New Directions in MSā€ˆResearch: New Therapeutic Approaches

Previous: Stem Cells | Next: Genetic Studies

In medicine, the term “biomarker” refers to anything that can be used as an indicator of a particular disease state; in effect, a biomarker is a surrogate for the disease state. It often refers to a protein measured in blood, whose concentration reflects the severity or presence of disease and/or that which can be used to measure therapeutic effectiveness. Many types of biomarkers are being researched in MS, and these are likely to grow in importance in the coming years.

Although the term itself is relatively new, biomarkers have long been used in medicine. For example, body temperature is a well-known biomarker for fever, blood pressure helps determine the risk of stroke, and cholesterol levels are a biomarker and risk indicator for coronary and vascular disease. Biomarkers are often seen as the key to the future of “personalized medicine.” This refers to treatments that can be individually tailored to specific patients for highly efficient intervention in disease processes.

The concept of personalizing MS care has been implemented in a general way by the use of disease-modifying therapies based on someone’s clinical course – CIS, RRMS, SPMS, PRMS, or PPMS – categories entirely based on a patient’s clinical history. This approach has been refined as clinicians may recommend “more aggressive” therapies based on markers of disease severity (such as MRI lesions), as well as on demographic factors that may be concerning for a more difficult disease course.

The search for biomarkers of MS is referred to throughout this publication, and studies are ongoing with all major MS drugs to find markers that will help determine who should be treated with that drug as well as how effective the drug is after therapy is begun. We already utilize one type of blood test to help predict ongoing therapeutic response – neutralizing antibodies to the interferons and Tysabri. A major goal of biomarker studies is to be able to decide which patient is most likely to respond to which therapy before it is started, so the decision about which medication to start can be optimized.

For example, current studies are showing that it may soon be possible to determine who might be a suboptimal responder to interferons, based on immune system-related substances measured in the blood. Another study evaluated whether the type of cytokine present prior to treatment with Copaxone might act as a biomarker to identify those individuals with RRMS who are more likely to respond to immunomodulating treatments. It showed that people who responded to Copaxone secreted higher levels of specific inflammatory cytokines prior to treatment.

A genetic study, with results reported in 2012, looking at the response to Copaxone, also suggested that multiple genetic markers may predict a favorable response to this medication. A further study of genetic predictors of response to Copaxone was presented at ECTRIMS in fall 201464 and suggested that a particular array of genetic markers could accurately predict a high response to Copaxone. This investigative procedure is to be evaluated in further studies.

An additional use of biomarkers will be to predict and minimize the risk of medication-related adverse events. This approach has already proved effective for new infectious biomarkers, such as the development of a blood test for JC virus antibodies, to identify who is at greater or lesser PML risk when treated with Tysabri. Based on this blood test, the option of using Tysabri can be more precisely personalized to maximize the benefit/risk ratio for this medication in practice. This type of biomarker strategy may also prove useful in predicting the risk on an individual basis of non-infectious adverse events to certain investigational medicines.

A strong link exists between biomarkers and genetics, and the line between them may sometimes appear blurred. This is because many of the biomarkers that are being discovered relate to the activity of specific genes that code for proteins involved in inflammation, or are otherwise linked to the response to disease-modifying therapies. Studies of the gene expression signature, through global gene expression analysis, reveals the pattern of the entire DNA in an individual. This type of study has become possible due to recent advances in high-speed genetic pattern analysis.

For example, genes found to be expressed differently in MS effectively become biomarkers for disease progression and may change as the result of treatment. A recent study identified several candidate genes that could potentially serve as biomarkers of interferon treatment or targets for treatment in MS.

Additionally, a study using gene-expression analysis of whole blood showed significant differences in expression profiles of patients with optic neuritis versus healthy controls.

Another study showed that interferon therapy induces the expression of genes involved in interferon regulation and signaling; a subgroup of patients with a higher risk for relapses showed a different expression of specific genes.

An ongoing clinical trial sponsored by the National Institutes of Health (NIH) is studying more than 1,000 people with RRMS who participated in the CombiRx study. This study includes patients on Avonex only, Copaxone only, or a combination of both. Samples of serum and white blood cells are being obtained from each patient prior to the study and at regular intervals thereafter.

Although Copaxone and Avonex did not differ greatly in their efficacy in the CombiRx trial, certainly both drugs work well for some and less well for others. This study aims to identify biomarkers (genes and the proteins they encode) and link them to clinical- and MRI-based outcomes, such as the extent of inflammation and rate of disease progression. It will examine how biomarkers may be related to disease development and progression, as well as differences among patients’ symptoms and response to treatment. Based on these genetic biomarkers, likely best-responders to either form of therapy can be identified.

Previous: Stem Cells | Next: Genetic Studies