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HLA-B*35: 05 is a protective allele with a unique structure among HIV-1 CRF01_AE-infected Thais, in whom the B*57 frequency is low

Mori, Masahiko; Wichukchinda, Nuanjun; Miyahara, Reiko; Rojanawiwat, Archawin; Pathipvanich, Panita; Maekawa, Tomoyuki; Miura, Toshiyuki; Goulder, Philip; Yasunami, Michio; Ariyoshi, Koya; Sawanpanyalert, Pathom


In this paper by Masahiko Mori et al. [1], four additional affiliations were missed.

The correct affiliation should read as below:

Masahiko Moria,b,c, Nuanjun Wichukchindac, Reiko Miyaharaa, Archawin Rojanawiwatc, Panita Pathipvanichd, Tomoyuki Maekawaa, Toshiyuki Miuraa, Philip Goulderb, Michio Yasunamia, Koya Ariyoshia,e, and Pathom Sawanpanyalertc.

aDepartment of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan, bDepartment of Paediatrics, University of Oxford, Oxford, UK, cThai National Institute of Health, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, dDay Care Center, Lampang Hospital, Lampang, Thailand, and eNagasaki University Global COE Program, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan.

AIDS. 29(10):1275, June 19th, 2015.

doi: 10.1097/QAD.0000000000000206
Basic Science

Objective: To identify protective human leukocyte antigen (HLA) alleles in an HIV-infected south-east Asian population, in whom HLA-B*57 prevalence is lower than other ethnic groups, and HIV-1 CRF01_AE is the dominant circulating subtype.

Design: Cross-sectional study of Thai patients with chronic HIV infection.

Methods: Five hundred and fifty-seven HIV-1 CRF01_AE-infected Thais were recruited. Their HLA type and viral load were determined to statistically analyze the association of each allele in viral control. In-silico molecular dynamics was also used to evaluate the effect of HLA structure variants on epitope binding.

Results: HLA-B*35:05 was identified as the most protective allele (P = 0.003, q = 0.17), along with HLA-B*57:01 (P = 0.044, q = 0.31). Structurally, HLA-B*35:05 belonged to the HLA-B*35-PY group of HLA-B*35 alleles; however, unlike the other HLA-B*35 alleles that carry Arg (R) at residue 97, it has unique sequences at T94, L95, and S97, located within the peptide-binding groove. Analysis of the three-dimensional HLA structure and molecular dynamics indicates that S97 in HLA-B*35:05 leads to less flexibility in the groove, and shorter distances between the α-helixes compared with the disease-susceptible HLA-B*35-PY allele, HLA-B*35:01.

Conclusion: These data indicate the existence of a protective effect of HLA-B*57 across ethnic groups and highlight HLA-B*35:05 as an allele uniquely protective in subtype CRF01_AE-infected Thais. The divergence of HLA-B*35:05 from conventional HLA-B*35-PY structural sequences at the peptide-binding groove is consistent with previous studies that have identified HLA residue 97 as strongly influential in shaping HLA impact on immune control of HIV, and that a more restricted peptide-binding motif may be associated with improved control.

Supplemental Digital Content is available in the text

Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, Sakamoto, Nagasaki City, Nagasaki, Japan.

Correspondence to Koya Ariyoshi, MD, PhD, Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, 1-12-4, Sakamoto, Nagasaki City, Nagasaki 852-8523, Japan. Tel: +81 95 8197842; fax: +81 95 8197843; e-mail:

Received 23 August, 2013

Revised 7 January, 2014

Accepted 7 January, 2014

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (

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Cytotoxic T lymphocytes (CTLs) play a critical role in the control of viral replication in HIV or simian immunodeficiency virus (SIV) infection [1,2]. The effectiveness of anti-HIV CTL activity is strongly influenced by the highly polymorphic host class I human leukocyte antigen (HLA) genes expressed, as well by differences in viral sequence. The HLA region is the most polymorphic loci in the human genome and is found on chromosome 6 [3]; as of July 2013, 6966 of class I HLA molecules (2244 of HLA-A, 2934 of HLA-B, and 1788 of HLA-C alleles) have been registered in the website database [4]. The HIV strains circulating in different geographical regions are also highly diverse; 13 prototype clades and 43 circulating recombinant forms (CRFs) have been reported [5]. Under such HLA polymorphism and HIV viral diversity environment, so far 1539 of CTL epitopes including 250 best-defined epitopes and their restricting HLA allele information have accumulated in the Los Alamos database (CTL/CD8+ Epitope Summary. However, most of these have been derived from subtype B-infected whites in Europe and North America, and from subtype C-infected Africans in sub-Saharan Africa. Studies remain sparse from south-east Asia, where 1.5 million patients are living with HIV, of whom approximately 90% are infected with the subtype CRF01_AE (Geography Search Interface, Los Alamos database.

