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Translational Research

Impact of HLA Allele-KIR Pairs on Disease Outcome in HIV-Infected Thai Population

Mori, Masahiko MD, PhD*,†; Wichukchinda, Nuanjun PhD; Miyahara, Reiko MD, PhD*; Rojanawiwat, Archawin MD, PhD; Pathipvanich, Panita MD§; Miura, Toshiyuki MD, PhD*; Yasunami, Michio MD, PhD*,║; Ariyoshi, Koya MD, PhD*; Sawanpanyalert, Pathom MD, PhD

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: July 1, 2018 - Volume 78 - Issue 3 - p 356-361
doi: 10.1097/QAI.0000000000001676

Abstract

INTRODUCTION

Class I human leukocyte antigen (HLA) molecules interact with both cytotoxic T lymphocytes (CTLs) through their T-cell receptors and natural killer (NK) cells through their killer immunoglobulin-like receptors (KIRs). Associations between certain HLA-KIR pairs and clinical outcomes were previously reported in various diseases such as hematopoietic stem cell transplantation and its outcome in leukemia,1 fetal growth, preeclampsia and miscarriage in reproductive diseases,2 autoimmune diseases,3 and infectious diseases including hepatitis C virus4 and malaria.5 In HIV infection, however, the contribution of NK cells to disease control in vivo is less clear.

NK cells are regulated by the combinatorial effect of many activating and inhibitory receptors, including KIRs.6 KIRs contain 2 or 3 external immunoglobulin-like domains (2D, 3D) and have either long or short cytoplasmic tails, which determine whether they are inhibitory (L1, L2, L3, L4 etc; “L” stands for “long tail”) or activating (S1, S2, S3, S4 etc; “S” stands for “short tail”) receptors, respectively.7,8 Some KIRs recognize certain HLA class I molecules as their ligands. For example, the ligands for KIR3DL1 receptors are HLA-B molecules containing the Bw4 motif at residues 77–83.9,10 The high level of expression of the KIR allotype KIR3DL1 and its ligands HLA-Bw4 alleles with isoleucine at residue 80 (Bw4-80I) has been associated with improved HIV clinical outcome via modulation of antiviral NK activity.11,12 Interestingly, some of the most “disease-protective” (ie, associated with lower viral setpoint13–15) class I HLA alleles in HIV infection, such as HLA-B*57 in different ethnical groups,13–15 and HLA-B*58:01 in African population,13 constitute the Bw4-80I group.12

However, with the exception of the correlation between higher HLA-C expression level and better clinical outcome,16 the effect of HLA-C alleles or HLA-C-KIR2D pairs on HIV clinical outcome is not well understood. HLA-C alleles are ligands of KIR2D and are classified into either the HLA-C group 1 (HLA-C1) or group 2 (HLA-C2), depending on sequences at residues 77 and 80.17,18 HLA-C molecules expressing serine at residue 77 and asparagine at 80 belong to the HLA-C1 group, and HLA-C molecules expressing asparagine at residue 77 and lysine at 80 belong to the HLA-C2 group. The HLA-C1 group has binding affinity for KIR2DL2, KIR2DL3, and KIR2DS2, and HLA-C2 group alleles bind to KIR2DL1 and KIR2DS1.6,19 Previous reports showed the disease-susceptible effect of HLA-C1-KIR2DL3 pair on the rate of HIV infection and postinfection clinical outcome in the Thai population.20

With respect to the HLA-KIR interaction, associations between viral escape and KIR expression were demonstrated in chronically HIV-infected individuals, which suggested an ongoing viral adaptation to NK-cell–mediated immune pressure.21,22 However, whether there is an association between HLA-KIR interaction and HIV clinical outcome at the level of HLA alleles has not been fully investigated. Our aim here was to identify the effect of KIR interaction with their ligand HLA alleles on HIV clinical outcome in a cohort of 209 chronically infected, treatment-naive adults from Thailand.

METHODS

Subjects and Data Collection

This study was approved by the Thai Ministry of Public Health Ethics Committee and was conducted according to the set guidelines for research. All patients provided informed consent for the collection of samples and subsequent analysis of the data.

Chronically HIV CRF01_AE-infected adult individuals (n = 209) were recruited from Lampang Hospital, Thailand, from July 2000 until October 2002, as previously reported.15,20 Their HIV infection was diagnosed by antibody testing at the hospital, and EDTA-treated blood was taken from each individual. Plasma and buffy coat fractions were separated and stored at −80°C. All study participants were antiretroviral treatment (ART) naive with absolute CD4+ T-cell counts of ≥200/μL at enrollment. Viral load data at enrollment, follow-up data of ART introduction, and mortality were also collected during the follow-up period until October 2010.

