Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Killer immunoglobulin-like receptors and HLA act both independently and synergistically to modify HIV disease progression

Abstract

Variation in the host response to infection by pathogens including HIV-1 may be conferred by polymorphic genetic factors such as HLA and killer immunoglobulin-like receptors (KIR) genes. Here, we examined KIR and HLA genotype effects on pretreatment viral load, rate of CD4+ T-cell decline and progression to AIDS among adult HIV-1-infected patients within the Western Australian HIV Study Cohort. In this study, carriage of KIR genes within the ‘B’ haplotype (eg KIR2DS2) was specifically associated with a more rapid CD4+ T-cell decline over time and progression to AIDS. In contrast, KIR gene repertoire had no effect on pretreatment viral load while selected HLA alleles (eg HLA-B*5701, HLA-B*2705) demonstrated significant protective effects on viremia. Furthermore, interactions between specific HLA and KIR genes did appear to influence HIV disease progression. The results suggest that host genetic variation within the HLA and KIR gene complexes have clinically relevant effects on the course of HIV-1/AIDS, acting independently as well as synergistically to modify disease progression at multiple levels.

Introduction

Host genetic factors are known to influence the course of HIV-1 infection, and are likely to operate at several levels to influence disease phenotype.1, 2 For example, the ability to mount an effective and durable cytotoxic T-lymphocyte response to HIV has been shown to influence pretreatment viral load,3, 4 which in turn predicts CD4+ decline and progression to AIDS.3, 5, 6, 7 In this context, associations between viral load set point and particular HLA class I alleles and MHC haplotypes have been identified,8, 9, 10, 11 with evidence that HLA-restricted immune responses represent a major selective force for viral adaptation at both the individual and population level.4 However, other genetic factors such as the NK cell receptors, Killer Immunoglobulin-like Receptor (KIR) genes, which directly interact with HLA could also affect the susceptibility of CD4+ T-cells to undergo cell lysis independent of the viral burden, and may also play a role in determining the development of individual AIDS-defining illnesses by specifically shaping the immunological response to opportunistic pathogens.1, 2

The KIR genes on chromosome 19p13.4, like the HLA genes on chromosome 6p21.3, are recognition molecules critical for host immune responses and are encoded within a highly polymorphic region of the human genome. The KIR gene complex demonstrates strong interlocus linkage disequilibrium (LD), producing a number of relatively common KIR genotypes12, 13, 14, 15 that can be resolved into two broad haplotypes (denoted ‘A’ and ‘B’) consisting of a centromeric and a telomeric region separated by framework loci that are common to both haplotypes (see Figure 1). As is the case for the MHC region, this haplotypic organisation is likely to define the limits within which disease associations can be resolved to individual genetic loci.16, 17 There are now numerous studies indicating the relevance of the KIR genes with their HLA ligands to a number of diseases (eg Psoriatic Arthritis, diabetes) and infection outcome (Hepatitis C).18, 19, 20

Figure 1
figure1

Genomic organisation of the common KIR haplotypes ‘A’ and ‘B’. Open boxes indicate framework loci. Hash indicates that the locus has been tested in this study. Modified from Martin et al15.

A role for the KIR system in influencing outcome in HIV-1 infection is likely given the role of KIRs in controlling NK mediated cytotoxicity. For example, KIRs monitor the expression of self-MHC class I motifs presented on the surface of infected cells and can induce cytotoxicity when expression is absent (‘missing self’),21 thereby providing a mechanism by which immune surveillance can be preserved in the face of downregulated MHC Class I expression induced by HIV regulatory proteins22, 23 and by other immunomodulatory viruses such as Kaposi's sarcoma-related human herpesvirus.24, 25 In this respect there is evidence that these viruses have evolved under selective pressure provided by KIR-mediated cytotoxicity, as their propensity to escape immune surveillance through reduced surface MHC Class I expression has been balanced by the preserved expression of specific MHC class I loci (eg HLA-C and HLA-E) that generally act as inhibitory ligands for KIRs.21 Accordingly, recent in vitro evidence strongly supports a role for HLA-C and HLA-E expression in preventing NK-mediated cytotoxic responses directed against HIV-1-infected CD4+ T-cells.26, 27

The effects of KIRs on host immune responses are modulated by their specific interaction with their ligands, which may result in either activation or inhibition of cytotoxicity. Several inhibitory KIR ligands are known (reviewed in Long et al28) although the ligands for a number of activating KIRs remain unknown. The immunological consequences of KIR/ligand binding may therefore reflect specific interactions between KIR and HLA molecules, and the balance between activating and inhibitory responses that are mediated by multiple KIRs. In the case of HIV-1 infection, a previous study has revealed an association between rapid progression to AIDS and an activating KIR gene (KIR3DS1), and selective abrogation of this effect in the presence of HLA Bw4 alleles that encode an inhibitory KIR ligand.29 The epistatic interaction between these HLA and KIR alleles resulted in significant protection from AIDS.

