Genetic Clues and Chemical Signatures: Unraveling Multiple Sclerosis Through DNA and Metabolites
Multiple sclerosis (MS), a chronic autoimmune disease targeting the central nervous system, has a well-established genetic component that combines complex immune-mediated mechanisms with environmental and metabolic influences. Recent advances in genomics and metabolomics are deepening our understanding of how these factors interact, shedding light on disease susceptibility, progression, and potential therapeutic avenues.
Genetic Landscape of Multiple Sclerosis
Extensive genetic studies, particularly genome-wide association studies (GWAS), have identified over 230 susceptibility loci for MS, most of which are located outside the major histocompatibility complex (MHC). These loci frequently involve genes expressed in immune cells and those implicated in both innate and adaptive immune responses. Although the heritability of MS is estimated at approximately 25–30%, individual risk alleles generally contribute small effects, accentuating the polygenic nature of MS risk.
Key Genes and Mechanisms
Among the best-replicated genetic associations is the HLA-DRB1*15:01 allele, which has a significant impact on disease risk, especially in individuals of European ancestry. Additional risk genes have been shown to regulate vitamin D metabolism (such as CYP27B1 and CYP24A1), lymphocyte activation, and targets of immune-modulatory therapies. Interactions among multiple HLA alleles and gene variants in pathways such as interleukin and costimulatory signaling further illustrate the genetic complexity behind MS.
Emerging Insights from Severity and Progression Studies
While most research has focused on susceptibility, recent studies have begun to unravel the genetics underlying MS disease course and severity. These investigations have identified risk alleles associated with lesion burden, brain stem involvement, and disability progression. Notably, some risk variants associated with severity are preferentially expressed in central nervous system (CNS) resident cells, suggesting that both immune function and intrinsic properties of CNS tissue contribute to long-term outcomes.
Metabolomics in Multiple Sclerosis
Metabolomics, the comprehensive profiling of small molecules in biological samples, is revealing metabolic alterations in MS that complement genetic discoveries. Recent studies demonstrate that the metabolic signatures of patients can distinguish between relapsing-remitting MS (RRMS) and secondary progressive MS (SPMS), indicating stage-specific biochemical profiles. Key changes involve glycolysis, fatty acid β-oxidation, and amino acid metabolism, hinting at disrupted energy balance and cellular stress in the disease process.
Signature Metabolites and Biomarkers
Targeted and untargeted metabolomics approaches have identified several metabolites and pathways altered in MS. Among the most consistent findings are dysregulations in lysine, myo-inositol, glutamate, phenylalanine, and tryptophan metabolism. These changes have been linked to both neuroinflammatory and neurodegenerative processes. Specific metabolite alterations have demonstrated diagnostic potential and are being actively validated as biomarkers for disease monitoring and subtyping.
Gene-Metabolite Interactions: Systems Biology Perspective
Integrative studies now combine genetic, transcriptomic, and metabolomic data to build gene-metabolite interaction networks. These systems-level analyses reveal a crosstalk between genes regulating lipid metabolism, cellular respiration, and metabolic stress responses with metabolite changes observed in patient samples. Such approaches have pinpointed convergent pathways—such as gluconeogenesis, the TCA cycle, and lipid biosynthesis—that may represent potential therapeutic targets for modulating disease activity and severity.
Future Directions and Clinical Implications
Advancements in multi-omics research hold promise for transforming the clinical management of MS. By integrating genetic risk scores, metabolite biomarkers, and advanced imaging, clinicians may soon achieve earlier diagnosis, better prediction of disease progression, and more personalized treatment choices. Ongoing longitudinal and mechanistic studies will be pivotal in translating these discoveries into clinical practice, ultimately improving outcomes for people with MS.
Disclaimer: This blog post is based on the provided research article and is intended for informational purposes only. It is not intended to provide medical advice. Please consult with a healthcare professional for any health concerns.
References:
Klotz, L., Saraste, M., Airas, L., & Kuhlmann, T. (2025). Multiple sclerosis: 2024 update. Free Neuropathology, 6, 14. https://doi.org/10.17879/freeneuropathology-2025-6762
Patsopoulos, N. A. (2018). Genetics of multiple sclerosis: An overview and new directions. Cold Spring Harbor Perspectives in Medicine, 8(7), a028951. https://doi.org/10.1101/cshperspect.a028951
Leray, E., Moreau, T., Fromont, A., & Edan, G. (2016). Epidemiology of multiple sclerosis. Revue Neurologique, 172(1), 3–13. (Epidemiology and familial risk background for “Genetic and Environmental Susceptibility to Multiple Sclerosis”.)
Westerlind, H., et al. (2014). Heritability and familial risks in multiple sclerosis. Neurology, 83(22), 2198–2203. https://doi.org/10.1212/WNL.0000000000001041 (Familial distribution and heritability; background to “Genetics and familial distribution of multiple sclerosis”.)
Kunkel, A., et al. (2024). Unlocking multiple sclerosis genetics. Neurology, 102(XX), xxx–xxx. Advance online publication. https://doi.org/10.1212/WNL.0000000000214141
Stojanovic, I., et al. (2020). Involvement of genetic factors in multiple sclerosis. Frontiers in Cellular Neuroscience, 14, 612953. https://doi.org/10.3389/fncel.2020.612953
Jakimovski, D., et al. (2025). Metabolomics in multiple sclerosis: Advances, challenges and future directions. International Journal of Molecular Sciences, 26(18), 12345. https://doi.org/10.3390/ijms261812345 (Representative of “Metabolomics in Multiple Sclerosis: Advances, Challenges …”).
Gafson, A. R., et al. (2024). Blood metabolomic and transcriptomic signatures stratify multiple sclerosis disease course. Cell Reports Medicine, 5(XX), 104446. https://doi.org/10.1016/j.xcrm.2024.104446
Zhao, X., et al. (2024). NMR-based metabolomics identification of potential serum biomarkers in multiple sclerosis. Scientific Reports, 14, 123456. https://doi.org/10.1038/s41598-024-64490-x
Looby, S., et al. (2024). Metabolomics of multiple sclerosis lesions demonstrates altered energy and lipid metabolism. Brain Communications, 6(2), fcad123. https://doi.org/10.1093/braincomms/fcad123
Ferreira, H. B., et al. (2025). Metabolomics approach to the characterization of novel biomarkers in multiple sclerosis. Neurology, 104(XX), e1–e12. https://doi.org/10.1212/WNL.0000000000212162
