Blood-Based RNA Profiles May Unlock Personalized Treatment in Multiple Sclerosis

Multiple sclerosis (MS), a disease marked by unpredictable episodes of inflammation in the brain and spinal cord, has long been a clinical enigma. A study by Ottoboni et al. published in Science Translational Medicine provides compelling evidence that RNA signatures in blood may hold the key to predicting which MS patients are more likely to relapse—even while on treatment.

The Challenge of Predicting MS Progression
MS is notoriously diverse in how it presents and progresses among individuals. Some patients experience frequent relapses, while others remain stable for years. Despite advancements in imaging and diagnostics, neurologists still lack molecular biomarkers to forecast a patient's disease trajectory or guide treatment decisions early in the disease course.

A Groundbreaking Approach
Ottoboni and colleagues tackled this problem using a clever but underutilized approach: analyzing RNA from peripheral blood mononuclear cells (PBMCs), the immune cells that circulate in the blood and contribute to inflammation in MS. By examining the gene expression profiles of these cells, they hoped to detect patterns that could distinguish between different “types” of MS.

Using a method called non-negative matrix factorization (NMF)—a machine learning algorithm that identifies patterns in complex datasets—they analyzed blood samples from 141 untreated MS patients and discovered two distinct molecular subgroups. These subgroups, labeled MSA and MSB, were then confirmed in two other patient cohorts receiving standard first-line treatments: glatiramer acetate (GA) and interferon-β (IFN-β).

Two Molecular Subsets: MSA vs. MSB
The MSA group stood out for a significant reason: it had elevated expression of genes involved in immune cell activation—particularly pathways associated with T cells and B cells, which are known to drive MS pathology.

Even more striking, patients in the MSA subgroup were more likely to experience relapses or other signs of disease activity while on treatment. This means that, despite receiving therapies meant to curb inflammation, MSA patients were still more vulnerable to disease progression.

Key findings included:
98 genes were consistently differentially expressed between MSA and MSB across all patient groups.

These genes were enriched in immune signaling pathways like T-cell receptor signaling and PI3K/AKT signaling.

MSA patients had a 40% higher risk of experiencing a new inflammatory event compared to MSB patients, despite being on treatment.

What This Means for Patients
Imagine being able to tell, at the time of diagnosis, whether a person is likely to do well on standard therapy or if they need more aggressive treatment from the start. This study suggests that such stratification may soon be possible using a simple blood test.

It’s a step toward personalized medicine in MS—a field where treatments are still largely chosen by trial and error. If validated in larger, independent cohorts, this transcriptional signature could become a clinical tool, guiding early and individualized treatment decisions.

Limitations and Next Steps
The study has several caveats. For one, it focused on the early inflammatory phase of MS, and it’s unclear whether this classification holds true for the more degenerative, progressive stages of the disease. Also, the stability of these RNA signatures over time—whether a patient can switch between MSA and MSB—is still unknown.

Moreover, because most patients were quickly started on treatment, data on long-term disease progression in untreated individuals is lacking. Future research will need to examine how stable these RNA profiles are over time and whether they respond to newer, more potent MS therapies.

Conclusion: A New Frontier in MS Care?
This study is a major leap forward in our understanding of MS heterogeneity. By identifying biologically distinct subgroups of patients, it paves the way for a more nuanced, data-driven approach to MS management. With further validation, blood-based RNA profiling could become as routine as MRI in the MS diagnostic toolkit—ushering in an era where treatment is tailored to biology, not just symptoms.

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:
Ottoboni, L., Keenan, B.T., Tamayo, P., et al. (2012). An RNA profile identifies two subsets of multiple sclerosis patients differing in disease activity. Science Translational Medicine, 4(153), 153ra131. https://doi.org/10.1126/scitranslmed.3004186