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.

Background: The myelin basic protein (MBP) gene may confer genetic susceptibility to multiple sclerosis ( MS). The association of MS with alleles of the (TGGA)(n) variable number tandem repeat ( VNTR) 5' to the MBP gene is the subject of conflicting reports. Objective: To study possible MS association with VNTR alleles of MBP gene in ethnic Italians and ethnic Russians. Methods: Two hundred sixty-nine unrelated patients with definite MS and 385 unrelated healthy control subjects from Italy and Russia were genotyped for the MBP VNTR region and for the human leukocyte antigen (HLA) class II DRB1 gene. The phenotype, allele, and genotype frequencies for two groups of MBP alleles were determined. Patients and control subjects were stratified according to HLA-DRB1 phenotypes. Results: The distribution of MBP alleles and genotypes in the two ethnic groups, including both MS patients and control subjects, was very similar. When MS patients and healthy control subjects were stratified according to HLA-DRB1 phenotypes, a significant association of MS with MBP alleles was found only in the DR4- and DR5-positive subgroups. A significant association with MBP alleles was also observed in the nonstratified groups, owing mainly to the contribution of the DR4- and DR5-positive individuals. Conclusion: Polymorphism of the MBP or another gene in its vicinity appears to contribute to the etiology of MS for the subgroups of DR4- and DR5-positive Italians and Russians.

The myelin basic protein gene (MBP) can confer the susceptibility to multiple sclerosis, because its protein product is the main protein component of myelin of the central nervous system and a potential autoimmune antigen in the disease. A possible association of multiple sclerosis with alleles and genotypes of a microsatellite repeat (TGGA) n , located to the 5′ side from the first exon of MBP in ethnic Russians (126 patients with definite multiple sclerosis and 142 healthy controls from Central Russia) was analyzed in a case–control study. Upon separation of the tetranucleotide repeat amplification products in 1.5% agarose gel, one can see two distinct bands that can be analyzed as two allele groups (A and B). The distribution of allele A and B group frequencies as well as phenotype frequency of alleles B and genotype frequency of A/A differs significantly in multiple sclerosis patients and healthy controls. Alleles A and genotype A/A are associated with multiple sclerosis. We also analyzed the association of multiple sclerosis with combined bearing of alleles and genotypes A and B of MBP and groups of alleles of the DRB1 gene of the major histocompatibility complex that correspond to serological specificities DR1-DR18. The comparison of subgroups of multiple sclerosis patients and healthy individuals, stratified according to HLA-DRB1 phenotypes, has shown a reliable increase in the phenotype frequency of allele B in healthy individuals and the genotype A/A frequency in patients, only among DR4- and DR5-positive individuals. No significant difference was found in the MBP allele and genotype distribution between multiple sclerosis patients and healthy individuals in combined groups of (DR4,DR5)-negative individuals, i.e., in the group of carriers of any phenotype except DR4 and DR5. Thus, MBP or some other nearby gene is involved in the multiple sclerosis development in Russians, predominantly (or exclusively) among DR4 and DR5 carriers. In this case, without stratification of analyzed individuals by the MBP alleles, multiple sclerosis is associated only with DR2(15), but not DR4 and DR5 alleles of DRB1. The results obtained are in favor of the genetic heterogeneity of multiple sclerosis, and suggest the possibility of epistatic interactions between the MBP and DRB1 genes.

The authors studied the possible association between the presence of a 32-base pair deletion allele in CC chemokine receptor 5 gene [3p21] (CCR5 Delta 32 allele) and the occurrence of MS. The presence of CCR5 Delta 32 homozygotes among patients with MS indicates that the absence of CCR5 did not protect against MS. Moreover, the CCR5 Delta 32 mutation was associated with MS in HLA-DR4-positive Russians (p(corr) < 0.001, odds ratio [OR] = 25.0). The (CCR5 Delta 32,DR4)-positive phenotype was negatively associated with early MS onset (at ages < or = 18 years) (p = 0.0115, OR = 0.1).