The protective effect of HLA-B*57 alleles on HIV viral control has been consistently reported in both African and white populations [6–9]. However, the prevalence of HLA-B*57 alleles differs among ethnic groups, being expressed in 7–9% of Africans, in 5–7% of whites, but in less than 3% of Asians [1,10].

HLA-B*27 has also been identified as a protective allele in white populations [9,11] and HLA-B*58:02 as a disease-susceptible allele in African populations [6,8]. HLA alleles have also been classified into HLA supertypes according to the common structure of anchor positions [12,13], and the influence of these supertypes on clinical outcome has been described. For instance, the advantage of supertype B58s and B62s and disadvantage of B07s and B44s for viral control among African and white cohorts have been reported [14–16]. However, the impact of HLA supertypes for HIV viral control among Asians has not yet been investigated.

Recently, a European ancestry genome-wide association study (GWAS) reported the significant association between sequence variants at HLA residue 97 and HIV viral control [17,18]: Arg (R) at residue 97 affected peptide binding together with the surrounding Ser (S) at residue 116, allowing flexibility of R97 and subsequent binding of various peptides [19]. It is proposed that such flexibility at the HLA binding groove may increase self-peptide binding at the thymic level and in turn reduces the T-cell receptor (TCR) repertoire subsequently available for virus-specific T-cell responses [20], leading to a higher chance of viral escape mutations with higher viral set points [20–22]. The evaluation of single HLA amino acid variants on structural change or flexibility can also be analyzed by molecular dynamics modeling using three-dimensional crystal structure data, as developed for analysis of drug resistance and peptide–ligand interactions [23–25].

We here analyze the impact of HLA class I molecules on immune control of HIV in a study cohort in Thailand using a combination of statistical and molecular dynamics modeling approaches. Our objective was to identify protective HLA alleles in HIV-infected Asians, in whom HLA-B*57 prevalence is lower than other ethnic groups and HIV-1 CRF01_AE is the dominant circulating subtype of virus.

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Ethical statement

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 and subsequent analysis of the samples.

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This study was conducted as a part of Lampang cohort study, which has been described in detail elsewhere [26,27]. Briefly, this is a hospital-based cohort study of 557 HIV-1 CRF01_AE-infected participants, comprising individuals attending a government referral hospital in northern Thailand. Recruitment was undertaken between July 2000 and October 2002. All study participants were antiretroviral treatment naive and tested for viral load at enrollment. Ethylenediaminetetraacetic acid (EDTA)-treated buffy coat samples were used in this study.

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Class I human leukocyte antigen and typing

Genomic DNA was extracted from the buffy coat using the QIAamp DNA blood Mini Kit (Qiagen, Hilden, Germany) and four digits class I HLA typing for A, B, and C allele was performed by bead-based array hybridization (WAKFlow HLA typing kit; Wakunaga Pharmaceutical, Hiroshima, Japan) according to manufacturer's instructions at a commercial laboratory (Kyoto HLA Laboratory, Kyoto, Japan).

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Statistical analysis

Statistical analysis was performed using Excel 2007 against 557 participants. For gene polymorphism associations with viral load, a Kruskal–Wallis test was performed for alleles expressed in four or more persons, that is, at population frequency of 0.7% or greater. To determine whether individual alleles were associated with significantly high or low viral load, Mann–Whitney U-test with false discovery rate analysis (q <0.2 as significance) was performed comparing viral load in participants with and without the allele as previously reported [28–31]. The same analyses, seeking associations with high or low viral load, were performed among HLA supertype comprising alleles. Linkage disequilibrium among HLA alleles was determined by Fisher's exact test using the Los Alamos database program (HLA Linkage Disequilibrium.