HLA and KIR Typing

Genomic DNA was extracted from buffy coats using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) and used for 4-digit class I HLA typing of A, B, and C alleles, performed by bead-based array hybridization (WAKFlow HLA typing kit; Wakunaga Pharmaceutical, Hiroshima, Japan) according to the manufacturer's instructions at a commercial laboratory (Kyoto HLA Laboratory, Kyoto, Japan). KIR typing (KIR2DL1, KIR2DL2, KIR2DL3, KIR2DS1, KIR2DS2, KIR3DL1, and KIR3DS1) was performed as previously described.23

Statistical Analysis

Statistical analysis was performed using SPSS 21.0 (IBM, Armonk, NY). Correlation between HLA allele-KIR pair frequency and median viral load of individuals with that pair was analyzed by the Spearman correlation test. The effect of HLA allele-KIR pairs on viral load was tested with the Mann–Whitney U test. The log-rank test was performed for the longitudinal analysis of survival rate, and Cox hazard model was applied for multivariate analysis.

RESULTS

Characteristics of the Cohort

Of the 209 chronically HIV-infected individuals, 159 (76%) were women and 50 (24%) were men (Table 1). At enrollment, median absolute CD4+ T-cell count was 396 cells/μL [interquartile range (IQR) 286–519], and median viral load was 4.7 log10 copies/mL (IQR 4.2–5.2). The distribution of HLA, KIR, and HLA allele-KIR pairs are shown in Table 1 and Supplemental Digital Content Figure 1, http://links.lww.com/QAI/B134.

TABLE 1.
TABLE 1.:
Characteristics of Subjects

Positive Correlation Between HLA-KIR Pair Frequency and Viral Load

To investigate the effect of HLA allele-KIR pair on clinical outcome, first we analyzed the correlation between frequency of HLA allele-KIR pairs and viral load. Positive correlation between an HLA allele-KIR pair frequency and median viral load among subjects with that HLA allele-KIR pair was identified in all 69 HLA allele-KIR pairs (r = 0.5, P < 0.001) (Fig. 1). Within these 69 pairs, we also identified significant positive correlation in 49 HLA allele-KIR2D pairs (r = 0.5, P < 0.001), 20 HLA allele-KIR3D pairs (r = 0.5, P = 0.04), 41 HLA allele-inhibitory KIR pairs (r = 0.4, P = 0.01), and 28 HLA allele-stimulatory KIR pairs (r = 0.5, P = 0.01) (Supplemental Digital Content Figs. 2A–D, http://links.lww.com/QAI/B134). These results suggest that the HIV virus would be more adapted to NK-cell immune responses in individuals with more frequent HLA-KIR pairs.

FIGURE 1.
FIGURE 1.:
Correlation between HLA allele-KIR pair frequency and viral load. Correlation between frequency of HLA allele-KIR pairs and median viral load among subjects with a particular HLA allele-KIR pair. In total, 69 HLA allele-KIR pairs were identified. The Spearman correlation test is shown.

Associations of HLA-KIR Pairs and Viral Load Differences

Next, we looked at the differences in viral load associated with certain HLA allele-KIR pairs. To avoid overestimation of the CTL-related effect of an HLA allele on clinical outcome, we analyzed viral load differences between subjects expressing a particular HLA allele-KIR pair vs subjects expressing the same HLA but lacking that KIR (for example, differences in viral load between HLA-B*57:01+KIR3DL1+ve subjects vs HLA-B*57:01+KIR3DL1−ve subjects). In total, 5 of 69 HLA allele-KIR pairs scored significant viral load differences: HLA-C*01:02+KIR2DL2+ vs HLA-C*01:02+KIR2DL2− (median 5.0 vs 4.6 log10 copies/mL, respectively, P = 0.02), HLA-C*12:03+KIR2DL2+ vs HLA-C*12:03+KIR2DL2−, (4.3 vs 5.6 log10 copies/mL, respectively, P = 0.01), HLA-B*46:01+KIR2DL2+ vs HLA-B*46:01+KIR2DL2−, (5.0 vs 4.6 log10 copies/mL, respectively, P = 0.02), HLA-C*12:02+KIR2DL3+ vs HLA-C*12:02+KIR2DL3−, (5.0 vs 3.8 log10 copies/mL, respectively, P = 0.03), and HLA-C*12:03+KIR2DS2+ vs HLA-C*12:03+KIR2DS2−, (4.3 vs 5.6 log10 copies/mL, respectively, P = 0.01) (Table 2 and Supplemental Digital Content Table 1, http://links.lww.com/QAI/B134). Interestingly, HLA alleles within the HLA-C1 group in combination with their common receptor KIR2DL2 were associated with a differential effect on viral load: increase in viral load in HLA-C*01:02+KIR2DL2+ve and HLA-B*46:01+KIR2DL2+ve subjects and decrease in HLA-C*12:03+KIR2DL2+.

