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

Association study of promoter polymorphisms of interferon alpha and beta receptor subunit 1 (IFNAR1) gene and therapeutic response to interferon-beta in patients with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is an autoimmune disease described by inflammatory neuronal losses and resultant failures. The disease could abate by interferon-beta (IFN-β) therapy in MS patients. However, the drug response productivity is changeable between patients, and the accurate mechanism of action of the IFN-β is not obvious. The present study aims to investigate the role of interferon alpha and beta receptor subunit 1 (IFNAR1) promoter polymorphisms towards IFN-β treatment response in MS patients.

METHODS

The subjects herein were separated into either responder (n = 57) or non-responder (n = 43) groups according to IFN-β treatment and Expanded Disability Status Scale score. The Sanger sequencing method was used for genotyping.

RESULTS

Among nearly 64 Single Nucleotide Polymorphisms (SNPs), we found a significant association between the rs2850015 polymorphism and the responders and non-responders to IFN-β treatment in the recessive model of inheritance (P = 0.02). The results also revealed a significant change in the two groups of responders and non-responders to the treatment for rs36158718 as an Insertion/Deletion (INDEL) (P = 0.02). Moreover, bioinformatic analyses predicted a remarkable role for both rs2850015 and rs36158718 related to the changes of binding affinity of transcription factors and alterations in their alleles.

CONCLUSION

The present study results suggest that the genetic heterogeneity in the promoter region of IFNAR1 could affect the response to IFN-β. However, further studies with a larger sample size are needed to further demonstrate this relationship.

Interferon-β corrects massive gene dysregulation in multiple sclerosis: Short-term and long-term effects on immune regulation and neuroprotection

Background

In multiple sclerosis (MS), immune up-regulation is coupled to subnormal immune response to interferon-β (IFN-β) and low serum IFN-β levels. The relationship between the defect in IFN signalling and acute and long-term effects of IFN-β on gene expression in MS is inadequately understood.

Methods

We profiled IFN-β-induced transcriptome shifts, using high-resolution microarrays on 227 mononuclear cell samples from IFN-β-treated MS Complete Responders (CR) stable for five years, and stable and active Partial Responders (PR), stable and active untreated MS, and healthy controls.

Findings

IFN-β injection induced short-term changes in 1,200 genes compared to baseline expression after 4-day IFN washout. Pre-injection after washout, and in response to IFN-β injections, PR more frequently had abnormal gene expression than CR. Surprisingly, short-term IFN-β induced little shift in Th1/Th17/Th2 gene expression, but up-regulated immune-inhibitory genes (ILT, IDO1, PD-L1). Expression of 8,800 genes was dysregulated in therapy-naïve compared to IFN-β-treated patients. These long-term changes in protein-coding and long non-coding RNAs affect immunity, synaptic transmission, and CNS cell survival, and correct the disordered therapy-naïve transcriptome to near-normal. In keeping with its impact on clinical course and brain repair in MS, long-term IFN-β treatment reversed the overexpression of proinflammatory and MMP genes, while enhancing genes involved in the oligodendroglia-protective integrated stress response, neuroprotection, and immunoregulation. In the rectified long-term signature, 277 transcripts differed between stable PR and CR patients.

Interpretation

IFN-β had minimal short-term effects on Th1 and Th2 pathways, but long-term it corrected gene dysregulation and induced immunoregulatory and neuroprotective genes. These data offer new biomarkers for IFN-β responsiveness.

Funding

Unrestricted grants from the US National MS Society, NMSS RG#4509A, and Bayer Pharmaceuticals

Pharmacogenetics: A strategy for personalized medicine for autoimmune diseases

For many years, a considerable number of patients with autoimmune diseases (ADs) have suffered from a lack of drug response and drug-related toxicity. Despite the emergence of new therapeutic options such as biological agents, patients continue to struggle with these problems. Unfortunately, new challenges, including the paradoxical effects of biological drugs, have complicated the situation. In recent decades, efforts have been made to predict drug response as well as drug-related side effects. Thanks to the many advances in genetics, evaluation of markers to predict drug response/toxicity before the initiation of treatment may be an avenue toward personalizing treatments. Implementing pharmacogenetics and pharmacogenomics in the clinic could improve clinical care; however, obstacles remain to effective personalized medicine for ADs. The present study attempted to clarify the concept of pharmacogenetics/pharmacogenomics for ADs. After an overview on the pathogenesis of the most common types of treatments, this paper focuses on pharmacogenetic studies related to the selected ADs. Bridging the gap between pharmacogenetics and personalized medicine is also discussed. Moreover, the advantages, disadvantages and recommendations related to making personalized medicine practical for ADs have been addressed.