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Human leukocyte antigen sequence, three-dimensional crystal structure, and in-silico molecular dynamics analysis among HLA-B*35 alleles

For the comparison of HLA sequence and structure among HLA-B*35 alleles, we obtained HLA sequence information from the IGMT/HLA database [4], and HLA crystal structure information from the RCSB Protein Data Bank (PDB; For this study, we compared the HLA sequence variants among HLA-B*35 alleles identified in this cohort (HLA-B*35:01, B*35:03, and B*35:05). The structural model of HLA-B*35:01 was constructed from coordinates derived from PDB with the accession code 2CIK. Using 2CIK as a template, structural model for HLA-B*35:05 was made by homology modeling method with commercial software Molecular Operating Environment (MOE; Chemical Computing Group, Montreal, Canada). The effect of residue 97 variants on the HLA structure was also analyzed by the in-silico molecular dynamics program NAMD [32], measuring the distance between α-helixes of residues 74 Tyr (Y) and 147 Trp (W), which are adjacent with residue 97. Distance was measured in each 0.5 ps (pico second), with repeats up to 1000 ps of movement and 2000 times in total. The distance differences between two alleles were analyzed by a t-test.

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Sequence difference analysis at HLA-B*35:01-restricted Gag 253–262 NPPIPVGDIY (NY10) between HLA-B*35:01 and HLA-B*35:05

Recently, Gag 253–262 NPPIPVGDIY (NY10) was reported as a HLA-B*35:01-restricted epitope, with a D260E escape mutation causing HLA-epitope binding instability and consequent increase in viral load [33]. We analyzed sequence differences at this site and its flanking residue of Asn (N) 252 between HLA-B*35:01 positives and HLA-B*35:05 positives, among 216 CRF01_AE-infected Thais using our previously published data wherein the sequence data were obtained by direct sequencing of PCR products [27], and updated four digit HLA information.

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Characteristic of study population and human leukocyte antigen allele expression

Of 557 HIV-1 CRF01_AE-infected individuals recruited, 300 were women and 257 were men. The median age was 32 years (range 15–63 years), median baseline CD4+ T-cell 86 cells/μl (range 0–1191/μl), and median baseline viral load 5.26 log copies/ml (range 2.60–6.72 log copies/ml). With respect to HLA type, 111 alleles (27 HLA-A, 58 HLA-B, and 26 HLA-C alleles) were detected (Supplemental Table 1, The most prevalent HLA-A allele was HLA-A*11:01 (58.7% in population frequency), followed by HLA-A*24:02 (25.0%) and HLA-A*02:03 (24.4%). Of the HLA-B alleles, HLA-B*46:01 was the most prevalent (26.6%), followed by HLA-B*40:01 (20.1%) and HLA-B*13:01 (17.8%). HLA-B*57:01 was detected in only 1.4% of the study cohort. Of the HLA-C alleles, HLA-C*01:02 was the most prevalent (31.6%), followed by HLA-C*07:02 (30.3%) and HLA-C*08:01 (18.3%).

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Unique protective human leukocyte antigen allele associated with HIV viral load in an Asian population

Figure 1 shows the association of class I HLA alleles with viral load. This analysis included the 71 alleles that were expressed by more than three individuals and showed that viral load varied significantly among them (P = 0.034, Kruskal–Wallis test; Fig. 1a). Viral load varied more as a result of differences between HLA-B alleles (P = 0.068), than between HLA-A alleles (P = 0.077) or HLA-C alleles (P = 0.29; Fig. 1b). Three individual alleles were significantly associated with low viral load, namely, HLA-B*35:05 (P = 0.003), HLA-B*57:01 (P = 0.044), and HLA-A*24:07 (P = 0.025). Four individual alleles were significantly associated with high viral load, namely, HLA-B*15:04 (P = 0.038), HLA-B*56:01 (P = 0.011), HLA-A*11:02 (P = 0.015), and HLA-C*07:02 (P = 0.018). In each case, these associations were statistically significant (P <0.05, Mann–Whitney U-test) without correction for multiple tests. Only in the case of HLA-B*35:05 was this association significant after correcting for multiple tests, using q < 0.2 (q = 0.17, Supplemental Table 1, Significant viral control by HLA-B*35:05 was also identified among 209 participants with CD4+ T-cell counts more than 200 cells/μl (median 3.9 log copies/ml of viral load, P = 0.010 and q = 0.16) (Supplemental Table 2,

