Dr. Valentina Fossati Hunts for the Biomarkers Behind MS

What They Did: Researchers at the National Institutes of Health (NIH) and Montana State University along with NYSCF Senior Principal Investigator Dr. Valentina Fossati examined cerebrospinal fluid (fluid found in the brain and spinal cord) of patients with multiple sclerosis to identify possible biomarkers (measurable substances that indicate disease) that can teach us about multiple sclerosis causes and progression.

What They Found: Using machine learning techniques, the team identified potential biomarkers indicating activity of different cell types in multiple sclerosis. Specifically, these biomarkers suggested that activity of toxic astrocytes (a type of support cell in the brain) could help drive the disease, and that this toxicity could be triggered by cells called microglia, the immune cells of the brain. Human stem cell-derived oligodendrocytes generated at NYSCF were used to build the training dataset, which was then compared to the cerebrospinal fluid samples.

Why It Matters: Identifying biomarkers for the disease will help us develop improved methods for multiple sclerosis diagnosis, and understanding the contributions of cells in the brain such as astrocytes and microglia will help us develop targeted multiple sclerosis treatments.

Multiple sclerosis is a complex disease, involving multiple cell types in the body that can be difficult to access and observe. It can also take a while to diagnose, as multiple sclerosis symptoms are often non-specific and can point to a number of diseases. One way scientists can detect multiple sclerosis early on and draw conclusions about its underlying causes is by identifying biomarkers— measurable substances that signal a disease’s presence.

In a new collaborative study published in Multiple Sclerosis and Related Disorders by NYSCF Senior Principal Investigator Dr. Valentina Fossati and researchers at the National Institutes of Health (NIH) and Montana State University, scientists measured thousands of molecules in samples of cerebrospinal fluid from hundreds of multiple sclerosis patients. Their results revealed new potential multiple sclerosis biomarkers that could help us learn more about the disease’s progression, develop improved methods for diagnosis, and monitor the effectiveness of treatments. CSF is relatively easy to access—it can be removed from the spinal cord through a procedure called a spinal tap—and it often contains proteins that can serve as biomarkers for brain disease.

The team collected samples of cerebrospinal fluid from 431 patients— some with multiple sclerosis and some which served as healthy controls. They then measured the levels of different proteins in the CSF and identified a few that could serve as possible biomarkers. Finally, they compared how levels of these potential biomarkers correlated with multiple sclerosis symptoms in patients.

The researchers discovered potential multiple sclerosis biomarkers that indicated increased levels of toxic astrocytes (a type of support cell in the brain) in patients with the disease. The more of the biomarker that was present, the more severe the patient’s multiple sclerosis symptoms appeared to be. The team also hypothesized that toxic astrocytes could be triggered by increased activation of microglia (typically thought of as the immune cells of the brain).

Establishing biomarkers for multiple sclerosis will help us learn more about the disease’s progression as well as develop improved diagnostics that could allow us to identify it earlier on and improve patient prognosis. Understanding how different cells contribute to the disease will also inform the creation of targeted multiple sclerosis treatments, and biomarkers can help us monitor patient responses to new treatments.

Learn more about NYSCF’s multiple sclerosis research here.

Journal citation:

Cerebrospinal fluid biomarkers link toxic astrogliosis and microglial activation to multiple sclerosis severity.
Masvekar, Ruturaj et al. Multiple Sclerosis and Related Disorders. 2018. DOI: https://doi.org/10.1016/j.msard.2018.11.032