Decoding Multiple Sclerosis: A Systems Biology Approach
Multiple Sclerosis (MS) is a complex immune-mediated neurodegenerative disease. It's a chronic autoimmune disease where the body's immune system attacks the central nervous system, leading to a range of symptoms and disabilities. Despite decades of research, the exact causes of MS remain elusive. A recent study has taken a novel approach to unraveling the complexities of MS, using a method called systems biology, which looks at the big picture by combining different types of data.
The Challenge of MS
MS is a leading cause of disability in young adults globally. In 2013, about 2.3 million people were diagnosed with MS, and the numbers are increasing. The disease is more prevalent in women than men, with the highest rates in North America and Europe. The financial cost of MS is also high, with an estimated $40,000 per patient per year spent on treatment and management in 2007.
MS usually starts with a clinically isolated syndrome (CIS), a single episode of inflammatory demyelination. About 30-70% of people with CIS go on to develop MS. The disease can take different forms. The most common is relapsing-remitting MS (RRMS), where people experience flare-ups followed by periods of recovery. Over time, many with RRMS develop secondary-progressive MS (SPMS), a phase of continuous neurodegeneration without remission. Primary-progressive MS (PPMS) is another form characterized by progressive disability from the beginning.
Environmental and Genetic Factors
It’s thought that MS arises from a complex interplay of environmental and genetic factors. Environmental factors include a lack of vitamin D, smoking, and exposure to the Epstein-Barr virus (EBV). The HLA-DR*1501 variant is a major genetic susceptibility factor for MS, but many other genetic factors have a low to moderate impact.
The Systems Biology Approach
The study mentioned in the beginning uses a systems biology approach, analyzing multiple datasets simultaneously to identify patterns that might be missed with traditional methods. The researchers combined gene expression profiles from different studies, comparing data from healthy individuals, MS patients, and MS patients undergoing treatment. They also included data related to other diseases like EBV infection, tuberculosis, and other autoimmune disorders. This allowed them to identify molecules and pathways that are consistently altered in MS.
Key Findings
* The "Untreated" Group: In the "untreated" group of MS patients, 16 molecules were found to be consistently altered. These included ANKRD10, which is involved in myelination and was found to be upregulated. Other molecules such as C1ORF228, CNTNAP2 and LPP, were also found to be related to EBV infection, with CNTNAP2 also implicated in inflammation and other autoimmune diseases. Many of these molecules have been linked to neuronal processes in the CNS and peripheral blood mononuclear cells (PBMCs).
* The "Treated" Group: In MS patients undergoing treatment, a different set of 16 molecules were identified as being significantly altered. Notably, RSAD2 and MX1 were highly upregulated. These molecules are known to be associated with interferon-beta (IFN-β) treatment activity. Interestingly, these molecules showed a strong overlap with those seen in other autoimmune diseases, suggesting a common treatment-related response.
* The Interferon Gamma (IFN-γ) Pathway: The most significant pathway across all significant molecules identified in the study was the IFN-γ signaling pathway. This pathway is involved in immune response and is activated in response to viral infections. Many of the molecules in the IFN-γ pathway are upregulated in MS, which may indicate that it is a key driver of the disease. Additionally, the Toll-like receptor (TLR) signaling pathway was found to be relevant in the "Treated" group which was correlated with the effect of antiviral treatments.
What Does it Mean?
This study highlights the power of systems biology in understanding complex diseases like MS. By integrating data from multiple sources, researchers can identify key molecules and pathways that are involved in the disease. This approach allows for the generation of new hypotheses and provides a direction for further research.
One of the most interesting findings was the identification of the IFN-γ signaling pathway as a central player in MS. While this pathway is known to be involved in the immune response, its role in MS is still uncertain. The study suggests that a viral infection may trigger this pathway in MS patients. Also, the study suggests that while MS is not directly caused by EBV infection, it is linked to it, and that EBV is not the only factor.
Another important aspect was the finding that the molecular profile of treated MS patients is very similar to that of patients with other autoimmune diseases. This may mean that treatments like IFN-β, can mask the specific effects of MS and result in a generic autoimmune response.
What's Next?
The authors acknowledge some limitations of this study. Since the data was based on blood samples, further confirmation is needed to confirm that these findings are reflected in the brain tissue. Future studies should investigate the role of the identified molecules within different MS phenotypes, and determine the cell types that produce them. This may lead to the development of more targeted therapies for MS.
This study highlights that a lot of important molecules and elements involved in MS aetiology remain to be discovered, and that the results obtained might give a starting point to establish traditional approaches by knowing in which processes to focus.
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:
Cervantes-Gracia, K., Husi, H. Integrative analysis of Multiple Sclerosis using a systems biology approach. Sci Rep 8, 5633 (2018).
