PASylation technology improves recombinant interferon-ß1b solubility, stability, and biological activity.

Recombinant interferon-ß1b (IFN-ß1b) is an effective remedy against multiple sclerosis and other diseases. However, use of small polypeptide (molecular weight is around 18.5 kDa) is limited due to poor solubility, stability, and short half-life in systemic circulation. To solve this problem, we constructed two variants of PASylated IFN-ß1b, with PAS sequence at C- or N-terminus of IFN-ß1b. The PAS-modified proteins demonstrated 4-fold increase in hydrodynamic volume of the molecule combined with 2-fold increase of in vitro biological activity, as well as advanced stability and solubility of the protein in solution as opposed to unmodified IFN-ß1b. Our results demonstrate that PASylation has a positive impact on stability, solubility, and functional activity of IFN-ß1b and potentially might improve pharmacokinetic properties of the molecule as a therapeutic agent.

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.

Three allele combinations associated with multiple sclerosis.

BACKGROUND: Multiple 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. METHODS: 286 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, TGFbeta1, CCR5 and CTLA4 genes and TNFa and TNFb microsatellites. Each allele carriership in patients and controls was compared by Fisher's 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. RESULTS: We identified two previously unknown MS-associated tri-allelic combinations:-509TGFbeta1*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 CCR5Delta32, DRB1*04 were also reidentified as MS-associated. CONCLUSION: These 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.

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.