In this study, we have studied associations between KIR genotypes and haplotypes and their HLA ligands with HIV-1 disease outcomes. Our results suggest that KIR and HLA alleles act both independently and synergistically to modify the host response to HIV infection, and that effects of KIR genotype can be seen at multiple levels in the progression of HIV/AIDS. Moreover, the magnitude of some of these host genetic effects on the course of HIV-1 disease progression may be relevant to the clinical management of HIV-1 infection.

Results

HLA and KIR genotype have different effects on initial %CD4+ T cells and rate of CD4+ T-cell decline

Initially, we examined associations between host genetic markers, including KIR genotype and markers previously shown to influence HIV outcome, and CD4+ T-cell measures, utilising a well-characterised longitudinal cohort of 191 Caucasoid HIV-1 infected individuals from the Western Australian HIV cohort30 (Table 1) with documented seroconversion times. The results for all markers examined in this longitudinal study are given in Table 2. Carriage of HLA-B*5701 was associated with significantly higher average initial %CD4+ T-cells (P=0.05), but was not associated with differences in the rate of subsequent %CD4+ decline (P=0.4), as shown in Figure 2a. In contrast, two KIR loci known to be in strong LD carried on the centromeric region of the ‘B’ haplotype (KIR2DS2 and KIR2DL2) were significantly associated with rapid rate of %CD4+ decline (P=0.005 and 0.006, respectively; Table 2). In particular, as shown in Figure 2b, the presence of KIR2DS2 was associated with a significantly faster rate of %CD4+ decline (P=0.005) while having no significant impact on CD4+ T cells at the time of seroconversion (P=0.4). Given the decay in the LD across the KIR region,12, 13, 14, 15 the KIR2DS2 results may reflect the importance of the centromeric part of the ‘B’ haplotype. Interestingly, in our cohort, we were unable to show any significant effect of KIR3DS1 on either %CD4+ decline or time to AIDS.

Table 1 Demographic and clinical profiles of HIV-1 seropositive patient groups analysed for three key outcome measures
Table 2 Single gene analyses of HLA and KIR variants with relation to %CD4+ decline and time to AIDS within the longitudinal study of the seroconverter cohort
Figure 2
figure2

Effect of HLA and KIR on %CD4+ parameters. (a) HLA-B*5701 is associated with higher average %CD4+ levels (P=0.05) and (b) KIR2DS2 is associated with rapid %CD4+ decline (P=0.003). Mixed effects regression models adjusted for age, sex, and route of transmission were used for the analyses. The thin dotted lines represent individual %CD4+ profiles based on sequential pretreatment measures for HIV-1 infected individuals from the time of seroconversion. The solid bold lines show estimated population-average trends of %CD4+ in the presence (red lines) and absence (blue lines) of (a) HLA-B*5701 and (b) KIR2DS2. Restricting the data shown to no more than 4 years follow-up gave stronger results in the mixed-effects models: increased rate of decline in the presence of KIR2DS2 (P=0.001), while greater difference at baseline in the presence of HLA-B*5701 (P=0.02), but similar rate of decline (P=0.8).

We next examined whether the number of KIR2DS2 copies was important. Our KIR typing method (described in Patients and methods) does not allow the direct determination of gene copy number; however, we used the allelic nature of KIR2DL3 with KIR2DL2 and thus KIR2DS2 to indirectly define the number of KIR2DS2 copies. The gene number of KIR2DS2 was associated with more rapid CD4+ T-cell decline (P=0.004; Figure 3a). These results are consistent with the finding that KIRs generally encoded on the ‘B’ group haplotypes are associated with relatively faster rates of CD4+ T-cell decline compared with functional KIRs present within the ‘A’ haplotype (see Table 2).

