O. O. Favorova

Hydrolysis of myelin basic protein by polyclonal catalytic IgGs from the sera of patients with multiple sclerosis

Various catalytic antibodies or abzymes have been detected recently in the sera of patients with several autoimmune pathologies, where their presence is most probably associated with autoimmunization. Recently we have shown that DNase, RNase, and polysaccharide‐hydrolyzing activities are associated with IgGs from the sera of patients with multiple sclerosis (MS). Here we present evidence demonstrating that highly purified MS IgGs (but not Igs from the sera of healthy individuals) catalyze specifically hydrolysis of human myelin basic protein (hMBP). In contrast to many known proteases, IgGs do not hydrolyze many other different proteins. Specific inhibitors of acidic and thiol proteases have no remarkable effect on proteolytic activity of IgGs. However, specific inhibitor of serine (PMSF, AEBSF, and benzamidin) and metal‐dependent (EDTA) proteases significantly inhibit activity of proteolytic abzymes. Interestingly, the ratio of serine‐like and metal‐dependent activities of MS IgGs varied very much from patient to patient. The findings speak in favor of the generation by the immune systems of individual MS patients of a variety of polyclonal anti‐MBP IgGs with different catalytic properties.

Catalytic heterogeneity of polyclonal DNA-hydrolyzing antibodies from the sera of patients with multiple sclerosis

Various catalytic antibodies or abzymes have been detected recently in the sera of patients with several autoimmune pathologies, where their presence is most probably associated with autoimmunization. Recently we have shown that DNase activity is associated with IgGs from the sera of patients with multiple sclerosis (MS) but not with those from the sera of normal humans. Here we present evidence showing that MS IgG, its F(ab) fragments, and separated L-chains catalyze DNA hydrolysis. The properties of the DNase activity of these polyclonal IgGs distinguish them from other known human DNases. In addition, their specific activities with different oligonucleotide substrates and the range of optimal pHs, apparent K(M) values and substrate specificities varied widely for different patients. The findings speak in favor of the generation by the immune systems of individual patients of a variety of polyclonal catalytic IgG pools, from relatively small to extremely large ones.

Amylolytic activity of IgM and IgG antibodies from patients with multiple sclerosis

IgG and IgM antibodies from the sera of patients with multiple sclerosis (MS) were found to possess amylolytic activity hydrolyzing alpha-(1-->4)-glucosyl linkages of maltooligosaccharides, glycogen, and several artificial substrates. Individual IgM fractions isolated from 54 analyzed patients with the clinically definite diagnoses of MS had approximately three orders of magnitude higher specific amylolytic activity than that for healthy donors, whereas IgG from only a few patients had high amylolytic activity. Strict criteria were used to prove that the amylolytic activity of IgMs and IgGs is their intrinsic property and is not due to any enzyme contamination. Fab fragments produced from IgM and IgG fractions of the MS patients displayed the same amylolytic activity. IgMs from various patients demonstrated different modes of action in hydrolyzing maltooligosaccharides.

A Markov chain Monte Carlo technique for identification of combinations of allelic variants underlying complex diseases in humans.

In recent years, the number of studies focusing on the genetic basis of common disorders with a complex mode of inheritance, in which multiple genes of small effect are involved, has been steadily increasing. An improved methodology to identify the cumulative contribution of several polymorphous genes would accelerate our understanding of their importance in disease susceptibility and our ability to develop new treatments. A critical bottleneck is the inability of standard statistical approaches, developed for relatively modest predictor sets, to achieve power in the face of the enormous growth in our knowledge of genomics. The inability is due to the combinatorial complexity arising in searches for multiple interacting genes. Similar “curse of dimensionality” problems have arisen in other fields, and Bayesian statistical approaches coupled to Markov chain Monte Carlo (MCMC) techniques have led to significant improvements in understanding. We present here an algorithm, APSampler, for the exploration of potential combinations of allelic variations positively or negatively associated with a disease or with a phenotype. The algorithm relies on the rank comparison of phenotype for individuals with and without specific patterns (i.e., combinations of allelic variants) isolated in genetic backgrounds matched for the remaining significant patterns. It constructs a Markov chain to sample only potentially significant variants, minimizing the potential of large data sets to overwhelm the search. We tested APSampler on a simulated data set and on a case-control MS (multiple sclerosis) study for ethnic Russians. For the simulated data, the algorithm identified all the phenotype-associated allele combinations coded into the data and, for the MS data, it replicated the previously known findings.

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

INTRODUCTION IFN-beta 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-beta 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 p(perm) = 0.0008), followed by JAK2-IL10-CASP3 (p(perm) = 0.001). DISCUSSION The genetic mechanism of response to IFN-beta is complex and as yet poorly understood. Data mining algorithms may help in uncovering hidden allele combinations involved in drug response versus nonresponse.

Association of SNPs of CD40 Gene with Multiple Sclerosis in Russians

Multiple sclerosis (MS) is a serious, incurable neurological disease. In 2009, the ANZgene studies detected the suggestive association of located upstream of CD40 gene in chromosome 20q13 (p = 1.3×10−7). Identification of the causal variant(s) in the CD40 locus leads to a better understanding of the mechanism underlying the development of autoimmune pathologies. We determined the genotypes of rs6074022, rs1883832, rs1535045, and rs11086996 in patients with MS (n = 1684) and in the control group (n = 879). Two SNPs were significantly associated with MS: rs6074022 (additive model C allele OR = 1.27, 95% CI = [1.12–1.45], p = 3×10−4) and rs1883832 (additive model T allele OR = 1.20, 95% CI = [1.05–1.38], p = 7×10−3). In the meta-analysis of our results and the results of four previous studies, we obtain the association p-value of 2.34×10−12, which confirmed the association between MS and rs6074022 at a genome-wide significant level. Next, we demonstrated that the model including rs6074022 only sufficiently described the association. From our analysis, we can speculate that the association between rs1883832 and MS was induced by LD, whereas rs6074022 was a marker in stronger LD with the functional variant or was the functional variant itself. Our results indicated that the functional variants were located in the upstream region of the gene CD40 and were in higher LD with rs6074022 than LD with rs1883832.

