, TIMP1, and SPON2. The second group, associated with clinical and patient-reported outcomes, was characterized by carnitine and lipid derivatives (palmitoleoylcarnitine [C16:1], myristoylcarnitine [C14], sphingomyelins) together with proteins linked to ubiquitination, proteostasis, oxidative stress, and cytoskeletal regulation, including HSPB1, HSPA5, PARK7, BAG3, UBE2L6, ATXN3, GLO1, and PRDX1.

Using multi-omic analysis, we identified distinct molecular groups and pathways associated with multiple MS severity metrics in a large cohort.