Fig. 1

Fig. 1

We next investigated whether linkage disequilibrium might explain some of these associations (Supplemental Figure 1, Among these alleles, we observed linkage disequilibrium between HLA-B*57:01 and HLA-C*06:02, and among HLA-A*24:07, HLA-B*35:05, and HLA-C*04:01. All HLA-B*57:01-positive persons also carried HLA-C*06:02 and no significant difference in viral load was observed in HLA-C*06:02 persons not expressing HLA-B*57:01 (P = 0.58) (Supplemental Figure 1A, In the case of the HLA-A*24:07-B*35:05-C*04:01, a significantly lower viral load was found in HLA-B*35:05-positive/HLA-A*24:07-negative individuals, whereas no such effect was found in HLA-A*24:07-positive/HLA-B*35:05-negative individuals (Supplemental Figure 1B, There was no linkage disequilibrium association to explain the association with disease susceptibility of HLA-A*11:02, HLA-B*15:04, HLA-B*56:01, or HLA-C*07:02.

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Significant viral load difference among B07s comprising human leukocyte antigen alleles

We next analyzed viral load differences among HLA supertypes, and here we did not find any significant viral load difference among A supertypes (P = 0.17 by Kruskal–Wallis test) nor B supertypes (P = 0.61). This result was not unexpected, given the coexistence of HLA alleles associated with low viral load and high viral load within the same supertype. For example, B07s comprised eight alleles, including the protective HLA-B*35:05 and the susceptible HLA-B*56:01 (P = 0.027 by Kruskal–Wallis test, Fig. 2). However, there were no significant viral load differences among comprising alleles in other supertypes. Viral load discrepancy among supertype comprising HLA alleles was previously reported in B58s among subtype C-infected African, including protective HLA-B*57:03 and HLA-B*58:01, then susceptible HLA-B*58:02, suggesting the difficulty of CTL-induced vaccine development based on HLA's structural similarity, that is, supertope [34].

Fig. 2

Fig. 2

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Impact of human leukocyte antigen sequence variation among HLA-B*35 alleles

HLA-B*35:05 has Asp (D) at residue 114 and Ser (S) at 116, as does the disease-susceptible HLA-B*35:01 (Fig. 3a). However, distinct from other HLA-B*35 alleles with Ile (I) at residues 94 and 95, and Arg (R) at residue 97, HLA-B*35:05 has Thr (T) at residue 94, Leu (L) at 95, and Ser (S) at 97, located at the peptide-binding groove (Fig. 3b, 3c, and 3d).

Fig. 3

Fig. 3

We compared the effect of sequence variation at residue 97 on the structure of the peptide-binding site of HLA-B*35:01 and HLA-B*35:05. Supplemental Figure 2, shows the difference in the flexibility at residue 97 between the two alleles by a space-filling method. Arg (R) 97 in HLA-B*35:01 protrudes further into the peptide-binding groove than Ser (S) 97 in HLA-B*35:05, with its short side chain. Analysis of the interaction of residue 97 with its neighboring residues showed that Arg (R) 97 in HLA-B*35:01 forms a salt bridge with Asp (D) 114 (Fig. 4a), whereas Ser (S) 97 in HLA-B*35:05 forms a predominant hydrogen bond of <2.5Å (2.3Å) with the α-helix-comprising residue of Tyr (Y) 74 (Fig. 4b). In the distance calculation between α-helixes Tyr (Y) 74 and Trp (W) 147, which lie adjacent to residue 97 (Fig. 4c), a significantly shorter distance was identified in HLA-B*35:05 compared with HLA-B*35:01 (7.1 ± 0.6 in HLA-B*35:05 vs. 7.8 ± 0.8 of mean ± SD Å in HLA-B*35:01, respectively, P <0.0001 by t-test; Fig. 4d). Because of these structural differences conferred by residue 97 variants, these two alleles will have a difference in peptide-binding capacity at the F pocket side, with a greater chance of peptide binding in HLA-B*35:01, and lesser one in HLA-B*35:05.

