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Introduction: We have reanalyzed the genomic data from the International Collaboration for the Genomics of HIV (ICGH), focusing on HIV-1 Elite Controllers (EC). Methods: A genome-wide association study (GWAS) was performed, comparing 543 HIV-1 EC individuals with 3,272 uninfected controls (CTR) of European ancestry. 8 million single nucleotide polymorphisms (SNPs) and HLA class I and class II gene alleles were imputed to compare EC and CTR. Results: Two thousand six hundred twenty-six SNPs were associated with EC (p<5.10-8), all located within the Major Histocompatibility Complex (MHC) region. Stepwise regression analysis narrowed this list to 17 SNPs. In parallel, 22 HLA class I and II alleles were associated with EC. Through meticulous mapping of the LD between all identified signals and employing reciprocal covariate analyses, we delineated a final set of 6 independent SNPs and 3 HLA class I gene alleles that accounted for most of the associations observed with EC. Our study revealed the presence of cumulative haploblock effects (SNP rs9264942 contributing to the HLA-B*57:01 effect) and that several HLA allele associations were in fact caused by SNPs in linkage disequilibrium (LD). Upon investigating SNPs in LD with the selected 6 SNPs and 3 HLA class I alleles for their impact on protein function (either damaging or differential expression), we identified several compelling mechanisms potentially explaining EC among which: a multi-action mechanism of HLA-B*57:01 involving MICA mutations and MICB differential expression overcoming the HIV-1 blockade of NK cell response, and overexpression of ZBTB12 with a possible anti-HIV-1 effect through HERV-K interference; a deleterious mutation in PPP1R18 favoring viral budding associated with rs1233396. Conclusion: Our results show that MHC influence on EC likely extends beyond traditional HLA class I or class II allele associations, encompassing other MHC SNPs with various biological impacts. They point to the key role of NK cells in preventing HIV-1 infection. Our analysis shows that HLA-B*57:01 is indeed associated with partially functional MICA/MICB proteins which could also explain this marker's involvement in other diseases such as psoriasis. More broadly, our findings suggest that within any HLA class I and II association in diseases, there may exist distinct causal SNPs within this crucial, gene-rich, and LD-rich MHC region. [ABSTRACT FROM AUTHOR]

Abstract Background We have developed a new haplotyping program based on the combination of an iterative multiallelic EM algorithm (IEM), bootstrap resampling and a pseudo Gibbs sampler. The use of the IEM-bootstrap procedure considerably reduces the space of possible haplotype configurations to be explored, greatly reducing computation time, while the adaptation of the Gibbs sampler with a recombination model on this restricted space maintains high accuracy. On large SNP datasets (>30 SNPs), we used a segmented approach based on a specific partition-ligation strategy. We compared this software, Ishape (Iterative Segmented HAPlotyping by Em), with reference programs such as Phase, Fastphase, and PL-EM. Analogously with Phase, there are 2 versions of Ishape: Ishape1 which uses a simple coalescence model for the pseudo Gibbs sampler step, and Ishape2 which uses a recombination model instead. Results We tested the program on 2 types of real SNP datasets derived from Hapmap: adjacent SNPs (high LD) and SNPs spaced by 5 Kb (lower level of LD). In both cases, we tested 100 replicates for each size: 10, 20, 30, 40, 50, 60, and 80 SNPs. For adjacent SNPs Ishape2 is superior to the other software both in terms of speed and accuracy. For SNPs spaced by 5 Kb, Ishape2 yields similar results to Phase2.1 in terms of accuracy, and both outperform the other software. In terms of speed, Ishape2 runs about 4 times faster than Phase2.1 with 10 SNPs, and about 10 times faster with 80 SNPs. For the case of 5kb-spaced SNPs, Fastphase may run faster with more than 100 SNPs. Conclusion These results show that the Ishape heuristic approach for haplotyping is very competitive in terms of accuracy and speed and deserves to be evaluated extensively for possible future widespread use.