The investigation of relevancy between PIAS1 and PIAS2 gene expression and disease severity of multiple sclerosis

Introduction: PIAS1 and PIAS2 (protein inhibitor of activated STAT 1,2) play key roles in the pathogenesis of autoimmune and inflammatory diseases. This study aims to evaluate the gene expression of these factors in multiple sclerosis (MS) patients compared to healthy individuals and correlate them with the severity of MS. Materials and methods: Sixty participants, including 30 patients with MS and 30 healthy controls were studied. The expression of PIAS1 and PIAS2 genes in peripheral blood samples of all participants was measured by real-time PCR. The severity of MS was evaluated using the Expanded Disability Status Scale (EDSS). Finally, we evaluated the correlation between the expression of PIAS1 and PIAS2 genes with disease severity. Results: The expression of PIAS1 gene was increased in patients with MS compared to healthy subjects (P value<.001). Also, there was a significant correlation between the expression of PIAS1 and PIAS2 genes with disease severity according to EDSS. Conclusion: Our study suggests the expression of PIAS1 and PIAS2 genes as a prognostic and diagnostic marker in MS disease.

Pharmacogenomics of Multiple Sclerosis: A Systematic Review

Background: Over the past two decades, various novel disease-modifying drugs for multiple sclerosis (MS) have been approved. However, there is high variability in the patient response to the available medications, which is hypothesized to be partly attributed to genetics. Objectives: To conduct a systematic review of the current literature on the pharmacogenomics of MS therapy. Methods: A systematic literature search was conducted using PubMed/MEDLINE database searching for articles investigating a role of genetic variation in response to disease-modifying MS treatments, published in the English language up to October 9th, 2018. PRISMA guidelines for systematic reviews were applied. Studies were included if they investigated response or nonresponse to MS treatment defined as relapse rate, by expanded disability status scale score or based on magnetic resonance imaging. The following data were extracted: first author's last name, year of publication, PMID number, sample size, ethnicity of patients, method, genes, and polymorphisms tested, outcome, significant associations with corresponding P-values and confidence intervals, response criteria, and duration of the follow-up period. Results: Overall, 48 articles published up to October 2018, evaluating response to interferon-beta, glatiramer acetate, mitoxantrone, and natalizumab, met our inclusion criteria and were included in this review. Among those, we identified 42 (87.5%) candidate gene studies and 6 (12.5%) genome-wide association studies. Existing pharmacogenomic evidence is mainly based on the results of individual studies, or on results of multiple studies, which often lack consistency. In recent years, hypothesis-free approaches identified novel candidate genes that remain to be validated. Various study designs, including the definition of clinical response, duration of the follow-up period, and methodology as well as moderate sample sizes, likely contributed to discordances between studies. However, some of the significant associations were identified in the same genes, or in the genes involved in the same biological pathways. Conclusions: At the moment, there is no available clinically actionable pharmacogenomic biomarker that would enable more personalized treatment of MS. More large-scale studies with uniform design are needed to identify novel and validate existing pharmacogenomics findings. Furthermore, studies investigating associations between rare variants and treatment response in MS patients, using next-generation sequencing technologies are warranted.

Pharmacogenetics of glatiramer acetate therapy for multiple sclerosis: the impact of genome-wide association studies identified disease risk loci

AIM

Association analysis of genome-wide association studies (GWAS) identified multiple sclerosis (MS) risk genetic variants with glatiramer acetate (GA) treatment efficacy.

PATIENTS & METHODS

SNPs in 17 GWAS-identified immune response loci were analyzed in 296 Russian MS patients as possible markers of optimal GA treatment response for at least 2 years.

RESULTS

Alleles/genotypes of EOMES, CLEC16A, IL22RA2, PVT1 and HLA-DRB1 were associated by themselves with event-free phenotype during GA treatment for at least 2 years (p _f  = 0.032 - 0.00092). The biallelic combinations including EOMES, CLEC16A, IL22RA2, PVT1, TYK2, CD6, IL7RA and IRF8 genes were associated with response to GA with increased significance level (p _f  = 0.0060 - 1.1 × 10^-5). The epistasic interactions or additive effects were observed between the components of the identified biallelic combinations.

