Pharmacogenetics of glatiramer acetate therapy for multiple sclerosis reveals drug-response markers

Abstract

Genetic-based optimization of treatment prescription is becoming a central research focus in the management of chronic diseases, such as multiple sclerosis, which incur a prolonged drug-regimen adjustment. This study was aimed to identify genetic markers that can predict response to glatiramer acetate (Copaxone) immunotherapy for relapsing multiple sclerosis. For this purpose, we genotyped fractional cohorts of two glatiramer acetate clinical trials for HLA-DRB1*1501 and 61 single nucleotide polymorphisms within a total of 27 candidate genes. Statistical analyses included single nucleotide polymorphism-by-single nucleotide polymorphism and haplotype tests of drug-by-genotype effects in drug-treated versus placebo-treated groups. We report the detection of a statistically significant association between glatiramer acetate response and a single nucleotide polymorphism in a T-cell receptor beta (TRB@) variant replicated in the two independent cohorts (odds ratio=6.85). Findings in the Cathepsin S (CTSS) gene (P=0.049 corrected for all single nucleotide polymorphisms and definitions tested, odds ratio=11.59) in one of the cohorts indicate a possible association that needs to be further investigated. Additionally, we recorded nominally significant associations of response with five other genes, MBP, CD86, FAS, IL1R1 and IL12RB2, which are likely to be involved in glatiramer acetate's mode-of-action, both directly and indirectly. Each of these association signals in and of itself is consistent with the no-association null-hypothesis, but the number of detected associations is surprising vis-à-vis chance expectation. Moreover, the restriction of these associations to the glatiramer acetate-treated group, rather than the placebo group, clearly demonstrates drug-specific genetic effects. These findings provide additional progress toward development of pharmacogenetics-based personalized treatment for multiple sclerosis.

Clinical implications of neuropharmacogenetics

“…Compared to IFN-β, only a few studies have investigated genetic markers for response to GA and with inconclusive results. One study has suggested an association with HLA Class II [97] but this was not replicated in a subsequent study [98] in which a significant association with polymorphisms in the T-cell receptor beta and Cathepsin S genes were found.…”

Personalized Medicine Toward Multiple Sclerosis;Current Challenges and Future Prospects

“…Auto-immune process is the main player in the demyelination of MS, and studies propose that GA binds to the MHC class II molecules, resulting in the impairment in the development of auto-immune responses. 32 Consequently, researchers have speculated the presence of important genetic variations in the HLA locus that may impress the quality of GA response in MS. 33 While several genetic variants have been found in the HLA locus to be associated with the GA response in MS, there is uncertainty about the importance of HLA locus in the GA treatment response. Although studies have indicated that DRB1*1501 allele may be useful as a predictor of response status to GA therapy, some surveys have rejected its significance in replication trials.…”

“…Although studies have indicated that DRB1*1501 allele may be useful as a predictor of response status to GA therapy, some surveys have rejected its significance in replication trials. 11,[33][34][35][36] The discrepancy between the observations may stem from the difference in the ethnicity of the studied population, sample size, respondent or non-respondent definition criteria, and protocol of the study. Moreover, this allele has also been shown as a significant predictor of susceptibility to MS. 37 On the other hand, some genetic variants in genes such as T cell receptor beta locus (TRB) and cathepsin S (CTSS) need replication studies for more validations; combinational impression of the genes, which encode inflammatory cytokines and cytokine receptors like TGFB1*T, DRB1*15, and IFNAR1*G, CCR5*d; and finally HLA haplotypes including DR17-DQ2 and DR15-DQ6.…”

From Human Genetics and Genomics to Pharmacogenetics and Pharmacogenomics: Past Lessons, Future Directions

“…Lung cancer and smoking NQO1 0.048 (Rosvold et al, 1995) Induced CYP1A2 metabolic activity CYP1A2 <0.05 (Nakajima et al, 1999) Risk of colorectal cancer SULT1A1 0.009 (Bamber et al, 2001) Myocardial infarction GCLM <0.001 Ethnic differences in risk of heart failure ADRA2C, ADRB1 <0.001, 0.004 (Small et al, 2002) Successful weight reduction by sibutramine GNB3 0.031, 0.004 (Hauner et al, 2003) Vulnerability to illegal drug abuse HTR2B 0.0335 (Lin et al, 2004) Caffeine metabolism CYP1A2 0.036, 0.038 (Chen et al, 2005) Risk of young onset, late onset Parkinson disease NAT2 0.003 (Chaudhary et al, 2005) Coffee intake and risk of myocardial infarction CYP1A2 0.04 (Cornelis et al, 2006) Smoking and obesity in prostate, lung, colorectal and ovarian cancer patients DRD2 0.02, 0.007 (Morton et al, 2006) Antidepressant efficacy in depression patients GNB3 0.02, 0.03 (Wilkie et al, 2007) Risk of aspirin-intolerant asthma PTGER2, PTGER3, PTGIR, TBXA2R 0.023, 0.038 Gefitinib responsiveness in non-small-cell lung cancer EGFR 0.014, 0.029 Risk of atherosclerosis CYP2J2 0.036 Risk of toxic liver injury ABCC2 0.04 (Choi et al, 2007) Risk of primary lung cancer ERCC1 0.034 Induction of extrapyramidal symptoms by antipsychotics RGS2 0.003, 0.009 (Greenbaum et al, 2007) Fracture risk (bone mass) after estrogen treatment P2RX7 <0.01, 0.02 (Ohlendorff et al, 2007) Glatiramer acetate therapy for multiple sclerosis TRB@ locus 0.049 (Grossman et al, 2007) (Bertina et al, 1994) Risk of type-2 diabetes PPARG 0.002 (Altshuler et al, 2000) Risk of Crohn disease NOD2 2×10 Partial list (limited to two dozen examples) of recent GWA studies in which one or a few SNPs are associated with a complex disease or multiplex phenotype (note highly significant P-values of <1 × 1(10 −6 ).…”