Figure 3
figure3

KIR2DS2 dosage effect on (a) profiles of %CD4+ decline and (b) Kaplan–Meier plots of progression to AIDS. KIR2DS2 gene number defined by: 0—presence of KIR2DL3 and absence of both KIR2DL2 and KIR2DS2; 1—presence of KIR2DL3 and both KIR2DL2 and KIR2DS2; 2—absence of KIR2DL3 and presence of both KIR2DL2 and KIR2DS2. Plots are adjusted for age, sex and route of transmission. The copy number of KIR2DS2 was significantly associated with more rapid decline of CD4+ T cells (P=0.004; Wald test) and more rapid progression to AIDS (P=0.01, likelihood ratio test).

HLA and KIR genotype both influence rate of progression to AIDS

We next examined whether host genetic factors influence the risk of progression to AIDS in the same longitudinal cohort. These analyses were designed to assess the contribution of HLA and/or KIR genetic factors to AIDS risk bearing in mind that genetic effects could impact this risk in two ways, either through an influence on the severity of immune deficiency over time (measured by CD4+ T-cell count decline) or by directly modifying the risk of developing specific AIDS-defining illnesses over and above their effects on CD4+ T-cells.

HLA genotype associations

As expected from the previous observations regarding their impact on CD4+ T-cell levels, HLA-B*5701 was associated with prolonged time to AIDS diagnosis (relative hazard (RH)<0.1, P<0.001) (Table 2). In contrast, HLA-B*35 Px alleles were associated with a trend towards an increased RH for rapid progression to AIDS. The known KIR ligands HLA-B Bw4 or Bw4(80Ile) and the HLA-C C1 and C2 alleles revealed no significant effects on HIV outcomes in univariate analysis (Table 2).

KIR genotype associations

As may have been anticipated by the effects of the centromeric ‘B’ haplotype (marked by KIR2DS2 and KIR2DL2) on CD4+ T-cell decline, analyses showed KIR2DS2 was associated with faster progression to AIDS (RH=2.1, P=0.04). However, this effect on AIDS risk did not appear to be completely explained by the more rapid decline in immune function seen in the CD4+ profiles. While a centromeric ‘B’ haplotype dosage effect on time to AIDS is also evident (Figure 3b, RH=2.1 per KIR2DS2 copy number, P=0.01), it appears that there is a moderating influence that can be attributed to the inhibitory gene KIR2DL3 (RH=0.2, P=0.02) and/or one of the other ‘A’ haplotype genes in strong LD with it, such as KIR2DL1(A) (RH=0.3, P=0.1) or KIR3DL1 (RH=0.1, P=0.02). Hence, these data suggest that the detrimental effects of the number of centromeric ‘B’ haplotypes present on HIV-1 disease are mediated in part by a direct impact on CD4+ T-cell decline, but the risk of developing an AIDS-defining illnesses may be modified by specific genetic effects that are independent of the severity of CD4+ depletion. Interestingly, KIR2DS3, the gene with the lowest frequency (0.25), had the highest RH for time to AIDS of all the activating genes (RH=2.2, P=0.05). While this gene can be located at either the centromeric or telomeric end of the ‘B’ haplotype, it appears to more often be the former (LD=0.07 vs LD=0.05). Of note also, the haplotype dosage effect observed at the centromeric end was not evident at the telomeric end (P=0.2; data not shown). Although the absence of the inhibitory gene KIR3DL1 was associated with faster progression to AIDS (RH=1/0.1=10, P=0.02), no significant detrimental effect was specifically observed with presence of either KIR2DS1 or KIR3DS1.

Notably, adjusting for carriage of HLA-B*5701 and -B*2705 in multiple gene analyses did little to abrogate the observed KIR gene effects on progression to AIDS. In particular, the effects of carriage of KIR2DL3, KIR3DL1 and KIR2DL3 remained significant (P=0.05, 0.03 and 0.05, respectively) as did the gene number of KIR2DS2 (P=0.01).

HLA, but not KIR genotype, influences pretreatment viral load set-point

We next set out to confirm previously reported associations between host genetic markers and pretreatment viral load set point, utilising the cross-sectional cohort of 174 Caucasian individuals with high-resolution pretreatment viral load data obtained for the purposes of investigating host–viral interactions at a population level.4 As expected, HLA-B*5701 (P=0.002), -B*2705 (P=0.07), -B Bw4 (P=0.02) and CCR5Δ32 (P=0.04) were strongly associated with a significantly lower viral load set point,1, 2, 31 although the effects of HLA-B Bw4 were abrogated in multivariate analysis adjusted for the Bw4-associated alleles HLA-B*5701 and -B*2705. No significant associations between any KIR gene and viral load set point were detected (all had a P>0.2).