Three allele combinations associated with Multiple Sclerosis

BackgroundMultiple sclerosis (MS) is an immune-mediated disease of polygenic etiology. Dissection of its genetic background is a complex problem, because of the combinatorial possibilities of gene-gene interactions. As genotyping methods improve throughput, approaches that can explore multigene interactions appropriately should lead to improved understanding of MS.Methods286 unrelated patients with definite MS and 362 unrelated healthy controls of Russian descent were genotyped at polymorphic loci (including SNPs, repeat polymorphisms, and an insertion/deletion) of the DRB1, TNF, LT, TGFβ1, CCR5 and CTLA4 genes and TNFa and TNFb microsatellites. Each allele carriership in patients and controls was compared by Fishers exact test, and disease-associated combinations of alleles in the data set were sought using a Bayesian Markov chain Monte Carlo-based method recently developed by our group.ResultsWe identified two previously unknown MS-associated tri-allelic combinations:-509TGFβ1*C, DRB1*18(3), CTLA4*G and -238TNF*B1,-308TNF*A2, CTLA4*G, which perfectly separate MS cases from controls, at least in the present sample. The previously described DRB1*15(2) allele, the microsatellite TNFa9 allele and the biallelic combination CCR5Δ32, DRB1*04 were also reidentified as MS-associated.ConclusionThese results represent an independent validation of MS association with DRB1*15(2) and TNFa9 in Russians and are the first to find the interplay of three loci in conferring susceptibility to MS. They demonstrate the efficacy of our approach for the identification of complex-disease-associated combinations of alleles.

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.

Polymorphism of apolipoprotein E (APOE) and lipoprotein lipase (LPL) genes and ischaemic stroke in individuals of Yakut ethnicity

There is evidence that most forms of ischaemic stroke (IS) result from synergistic effects of the modifiable predisposing factors and multiple genes. In the present work, we report results of case-control study of IS association with apolipoprotein E gene (APOE) (promoter and coding polymorphisms) and lipoprotein lipase gene (LPL) (presence/absence of a HindIII cutting site). We studied 107 unrelated patients of Yakut ethnicity (69 men and 38 women, mean age 58.4+/-11.5 years) with first-ever IS in carotid/middle cerebral artery regions. The control group included 101 subjects of the same ethnicity (61 men and 40 women, mean age 57.6+/-11.6 years) free of clinically detectable cerebrovascular disease, and without any history of stroke. A positive association of IS with APOE -427T allele (p=0.0012, OR=3.99) and -427T/T genotype (p=0.0005, OR=4.96) and a negative association with -427C allele (p=0.0012, OR=0.25), -427T/C genotype (p=0.0003, OR=0.18), epsilon2 allele (p=0.018, OR=0.35), epsilon2/3 genotype (p=0.017, OR=0.28) and -491A/-427C/epsilon2 haplotype (p=0.0026, OR=0.18) were observed. For atherothrombotic subgroup the same allele and genotype associations were found plus association with APOE -491A allele (p=0.026, OR=3.98). No reliable IS associations were found with LPL T+495G (HindIII) polymorphism. An association of APOE promoter polymorphisms (A-491T, T-427C) with an IS is shown in our study for the first time. Our study provides evidence for the role of APOE gene as a prognostic genetic marker for IS, especially for its atherothrombotic subtype.

Genome-wide significant association with seven novel multiple sclerosis risk loci

Objective A recent large-scale study in multiple sclerosis (MS) using the ImmunoChip platform reported on 11 loci that showed suggestive genetic association with MS. Additional data in sufficiently sized and independent data sets are needed to assess whether these loci represent genuine MS risk factors. Methods The lead SNPs of all 11 loci were genotyped in 10 796 MS cases and 10 793 controls from Germany, Spain, France, the Netherlands, Austria and Russia, that were independent from the previously reported cohorts. Association analyses were performed using logistic regression based on an additive model. Summary effect size estimates were calculated using fixed-effect meta-analysis. Results Seven of the 11 tested SNPs showed significant association with MS susceptibility in the 21 589 individuals analysed here. Meta-analysis across our and previously published MS case-control data (total sample size n=101 683) revealed novel genome-wide significant association with MS susceptibility (p<5×10−8) for all seven variants. This included SNPs in or near LOC100506457 (rs1534422, p=4.03×10−12), CD28 (rs6435203, p=1.35×10−9), LPP (rs4686953, p=3.35×10−8), ETS1 (rs3809006, p=7.74×10−9), DLEU1 (rs806349, p=8.14×10−12), LPIN3 (rs6072343, p=7.16×10−12) and IFNGR2 (rs9808753, p=4.40×10−10). Cis expression quantitative locus effects were observed in silico for rs6435203 on CD28 and for rs9808753 on several immunologically relevant genes in the IFNGR2 locus. Conclusions This study adds seven loci to the list of genuine MS genetic risk factors and further extends the list of established loci shared across autoimmune diseases.