TABLE 2.
TABLE 2.:
Effect of HLA-KIR Pair on Viral Load

These results suggest that significant viral load differences associated with the expression of certain HLA allele-KIR pairs exist not only at the level of a ligand HLA group, as previously reported for the disease-protective HLA-Bw4 group (ligand of KIR3DL1)12 and disease-susceptible HLA-C1 group (ligand of KIR2DL3),20 but also at the level of specific HLA alleles within 1 HLA group.

Higher Mortality Rate Among HLA-B*46:01+KIR2DL2+ve Subjects Independent of CD4+ T Cell Count, Sex, Age, and ART Introduction

Finally, we assessed longitudinal impact of HLA allele-KIR pairs on survival rate. We found that HLA-B*46:01+KIR2DL2+ve subjects (n = 23) had higher mortality rate compared with the subjects not expressing this pair (HLA-B*46:01-KIR2DL2−ve, n = 93) or expressing only HLA-B*46:01 (n = 38) or only KIR2DL2 (n = 55) (P = 0.01) (Fig. 2). In the multivariate analysis, expression of the HLA-B*46:01+KIR2DL2+ pair remained a significant factor associated with higher mortality rate {with adjusted hazard ratio (aHR) 5.9 [95% confidential interval range (CI) 1.3 to 27], P = 0.02} independent of the absolute CD4+ T-cell count [aHR 0.996 (95% CI: 0.993 to 0.999), P = 0.004], sex [aHR 2.2 (95% CI: 1.1 to 4.3), P = 0.03 in men], age [aHR 1.05 (95% CI: 1.02 to 1.1), P = 0.007], and ART introduction [aHR 0.2 (95% CI: 0.09 to 0.4), P < 0.001] (Table 3). These results strongly suggest that the HLA-B*46:01+KIR2DL2+ pair has a disease-susceptible effect on HIV clinical outcome in this cohort.

FIGURE 2.
FIGURE 2.:
Effect of HLA-B*46:01-KIR2DL2 pair on the survival rate of HIV-infected patients. Kaplan–Meier curves showing survival rates of subjects who are HLA-B*46:01-KIR2DL2−ve, HLA-B*46:01+KIR2DL2−ve, HLA-B*46:01-KIR2DL2+ve, or HLA-B*46:01+KIR2DL2+ve. P value obtained from the log rank test.
TABLE 3.
TABLE 3.:
Multivariate Cox Proportional Hazard Model of the Effect of HLA-B*46:01-KIR2DL2 Pair on the Survival Rate of HIV-Infected Subjects

DISCUSSIONS

This study systematically investigated the effect of the expression of particular KIRs and their HLA ligands on clinical outcome in a Thai cohort of ART-naive adults chronically infected with HIV CRF01_AE. Here, we have identified several HLA allele-KIR pairs associated with differential clinical outcome by both cross-sectional and longitudinal analyses. We also found that the alleles within the HLA-C1 group, all ligands of their NK-cell receptor KIR2DL2, had opposing effects on clinical outcome as defined by viral load.

The association between HLA-KIR interaction and HIV clinical outcome was first reported in 2001 in the context of the disease-protective HLA-Bw4 group.24 Later, the advantageous effect of high cellular surface expression of KIR3DL1*h/*y allotype in combination with HLA-Bw4-80I was reported.12 However, reports about associations between specific HLA alleles paired with their cognate KIRs and HIV clinical outcome remain sparse.12,25 Here, we identified 5 HLA allele-KIR pairs with significant viral load differences between KIR+ve and KIR−ve subjects who expressed the cognate ligand HLA alleles, thus eliminating an overestimation because of CTL-mediated effects. Among these 5 HLA allele-KIR pairs detected, we found that the alleles constituting the HLA-C1 group and interacting with their receptor KIR2DL2 had opposing effects on viral load differences. This suggests that previous reports about associations between HLA group-KIR pairs and disease outcomes1–5 may have contained a mixture of disease-protective and susceptible HLA allele-KIR pairs within the reported HLA groups, thus underestimating the effect. Indeed, there was no significant viral load difference between HLA-C1 group+KIR2DL2+ve subjects and HLA-C1 group+KIR2DL2−ve subjects (median 4.8 vs 4.7 log10 copies/mL, P = 0.8) in our previous report.20 These findings suggest that analyses performed at the level of particular HLA alleles within a given group may reveal more effects of HLA-KIR interaction on disease outcome.