CONCLUSION

We pinpointed the involvement of several GWAS-identified MS risk loci in GA therapy efficacy. These findings may be aggregated to predict the optimal GA response in MS patients.

Genes of tumor necrosis factors and their receptors and the primary open angle glaucoma in the population of Central Russia

AIM

To examine the association of genetic polymorphisms (-308)G/A TNFα, (+250)A/G Ltα, (+36)A/G TNFR1, (+1663)A/G TNFR2 with the development of primary open angle glaucoma (POAG) among people in Central Russia.

METHODS

The study sample included 443 individuals, of which 252 patients with POAG and 191 individuals in the control group. Genotyping of (-308)G/A TNFα, (+250)A/G Ltα, (+36)A/G TNFR1, (+1663)A/G TNFR2 was performed using polymerase chain reaction. The distribution of alleles and genotypes of the studied DNA markers in the groups was examined by 2×2 contingency tables and χ² with the Yates's correction for continuity and odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

Allele (-308)G TNFα (Р=0.01, OR=1.78, 95%CI 1.12-2.85) was identified as a risk factor for POAG. Homozygotes (-308) AA TNFα are at a lowest risk for development of the disease (Р=0.01, OR=0.0005). The following combination of genetic variants of cytokines were associated with a reduced risk of POAG: (+1663)A TNFR2 and (+250)G Ltα (OR=0.34).

CONCLUSION

Genetic polymorphisms (-308)G/A TNFα, (+250)A/G Ltα, (+1663)A/G TNFR2 associated with the development of POAG in the population of Central Russia.

Pharmacogenetic Biomarkers to Predict Treatment Response in Multiple Sclerosis: Current and Future Perspectives

Disease-modifying therapies (DMTs) have significantly advanced the treatment of relapsing multiple sclerosis (MS), decreasing the frequency of relapses, disability, and magnetic resonance imaging lesion formation. However, patients' responses to and tolerability of DMTs vary considerably, creating an unmet need for biomarkers to identify likely responders and/or those who may have treatment-limiting adverse reactions. Most studies in MS have focused on the identification of pharmacogenetic markers, using either the candidate-gene approach, which requires prior knowledge of the genetic marker and its role in the target disease, or genome-wide association, which examines multiple genetic variants, typically single nucleotide polymorphisms (SNPs). Both approaches have implicated numerous alleles and SNPs in response to selected MS DMTs. None have been validated for use in clinical practice. This review covers pharmacogenetic markers in clinical practice in other diseases and then reviews the current status of MS DMT markers (interferon β, glatiramer acetate, and mitoxantrone). For a complex disease such as MS, multiple biomarkers may need to be evaluated simultaneously to identify potential responders. Efforts to identify relevant biomarkers are underway and will need to be expanded to all MS DMTs. These will require extensive validation in large patient groups before they can be used in clinical practice.

[Clinical and molecular genetic analysis of a case of familial multiple sclerosis in the Republic of Bashkortostan]

AIM

To investigate clinical manifestations of multiple sclerosis (MS) and the genetic makeup of six affected members of one family.

MATERIAL AND METHODS

Six members of the family of Russian ethnic origin were examined. Pedigree analysis and genotyping of polymorphic markers of candidate genes for multiple sclerosis were performed.

RESULTS AND CONCLUSION

The accumulation of alleles that were associated with autoimmune diseases according to the results of genome-wide association studies (rs1109670*C, rs3129934*T, rs9523762*G, rs1570538*T) was found in the family. The results confirm the contribution of several genetic variants to familial forms of MS.

Combinations of Genetic Variants Occurring Exclusively in Patients

In studies of polygenic disorders, scanning the genetic variants can be used to identify variant combinations. Combinations that are exclusively found in patients can be separated from those combinations occurring in control persons. Statistical analyses can be performed to determine whether the combinations that occur exclusively among patients are significantly associated with the investigated disorder. This research strategy has been applied in materials from various polygenic disorders, identifying clusters of patient-specific genetic variant combinations that are significant associated with the investigated disorders. Combinations from these clusters are found in the genomes of up to 55% of investigated patients, and are not present in the genomes of any control persons.

