Genetic polymorphisms, their allele combinations and IFN-β treatment response in Irish multiple sclerosis patients

Author:

O’Doherty Catherine1,Favorov Alexander2,Heggarty Shirley3,Graham Colin3,Favorova Olga4,Ochs Michael5,Hawkins Stanley6,Hutchinson Michael7,O’Rourke Killian7,Vandenbroeck Koen8

Affiliation:

1. University of South Australia, Adelaide, Australia

2. Laboratory for Bioinformatics, GosNIIGenetika, Moscow, Russia and Johns Hopkins School of Medicine, MD, USA

3. Queens University, Belfast, UK

4. Russian State Medical University, Moscow, Russia

5. Johns Hopkins School of Medicine, MD, USA

6. Royal Victoria Hospital, Belfast, UK

7. St Vincent’s Hospital, Dublin, Ireland

8. Neurogenomiks Laboratory, Ikerbasque and Universidad Del País Vasco (UPV-EHU), Parque Tecnológico de Bizkaia, 48170 Zamudio, Spain.

Abstract

Introduction: IFN-β is widely used as first-line immunomodulatory treatment for multiple sclerosis. Response to treatment is variable (30–50% of patients are nonresponders) and requires a long treatment duration for accurate assessment to be possible. Information about genetic variations that predict responsiveness would allow appropriate treatment selection early after diagnosis, improve patient care, with time saving consequences and more efficient use of resources. Materials & methods: We analyzed 61 SNPs in 34 candidate genes as possible determinants of IFN-β response in Irish multiple sclerosis patients. Particular emphasis was placed on the exploration of combinations of allelic variants associated with response to therapy by means of a Markov chain Monte Carlo-based approach (APSampler). Results: The most significant allelic combinations, which differed in frequency between responders and nonresponders, included JAK2–IL10RB–GBP1–PIAS1 (permutation p-value was pperm = 0.0008), followed by JAK2–IL10–CASP3 (pperm = 0.001). Discussion: The genetic mechanism of response to IFN-β is complex and as yet poorly understood. Data mining algorithms may help in uncovering hidden allele combinations involved in drug response versus nonresponse.

Publisher

Future Medicine Ltd

Subject

Pharmacology,Genetics,Molecular Medicine

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