HLA and KIR working synergistically

Regulation of NK cell function is mediated through the interaction of inhibitory and activating KIR with their HLA ligands, effects that may not be captured in simple single gene analyses. As this study lacks the numbers to sufficiently power multiple gene analyses that include interaction terms, we have chosen instead to investigate potential interactions between KIR and their known HLA ligands on HIV disease progression by qualitatively examining differences observed between the single gene analyses of Table 2 and the gene effects when the sample was restricted to those carrying the appropriate ligand. In particular, in analyses of effects on progression to AIDS and rate of %CD4+ decline, we considered KIR3DL1 or KIR3DS1 and carriage of HLA-B Bw4 alleles (including the subset of alleles carrying Bw4(80Ile)); KIR2DL2, KIR2DS2 or KIR2DL3 and carriage of HLA-C C1 alleles; and KIR2DS1 or KIR2DL1 and carriage of HLA-C C2 alleles.

We first looked at effects of KIR genes in the presence of their putative ligands on time to AIDS. When the sample was restricted to those carrying HLA-B Bw4 alleles, there was a marked increase in the protection afforded by carriage of KIR3DL1 (RH=0.04, P=0.007, n=82). While there was no evidence of an interactive effect between HLA-B Bw4 and KIR3DS1 on development of AIDS, when this analysis was restricted to the carriers of HLA-B Bw4(80Ile), there was a notable increase in the RH associated with KIR3DS1 (RH=14, P=0.02, n=34). Interestingly, this effect is opposite to that observed by Martin et al29 in their European American cohort although they were unable to demonstrate a significant synergistic relationship when considering death or time to AIDS using the 1987 definition (as used in our study).

Restriction to carriers of HLA-C C1 made little difference to the protective effect of KIR2DL3 (RH=0.25, P=0.02) although a moderate increase in the RHs associated with both KIR2DS2 and KIR2DL2 was observed (RH=2.40, P=0.02, n=125 and RH=2.23, P=0.03, n=128 respectively). When this analysis was restricted to carriers of HLA-C C1 no significant effects of either KIR2DS1 or KIR2DL1(A and B) were observed but there was a notable increase in the protection associated with KIR2DL1(A) (RH=0.04, P=0.02, n=46).

KIR gene effects on rate of %CD4+ decline in ligand-restricted analyses were also found to be enhanced in most cases, either notably (KIR3DL1, KIR2DS1, KIR2DL2) or at least slightly (KIR2DL3, KIR2DL1, KIR2DS1). The one exception was the effect of KIR3DS1 among carriers of HLA-B Bw4(80Ile). In contrast to the tendency for an increased rate of %CD4+ T-cell decline associated with carriage of KIR3DS1 in the unrestricted analysis is shown in Table 2 (relative rate of decline=1.2, P=0. 3), a slower rate of decline was observed when restricting to carriers of HLA-B Bw4(80Ile) (relative rate of decline=0.7, P=0.6, n=36). In this case, the direction of the observed effect is consistent with delayed progression to a CD4+ count <200 as found by Martin et al.29

Discussion

Our study shows associations between both HLA and KIR genotype and the outcome of HIV-1 infection, which operate at multiple levels to modulate the progression of HIV disease. From a clinical perspective, these host genetic factors have appreciable effects on HIV-associated outcomes. For example, on average carriers of the KIR2DS2 gene would be anticipated to progress to 15% CD4+ T cells (approximating a CD4+ T-cell count of 200 cells/mm3) approximately 4 years faster than those who lacked this gene (see Figure 2), despite similar levels of viremia during this pretreatment phase. Similarly, the activating receptors (eg KIR2DS2, KIR2DS3) usually located on the KIR ‘B’ haplotype were associated with multiple measures of detrimental outcome. It is therefore plausible that inheritance of this haplotype provides an increased risk of ‘unbalanced’ effects of activating KIRs that may be modified by a number of factors. Exploratory studies such as this, which involve complex regions containing genes under strong LD (eg KIR and MHC), highlight the need for single-gene analyses to be considered in the context of haplotype organisation.