Genetic predisposition of IL-10 promoter polymorphisms with risk of multiple sclerosis: A meta-analysis

Interleukin-10 (IL-10) is a anti-inflammatory cytokine, which controls inflammation by inhibiting the synthesis of several cytokines produced by Th1 cells and macrophages. The association between Interleukin-10 promoter polymorphisms with the risk of multiple sclerosis (MS) remains inconclusive. In this study, a meta-analysis has been performed to assess the relationship between IL-10 gene polymorphisms rs1800896, rs1800871 and rs1800872 with the risk of MS. Nine case-control studies were selected involving 2755 participants. The association between the polymorphisms and MS was examined by the pooled odds ratios (ORs) with 95% confidence intervals (CIs) in allelic, homozygote, heterozygote, dominant and recessive genetic models. Of analyzed genetic models, the pooled ORs and CIs of each SNPs calculated based on random (I²>50) or fixed effects (I²<50) methods, which showed no significant association (p-value>0.05) of genetic predisposition with MS susceptibility across Asian and Caucasian populations. In addition, assessment based on funnel plot and Egger's linear regression test suggests no publication bias in all analyzed genetic models. Overall, our results demonstrated that rs1800896, rs1800871 and rs1800872 polymorphisms may not be the risk factor for the development of MS in both the populations.

Association of CD58 Polymorphism with Multiple Sclerosis and Response to Interferon ß Therapy in A Subset of Iranian Population

Objective

Multiple sclerosis (MS) is one of the leading neurodegenerative causes of physical disability world-wide. Genetic aberrations of autoimmunity pathway components have been demonstrated to significantly influence MS development. Cluster of Differentiation 58 (CD58) is pertained to a group of genes which had been assayed in several recent association studies. Given the significance of CD58 in modulation of T regulatory cells that control autoimmune responses, the present study was conducted to investigate the frequency of rs12044852 polymorphism and its effect on the outcome of interferon beta (IFN-β) therapy in a subset of Iranian MS patients.

Materials and Methods

Two hundred MS patients and equal number of healthy controls were recruited to be genotyped in an experimental case-control based study through polymerase chain reaction using specific sequence primers (PCR-SSP). Relapsing remitting multiple sclerosis (RRMS) patients administered IFN-β therapy were followed up with clinical visits every three months up to two years. The mean of multiple sclerosis severity score (MSSS) and expanded disability status scale (EDSS) were measured to monitor the change in severity of MS in response to IFN-β therapy. Pearson’s Chi-square and analysis of variance (ANOVA) tests were the main statistical methods used in this study.

Results

Strong association was found between the CC genotype and onset of MS (p=0.001, OR=2.22). However, there was no association between rs12044852 and various classifications and severity of MS. Pharmacogenetics-based analysis indicated that carriers of CC genotype had the highest MSSS score compared to others, implying a negative impact of rs12044852 on response to IFN-β therapy.

Conclusion

Taken together, our findings revealed the critical effect of rs12044852 polymorphism of CD58 on the progression of MS disease. This indicates that genotyping of MS patients may expedite achieving personalized medical management of MS patients.

Comparative pharmacogenetics of multiple sclerosis: IFN-β versus glatiramer acetate

Various diseases require the selection of preferable treatment out of available alternatives. Multiple sclerosis (MS), an autoimmune inflammatory/neurodegenerative disease of the CNS, requires long-term medication with either specific disease-modifying therapy (DMT) - IFN-β or glatiramer acetate (GA) - which remain the only first-line DMTs in all countries. A significant share of MS patients are resistant to treatment with one or the other DMT; therefore, the earliest choice of preferable DMT is of particular importance. A number of conventional pharmacogenetic studies performed up to the present day have identified the treatment-sensitive genetic biomarkers that might be specific for the particular drug; however, the suitable biomarkers for selection of one or another first-line DMT are remained to be found. Comparative pharmacogenetic analysis may allow the identification of the discriminative genetic biomarkers, which may be more informative for an a priori DMT choice than those found in conventional pharmacogenetic studies. The search for discriminative markers of preferable first-line DMT, which differ in carriage between IFN-β responders and GA responders as well as between IFN-β nonresponders and GA nonresponders, has been performed in 253 IFN-β-treated MS patients and 285 GA-treated MS patients. A bioinformatics algorithm for identification of composite biomarkers (allelic sets) was applied on a unified set of immune-response genes, which are relevant for IFN-β and/or GA modes of action, and identical clinical criteria of treatment response. We found the range of discriminative markers, which include polymorphic variants of CCR5, IFNAR1, TGFB1, DRB1 or CTLA4 genes, in different combinations. Every allelic set includes the CCR5 genetic variant, which probably suggests its crucial role in the modulation of the DMT response. Special attention should be given to the (CCR5*d+ IFNAR1*G) discriminative combination, which clearly points towards IFN-β treatment choice for carriers of this combination. As a whole the comparative approach provides an option for the identification of prognostic composite biomarkers for a preferable medication among available alternatives.

