Metabolomics in Multiple Sclerosis Diagnostics and Disease Mechanisms

Metabolomics—the systematic analysis of small-molecule metabolites—has emerged as a powerful approach to unravel the complex biochemical alterations underlying multiple sclerosis (MS). By profiling biofluids such as cerebrospinal fluid, plasma and even tears, researchers can detect specific metabolic signatures that reflect demyelination, neuroinflammation and neurodegeneration. Advances in lipidomics, a branch of metabolomics focused on lipid species, have proved especially illuminating given the central role of myelin lipids in MS pathology. High-throughput technologies, notably mass spectrometry and nuclear magnetic resonance, enable both targeted and untargeted surveys of hundreds of metabolites. These platforms are now being harnessed to discover diagnostic biomarkers, stratify disease subtypes, predict progression and reveal perturbed pathways—ranging from sphingolipid metabolism to energy-production cycles. Collectively, metabolomic studies promise to enhance early diagnosis, guide personalised therapy and illuminate novel therapeutic targets by linking molecular perturbations to clinical outcomes.

Research from Nature Portfolio

Recent studies have demonstrated the feasibility of constructing high-accuracy classifiers for MS based solely on serum lipid mediator profiles. Unsupervised machine-learning techniques—including self-organising maps and random forests—have identified minimal panels of eight lipid mediators capable of distinguishing MS patients from healthy individuals with ~95 % sensitivity and specificity. This approach underscores the diagnostic potential of complex lipid signatures and the value of advanced computational analysis in biomarker discovery. Another seminal report applied a lipidomic workflow to cerebrospinal fluid collected at diagnosis, revealing a signature of 15 lipid species spanning fatty acids, phospholipids and other lipid families. This CSF signature not only discriminated MS patients from controls but also suggested candidate molecules for early diagnostic assays and mechanistic studies focused on myelin breakdown and immune activation.

Metabolomics in Multiple Sclerosis Diagnostics and Disease Mechanisms publication trend

The graph below shows the total number of articles in metabolomics in multiple sclerosis diagnostics and disease mechanisms across all publications each year (not limited to Nature Index journals).

Technical terms

Metabolomics: Comprehensive study of small-molecule metabolites in biological systems.

Lipidomics: Subfield of metabolomics focused on global analysis of lipid species.

Mass spectrometry: Analytical technique to identify and quantify molecules based on mass-to-charge ratios.

Biomarker: Measurable indicator of a biological state or condition used for diagnosis or monitoring.

Sphingolipid: Class of lipids involved in cell membrane structure and signalling, with roles in myelin integrity.

References

1. CSF sphingolipids are correlated with neuroinflammatory cytokines and differentiate neuromyelitis optica spectrum disorder from multiple sclerosis. Journal of Neurology Neurosurgery & Psychiatry (2024).
2. Transcriptomic profiling identifies ferroptosis and NF-κB signaling involved in α-dimorphecolic acid regulation of microglial inflammation. Journal of Translational Medicine (2025).
3. Association of Arachidonic Acid–Derived Lipid Mediators With Disease Severity in Patients With Relapsing and Progressive Multiple Sclerosis. Neurology (2023).
4. Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity Stratification (LipidMS). International Journal of Molecular Sciences (2024).
5. Multi-omics profiling reveals peripheral blood biomarkers of multiple sclerosis: implications for diagnosis and stratification. Frontiers in Pharmacology (2024).
6. An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview. Cellular and Molecular Life Sciences (2021).