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Pharmacogenomics of Multiple Sclerosis: A Systematic Review
Keli Hočevar1, Smiljana Ristić2, Borut Peterlin1
1Clinical Institute of Medical Genetics, University Medical Centre Ljubljana, Ljubljana, Slovenia.
Genetics influence multiple sclerosis (MS) drug response, but current pharmacogenomic biomarkers are not clinically actionable. More large-scale, standardized studies are needed to validate genetic associations for personalized MS treatment.
Area of Science:
- Pharmacogenomics
- Neuroimmunology
- Genetics
Background:
- Multiple sclerosis (MS) treatments show variable patient responses, potentially due to genetic factors.
- Numerous disease-modifying drugs for MS have been developed over the last two decades.
- Understanding genetic influences could lead to personalized MS therapy.
Purpose of the Study:
- To systematically review the existing literature on the pharmacogenomics of multiple sclerosis (MS) therapy.
- To identify genetic variations associated with patient response to MS disease-modifying treatments.
- To assess the current state of pharmacogenomic biomarkers for MS treatment selection.
Main Methods:
- Systematic literature search of PubMed/MEDLINE up to October 2018, adhering to PRISMA guidelines.
- Inclusion of studies investigating genetic variation and response to MS treatments (interferon-beta, glatiramer acetate, mitoxantrone, natalizumab).
- Data extraction included study design, genes, polymorphisms, outcomes, and statistical significance.
Main Results:
- 48 articles were reviewed, primarily candidate gene studies (87.5%).
- Pharmacogenomic evidence for MS drugs is often inconsistent across studies.
- Hypothesis-free approaches identified novel genes requiring validation; study design variations contribute to discordance.
Conclusions:
- Currently, no clinically actionable pharmacogenomic biomarkers exist for personalized MS treatment.
- Large-scale, uniformly designed studies are essential to validate and discover pharmacogenomic associations.
- Future research should explore rare variants and utilize next-generation sequencing for MS pharmacogenomics.
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