Personalizing the Fight Against Multiple Sclerosis: How Precision Medicine is Changing Care
Multiple sclerosis (MS) is a complex neurodegenerative disease that affects nearly a million people in the United States alone. For young adults, it is the leading cause of non-traumatic disability. While MS care has advanced dramatically over the past two decades—with more than 18 approved disease-modifying therapies (DMTs)—patients and physicians still face a stubborn challenge: no two cases of MS are exactly alike.
This heterogeneity—differences in disease onset, severity, response to treatment, and progression—has pushed the field toward a new paradigm: precision medicine. Instead of treating MS as a single disease defined by outward symptoms, precision medicine aims to classify and treat patients based on the biology that drives their disease.
What Is Precision Medicine in MS?
Precision medicine isn’t just a buzzword. It is a shift in medical thinking that relies on:
Biology first: defining disease subtypes based on molecular and cellular mechanisms, not just symptoms.
Prediction and prevention: identifying people at risk before disease onset.
Personalized therapy: using biomarkers and genetic tools to match the right patient with the right treatment.
Patient participation: integrating patient-reported outcomes, lifestyle data, and wearable technology into decision-making.
In MS, this means moving beyond a “one-size-fits-all” approach toward a tailored system where treatment is guided by a patient’s unique biological fingerprint.
The Problem: MS Heterogeneity
MS manifests in many ways:
Some patients accumulate only mild disability decades after diagnosis.
Others develop aggressive disease, with rapid progression and early severe disability.
Younger patients tend to have a more inflammatory disease, while older patients often present with progressive, less inflammatory forms.
Even imaging studies reveal different “phenotypes,” with some patients showing heavy lesion loads and others primarily atrophy.
These differences are more than clinical curiosities—they affect treatment choices, prognosis, and healthcare costs. Currently, the annual cost of DMTs in the U.S. averages $50,000–$60,000 per patient, making the stakes of precision therapy both medical and financial.
Biomarkers: The Key to Unlocking Precision
To bring precision medicine into MS practice, the field needs reliable biomarkers. Chitnis and Prat outline five key categories:
Prevention biomarkers – to identify people at risk (e.g., genetic risk alleles, vitamin D deficiency, Epstein–Barr virus exposure).
Diagnostic biomarkers – to distinguish MS from mimicking conditions early in the disease.
Prognostic biomarkers – to predict disease course (e.g., neurofilament light chain (NfL) for axonal damage; glial fibrillary acidic protein for disability progression).
Treatment response biomarkers – to determine which therapy a patient is most likely to benefit from (e.g., interferon-response gene signatures, HLA associations with glatiramer acetate).
Safety biomarkers – to stratify risk of adverse events like progressive multifocal leukoencephalopathy (PML) in patients treated with natalizumab or other immunosuppressants.
While progress has been made—particularly with serum and CSF neurofilament levels—most biomarkers are still in the validation stage.
Measuring Outcomes in a Patient-Centered Way
Traditional tools like the Expanded Disability Status Scale (EDSS) have been the gold standard, but they emphasize mobility over cognition or quality of life. Precision medicine requires a broader toolbox, including:
Functional composites (motor, hand function, cognition).
Patient-reported outcomes (fatigue, mood, quality of life, work performance).
Digital health tools (apps and biosensors tracking gait, activity, sleep).
Advanced imaging (MRI phenotypes, cortical pathology, PET imaging).
This integrated approach captures a patient’s real-life experience, not just what is seen in the clinic.
The Future: Data Integration and Machine Learning
The real promise of precision medicine lies in integration. Imagine combining:
Clinical data (symptoms, disability scores).
Neuroimaging metrics.
Genomic, proteomic, and microbiome data.
Daily-life data from wearables and apps.
Together, these streams could feed into machine-learning models that predict individual disease trajectories and suggest personalized treatment strategies.
Such systems would not only help physicians make informed choices but also empower patients to take an active role in managing their disease.
Why It Matters
For patients, precision medicine offers the hope of:
Faster, more accurate diagnosis.
Early prediction of disease severity.
Treatments tailored to their biology, minimizing trial-and-error.
Better quality of life through proactive monitoring.
For healthcare systems, it promises reduced costs by avoiding ineffective therapies and unnecessary disability progression.
And for science, MS may serve as a model for applying precision medicine to other neurodegenerative and autoimmune diseases.
Final Thoughts
Chitnis and Prat’s roadmap reminds us that MS is not one disease, but many biological pathways converging on a common clinical picture. Precision medicine holds the potential to untangle these pathways and rewrite the future of care—making treatment not just reactive, but predictive, personalized, and participatory.
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:
Landi D, Grimaldi A, Bovis F, et al. Influence of Previous Disease-Modifying Drug Exposure on T-Lymphocyte Dynamic in Patients With Multiple Sclerosis Treated With Ocrelizumab. Neurol Neuroimmunol Neuroinflamm. 2022;9(3):e1157. doi:10.1212/NXI.0000000000001157