STAT3 genetic variant, alone and in combination with STAT5b polymorphism, contributes to breast cancer risk and clinical outcomes

The genetic or abnormal activation of signal transducer and activator of transcription (STATs) family proteins play an important role with regard to disease progression in variety of human malignancies, yet no data are available for candidate gene and breast cancer (BC) risk. To address this, we investigate the correlation between STAT3, STAT5b polymorphisms and BC susceptibility, clinicopathological parameters, and clinical outcomes. A case-control study was carried out in 1,240 BC patients and 882 healthy controls using TaqMan assay and PCR-RFLP method. A significant decreased risk of BC was associated with STAT3 G allele and combined effect (validation alleles). Furthermore, patients after anthracycline-based chemotherapy, carrying combined effect of STAT3 rs4796793 and STAT5b rs6503691, had significantly increased progression-free survival (PFS) [adjusted HR (95 % CI) 0.831 (0.704-0.980), P = 0.028]. More importantly, ER-negative patients with STAT5b CT/TT genotype was associated with a longer PFS [adjusted HR (95 % CI) 0.519 (0.293-0.920), P = 0.025], recurrence-free survival [adjusted HR (95 % CI) 0.529 (0.298-0.939), P = 0.030], and overall survival [adjusted HR (95 % CI) 0.547 (0.308-0.973), P = 0.040]. These results indicated that STAT3 and STAT5b polymorphisms might be a candidate pharmacogenomic factor to assess susceptibility and prognosis in BC patients.

Candidate gene study of TRAIL and TRAIL receptors: association with response to interferon beta therapy in multiple sclerosis patients

TRAIL and TRAIL Receptor genes have been implicated in Multiple Sclerosis pathology as well as in the response to IFN beta therapy. The objective of our study was to evaluate the association of these genes in relation to the age at disease onset (AAO) and to the clinical response upon IFN beta treatment in Spanish MS patients. We carried out a candidate gene study of TRAIL, TRAILR-1, TRAILR-2, TRAILR-3 and TRAILR-4 genes. A total of 54 SNPs were analysed in 509 MS patients under IFN beta treatment, and an additional cohort of 226 MS patients was used to validate the results. Associations of rs1047275 in TRAILR-2 and rs7011559 in TRAILR-4 genes with AAO under an additive model did not withstand Bonferroni correction. In contrast, patients with the TRAILR-1 rs20576-CC genotype showed a better clinical response to IFN beta therapy compared with patients carrying the A-allele (recessive model: p = 8.88×10⁻⁴, p_c = 0.048, OR = 0.30). This SNP resulted in a non synonymous substitution of Glutamic acid to Alanine in position 228 (E228A), a change previously associated with susceptibility to different cancer types and risk of metastases, suggesting a lack of functionality of TRAILR-1. In order to unravel how this amino acid change in TRAILR-1 would affect to death signal, we performed a molecular modelling with both alleles. Neither TRAIL binding sites in the receptor nor the expression levels of TRAILR-1 in peripheral blood mononuclear cell subsets (monocytes, CD4+ and CD8+ T cells) were modified, suggesting that this SNP may be altering the death signal by some other mechanism. These findings show a role for TRAILR-1 gene variations in the clinical outcome of IFN beta therapy that might have relevance as a biomarker to predict the response to IFN beta in MS.

