Recent discussions of risk gene variation and pharmacogenitc studies were highlighted at a parallel session during the 29th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS). Genome-Wide Association Studies (GWAS) have identified over 100 common risk variants in just over a quarter of observed heritability.
Recent discussions of risk gene variation and pharmacogenitc studies were highlighted at a parallel session during the 29th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS). Genome-Wide Association Studies (GWAS) have identified over 100 common risk variants in just over a quarter of observed heritability. These developments imply a new approach to multiple sclerosis (MS) studies as risk gene identification can be attributed to MS not only as a pure risk disease, but also to its prognosis and response to treatment. Dr Jan Hillert, professor of neurology, Karolinska University, Sweden, explored the relationship between pharamacogenetics (PGt) and treatment of MS including efficacy and drug resistance. Nikolaos A. Patsopoulos, MD, PhD, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, presented a study on common genetic variability, and what this variability means for MS susceptibility.
Dr Hillert discussed the implications for pharmacogenetics, asserting that the association between risk gene identification and MS susceptibility could “enable a truly personalized medicine approach to individualized treatment decisions.” Hillert explained that to date, pharmacogenetic studies of efficacy of MS disease-modifying drugs (DMD) are weakened by a lack of published and conclusive studies. There are currently no MS drugs on the market that carry PGt markers in their labels.
While findings in adverse events and drug resistance in the PGt-MS DMD relationship are similarly limited, they reveal the potential value of PGt markers in MS treatment decisions. One study by Sundqvist et al shows the association between high risk of JC virus with human leukocyte antigen (HLA) class II variants, a concern for patients with MS who are treated with natalizumad, a DMD with links to progressive multifocal leukoencephalopahty (PML). Looking at drug resistance, an unpublished study by Link et al demonstrated a heightened risk of developing neutralizing anti-drug antibodies in MS when interferon beta is used in the presence of HLA genes.
Hillert highlighted the Karolinska Integrated platform for MS research as an effective setting for further research into pharmacogenetics and its relationship with DMD in MS. Its pharmacy database, Swedish statistics database, and 100 health-related public registries make it an optimal platform for meaningful MS research.
According to Hillert, the pharmacogenetics of MS will need to be highly-sensitive, “identifying responders to treatment on the short term as well as long term...differentiate factors influencing non response from a severe disease course, and will need, if possible, to identify individuals developing side effects or resistance to treatment.”
Dr N. A. Patsopoulos, on behalf of the International Multiple Sclerosis Genetics Consortium (IMSGC), delved into a broader study of risk gene variation, and presented clinical data from an extensive genome-wide discovery study representing common genetic variability in 14,802 MS cases, and 26,703 controls. The study identified 88 statistical independent effects at the genome-wide level (P value < 5 x 10-08), and 126 suggestive effects at P value < 10-5, and in 36 of the loci, found evidence of multiple variants with statistically independent effects with MS susceptibility. As a result of this longitudinal study, doctors can “quantify the exact variance explained by each susceptibility allele using multivariate models and to estimate the overall contribution of genetic variability to MS susceptibility.”
In order to effectively map these identified effects, Dr Patsopoulous and his team combined the results with 2 other sets of data: data representing the effect of each SNP on RNA expression of nearby genes in 3 different sets of immune cells; and epigenomic data from the ENCODE project which describes the state of chromatin in over 300 different cell types. The resulting genetic map makes it possible to identify the most likely causal variant in each locus, and furthermore, it suggests that both adaptive and innate immune functions are equally involved in MS susceptibility.