The expression of appropriate HLA ligands for inhibitory (and potentially activating) KIRs provides another source of host genetic variation that may shape the NK-mediated response to infection (reviewed in Khakoo and Carrington32). The haplotypic organisation of the MHC region is also likely to be an important factor when considering epistatic associations between HLA and KIR genes, in that inheritance of HLA-B/-C haplotypes directly shapes the repertoire of HLA-restricted epitopes (eg HLA-C C1/C2, HLA-B Bw4/Bw6) that can be utilised by KIRs to modulate NK-mediated cytotoxicity.33

A limitation of this study is that the method used to type the KIR genes detects the presence or absence of a gene, but does not define recently described alleles.34 Hence, improved discrimination of allelic variants may better define the haplotypes within the KIR complex, as has been shown in the MHC, and may allow the identification of even stronger associations between disease phenotypes and KIR genotype.

In conclusion, our findings indicate that KIR genes influence HIV disease progression, contributing along with HLA and chemokine receptor/ligands to a complex network of genetic effects that combine to create a highly individualised host immune response to infection. These findings are consistent with those of Martin et al,29 who have previously demonstrated that KIR/HLA ligand interactions influence HIV outcome. In this study they showed a synergistic effect of KIR3DS1 and HLA-B Bw4 (80Ile) on HIV outcomes that take into account CD4+ T-cell counts (AIDS 1993 definition). However, this association was not evident when the 1987 definition for AIDS (which does not include CD4+ T-cell measures) was used. The results from our study show a significant association between rapid progression to AIDS and the presence of KIR3DS1 and HLA-B Bw4 (80Ile) using the 1987 AIDS definition. However, when the analysis examined %CD4+ decline among the seroconverter group, the presence of KIR3DS1 and HLA-B Bw4 (80Ile) was associated with slower %CD4+ decline (although not significant), akin to the results found by Martin et al (2002). As the 1987 definition of AIDS is primarily dependent on the reporting of opportunistic infections, differences observed in analysis outcomes could well be compounded by population differences such as variation in prevalence of and susceptibility to specific pathogens.

Our study provides further evidence that KIR-restricted NK-dependent cytotoxicity relies on a highly developed system that is relevant to clinical disease and its management. Furthermore, the effect of KIR and HLA on HIV outcome can occur at different levels as highlighted by the association of KIR2DS2 with more rapid %CD4 decline and progression to AIDS but having no effect on viral load.

Patients and methods

Patients

Patients for this study were drawn from participants within the Western Australian HIV Cohort study.30 Comprehensive demographic and clinical data for each patient including history of HIV disease outcome and opportunistic infection, antiretroviral drug treatment, and viral load measurements, CD4+ T-cell and total lymphocyte counts were available at approximately 3–4 month intervals (mean=3.8 months). From this patient group, two cohorts were derived for our studies. First, longitudinal analyses of pretreatment CD4+ T-cell decline and survival analyses investigating progression to AIDS were undertaken within a cohort of 191 Caucasian individuals in whom time of seroconversion could be ascertained by either a documented seroconversion event or an interval of no more than 3 years between negative and positive HIV antibody results. In the latter case, time of seroconversion has been taken to be the mid-point of the seroconversion interval. Second, in order to examine effects of genetic factors on pretreatment viral load set point, cross-sectional analyses were undertaken in a cross-sectional cohort of 174 Caucasian HIV patients prior to any antiretroviral treatment. The demographic and clinical profiles of study participants are shown in Table 1.

HLA class I high-resolution typing

HLA class I typing was performed by direct DNA sequencing using published methods.35 Allele assignments were obtained using the locally developed program Assign. Ambiguities were resolved following sequencing with allele specific subtyping primers or by allele assignments based upon known allelic frequencies in our population.

KIR PCR–SSP typing

The KIR gene repertoire was determined by the use of PCR–sequence specific priming (SSP) assays for 13 different KIR genes. PCR–SSP for KIR2DL1, 2DL2, 2DL3, 2DL5, 3DL1, 2DS1, 2DS2, 2DS3, 2DS4 (functional), KIR1D, 2DS5 and 3DS1 genes were performed separately in single reactions using primers and conditions previously described.36, 37, 38, 39 LD between pairs of KIR genes were calculated using the formula of Cavalli-Sforza and Bodmer.40

Statistical methods

Longitudinal CD4+ T-cell analysis (decline in immune function)

Linear mixed effects models were utilised for the assessment of decline in sequential pretreatment %CD4+ over 10 years postseroconversion. Measurements of %CD4+ were used in preference to cell number because they are less prone to transient fluctuations and can be modelled directly rather than requiring a square-root transform to obtain approximately normal within-individual errors (correlation between %CD4+ and sqrt(CD4+ count)=0.71, P<0.0001). Quadratic functions were used for estimation of %CD4+ profiles at both the individual-specific (random effects) and population-average (fixed effects) levels. Indicators for the genetic variables of interest were included as covariates acting on the linear term as well as the intercept of the fixed effects. This enabled assessment of possible genetic differences in both the rate of decline of %CD4+ in the years following infection with HIV-1 and the baseline levels following the acute infection phase. Wald type tests were used for these assessments. For each genetic variable (presence relative to absence), the relative rate of %CD4+ decline was calculated from the average decline of the fitted profiles over 10 years postseroconversion.

