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Response to interferon-beta treatment in multiple sclerosis patients: a genome-wide association study
S Mahurkar1, M Moldovan2,3, V Suppiah1
1School of Pharmacy and Medical Sciences and Sansom Institute for Health Research, University of South Australia, Frome Road, Adelaide, South Australia, Australia.
Identifying genetic markers can predict multiple sclerosis (MS) patient response to interferon-beta (IFN-β) treatment, potentially shortening the 2-year follow-up period. This study found FHIT, GAPVD1, and ZNF697 variants associated with treatment response.
Area of Science:
- Genetics
- Immunology
- Neurology
Background:
- Many multiple sclerosis (MS) patients exhibit non-response to interferon-beta (IFN-β) therapy.
- Assessing treatment response currently requires extensive clinical observation, up to two years.
- Predictive genetic markers could personalize MS management and improve treatment efficacy.
Purpose of the Study:
- To identify genetic markers that predict patient response to interferon-beta (IFN-β) treatment in multiple sclerosis.
- To improve the management of multiple sclerosis by enabling early prediction of treatment outcomes.
Main Methods:
- A two-stage genome-wide association study (GWAS) was conducted.
- Initial GWAS utilized data from 151 Australian MS patients.
- Replication analysis involved an independent cohort of 479 IFN-β-treated MS patients from Australia, Spain, and Italy.
Main Results:
- Eight single-nucleotide polymorphisms (SNPs) demonstrated evidence of association with IFN-β treatment response after validation.
- The strongest association was observed for the FHIT gene (Fragile Histidine Triad).
- Significant associations were also found for variants near GAPVD1 and ZNF697.
Conclusions:
- Genetic markers, particularly variants in FHIT, GAPVD1, and ZNF697, show potential for predicting interferon-beta (IFN-β) treatment response in multiple sclerosis patients.
- These findings could lead to more personalized treatment strategies for MS.
- Further research is warranted to validate and implement these genetic markers in clinical practice.
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