Predicting treatment response to IFNbeta or GA

A new baseline response marker to IFNbeta and GA? #MSBlog #MSResearch

"The study below looks for predictive genetic response markers to IFN-beta and GA and suggests that variants in a particular immune receptor called CCR5 is predictive of a response to these DMTs. This receptor is very interesting biologically and is the one that is the co-receptor that HIV uses to infect cells. A particular variant in this receptor renders the carrier resistant to infection with HIV. It would be interesting to ask how is this receptor linked to a treatment response in MS?"

"Predictive biomarkers such as the one described below need to validated in other studies and then tested in large cohort studies. To the best of my knowledge this is the first study to identify this receptor as a predictive marker. Therefore this result could be a false positive and why it is so important that the results are replicated."

"It is becoming increasingly important to be able to identify who is going to be a responder or non-responder to IFN-beta or GA before starting treatment. This will allow us to  screen individuals and offer them an effective 1st-line drug that is safe. This will allow us to select MS drugs so as not to expose too many MSers to risky therapies. If only it was this simple. Unfortunately, we don't have any validated baseline response markers in clinical practice; we have some promising ones identified in the academic setting but none that have made it into the clinic. The only marker that has made it into the clinic is neutralizing anti-interferon beta antibodies or NABs. The earliest we can screen for these is at about 6 months. NABs only predict failure of therapy in the future and are not a positive predictor."


Kulakova et ak. Comparative pharmacogenetics of multiple sclerosis: IFN-β versus glatiramer acetate. Pharmacogenomics. 2014 Apr;15(5):679-85.

Background: Various diseases require the selection of preferable treatment out of available alternatives. Multiple sclerosis (MS), an autoimmune inflammatory/neurodegenerative disease of the CNS, requires long-term medication with either specific disease-modifying therapy (DMT) - IFN-β or glatiramer acetate (GA) - which remain the only first-line DMTs in most countries. A significant share of MS patients are resistant to treatment with one or the other DMT; therefore, the earliest choice of preferable DMT is of particular importance. A number of conventional pharmacogenetic studies performed up to the present day have identified the treatment-sensitive genetic biomarkers that might be specific for the particular drug; however, the suitable biomarkers for selection of one or another first-line DMT are remained to be found. Comparative pharmacogenetic analysis may allow the identification of the discriminative genetic biomarkers, which may be more informative for an a priori DMT choice than those found in conventional pharmacogenetic studies. 

Objective: The search for discriminative markers of preferable first-line DMT, which differ in carriage between IFN-β responders and GA responders as well as between IFN-β nonresponders and GA nonresponders, has been performed in 253 IFN-β-treated MS patients and 285 GA-treated MS patients. 

Methods: A bioinformatics algorithm for identification of composite biomarkers (allelic sets) was applied on a unified set of immune-response genes, which are relevant for IFN-β and/or GA modes of action, and identical clinical criteria of treatment response. 

Results: We found the range of discriminative markers, which include polymorphic variants of CCR5, IFNAR1, TGFB1, DRB1 or CTLA4 genes, in different combinations. Every allelic set includes the CCR5 genetic variant, which probably suggests its crucial role in the modulation of the DMT response. 

Conclusion: Special attention should be given to the (CCR5*d+ IFNAR1*G) discriminative combination, which clearly points towards IFN-β treatment choice for carriers of this combination. As a whole the comparative approach provides an option for the identification of prognostic composite biomarkers for a preferable medication among available alternatives.