Survival analyses

Genetic factors affecting time from seroconversion to AIDS (1987 definition) were investigated by survival analysis of those in the longitudinal group who were under observation prior to the introduction of potent antiretroviral therapy in late 1996, with event times censored at this date. Cox regression models were used for the analyses with (partial) likelihood ratio tests determining the given P-values. Proportional hazards assumptions of the fitted models were assessed by application of the test of Grambsch and Therneau.41 The RHs pertaining to genetic type (presence relative to absence) were calculated from the fitted Cox models.

Cross-sectional analyses of genetic markers

Simple linear regression models were used for cross-sectional analyses investigating the influence of HLA class I alleles, CCR5Δ32 and the presence of individual KIR genes on viral load set point (first available pretreatment measure of plasma HIV-1 RNA (log10copies/ml) obtained at least 3 months after seroconversion). The models were fitted with indicators for genetic type as the main effect.

All analyses were carried out using the S-PLUS software package (Insightful Corporation, Seattle, USA) and were adjusted for sex, age (16–25, 26–35, 36–45, 46–65 years) and route of transmission (homosexual, heterosexual, intravenous drug use, other transmission of blood or tissue).

References

  1. 1

    Nolan D, Gaudieri S, John M, Mallal S . Impact of host genetics on HIV disease progression and treatment: new conflicts on an ancient battleground. AIDS 2004; 18: 1231–1240.

    CAS  Article  Google Scholar 

  2. 2

    Tang J, Kaslow RA . The impact of host genetics on HIV infection and disease progression in the era of highly active antiretroviral therapy. AIDS 2003; 17 (Suppl 4): S51–S60.

    Article  Google Scholar 

  3. 3

    Chouquet C, Autran B, Gomard E et al. Correlation between breadth of memory HIV-specific cytotoxic T-cells, viral load and disease progression in HIV infection. AIDS 2002; 16: 2399–2407.

    CAS  Article  Google Scholar 

  4. 4

    Moore CB, John M, James IR, Christiansen FT, Witt CS, Mallal SA . Evidence of HIV-1 adaptation to HLA-restricted immune responses at a population level. Science 2002; 96: 1439–1443.

    Article  Google Scholar 

  5. 5

    Ho DD . Viral counts count in HIV infection. Science 1996; 272: 1124–1125.

    CAS  Article  Google Scholar 

  6. 6

    O'Brien TR, Blattner WA, Waters D et al. Serum HIV-1 RNA levels and time to development of AIDS in the Multicenter Hemophilia Cohort Study. JAMA 1996; 276: 105–110.

    CAS  Article  Google Scholar 

  7. 7

    Lyles RH, Munoz A, Yamashita TE et al. Natural history of human immunodeficiency virus type 1 viremia after seroconversion and proximal to AIDS in a large cohort of homosexual men. Multicenter AIDS Cohort Study. J Infect Dis 2000; 181: 872–880.

    CAS  Article  Google Scholar 

  8. 8

    Steel CM, Ludlam CA, Beatson D et al. HLA haplotype A1 B8 DR3 as a risk factor for HIV-related disease. Lancet 1988; 1: 1185–1188.

    CAS  Article  Google Scholar 

  9. 9

    Mallal S, Cameron PU, French MA, Dawkins RL . MHC genes and HIV infection. Lancet 1990; 335: 1591–1592.

    CAS  Article  Google Scholar 

  10. 10

    Kaslow RA, Carrington M, Apple R et al. Influence of combinations of human major histocompatibility complex genes on the course of HIV-1 infection. Nat Med 1996; 2: 405–411.

    CAS  Article  Google Scholar 

  11. 11

    Flores-Villanueva PO, Hendel H, Caillat-Zucman S et al. Associations of MHC ancestral haplotypes with resistance/susceptibility to AIDS disease development. J Immunol 2003; 170: 1925–1929.

