Unlocking the Mysteries of Multiple Sclerosis Progression Through Blood Biomarkers

Multiple sclerosis (MS) is a complex immune-mediated neurodegenerative disease affecting millions worldwide, characterized by unpredictable attacks on the central nervous system (CNS). For those diagnosed, the journey often begins with relapsing-remitting MS (RRMS), marked by flare-ups followed by periods of recovery. However, over time, many patients transition into secondary progressive MS (SPMS), where neurological damage accumulates and recovery becomes limited. While understanding this shift from RRMS to SPMS is crucial for improving patient outcomes, accurately identifying it has remained elusive—until now.

A recent study published in iScience by Oppong et al. uncovers a breakthrough in distinguishing MS disease phases using blood-based biomarkers. Their findings highlight key metabolomic and transcriptomic changes in the blood that could provide a reliable way to stratify MS patients according to disease severity. This discovery opens new doors for both diagnostic precision and personalized treatment.

Blood Tells the Story: Metabolomics and MS
The study delves into the metabolomic signatures of over 250 serum metabolites in MS patients. Metabolites are small molecules that are byproducts of metabolism, and their levels can offer clues about cellular processes. Using machine learning, the researchers discovered that specific metabolites could accurately differentiate between RRMS and SPMS patients.

Notably, patients with SPMS exhibited elevated levels of metabolites related to cellular respiration, such as lactate and ketone bodies like acetoacetate and β-hydroxybutyrate. These changes suggest a metabolic shift from glycolysis (the breakdown of glucose for energy) to gluconeogenesis (producing glucose from non-carbohydrate sources) and ketogenesis (breaking down fats into ketone bodies). This metabolic stress may be a key factor driving the progression from RRMS to SPMS.

Gene Expression Mirrors Metabolomic Changes
The study also analyzed whole-blood transcriptomic data—essentially, a snapshot of gene activity in blood cells. Over 1,000 genes were differentially expressed between RRMS and SPMS, with many involved in metabolism, stress response, and immune signaling. By integrating these gene expression patterns with the metabolomic data, the researchers identified a gene-metabolite network that further highlighted the metabolic changes associated with disease severity.

Genes involved in lipid metabolism, such as SCD5 and PLA2G12A, were upregulated in SPMS, indicating a dysregulation in how cells process fats. The study suggests that these metabolic shifts may reflect broader cellular stress and damage that contribute to the neurodegeneration observed in progressive MS.

A Path Toward Personalized Medicine
What makes these findings particularly exciting is the potential for developing blood-based diagnostic tools. Currently, the transition from RRMS to SPMS is only diagnosed retrospectively, after significant and irreversible damage has occurred. However, the metabolomic signature identified in this study offers a glimpse of a future where patients could be stratified by disease phase much earlier, allowing for more targeted treatment strategies.

The authors propose that combining key metabolites—such as cholesterol esters, saturated fatty acids, and gluconeogenesis-related metabolites—could form the basis of a reliable scoring system. This system could outperform current clinical markers like age and disability scores in predicting disease progression.

The Broader Implications
Beyond its diagnostic potential, this study also hints at possible therapeutic interventions. The metabolic changes seen in SPMS suggest that targeting these pathways—perhaps by promoting glycolysis or reducing the reliance on gluconeogenesis and ketogenesis—could slow or prevent disease progression. This opens up exciting new avenues for research into treatments that could modulate metabolism to benefit MS patients.

Conclusion: Toward a New Era in MS Care
The study by Oppong et al. represents a significant leap forward in our understanding of multiple sclerosis. By identifying distinct metabolomic and transcriptomic signatures in the blood, they provide a path toward earlier, more accurate diagnosis of disease severity. This could enable personalized treatments that not only improve quality of life for MS patients but also potentially alter the course of the disease.

References:
Oppong, A. E., Coelewij, L., Robertson, G., Martin-Gutierrez, L., Waddington, K. E., Dönnes, P., ... & Jury, E. C. (2024). Blood metabolomic and transcriptomic signatures stratify patient subgroups in multiple sclerosis according to disease severity. Iscience, 27(3).