A number of potential mechanisms underlying the association between HLA-KIR expression and HIV clinical outcome has been proposed. The Thai RV144 vaccine trial indicated a role of antibody-dependent cellular cytotoxicity–competent antibodies in vaccine-conferred protection against HIV infection26–28 and advantageous effect of HLA-Bw4-KIR3DL1 and HLA-C2-KIR2DL1 pairs on antibody-dependent cellular cytotoxicity activation in NK cells was previously reported.29,30 Also, Alter et al22 reported that KIR-mediated viral mutation sites can enhance binding of NK cells through inhibitory KIRs, causing inhibition of NK-cell activation and subsequent escape from NK-cell–mediated lysis of infected cells. Furthermore, Holzemer et al21 recently reported existence of an HLA-C*03:04-KIR2DL3-associated escape mutation at position 303 within an HLA-C*03:04-specific epitope, YVDRFFKTL (Gag p24, residues 296–304). Considering these viral adaptation sites induced by HLA allele-KIR interactions and the opposing effects of individual alleles within an HLA group on clinical outcome identified in our study, detailed studies at the level of HLA alleles are needed to better understand the mechanism of class I HLA-induced anti-HIV immunity and subsequent development of HIV vaccine and immunotherapy.21,31,32

Our finding of the disease-susceptible effect of HLA-B*46:01-KIR2DL2 pair on viral load and survival rate is intriguing. HLA-B*46:01 is unique in terms of its geographic distribution and structure. This allele emerged in Southeast Asia about 50,000 years ago and is not encountered in Africa.33,34 In Southeast Asia, it is the most common HLA-B allele (20%–30% population frequency),35 and was also the most prevalent HLA-B allele in our cohort (29%). Structurally, HLA-B*46:01 is a product of a gene conversion between HLA-B*15:01 and HLA-C*01:0233,34 and belongs to the HLA-C1 group.35–37 By contrast, KIR2DL2 is less frequent in Southeast Asia (36%–45%,35 and 37% in our cohort) compared with other ethnical groups in other geographic locations, such as South African Xhosa among whom KIR2DL2 has more than 70% frequency.38 Interestingly, KIR2DL2 was reported as the disease-protective KIR associated with low viral load in a study of subtype C-infected South African cohort.39 This suggests that distinct effects of HLA allele-KIR pairs on HIV clinical outcome exist in areas with different viral subtypes, not just at the level of HLA-KIR pairs. Such unique geographic distribution and structures of HLA and KIR could have differential impact on HIV clinical outcome in each endemic area, and further reports and analyses from each endemic area including HLA allele-KIR pair–associated sites would be warranted.21,22

A limitation of this study is the lack of data on HLA-C level of expression. Correlations between higher HLA-C allele expression and lower HIV viral load, higher viral escape mutations, and higher HIV-specific CTL responses were previously reported in a study of European and African American cohorts.16 That study suggested an advantageous effect of high HLA-C expression level on HIV clinical outcomes. This finding could impact our results, particularly the correlations between HLA-KIR pair frequency and viral load. Further analysis is needed to address these points.

Another limitation of this study is the number of participants enrolled and the consequent genetic homogeneity of the cohort. The numbers of KIR2DL1−ve, KIR2DL3−ve, KIR3DL1−ve patients were small (n = 4, 5, and 6, respectively). Although we identified statistically significant associations of several HLA allele-KIR pairs and clinical outcome, further analysis with a larger number of participants, greater genetic diversity, and more clinical data such as ART regimen, its adherence and viral control rate would be necessary to confirm these findings.

In conclusion, this study investigated the effect of the expression of class I HLA and KIR on viral control in a chronically HIV-infected ART-naive Thai cohort. We identified 5 HLA allele-KIR pairs that had an impact on clinical outcome in this cohort. We also found that several alleles within the HLA-C1 group interacting with KIR2DL2 had opposing effects on viral loads. Our data highlight the importance of geographic differences in the prevalence of HLA-KIR pairs, which may affect the NK-cell response and the selection pressure exerted on HIV in each endemic area. The contribution of KIR-mediated viral control will most likely be determined by host differences such as HLA class I allele and KIR frequencies in different parts of the world, as well as the viral subtypes. The identification of disease-protective and susceptible HLA-KIR pairs unique to each endemic area will provide an opportunity to better define the nature of HLA-associated immune control of HIV.32

ACKNOWLEDGMENTS

The authors thank Ms. Phattaraporn Orataiwun, Ms. Suthira Kasemsuk, Ms. Sripai Saneewongna-Ayuthaya, Ms. Katkaew Thamachai, Ms. Anongnard Suyasarojna, Ms. Nutira Boonna, and Mr. Praphan Wongnamnong for their excellent technical assistance at Lampang Hospital.

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Keywords:

HIV; Southeast Asia; HLA; killer immunoglobulin-like receptor; disease outcome

Supplemental Digital Content

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