    CAS  Article  Google Scholar 

  12. 12

    Witt CS, Dewing C, Sayer DC, Uhrberg M, Parham P, Christiansen FT . Population frequencies and putative haplotypes of the killer cell immunoglobulin-like receptor sequences and evidence for recombination. Transplantation 1999; 68: 1784–1789.

    CAS  Article  Google Scholar 

  13. 13

    Martin AM, Freitas EM, Witt CS, Christiansen FT . The genomic organization and evolution of the natural killer immunoglobulin-like receptor (KIR) gene cluster. Immunogenetics 2000; 51: 268–280.

    CAS  Article  Google Scholar 

  14. 14

    Hsu K, Liu XR, Selvakumar A, Mickelson E, O'Reilly RJ, Dupont B . Killer Ig-like receptor haplotype analysis by gene content: evidence for genomic diversity with a minimum of six basic framework haplotypes, each with multiple subsets. J Immunol 2002; 169: 5118–5129.

    Article  Google Scholar 

  15. 15

    Martin AM, Kulski JK, Gaudieri S et al. Comparative genomic analysis, diversity and evolution of two KIR haplotypes A and B. Gene 2004; 335: 121–131.

    CAS  Article  Google Scholar 

  16. 16

    Dawkins R, Leelayuwat C, Gaudieri S et al. Genomics of the major histocompatibility complex: haplotypes, duplication, retroviruses and disease. Immunol Rev 1999; 167: 275–304.

    CAS  Article  Google Scholar 

  17. 17

    Price P, Witt C, Allcock R et al. The genetic basis for the association of the 8.1 ancestral haplotype (A1, B8, DR3) with multiple immunopathological diseases. Immunol Rev 1999; 167: 257–274.

    CAS  Article  Google Scholar 

  18. 18

    Martin MP, Nelson G, Lee JH et al. Cutting edge: susceptibility to psoriatic arthritis: influence of activating killer Ig-like receptor genes in the absence of specific HLA-C alleles. J Immunol 2002; 169: 2818–2822.

    CAS  Article  Google Scholar 

  19. 19

    van der Slik AR, Koeleman BP, Verduijn W, Bruining GJ, Roep BO, Giphart MJ . KIR in type 1 diabetes: disparate distribution of activating and inhibitory natural killer cell receptors in patients vs HLA-matched control subjects. Diabetes 2003; 52: 2639–2642.

    CAS  Article  Google Scholar 

  20. 20

    Khakoo SI, Thio CL, Martin MP et al. HLA and NK cell inhibitory receptor genes in resolving hepatitis C virus infection. Science 2004; 305: 872–874.

    CAS  Article  Google Scholar 

  21. 21

    Lanier LL . NK cell receptors. Annu Rev Immunol 1998; 16: 359–393.

    CAS  Article  Google Scholar 

  22. 22

    Collins KL, Chen BK, Kalams SA, Walker BD, Baltimore D . HIV-1 Nef protein protects infected primary cells against killing by cytotoxic T lymphocytes. Nature 1998; 391: 397–401.

    CAS  Article  Google Scholar 

  23. 23

    Cohen GB, Gandhi RT, Davis DM et al. The selective downregulation of class I major histocompatibility complex proteins by HIV-1 protects HIV-infected cells from NK cells. Immunity 1999; 10: 661–671.

    CAS  Article  Google Scholar 

  24. 24

    Lorenzo ME, Jung JU, Ploegh HL . Kaposi's sarcoma-associated herpesvirus K3 utilizes the ubiquitin–proteasome system in routing class major histocompatibility complexes to late endocytic compartments. J Virol 2002; 76: 5522–5531.

    CAS  Article  Google Scholar 

  25. 25

    Means RE, Ishido S, Alvarez X, Jung JU . Multiple endocytic trafficking pathways of MHC class I molecules induced by a Herpesvirus protein. EMBO J 2002; 21: 1638–1649.

    CAS  Article  Google Scholar 

  26. 26

    Ward JP, Bonaparte MI, Barker E . HLA-C and HLA-E reduce antibody-dependent natural killer cell-mediated cytotoxicity of HIV-infected primary T cell blasts. AIDS 2004; 18: 1769–1779.

    Article  Google Scholar 

  27. 27

    Bonaparte MI, Barker E . Killing of human immunodeficiency virus-infected primary T-cell blasts by autologous natural killer cells is dependent on the ability of the virus to alter the expression of major histocompatibility complex class I molecules. Blood 2004; 104: 2087–2094.