Identification of shared genes and pathways: a comparative study of multiple sclerosis susceptibility, severity and response to interferon beta treatment

Recent genome-wide association studies (GWAS) have successfully identified several gene loci associated with multiple sclerosis (MS) susceptibility, severity or interferon-beta (IFN-ß) response. However, due to the nature of these studies, the functional relevance of these loci is not yet fully understood. We have utilized a systems biology based approach to explore the genetic interactomes of these MS related traits. We hypothesised that genes and pathways associated with the 3 MS related phenotypes might interact collectively to influence the heterogeneity and unpredictable clinical outcomes observed. Individual genetic interactomes for each trait were constructed and compared, followed by prioritization of common interactors based on their frequencies. Pathway enrichment analyses were performed to highlight shared functional pathways. Biologically relevant genes ABL1, GRB2, INPP5D, KIF1B, PIK3R1, PLCG1, PRKCD, SRC, TUBA1A and TUBA4A were identified as common to all 3 MS phenotypes. We observed that the highest number of first degree interactors were shared between MS susceptibility and MS severity (p = 1.34×10⁻⁷⁹) with UBC as the most prominent first degree interactor for this phenotype pair from the prioritisation analysis. As expected, pairwise comparisons showed that MS susceptibility and severity interactomes shared the highest number of pathways. Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes. Finally, FYN was the most common first degree interactor in the MS drugs-gene network. By applying the systems biology based approach, additional significant information can be extracted from GWAS. Results of our interactome analyses are complementary to what is already known in the literature and also highlight some novel interactions which await further experimental validation. Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.

Allelic combinations of immune-response genes as possible composite markers of IFN-β efficacy in multiple sclerosis patients

Background: IFN-β is widely used as the first-line disease-modifying treatment for multiple sclerosis. However, 30–50% of multiple sclerosis patients do not respond to this therapy. Identification of genetic variants and their combinations that predict responsiveness to IFN-β could be useful for treatment prognosis. Materials & methods: The combinations of alleles of nine polymorphic loci in immune-response genes were analyzed in 253 Russian multiple sclerosis patients as possible determinants of clinically optimal IFN-β treatment response using APSampler software. Results: Carriage of TGFB1*-509C and CCR5*d was associated with favorable IFN-β response by itself. CCR5*d, IFNAR1*16725G, IFNG*874T and IFNB1*153T/T were the components of the combinations, associated with clinically optimal response to IFN-β. Carriage of composite markers (CCR5*d + IFNAR1*G + IFNB1*T/T) or (CCR5*d + IFNAR1*G + IFNG*T) is beneficial for IFN-β treatment efficacy. Discussion: The data obtained provides evidence of the cumulative effect of immune-response genes on IFN-β treatment efficacy. This joint contribution may reflect the additive effect of independent allelic variants and epistatic interactions between some of them.

Original submitted 2 July 2012; Revision submitted 21 September 2012

Single nucleotide polymorphisms in multiple sclerosis: disease susceptibility and treatment response biomarkers

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system characterized by unpredictable and variable clinical course. Etiology of MS involves both genetic and environmental factors. New technologies identified genetic polymorphisms associated with MS susceptibility among which immunologically relevant genes are significantly overrepresented. Although individual genes contribute only a small part to MS susceptibility, they might be used as biomarkers, thus helping to identify accurate diagnosis, predict clinical disease course and response to therapy. This review focuses on recent progress in research on MS genetics with special emphasis on the possibility to use single nucleotide polymorphism of candidate genes as biomarkers of susceptibility to disease and response to therapy.

A Polygenic Approach to the Study of Polygenic Diseases

Polygenic diseases are caused by the joint contribution of a number of independently acting or interacting polymorphic genes; the individual contribution of each gene may be small or even unnoticeable. The carriage of certain combinations of genes can determine the occurrence of clinically heterogeneous forms of the disease and treatment efficacy. This review describes the approaches used in a polygenic analysis of data in medical genomics, in particular, pharmacogenomics, aimed at identifying the cumulative effect of genes. This effect may result from the summation of gains of different genes or be caused by the epistatic interaction between the genes. Both cases are undoubtedly of great interest in investigating the nature of polygenic diseases. The means that allow one to discriminate between these two possibilities are discussed. The methods for searching for combinations of alleles of different genes associated with the polygenic phenotypic traits of the disease, as well as the methods for presenting and validating the results, are described and compared. An attempt is made to evaluate the applicability of the existing methods to an epistasis analysis. The results obtained by the authors using the APSampler software are described and summarized.