Abstract Background Genetic association studies aim at finding correlations between a disease state and genetic variations such as SNPs or combinations of SNPs, termed haplotypes. Some haplotypes have a particular biological meaning such as the ones derived from SNPs located in the promoters, or the ones derived from non synonymous SNPs. All these haplotypes are "subhaplotypes" because they refer only to a part of the SNPs found in the gene. Until now, subhaplotypes were directly computed from the very SNPs chosen to constitute them, without taking into account the rest of the information corresponding to the other SNPs located in the gene. In the present work, we describe an alternative approach, called the "global method", which takes into account all the SNPs known in the region and compare the efficacy of the two "direct" and "global" methods. Results We used empirical haplotypes data sets from the GH1 promoter and the APOE gene, and 10 simulated datasets, and randomly introduced in them missing information (from 0% up to 20%) to compare the 2 methods. For each method, we used the PHASE haplotyping software since it was described to be the best. We showed that the use of the "global method" for subhaplotyping leads always to a better error rate than the classical direct haplotyping. The advantage provided by this alternative method increases with the percentage of missing genotyping data (diminution of the average error rate from 25% to less than 10%). We applied the global method software on the GRIV cohort for AIDS genetic associations and some associations previously identified through direct subhaplotyping were found to be erroneous. Conclusion The global method for subhaplotyping can reduce, sometimes dramatically, the error rate on patient resolutions and haplotypes frequencies. One should thus use this method in order to minimise the risk of a false interpretation in genetic studies involving subhaplotypes. In practice the global method is always more efficient than the direct method, but a combination method taking into account the level of missing information in each subject appears to be even more interesting when the level of missing information becomes larger (>10%).

To elucidate the genetic factors predisposing to AIDS progression, we analyzed a unique cohort of 275 human immunodeficiency virus (HIV) type 1-seropositive nonprogressor patients in relation to a control group of 1352 seronegative individuals in a genomewide association study (GWAS). The strongest association was obtained for HCP5rs2395029 (P = 6.79 × 10-10; odds ratio, 3.47) and was possibly linked to an effect of sex. Interestingly, this single-nucleotide polymorphism (SNP) was in high linkage disequilibrium with HLA-B, MICB, TNF, and several other HLA locus SNPs and haplotypes. A meta-analysis of our genomic data combined with data from the previously conducted Euro-CHAVI (Center for HIV/AIDS Vaccine Immunology) GWAS confirmed the HCP5 signal (P = 3.02 × 10-19) and identified several new associations, all of them involving HLA genes: MICB, TNF, RDBP, BAT1-5, PSORS1C1, and HLA-C. Finally, stratification by HCP5 rs2395029 genotypes emphasized an independent role for ZNRD1, also in the HLA locus, and this finding was confirmed by experimental data. The present study, the first GWAS of HIV-1 nonprogressors, underscores the potential for some HLA genes to control disease progression soon after infection. [ABSTRACT FROM AUTHOR]

We have performed an extensive analysis of Th1/Th2 cytokine receptors IL2Rα, IL4Rα, IL10Rα, and IFNγR1 gene polymorphisms to evaluate their impact on AIDS progression. The coding regions and promoters of these genes were sequenced in the genetics of resistance to immunodeficiency virus cohort, composed of 327 HIV-1-positive patients with extreme progression phenotypes, slow and rapid progressors, and of 446 healthy control subjects, all of them of Caucasian descent. Overall, 104 single nucleotide polymorphisms and four insertions/deletions with a minor allelic frequency higher than 1% were identified, 21 of them being newly characterized. We observed weak associations for 13 polymorphisms of IL2Rα, IL4Rα, IL10Rα, and IFNγR1, and 11 haplotypes of IL2Rα, IL4Rα, and IFNγR1. However, we could not relate these positive signals to any relevant biological information on the gene function. To affirm these putative associations in AIDS, further confirmation on other AIDS cohorts will be needed. This complete catalog of polymorphisms in IL2Rα, IL4Rα, IL10Rα, and IFNγR1 cytokine receptor genes should also be useful for investigating associations in other immune-related diseases. [ABSTRACT FROM AUTHOR]

In the early stage of drug discovery programs, when the structure of a complex involving a target and a small molecule is available, structure-based virtual ligand screening methods are generally preferred. However, ligand-based strategies like shape-similarity search methods can also be applied. Shape-similarity search methods consist in exploring a pseudo-binding-site derived from the known small molecule used as a reference. Several of these methods use conformational sampling algorithms which are also shared by corresponding docking methods: for example Surflex-dock/Surflex-sim, FlexX/FlexS, ICM, and OMEGA-FRED/OMEGA-ROCS. Using 11 systems issued from the challenging "own" subsets of the Directory of Useful Decoys (DUD-own), we evaluated and compared the performance of the above-cited programs in terms of molecular alignment accuracy, enrichment in active compounds, and enrichment in different chemotypes (scaffold-hopping). Since molecular alignment is a crucial aspect of performance for the different methods, we have assessed its impact on enrichment. We have also illustrated the paradox of retrieving active compounds with good scores even if they are inaccurately positioned. Finally, we have highlighted possible positive aspects of using shape-based approaches in drug-discovery protocols when the structure of the target in complex with a small molecule is known.