    CAS  Article  Google Scholar 

  28. 28

    Long EO, Burshtyn DN, Clark WP et al. Killer cell inhibitory receptors: diversity, specificity, and function. Immunol Rev 1997; 155: 135–144.

    CAS  Article  Google Scholar 

  29. 29

    Martin MP, Gao X, Lee JH et al. Epistatic interaction between KIR3DS1 and HLA-B delays the progression to AIDS. Nat Genet 2002; 31: 429–434.

    CAS  Article  Google Scholar 

  30. 30

    Mallal SA . The Western Australian HIV Cohort Study. J Acquir Immune Defic Syndr Hum Retrovirol 1998; 17: S23–S27.

    Article  Google Scholar 

  31. 31

    Carrington M, Nelson G, O'Brien SJ . Considering genetic profiles in functional studies of immune responsiveness to HIV-1. Immunol Lett 2001; 79: 131–140.

    CAS  Article  Google Scholar 

  32. 32

    Khakoo SI, Carrington M . Receptors mediating interactions between natural killer cells and their viral associates. ASHI Quarterly 2004: 126–129.

  33. 33

    Gaudieri S, Nolan D, McKinnon E, Witt CS, Mallal S, Christiansen FT . Associations between KIR epitopes combinations expressed by HLA-B/-C haplotypes found in an HIV-1 infected study population may influence NK mediated immune responses. Mol Immunol 2005; 42: 557–560.

    CAS  Article  Google Scholar 

  34. 34

    Garcia CA, Robinson J, Guethlein LA, Parham P, Madrigal JA, Marsh SG . Human KIR sequences 2003. Immunogenetics 2003; 55: 227–239.

    CAS  Article  Google Scholar 

  35. 35

    Witt CS, Price P, Kaur G et al. Common HLA-B8-DR3 haplotype in Northern India is different from that found in Europe. Tissue Antigens 2002; 60: 474–480.

    CAS  Article  Google Scholar 

  36. 36

    Witt CS, Goodridge J, Gerbase-DeLima MG, Daher S, Christiansen FT . Maternal KIR repertoire is not associated with recurrent spontaneous abortion. Hum Reprod 2004; 19: 2653–2657.

    CAS  Article  Google Scholar 

  37. 37

    Uhrberg M, Valiante NM, Shum BP et al. Human diversity in killer cell inhibitory receptor genes. Immunity 1997; 7: 753–763.

    CAS  Article  Google Scholar 

  38. 38

    Norman PJ, Stephens HA, Verity DH, Chandanayingyong D, Vaughan RW . Distribution of natural killer cell immunoglobulin-like receptor sequences in three ethnic groups. Immunogenetics 2001; 52: 195–205.

    CAS  Article  Google Scholar 

  39. 39

    Gomez-Lozano N, Vilches C . Genotyping of human killer-cell immunoglobulin-like receptor genes by polymerase chain reaction with sequence-specific primers: An update. Tissue Antigens 2002; 59: 184–193.

    CAS  Article  Google Scholar 

  40. 40

    Cavalli-Sforza LL, Bodmer WF . The Genetics of Human Populations. WH Freeman and Company: San Francisco, 1971.

    Google Scholar 

  41. 41

    Grambsch P, Thernau T . Proportional hazards tests and diagnostics based on weighted residuals. Biometrika 1994; 81: 515–526.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the support of the Western Australian HIV cohort and the staff at the Department of Clinical Immunology and Biochemical Genetics (DCIBG), Royal Perth Hospital, Western Australia. We thank Dr Elizabeth Freitas, Filipa Carvalho and Annette Patterson for their contribution. SG is supported by a Healy Fellowship from the Raine Medical Research Foundation.DD and EM equally contributed to the work described in this manuscript. Part of this work was supported by the National Health and Medical Research Council Grant Number 237412.

Author information

Affiliations

Authors

Corresponding author

Correspondence to F T Christiansen.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Gaudieri, S., DeSantis, D., McKinnon, E. et al. Killer immunoglobulin-like receptors and HLA act both independently and synergistically to modify HIV disease progression. Genes Immun 6, 683–690 (2005). https://doi.org/10.1038/sj.gene.6364256

Download citation

Keywords

  • NK cells
  • HLA
  • AIDS
  • killer immunoglobulin-like receptors

Further reading

Search

Quick links