Pharmacogenomics in neurology: current state and future steps

In neurology, as in any other clinical specialty, there is a need to develop treatment strategies that allow stratification of therapies to optimize efficacy and minimize toxicity. Pharmacogenomics is one such method for therapy optimization: it aims to elucidate the relationship between human genome sequence variation and differential drug responses. Approaches have focused on candidate approaches investigating absorption-, distribution-, metabolism, and elimination (ADME)-related genes (pharmacokinetic pathways), and potential drug targets (pharmacodynamic pathways). To date, however, only few genetic variants have been incorporated into clinical algorithms. Unfortunately, a large number of studies have thrown up contradictory results due to a number of deficiencies, including small sample sizes, inadequate phenotyping, and genotyping strategies. Thus, there still exists an urgent need to establish biomarkers that could help to select for patients with an optimal benefit to risk relationship. Here we review recent advances, and limitations, in pharmacogenomics for agents used in neuroimmunology, neurodegenerative diseases, ischemic stroke, epilepsy, and primary headaches. Further work is still required in all of these areas, which really needs to progress on several fronts, including better standardized phenotyping, appropriate sample sizes through multicenter collaborations and judicious use of new technological advances such as genome-wide approaches, next generation sequencing and systems biology. In time, this is likely to lead to improvements in the benefit-harm balance of neurological therapies, cost efficiency, and identification of new drugs.

Pharmacogenomics and multiple sclerosis: moving toward individualized medicine

Notwithstanding the availability of disease-modifying treatments including interferon-β, glatiramer acetate, and natalizumab, a considerable proportion of multiple sclerosis (MS) patients experience continued progression of disease, clinical relapses, disease activity on MRI, and adverse effects. Application of gene expression, proteomic or genomic approaches is universally accepted as a suitable strategy toward the identification of biomarkers with predictive value for beneficial/poor clinical response to therapy and treatment risks. This review focuses on recent progress in research on the pharmacogenomics of disease-modifying therapies for MS. Although MS drug response biomarkers are not yet routinely implemented in the clinic, the diversity of reported, promising molecular markers is rapidly increasing. Even though most of these markers await further validation, given time, this research is likely to empower neurologists with an enhanced armamentarium to facilitate rational decisions on therapy and patient management.

Allelic combinations of immune-response genes associated with glatiramer acetate treatment response in Russian multiple sclerosis patients

BACKGROUND

Glatiramer acetate (GA) is widely used as a first-line disease-modifying treatment for multiple sclerosis (MS). However, a significant proportion of MS patient appears to experience modest benefit from GA-treatment. Genetic variants affecting the clinical response to GA are believed to be relevant as biomarkers of GA-treatment efficiency.

PATIENTS & METHODS

Nine polymorphisms in candidate genes were analyzed as possible determinants of GA response in 285 Russian MS patients. Special attention was given to identification of response-associated allelic combinations by means of the APSampler algorithm.

RESULTS

No significant associations were found for individual polymorphisms. Alleles DRB1*15, TGFB1*T, CCR5*d and IFNAR1*G were the components of the combinations, of which carriage was significantly higher in nonresponders than in responders. Carriers of the most significant combinations: DRB1*15 + TGFB1*T + CCR5*d + IFNAR1*G and DRB1*15 + TGFB1*T + CCR5*d (permutation p-values: 0.0056 and 0.013, respectively) had a 14 to 15-times increased risk of ineffective response to GA therapy.

DISCUSSION

The results suggest that the influence of immune-response genes on GA-induced response has a polygenic nature. The data are interpreted as evidence of additive and epistatic influences of the genes on GA efficiency for MS treatment.

IL28B polymorphisms are not associated with the response to interferon-β in multiple sclerosis

Recent studies have revealed an association between interleukin 28B (IL28B) and response to IFN-alpha treatment in hepatitis C patients. Here we investigated the influence of IL28B polymorphisms in the response to interferon-beta (IFNβ) in multiple sclerosis (MS) patients. We genotyped two SNPs of the IL28B gene (rs8099917 and rs12979860) in 588 MS patients classified into responders (n=281) and non-responders (n=307) to IFNβ. Combined analysis of the study cohorts showed no significant associations between SNPs rs8099917 and rs12979860 and the response to treatment. These findings do not support a role of IL28B polymorphisms in the response to IFNβ in MS patients.

