Background There are currently no specific biomarkers for multiple sclerosis (MS). Identifying robust biomarkers for MS is crucial to improve disease diagnosis and management. Methods This study first used six Mendelian randomisation methods to assess causal relationship of 174 metabolites with MS, incorporating data from European-ancestry metabolomics (n=8569-86 507) and MS (n=14 802 MS cases, 26 703 controls) genomewide association studies. Genetic scores for identified causal metabolite(s) were then computed to predict MS disability progression in an independent longitudinal cohort (AusLong study) of 203 MS cases with up to 15-year follow-up. Results We found a novel genetic causal effect of serine on MS onset (OR=1.67, 95% CI 1.51 to 1.84, p=1.73×10 -20), such that individuals whose serine level is 1 SD above the population mean will have 1.67 times the risk of developing MS. This is robust across all sensitivity methods (OR ranges from 1.49 to 1.67). In an independent longitudinal MS cohort, we then constructed time-dynamic and time-fixed genetic scores based on serine genetic instrument single-nucleotide polymorphisms, where higher scores for raised serum serine level were associated with increased risk of disability worsening, especially in the time-dynamic model (RR=1.25, 95% CI 1.10 to 1.42, p=7.52×10 -4). Conclusions These findings support investigating serine as an important candidate biomarker for MS onset and disability progression.