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Definitions

• the present invention relates, in general, to human immunodeficiency virus (HIV) and, in particular, to genetic variants associated with restriction of HIV disease progression.
• HIV human immunodeficiency virus
• BACKGROUND Humans show remarkable variation in vulnerability to infection by HIV-I and especially in the clinical outcome following infection.
• One of the most striking differences is the plasma level of virus in the non-symptomatic phase preceding progression to AIDS (the viral set point).
• VL plasma viral loads
• a small fraction of this variability can be explained by demographic factors and variants of known genes such as chemokines, chemokine receptors and cytokines (about 15% of the variation in the dataset, see also Telenti et al, Nat.
• HIV-I set point is a particularly important phenotype not only because of its dramatic variability among individuals, but also because of its relative stability within individuals over time and its impact on disease progression and on infectiousness (Mellors et al, Science 272:1167 (1996)).
• a better understanding of the causes of the differences in VL could provide pointers to new vaccines and drugs that control the virus.
• it is essential to move beyond the targeted candidate gene studies that have characterized work to date (Telenti et al, Nat. Rev. Microbiol. 4:865 (2006)).
• a whole-genome association study of variation in the host control of HIV- 1 has been carried out focusing on the determinants of VL set point and secondarily on the progression towards AIDS (measured by the decline of CD4 positive cells).
• This study resulted in the identification of three genetic variants (or groups of variants) that associate with HIV load and restriction of disease progression. Those variants are described below and in PCT/US2008/003964.
• the present invention relates generally to HIV. More specifically, the invention relates to genetic variants associated with restriction of HIV disease progression and to methods of using such variants as prognostic markers. Objects and advantages of the present invention will be clear from the description that follows.
• HCP5 rs2395029 genotype (T major allele, G minor allele) (Fig. IA) and with HLA-C 5' region rs9264942 genotype (T major allele, C minor allele) (Fig. IB).
• FIG. 1 Partial map of the HLA Class I region (chromosome 6 p21.3). Indicated are the p-values [-log(P)] of all genotyped SNPs annotated with the gene structure. The 2 independent SNPs that show genome- wide significant association with HIV-I VL at set point are displayed and marked in red. Graph was drawn from WGA Viewer software (see website: genome.duke.edu/centers/ pg2/index_html/downloads/AnnotationSoftware).
• FIG. 3 A Non linear effect of HLA-C expression levels on HIV-I VL at set point. In italic are shown the numbers of patients linked to each point in Sanger Genevar database for expression data and in the cohort for set point results, respectively.
• Figs. 3B and 3C show the distributions of respective data according to genotypes.
• Figures 4A-4J (Fig. 4A) rs9264942; (Fig. 4B) rs6457374; (Fig. 4C) rs2395029; (Fig. 4D) rs9261 174; (Fig. 4E) rs2074480, (Fig. 4F) rs7758512, (Fig. 4G) rs9261129; (Fig. 4H) rs3869068; (Fig. 41) rs2301753; and (Fig. 4J) rs2074479. Figure 5. Examples of deletions and duplications at the KIR locus. Sample names are shown on the left, the genes are shown along the bottom. The CNVs are displayed as red (darker) (deletion) or green (lighter) (duplication) bars.
• FIG. 6A Effect of CNVs at KIR2 locus on HIV progression (Fig. 6A) and setpoint (Fig. 6B). Error bars depict standard error, sample sizes are shown above.
• Figures 7A and 7B Linkage disequilibrium with the KIR CNVs, assessed for 500kb either side.
• Fig. 7A shows the LD with the deletion
• Fig. 7B the LD with the duplication.
• HIV-I HIV-I .
• the present invention results, in part, from the identification of three genetic variants (or groups of variants) associated with important differences in HIV load, the most important prognostic marker of HIV disease progression. Together, these variants can explain a substantial part of inter-individual variability in HIV plasma levels. Identification of these variants sheds new light on HIV pathogenesis and on interactions between the immune system and the virus, thereby revealing new therapeutic targets.
• the invention also results, in part, from the identification of an association between a deletion at chromosome 19 ql3.42 and HIV progression (see Example 2 below).
• the invention relates to two single nucleotide polymorphisms located in the 5' region of the HLA-C gene in the MHC Class I region on chromosome 6: SNP reference numbers are rs9264942 and rs6457374 (for identity of the polymorphisms referenced herein, see ncbi.nlm.nih.gov/projects/SNP). (Fig. 4.) These genetic variants are associated with differences in HLA-C mRNA expression, and their 5' location is likely to explain this effect (promoter/enhancer).
• HLA*CwA had been suspected of being associated with rapid HIV progression (Carrington et al, Science 283(5408): 1748- 1752 (1999)) but the effect was more recently attributed to linkage of this type with HLA*B35-Px (Carrington, Annu. Rev. Med. 54:535-551 (2003)). In fact, a partial linkage with rs9264942 is a more likely explanation. This is the first observed quantitative effect of an HLA Class I protein on HIV viral load, independently of HLA type.
• the invention relates to a single nucleotide polymorphism located in a putative coding region of the HCP5 gene in the MHC Class I region on chromosome 6: SNP reference number is rs2395029.
• SNP reference number is rs2395029.
• the function of the HCP5 gene was previously unknown. However, based on structural analogy with human endogenous retroviruses, a link to anti-retro viral immunity had been suggested (Kulski et al, Immunogenetics 49(5):404-412 (1999)).
• the genetic variant identified here is located in a region that shares homology with the pol sequence of certain retroviruses (human endogenous retroviruses).
• the present invention relates to seven single nucleotide polymorphisms distributed between three genes in the MHC Class I region on chromosome 6: HCG9, RNF39 and ZNRDl .
• the SNP reference numbers are rs9261 174, rs2074480, rs7758512, rs9261129, rs3869068, rs2301753 and rs2074479. These variants are in perfect linkage disequilibrium, and it is thus impossible to distinguish between them regarding causality on the observed phenotype (better or worse control of HIV viral load). They are associated with significant differences in the expression of the zinc ribbon domain-containing 1 (ZNRDl) gene, which is a transcription-associated gene.
• ZNRDl zinc ribbon domain-containing 1
• ZNRDl is known to play a role in multidrug resistance phenotype of gastric cancer cells through upregulation of other genes (Shi et al, Cancer Biol Ther. 3(4):377-381 (2004)). Considering its structure and function, it is expected to have a direct influence on regulation of HIV transcription.
• HLA-C and ZNRDl genes play a key role in HIV infectivity.
• HCP5 is responsible for the observed effect on HIV load, its products (RNA, peptides) can be expected to have a direct functional role in defense against retroviruses.
• the present invention relates to a method of assessing the rate of a non-symptomatic HIV patient progressing to AIDS.
• the method comprises assaying DNA from the patient for the presence of a copy number variant (CNV) at chromosome 19 ql3.42.
• CNV copy number variant
• a patient carrying a deletion at chromosome 19 ql 3.42 is likely to undergo a more rapid progression to AIDS than is a non-systematic HIV patient that does not carry the deletion.
• a patient carrying a duplication at chromosome 19 ql 3.42 is likely to undergo a less rapid progression to AIDS than is a non-systematic HIV patient that does not carry that duplication.
• Resequencing of the genomic DNA region around SNPs specifically identified herein may reveal other SNP(s) associated with viral load/disease progression (i.e., the associated interval) - these could be predicted based upon their presence in the same haplotype or by being in linkage disequilibrium with the specific SNPs disclosed here.
• a sample e.g., a biological sample such as blood
• genotyping techniques known in the art (e.g., a "CHIP" or SNP panel). All SNPs described herein are present on Illumina's HumanHap550 genotyping BeadChip (see illuma.com). Suitable techniques also include the use of polymerase chain reaction and extension primers, RJLP analysis and mass spectrometry (see also Ye et al, Hum. Mutat. 17(4):305 (2001), Chen et al, Genome Res. 10:549 (2000).)
• kits suitable for use in testing for the presence of the polymorphisms identified herein can include, for example, reagents (e.g., probes or primers) necessary to identify the presence of the above- referenced polymorphisms.
• Criteria for inclusion Patients were eligible for the study if they had: (i) a valid seroconversion date estimation proven by biological markers:
• subjects could be included if they showed one or more biological criteria of primary infection: incomplete western blot and/or positive p24 Ag and/or high viremia (>1 million copies per milliliter of blood) and a consistent dynamic pattern of the biological parameters (completion of western blot, negativization of p24 Ag, decrease of peak viremia) - a compatible clinical syndrome was considered supporting evidence;
• Second step elimination of VL not reflecting the steady-state, through a computerized algorithm.
• Three types of outliers were identified, corresponding to the 3-phasic evolution of HIV-I viremia:
• VL measured before the set point has been reached part of the initial peak of viremia observed during primary HIV infection: they have to be measured during the first year after seroconversion and have a value >0.25 loglO higher than average of subsequent VL.
• the reclustering step creates SNP calling errors (even with 1000 samples in the file) but a procedure has been identified to prevent the errant calls from being released in the final report.
• the SNP data is screened within BeadStudio by looking at two criteria. First, all SNPs with a cluster separation value below 0.3 are manually checked to ensure correct calls. Many of these SNPs can be manually fixed but some have to be deleted. Next, any SNP (excluding X chromosome SNPs) with a Het Excess value between -1.0 to -0.1 and 0.1 to 1.0 are evaluated to determine if the raw and normalized data show a clean call. Any SNP cluster that does not appear normal is deleted.
• SNPs that appear to show a deletion This is done because these can be artifacts from either the chemistry or an interfering SNP during hybridization. These procedures resulted in a success rate of genotyping calls ranging from 97.5%-99% (13,709-5355 deleted SNPs). Two percent of samples were selected randomly to be genotyped twice independently for quality purpose. The concordance rate for duplicate genotyping was 99.99%. Also, ten SNPs from different chromosomes were re-genotyped using TaqMan assays. The concordance between the BeadChip and Taqman genotype calling was 100%. A total of 535 samples were run on the whole-genome chips. In total, 49 samples were excluded. A few of these were because of complete genotype failure (i.e. below 98%) but most were because of the high level of calling stringency (1% rule).
• This step performs a basic check of the data accuracy on the data flow pipeline from the output of the Illumina genotyping facility to the analytical process.
• PipeQC software the MAF report from PLINK was checked against the original locus report generated by genotyping facility. A check was made that the two MAF reports match exactly.
• IBD identity by descent
• This step performs a check whether the genotype missing is skewed towards high or low phenotype values and hence may give rise to spurious association p-values.
• PLINK software was used to perform this check on the top SNPs discussed herein. No genotype data violated this check. 0
• This step performs a check whether the observed genotype data deviate from HWE. This check was performed using PLINK software on the top SNPs. A deviation from HWE was defined with a criterion of P-value less than 0.05. No o genotype data violated this check.
• Modified EIGENSTRAT method to control for stratification This method derives the principal components of the correlations among gene variants and corrects for those correlations in the association tests. In principle, therefore, the principal components in the analyses should reflect population ancestry. It has been noticed, however, that some of the leading axes appear to depend on other sources of correlation, such as sets of variants near one another that show extended association. The potential for inversions has been documented to create this effect and it may be created by other causes of extended linkage disequilibrium as well.
• EIGENSTRAT axes were selected for use as covariates to adjust for ancestry in subsequent linear regression analyses as follows:
• a progression phenotype was defined as the time to drop of CD4 cells below 350 per milliliter of blood or the time to antiretroviral treatment start, whichever came first.
• an evaluation was made as to whether there was evidence of CD4 decline (significantly decreasing CD4 slope determined by a simple regression).
• the estimated slope of the decline was used to extrapolate the time that CD4 counts would drop below 350 and this was used as the time to progression (Douek et al, Annu. Rev. Immunol. 21 :265 (2003)).
• the Euro-CHAVI cohort represents a consortium of 8 European and 1 Australian Cohorts/Studies that agreed to participate in the Host Genetic Core initiative of the Center for HIV/AIDS Vaccine Immunology (CHAVI).
• CHAVI is a consortium of universities and academic medical centers established by the National Institute of Allergy and Infectious Diseases, part of the Global HIV Vaccine Enterprise. 676 patients have been selected from those cohorts on the basis of the above-mentioned criteria.
• 686 patients were finally included, after elimination of individuals with insufficient quality phenotype (see above) or genotype (see Experimental Details). 386 of them were eligible for progression analysis (309 progressors and 77 non progressors).
• HCP5 HLA Complex P5
• This particular HLA-B allele has the strongest described protective impact on HIV-I disease progression (Migueles et al, Proc. Natl. Acad. Sci. USA 97:2709 (2000)) and has been associated with low HIV-I viral load (Altfeld et al, AIDS 17:2581 (2003)).
• HLA-B5701 is indeed the strongest host genetic factor restricting HIV-I infection through a direct effect on early viral load (Altfeld et al, PLoS Med. 3 :e403 (2006)).
• HLA-B5701 Given the strong functional data supporting a role for HLA-B5701 in restricting HIV, the first hypothesis must be that the association observed here is due to the effect of HLA-B5701 reflected in its tagging SNP within HCP5 (de Bakker et al, Nat. Genet. 38:1 166 (2006)). However, genetics allows no resolution on whether this effect is exclusively due to B5701 or if HCP5 variation also contributes to the control of HIV-I . In fact, HCP5 itself is also a novel and strong candidate for contributing to HIV-I control. HCP5 is a member of a human endogenous retrovirus family (HERV) with sequence homology to retroviral Pol genes (Kulski et al, Immunogenetics 49:404 (1999)).
• HERV human endogenous retrovirus family
• a model in which the newly-associated HCP5 variant and the HLA-B5701 allele have a combined haplotypic effect on HIV-I set point is consistent with the observation that suppression of viremia can be maintained in B5701 elite controllers even after HIV-I undergoes mutations that allow escape from cytotoxic T-lymphocytes (CTL) mediated restriction (Bailey et al, J. Exp. Med. 203:1357 (2006)).
• CTL cytotoxic T-lymphocytes
• the second variant, rs6457374 is located 3 kb nearer the HLA-C gene (-32 kb in 5' region) and has an independent effect on HLA-C expression and also associates with HIV-I set point, but not independently of rs9264942.
• HLA-C expression SNP shows significant association with HLA-B5701, B27, B35Px, as well as with the HLA allelic groups Bw4 & Bw6.
• HLA-C expression variant can explain the effect of these alleles on HIV-I set point, the reverse is not true.
• HLA-C 5' expression polymorphism rs9264942 on set point is independent of its association with HLA-B alleles previously implicated in HIV-I control.
• the addition of rs9264942 to the linear regression model improves fit significantly for all HLA-B alleles or groups of alleles that are supposed to have an influence on HIV disease, as shown in Table Ia.
• HLA-B5701 has an independent impact after taking into account rs9264942 effect.
• HLA-C The independency of HLA-C is also clearly seen in the mean values of HIV-I set point for each rs9264942 genotype (Table Ib): the minor allele C is associated with a decrease in VL independently of all considered alleles and groups of alleles. Numbers refer to a subgroup of 156 patients with available 4-digit HLA Class I allelic results, a.
• HIV-I nef selectively down regulates the expression of HLA-A and -B but not of HLA-C on the surface of infected cells (Cohen et al, Immunity 10:661 (1999)).
• this strategy was considered advantageous for the virus because HLA-A and -B present foreign (notably viral) epitopes to CD8 T-cells resulting in cell destruction, whereas HLA-C binds self peptides and interacts with natural killer cells (NK) in order to avoid NK attack.
• NK natural killer cells
• HLA-C also has the ability to present viral peptides to cytotoxic CD8+ T cells and consequently restrict HIV-I (Goulder et al, AIDS 11 : 1884 (1997)); ten HLA C-restricted CTL epitopes have been described in the LANL database (www.hiv.lanl.gov). These observations suggest that there could be a threshold in expression above which HLA-C mediated viral restriction becomes an effective defense mechanism against HIV-I . In such a scenario, the natural incapacity of HIV-I nef to down regulate HLA-C molecules becomes an important advantage for the immune system.
• the strongest association with clinical progression includes a set of seven polymorphisms located in and near the ring finger protein 39 (RNF39) and the zinc ribbon domain containing 1 (ZNRDl) genes, respectively (rs9261 174, rs3869068, rs2074480, rs7758512, rs9261 129, rs2301753 and rs2074479).
• these variants are >1 MB centromeric from the previous candidate SNPs.
• ZNRDl encodes an RNA polymerase subunit
• a possible interaction with HIV-I during transcription is the most plausible causal mechanism if this gene indeed restricts HIV-I .
• Efficiency in provirus transcription is highly variable among individuals. In one study, differences in transcription efficiency alone accounted for 64 to 83% of the total variance in virus production that was attributable to post-entry cellular factors (Ciuffi et al, J. Virol. 78:10747 (2004)).
• HCP5 can contribute to the control associated with HLA-B5701 which, if true, would present immediate therapeutic opportunities.
• HLA-C restriction can constitute an important part of the control of HIV-I at sufficiently high expression levels of HLA-C. The latter result implicates HIV-I nef in determining virulence through differential downregulation of HLA class I molecules, limiting the function of HLA-A and -B alleles but highlighting HLA-C because it is resistant to nef. Future vaccine strategies could target HLA-C restricted T cell responses.
• HMM Markov model
• the rawCNV output was converted to a file usable in plink for genome-wide analysis. Separate files were created for deletions and duplications, representing a homozygous CNV as BB, a heterozygous CNV as AB and a homozygous CNV as AA.
• the WGA analysis was then run on the white samples using an additive linear regression model including sex, age and 11 Eigenstrat axes as covariates.
• Figure 8 depicts the KIR gene locus (from Martin & Carrington, Methods MoI. Biol. 415:49-64 (2008)). Because the CNVs were called using SNP data, it is not possible to get the exact endpoints of the events, so it is not clear how the deletions and duplications affect the different genes shown here.
• Figure 7 illustrates that there is a gap in SNP coverage, which was increased when the HumanHap550 chip was upgraded from version 1 (13 SNPs in this region) to version 3 (6 SNPs in this region). The reason for the lost SNPs is not clear, though it is possible that these relatively common CNVs were causing dropped genotype calls and so they were removed for QC purposes.
• NK cells play an important role in controlling viral infections, having both effector and regulatory functions. They express an array of inhibitory and activating receptors, notably the KIRs, which due to their extreme variability have a unique role in fine-tuning the balance between self-tolerance and cytotoxicity. KIRs bind to their ligands on the surface of target cells, principally to MHC class I antigens. The degree of inhibition mediated by interactions between coinherited KIR and MHC class I gene products determines the activation threshold for NK cells. Several studies have described epistatic interactions between certain KIRs and MHC class I genes that modulate the host response to HIV.
• the 3DL1/3DS1 locus encoding receptors for HLA-B Bw4-80I (with an isoleucine in position 80), appears to be particularly important.
• the presence of an activating KIR3DS1 allele in combination with HLA-B Bw4-80I has been shown to associate with protection against HIV disease progression (Martin et al, Nat. Genet. 31(4):429- 34 (2002), Epub 2002 JuI 22), as well as against opportunistic infections in HIV+ individuals (Qi et al, Plos Pathog 2(8):e79(2006)).

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