Sieving treatment biomarkers from blood gene-expression profiles: a pharmacogenomic update on two types of multiple sclerosis therapy

Interferon-β (IFN-β) and glatiramer acetate are routinely used to inhibit disease activity in multiple sclerosis, but their mechanisms of action are incompletely understood. Individual treatment responses vary and candidate molecular markers that predict them have yet to be established. Why some patients respond poorly to a certain treatment while others respond well is addressed by the pharmacogenomic approach, which postulates that the molecular response to treatment correlates with the clinical effects, and thus seeks biological markers to estimate prognosis, guide therapy, comprehend the drugs' mechanisms of action and offer insights into disease pathogenesis. A poor clinical response can be owing to genetic variants in drug receptors or signaling components, or the appearance of neutralizing antibodies that interfere with the drug's binding efficacy. Independently, such mechanisms could lead to inadequate, that is to say unchanged, molecular responses, or exceedingly increased or decreased changes. By means of DNA microarray studies, various research groups endeavour to establish a clinically relevant relationship between the biological response to these drugs and treatment effects. Molecular profiles obtained in this way differ in the pattern and number of modulated genes, suggesting the existence of an individual 'drug-response fingerprint'. To further unravel the underlying regulatory interaction structure of the genes responsive to these immunotherapies represents a daunting but inevitable task. In this article, we focus on longitudinal ex vivo transcriptomic studies in multiple sclerosis and its therapy. We will discuss recurrently reported biomarker candidates, emphasizing those of immunologically meaning, and review studies with network module outputs.

Genomic markers to tailor treatments: waiting or initiating?

The decade since the publication of the Human Genome Project draft has ended with the discovery of hundreds of genomic markers related to diseases and phenotypes. However, the project has not yet delivered on its promise to tailor treatments for individuals. The number of genomic markers in clinical practice is very small. The number of markers to guide treatment decisions is even smaller. In order to speed up discovery and validation of genomic treatment selection markers, we call for considering the brilliant potential of randomized clinical trials. If biomedical research community can collaborate in organizing large-scale consortium of clinical trials associated with well-designed biobanks, these studies would soon act as huge laboratories for investigating genomic medicine; a big step forward towards personalizing medicine.

Single-nucleotide polymorphisms in response to interferon-beta therapy in multiple sclerosis

Interferon-beta (IFN-β) is one of the main first-line disease-modifying drugs indicated for the treatment of multiple sclerosis (MS). The drug exhibits only limited effectiveness, and does not produce clinical benefits in around 20%-50% of patients. The availability of biomarkers would be beneficial for identification of patients at high risk of treatment failure, before initiation of therapy. Over the last 5 years, the search for such biomarkers has intensified and various promising candidates have been uncovered. Here, we review the main attempts undertaken to identify polymorphic variants associated with response to IFN-β therapy in MS by means of candidate gene approaches and whole-genome association scans. Despite substantial progress made in the field, there is still a long way to go before biomarker discoveries can be incorporated into clinical practice to predict IFN-β-responder status in MS patients.

IFN-beta pharmacogenomics in multiple sclerosis

Multiple sclerosis (MS) is a condition of the CNS marked by inflammation and neurodegeneration. Interferon (IFN)-beta was the first, and still is the main, immunomodulatory treatment for MS. Its clinical efficacy is limited, and a proportion of patients, ranging between 20-55%, do not respond to the therapy. Identification and subsequently, implementation in the clinic of biomarkers predictive for individual therapeutic response would facilitate improved patient care in addition to ensuring a more rational provision of this therapy. In this article, we summarize the main findings from studies addressing the pharmacogenomics of clinical response to IFN-beta in MS by either whole-genome association scans, candidate gene or transcriptomics studies. Whole-genome DNA association screens have revealed a high representation of brain-specific genes, and have hinted toward both extracellular ligand-gated ion channels and type I IFNs pathway genes as important categories of genetic IFN-beta response modifiers. One hit, glypican 5 (GPC5), was recently replicated in an independent study of IFN-beta responsiveness. Recent RNA transcriptomics studies have revealed the occurrence of a pre-existing type I IFN gene-expression signature, composed of genes that are predominantly induced by type I IFNs, as a potential contributing feature of poor response to therapy. Thus, while the outlines of a complex polygenic mechanism are gradually being uncovered, the main challenges for the near future will reside in the robust validation of identified response-modifying genes as well as in the decipherment of the mechanistic relationships between these genes and clinical response to IFN-beta.