New drug development and clinical management of patients with chronic, polygenic diseases, such as Multiple Sclerosis (MS), are suboptimal due to our inability to measure putative pathogenic processes contributing to destruction of the central nervous system (CNS). While blood is an excellent source of biomarkers used in clinical practice for management of e.g., cardiovascular disease, cerebrospinal fluid (CSF) represents a biological fluid that bring us as close to the CNS tissue in living patients as possible. Therefore, CNS-specific biomarkers in CSF could provide an insight into pathogenic mechanisms underlying disease expression in patients, its temporal distribution, intra-individual heterogeneity, and ultimately lead to precision medicine-based polypharmacy regimens.
We sought to determine if CSF biomarkers can be aggregated to predict future rates of MS progression and provide molecular insight into mechanisms of CNS destruction and repair.
Using DNA-based SOMAscan technology we blindly measured 1,305 CSF biomarkers in longitudinal CSF samples of untreated MS patients divided into training (N=129) and validation (N=64) cohorts. We used machine learning algorithms in the training cohort to generate models of MS severity while the independent validation cohort samples were used to assess the predictive power of the models.
CSF biomarker-based random forest models, validated in an independent longitudinal cohort, were able to predict reliably future rates of disability progression in MS patients. We were able to rule out the hypothesis that neuro-degenerative aspects of MS represent “accelerated aging” and instead defined, on a molecular level, mechanisms that correlate with how fast MS patients lose central nervous system (CNS) tissue, reflected by volumetric brain imaging and by clinical disability outcomes.
Cluster analysis of identified biomarkers revealed intra-individual molecular heterogeneity of disease mechanisms that include both CNS- and immune-related pathways and may represent novel targets for drug development and personalized treatments that would inhibit MS progression.
Acknowledgments: The research was supported by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID).