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An Additive Effect of Protective Host Genetic Factors Correlates With HIV Nonprogression Status

Salgado, María PhD*; Simón, Ainhoa CLT*; Sanz-Minguela, Beatriz CLT*; Rallón, Norma Ibón PhD*; López, Mariola PhD*; Vicario, José Luis MD; Benito, José Miguel PhD*; Rodés, Berta PhD*

JAIDS Journal of Acquired Immune Deficiency Syndromes: April 2011 - Volume 56 - Issue 4 - p 300-305
doi: 10.1097/QAI.0b013e3182036f14
Basic and Translational Science

Introduction: In HIV-positive individuals, complex multifactorial mechanisms control viral infection. In addition to viral and immunological factors, the host genetic background also plays an important role. Our objective was to evaluate how various genetic factors associated with delayed AIDS onset.

Methods: Thirty HIV+ long-term nonprogressors (LTNPs) and 30 known progressors were analyzed. Host genes were analyzed in peripheral blood mononuclear cells DNA: CCR5 and HLA were polymerase chain reaction typed. HLA-C5′, HCP5 polymorphisms, and CCL3L1 copy number were determined using real-time polymerase chain reaction.

Results: The CCL3L1high-copy-CCR5 deletion genetic risk groups was overrepresented in LTNPs. However, separately, neither CCL3L1 nor CCR5 were significantly associated with clinical outcome. HLA seemed as a strong nonprogression determinant, mainly HLA-B and the less-studied HLA-C. HLA-Cw0102 and HLA-C5′ had an impact on LTNP phenotype along with HLA-B5701 and B2705. The presence of allele combinations like HLA- B*5701-Cw0602, HLA-B*2705-Cw0102, or HLA-B*3801-Cw1203 had the strongest effect in non-progression. As for HCP5, no independent effect was observed. The studied factors had additive effects, and although the number of patients was small, it seemed that carrying a high number of protective alleles associated with progression delay.

Conclusions: We showed the additive load of protective host factors was predictive of nonprogression, and that HLA-associated factors were predominant in this global effect.

From the *Infectious Diseases Department, Hospital Carlos III, Madrid, Spain; and †Centro de Transfusiones, Madrid, Spain.

Received for publication April 12, 2010; accepted October 24, 2010.

Partially supported by Fondo de Investigación Sanitaria (FIS) project CP05/00278.

The authors have no funding or conflicts of interest to disclose.

Correspondence to: Berta Rodés, PhD, Department of Infectious Diseases, Hospital Carlos III, Calle Sinesio Delgado 10, 28029 Madrid, Spain (e-mail:

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The vast interindividual variability in disease progression observed in HIV-1 infection has been attributed to either viral defects,1-4 some host determinants (reviewed in5,6), or a combination of both. Lately, increasing data on host genes has widened the importance of host factors in mediating pathogenesis and limiting AIDS. Several allelic variants in genes encoding chemokine receptors and ligands, cytokines, HLA, and products mediating cellular immunity have been shown to influence the disease outcome.7-9

Analysis in the Euro-CHAVI (Center of HIV/AIDS Vaccine Immunology) cohort using genome-wide analysis identified allelic variants in HCP5 and HLA-C genes that explained nearly 15% of the variation in the viral load (VL) set point.7 Recently, other genome-wide analysis performed in a nonprogressors cohort confirmed the role of HCP5 and HLA-C5′ variants in disease progression and identified several new associations, all of them near the HLA region,10,11 which is one of the most polymorphic regions of the entire human genome.12 In the context of HIV, different HLA alleles can be associated with particular disease outcomes due to differences in the peptide-binding groove of HLA molecules, and hence the different fragments of HIV peptides presented for recognition by CTL.13 HLA allele distribution has been studied as a potent predictor of progression through its influence on cell-mediated immunity (CMI).14

Both CCR5, the major HIV coreceptor, and CCL3L1 gene, which encodes for MIP1α protein known as the most potent HIV-suppressive CCR5 ligand,15 are central determinants of HIV-AIDS pathogenesis. The CCL3L1-CCR5 axis affects viral entry and replication. Mutations in CCR5 affecting protein expression have been associated with intersubject differences in HIV susceptibility.9 It has also been shown that the CCL3L1 copy number is associated with the level of chemokine concentration and its relationship with risk of HIV acquisition.8 The different CCL3L1-CCR5 genotypes also modify the HIV clinical outcomes independently of viral-entry mechanisms. These genetic risk groups (GRGs) defined according to different inherited combinations of CCL3L1 dose and CCR5 mutations have an effect on the extent of early immune damage.16

Here we determined the contribution of all aforementioned host parameters affecting disease progression in a well-characterized cohort of long-term nonprogressors (LTNPs) established in 1997 at the Hospital Carlos III17 and compared them with a group of HIV+ patients with clear evidence of progression.

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Thirty LTNPs from the Hospital Carlos III cohort17 and 30 HIV-1+ progressor (defined below) patients were studied; all patients were white Spaniards and carried HIV-1 subtype B viruse; their characteristics are described in Table 1. LTNP patients were defined at the time of cohort inclusion as HIV-1+ individuals with more than 10 years of infection (since diagnosis), CD4 counts above 500 cells per microliter and naive for antiretroviral therapy. At the time of the analysis, all had VLs below 10.000 copies per millilitre, 13 of them were considered “elite controllers” (VL <50 copies/mL). Progressors were defined as individuals either with symptomatic infection or with a steady significant decline of CD4+ T cells (>100 cells/μL per year) within few years after seroconversion. Most of them (86%) were already under highly active antiretroviral therapy or initiated therapy soon after the study, as an indicator of progression. Informed consent was obtained from all participants in accordance with the Hospital Ethics Committee. Peripheral blood mononuclear cells of infected individuals were obtained by Ficoll-Histopaque (Sigma Diagnostics, St Louis, MO) density gradient centrifugation, and genomic DNA was extracted from these cells using QIAamp DNA blood extraction kit (Qiagen, Hilden, Germany).



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CCR5 Genotyping and CCL3L1 Gene Copy Number Determination

The presence of the CCR5-Delta32 allele was determined by polymerase chain reaction (PCR) in genomic DNA extracted from peripheral blood mononuclear cells. Assay conditions have been described elsewhere.18 The CCL3L1 copy number was estimated according to the method of Townson and González8,19 with few modifications. Briefly, real-time PCR was performed by using universal conditions in an Applied Biosystems 7300 Real-Time PCR System to detect FAM fluorescence from the probe for CCL3L1 and VIC fluorescence from the probe for β-globin (HBB) during amplification. CCL3L1 and β-globin primer sequences and probes were described elsewhere.8 Previously, CCL3L1 gene was cloned using TOPO TA Cloning Kit (Invitrogen, Carlsbad, CA) and checked to have 1 copy of CCL3L1 by sequencing. With this plasmid, we demonstrated that the commercial DNA used for β-globin (HBB) gene quantification (Roche Diagnostics, Mannheim, Germany) (known to have only 2 copies of HBB for diploid genome) carried 2 copies of the CCL3L1 for diploid genome. The cycle number at which the fluorescence reached a fixed threshold (CT) was determined. Four serial 1:10 dilutions were used to generate standard curves of CT value against the log (DNA) for HHB and for the CCL3L1 gene. For each tested sample, duplicate wells were set-up for CCL3L1 and HHB, CT determined, and converted into template quantity using the standard curves. The amount of DNA added to each PCR reaction was between 2-10 ng. Copy number was the ratio of CCL3L1 quantity to β-globin quantity, multiplied by two. For the analysis of CCL3L1 genotypes, below 2 copies was considered low copy genotype, between 2 and 3 copies was considered moderate, and above 3 was considered high.

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HLA Typing

HLA typing was performed by PCR-SSO using Luminex technology (Gen-Probe, San Diego, CA) for HLA class I-A, B, and C loci. Robust low/intermediate/high resolution results were achieved in accordance with genotypes and/or allele combinations found. HLA protective or nonprotective criteria were defined by revision of the bibliography for white populations.20,21 We considered as protective HLA: supertype B27 (which includes B*1401, *1402, *1503, *1509, *1510, *1518, *2701, *2702, *2703, *2704, *2705, *2706, *2707, *2708, *3801, *3802, *3901, *3902, *3903, *3904, *4801, *4802, *7301), supertype B58 (B*1516, *1517, *5701, *5702, *58) and other specific HLA A, B, and C alleles (A*25, A*26, A*32, A*34, A*66, B*13, B*51, B*73, B*81 and C*08); and as nonprotective HLA: the supertype B7 (B*0702, *0703, *0704, *0705, *1508, *3501, *3502, *3503, *51, *5301, *5401, *5501, *5502, *5601, *5602, *6701, *7801) and other specific HLA A, B, and C alleles (A*01, A*23, A*24, A*29, B*08, B*22, B*37, B*44, B*49, B*53, B*54, C*04 and C*16).

To study the linkage disequilibrium between different HLA haplotypes and the association with nonprogression, we used the HLA linkage disequilibrium tool from Los Alamos Immunology database (

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Single Nucleotide Polymorphism Genotyping

Single nucleotide polymorphisms (SNPs) in the coding region of HCP5 (rs2395029 T>G), and ∼35 kilobase upstream of HLA-C (HLA-C5′) (rs9264942 T>C) were genotyped using Applied Biosystems 7300 real-time PCR System, based on allelic discrimination assays following manufacturer's instructions. Primers and probes were obtained by Custom TaqMan SNP Genotyping Assays (ABI).

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Statistical Analysis

Qualitative variables were analyzed by χ2 or Fisher tests, when appropriate, to assess differences in each studied factor under the progression effect. For quantitative variables, a t test was used. All statistical analyses were done with SPSS package.

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Additive Genetic Factor Analysis

Additive unweighted genetic scores were used to analyse the combined effect of different host factors.23 Alleles with a protective effect were added, and alleles with a risk effect were subtracted. The genetic factors used in the score were: CCR5-Delta32 (score 0,1,2), CCL3L1 (0,1,2,3), HLA-C5′ (0,1,2), HLA-B2705 (0,1,2), HLA-B5701 (0,1,2), HLA-Cw0102 (0,1,2), HLA-Cw0602 (0,1,2), HLA-Cw1203 (0,1,2), HLA-B35 (0,-1,-2), HLA-Cw0701 (0,-1,-2), HLA-Cw0501 (0,-1,-2).

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CCR5 and CCL3L1 Characterization

We observed a higher frequency of the CCR5-Delta32 genotype in LTNPs, although differences were not significant. Whereas the LTNP group presented 17% patients with a deleted CCR5 gene, progressors had 7% (Table 2). All deletions were in heterozygosis. The CCL3L1 copy number measured in our population had a distribution similar to the European population described in Gonzalez et al,8 with a mean of 2 copies per genome. When we compared the CCL3L1 distribution in both groups, we observed that LTNP had a slightly higher mean gene copy number than progressors although differences were not significant (LTNP = 2.07 vs progressors = 1.83; P = 0.320). In Figure 1, the frequency of copy number distribution in both groups is represented. Among patients who had 2 copies or less of the CCL3L1 gene, we found 75% and 72% of progressors and LTNPs, respectively. In patients with more than 2 copies, the percentage was 25% for progressors and 27% for LTNPs.





The contribution of CCL3L1-CCR5 genetic risk groups in disease progression was measured by the frequency of low (CCL3L1high-copy-CCR5deletion), moderate (CCL3L1low-CCR5del or CCL3L1high-CCR5non-del), and high (CCL3L1low-CCR5non-del) GRGs in each group of patients. Although not significant, there was a tendency for a higher presence of the low GRG in LTNP (LTNP: 14.2% vs Progressors: 4.3%). The rest of GRGs showed no differences between LTNPs and progressors (Table 2).

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Protective and Nonprotective HLA Allele Frequency in LTNP and Progressors Patients

Four digits HLA class I-A, B and C loci were obtained for each patient. Frequencies of the protective/nonprotective allele presence were related to each phenotype. Thus, protective alleles were significantly more frequent in the LTNP group (LTNP: 90% vs prog = 63%). However, the opposite was not true for nonprotective alleles, although there was a tendency towards a higher presence in progressors (LTNP = 70% vs prog = 83%) (Table 2).

We also analyzed specific alleles, where some HLA B and C alleles were related to either one of the phenotypes (Table 3), but no associations were found with HLA A alleles. We observed that in the group of LTNPs, besides the 2 most well known HLA B*5701 and HLA B*2705 alleles associated with nonprogression, 3 new HLA C alleles were present; HLA Cw0102 significantly overrepresented in the nonprogression phenotype (P = 0.05), Cw0602 and Cw1203 with a trend toward a higher presence in LTNPs (both with P = 0.08). Regarding nonprotective associated alleles, differences were not as appreciable as in protective alleles. HLA B*35 (from B*3501 to B*3508), which is known to be related to rapid progression, was not significantly increased in our group of progressors. On the other hand, new alleles HLACw0501 and HLA Cw0701 were in higher proportion in this group, although differences were not significant (Table 3).



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Association of HLA Haplotypes With Disease Progression by Linkage Disequilibrium

As an alternative approach to studying associations between different HLA haplotypes and nonprogression, we used the HLA linkage disequilibrium tool from Los Alamos Immunology database ( The HLA linkage disequilibrium between different alleles present in each group was measured. We observed that the overrepresented alleles in our population were associated. Thus, in the LTNP group, 6 of 8 HLA B*5701 subjects (75%) also carried HLA Cw0602 (P = 0.001). Likewise, 5 of 7 (71%) patients with HLA B*2705 carried Cw0102 (P = 0.002) and some of them4 also carried A*1101 (P = 0.016). HLA Cw1203 was associated with HLA A*2601 and B*3801 (P = 0.02). In progressors, no associations were seen between HLA B*3501 and other alleles, whereas HLA Cw0501 was linked with A*3002 and B*1801 (P = 0.009). HLA Cw0701, which individually was slightly linked to progression, seemed related with 2 nonprotective alleles (A*0101 and B*0801, P = 0.002).

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SNP Frequencies and Association With HLA Alleles

Table 2 shows the frequencies of HCP5 and HLA-C5′ polymorphisms in our patients. As expected, HCP5 heterozygosity (C/T) was highly represented in LTNP patients. In addition, we observed a higher percentage of both heterozygote and homozygote HLA-C5′ variant genotype (TC and CC) associated with nonprogression status.

Regarding the association of these changes with HLA specific alleles, HCP5 was 100% related to the HLA B*5701 presence (P = 0.000) and, in a lower proportion, to Cw0601 allele (67%, P = 0.000). HLA-C5′ wild type (TT) form was related with having HLA Cw0701 allele (56%, P = 0.007), which suggests the relationship of this common allelic variant with progression. The minority form of the polymorphism had a weak relationship with HLACw0501 (20.5%, P = 0.050) and HLA Cw2705 (16.3%, P = 0.086).

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The Combined Effect of HLA Alleles, HLA-C5′, CCR5, and CCL3L1 With Disease Progression

After analyzing the influence of each factor individually to the nonprogression status, we evaluated their combined effect in association with the LTNP phenotype. We took as protective factors: CCL3L1high-copy-CCR5deletion GRG genotype, carrying HLA B*5701, B*2705, Cw0102, Cw0602, or Cw1203 alleles, and the presence of HLA-C5′ variants. Thus, we observed important differences in the sum of protective factors within each group, being higher in LTNPs (mean LTNPs: 2.3 vs mean progressors: 0.8 P < 0.001). It seems that an additive effect of the protective factors had a greater association with the LTNP phenotype than each factor separately. We intended to determine the independent weight of each factor in the progression status, but the multivariate analysis could not be performed due to the small number of studied subjects and also to the particular distribution of some variables observed in our population. Finally, we follow a different approach where a simple genetic score (described in Methods) was used to correlate the number of protective and risk genetic factors with VL. We observed a correlation trend between increase VL and a low genetic score (P = 0.067). The average additive genetic score was 3.2 for LTNP and 0.76 for progressors (Fig. 2).



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A complex interplay between virus and host factors seems to mediate AIDS pathogenesis and differences among phenotypes. Host genetic factors with an important contribution to this interaction are the presence of protective HLA alleles influencing CMI14,24,25 as well as related allelic polymorphisms in HCP5 and HLA-C genes. Other host factors affecting CD4+ loss and progression are CCR5 and CCL3L1, which influence viral entry events, replication and CMI processes.16 In this study, we analyzed these genetic risk factors in 2 groups of patients with well-defined phenotypes to elucidate which had a stronger influence in determining their LTNP or progressive state.

We analyzed some genetic variants in CCR5 and CCL3L1 genes separately, and the interaction of both, and their association with HIV disease progression. No strong differences for the CCR5-Delta32 deletion were seen between our groups of LTNP and progressors as it has been observed in other cohorts.26-29 This suggests that CCR5-Delta32 allele alone was not a determinant of outcome in our LTNP cohort, probably due to the low prevalence of this genotype in the Spanish population. But, we cannot discount that other CCR5 variants or gene interactions affecting CCR5 expression, such as -2459 A/G genotype in the CCR5 promoter,30 could contribute to the LTNP trait in our cohort because we did not analyzed them. Similarly, CCL3L1 copy number alone had a small contribution to the LTNP trait, even though it has previously been linked to lower HIV-1 susceptibility.8 Our results are in agreement with the study by Nakajima et al.31 On the other hand, the over representation of 1 low risk CCR5-CCL3L1 GRG observed in our LTNP patients suggests that the combination of CCR5-CCL3L1 genotypes might have a protective effect on progression, but the small number of patients prevented us to have a more clear picture.

Taken together, the analyzed viral entry-related factors did not seem to have a major effect in our LTNP cohort. However, we cannot completely rule out their contribution because other GRG CCL3L1-CCR5 combinations could also sum toward nonprogression.

As for the HLA factor, strong differences were found in frequencies between both groups. HLA class I, and specifically the HLA B locus, has been studied widely in the progression field; HLA-B57 and related alleles14,24,32-35 and HLA B27 (in HIV-1 clade B-infected whites)14,32-34 have the most reproducible association with low viremia and prolonged survival. On the contrary, another set of structurally distinct HLA-B locus alleles, defined as the HLA-B7 supertype, has been associated with high viraemia, relatively poor CTL responses, and fast progression to AIDS in whites, predominantly with HIV-1 subtype B.14,33,34

These associations recurred in our patients' cohort where protective alleles were overrepresented in LTNP. Thus, the presence of a specific set of HLA protective alleles can be considered as a predictive factor for slower progression to AIDS. In addition, we observed an association not only with well-known HLA-B alleles but also with HLA-C and nonprogression status. No HLA-A alleles were associated with either phenotype, which is in agreement with previous studies that demonstrated that HLA-B alleles impose substantially greater selection pressure on the virus than HLA-A and, therefore, exert a dominant influence on viral set-point, absolute CD4 count and thereby in the rate of AIDS progression.36 In our study, these associations have been confirmed in by a novel approach; besides HLA B*5701 and B*2705, 3 nonreported HLA-C alleles have been related with LTNP status (Cw0102, Cw0602, and Cw1203). The role of HLA-C has historically been underestimated, but recent reports show that, in the same way the number of HLA-B-associated polymorphisms in Gag was strongly associated with lower VL, a strong correlation was also observed between the number of polymorphisms within Pol selected by HLA-C alleles and the median VL.37 This would suggest HLA-C as a new factor that may be involved with control of infection and progression to AIDS. However, due to the small sample size in our study, which reduces the statistical power, further studies are needed before this conclusion can be drawn.

In addition, we observed in a linkage disequilibrium approach that some of these alleles seemed together with higher frequency in LTNP patients. Combination of specific HLA alleles within a patient may have a stronger antiviral potency due to a better CMI against the virus and determine the host control. According to our data, carrying some allele combinations like HLA B*5701-Cw0602, HLA B*2705-Cw0102, or HLA B*3801-Cw1203 would be the strongest factors associated with nonprogression status.

Fellay et al7 identified 2 alleles in HCP5 and HLA-C genes which explained nearly 15% of the variation in the VL set point. A recent study11 confirmed this association with VL for SNPs HLA-C rs9264942 and HCP5 rs2395029 and additionally with delayed disease progression. In our study, we analyzed the association of these factors with well-established phenotypes, confirming the higher frequency of HLA-C5′ and HCP5 minor variants in LTNPs, the latter with strong association with HLA B*5701 and HLA Cw0602. Thus, these polymorphisms seem to play an important role in nonprogression either by a direct effect or by association with specific HLA. Recent reports have also confirmed the HCP5 association with nonprogression in a cohort of LTNP10 and its relationship with HLA B*5701 and HLA-Cw0638; which support that HCP5 does not explain HIV disease progression per se. On the contrary, HLA-C5′ rs9264942 minor variant was a predictive factor of nonprogression according to the univariate analysis. Unfortunately, due to the small size of the studied population, no multivariate analysis could be performed to discount the contribution of other factors.

Despite the fact that some of the studied factors have an association with LTNP phenotype, none of them in isolation has a decisive influence in the delay of AIDS symptoms. This suggests that it may be the cumulative effect of the protective genetic dose what determines any phenotype. For that reason, we compared in both groups of patients the number of positive factors present, obtaining strong differences between them and with results similar to the additive genetic score of 3 for LTNP and 0.9 for progressors recently reported by Casado et al.23 The cumulative number of protective genetic factors may be an important determinant of the HIV nonprogression, even though some factors may have an independent influence and/or a stronger influence than others. The latter are all related to cellular immunity, and interestingly may be specifically related to HLA-C mediated responses, in addition to the well-documented association with HLA-B.39

In conclusion, we observed in our cohort of LTNP patients that carrying a greater “protective genetic dose” may be a predictive factor of a delayed progression to AIDS. Although HLA-C's role on viral pathogenesis is still not well known, it could be important in protection against progression. Additional studies with larger populations are necessary to substantiate these findings.

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The authors thank Dr. Carlos Toro for advice and helpful discussions; the clinical investigators, Dr. Eugenia Vispo and Dr. Pablo Labarga, who provided and cared for study patients; and Dr. Vincent Soriano and Dr. Juan González-Lahoz for their support.

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HLA; genetic factors; LTNP; SNP

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