Fig. 4

Fig. 4

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Significant D260E escape mutations at HLA-B*35:01-restricted Gag 253–262 NPPIPVGDIY (NY10) in HLA-B*35:01, but not in HLA-B*35:05

Lastly, to examine differences in viral adaptation between HLA-B*35:01 and HLA-B*35:05, we analyzed the sequence difference at the Gag 253–262 NPPIPVGDIY (NY10) epitope, which was recently identified as an HLA-B*35:01-restricted epitope with a D260E escape mutation causing epitope-HLA binding instability [33]. In 216 individuals of CRF01_AE-infected Thais, significant D260E mutation was identified in HLA-B*35:01 positives [3/5 in HLA-B*35:01+ vs. 3/211 in HLA-B*35:01−, P = 0.0001 by Fisher's exact test, odds ratio (OR) 104, 95% confidence interval (CI) 12–868], but not in HLA-B*35:05 positives (0/4 in HLA-B*35:05+ vs. 6/212 in HLA-B*35:05−, P = 1; Table 1). In other sites, significantly higher mutations at I261X (2/5 vs. 2/209, P = 0.0025, OR 70, 95% CI 7.2–672) and the flanking N252X (5/5 vs. 94/209, P = 0.019) were also identified in HLA-B*35:01, but not in HLA-B*35:05 (0/4 vs. 6/212, P = 1 in I261X, and 2/4 vs. 97/212, P = 1, OR 1.2, 95% CI 0.2–8.6 in N252X).

Table 1

Table 1

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This is the first study to investigate the effect of HLA alleles on clinical outcome in a systematic way in an HIV-1 CRF01_AE-infected Asian cohort. In this study, we identified unique protective HLA alleles associated with viral control. As reported from other ethnic groups, and in HIV clade B and C infection [6–9], HLA-B*57 was also one of the most protective alleles in this Asian cohort. In addition, we identified a novel protective allele in HLA-B*35:05. This HLA-B*35:05 is identified among south-east Asian (2–5% in population frequency), but rare in African and whites. HLA-B*35 alleles have been classified into two groups, namely HLA-B*35-PY with a binding motif of Pro (P) at B pocket of HLA and Tyr (Y) at F pocket, including HLA-B*35:01 and HLA-B*35:08, and HLA-B*35-Px, with a binding motif of Pro (P) at B pocket, but not Tyr (Y) at F pocket, including HLA-B*35:02, HLA-B*35:03, HLA-B*35:04, and HLA-B*53:01 [35]. The disadvantage of Px for viral control was originally reported from clinical outcome studies among Africans and whites [35]. The mechanism underlying the difference in HIV disease outcome resulting from the two HLA-B*35 groups has not been determined, but may relate to the presence of Gag-specific CTLs capable of reducing viral load that have been detected in individuals expressing HLA-B*35:01 [35,36]. In addition, greater binding affinity to immunoglobulin-like transcript 4 (ILT4) has been described in individuals expressing HLA-B*35:03 compared to individuals expressing HLA-B*35:01, which causes dendritic cell dysfunction [37]. Furthermore, the existence of CTLs, which were not reactive against the original sequence epitope but only against variant sequence epitopes (heteroclitic reaction) have been described in individuals expressing HLA-B*35-Px alleles [38].

HLA-B*35:05, identified as one of the most protective alleles in this cohort, structurally belongs to the PY group [39], in common with HLA-B*35:01 carrying Asp (D) at HLA amino acid residue 114 and Ser (S) at residue 116 (D114-S116), compared to Asn (N) at 114 and Tyr (Y) or Phe (F) at 116 in HLA-B*35:03 (non-D114-S116). However, HLA-B*35:01 was associated with a significantly higher viral load than HLA-B*35:05 (Fig. 2, median 5.58 log copies/ml in HLA-B*35:01-positives, and 4.38 log copies/ml in HLA-B*35:05-positives, respectively, P = 0.010, Mann–Whitney U-test). Susceptibility of HLA-B*35:01 to high viral loads is consistent with two recent reports from studies of subtype B-infected whites and African–Americans, respectively [7,17]. In addition, HLA-B*35:01 is strongly associated with high viral load in clade B-infected cohorts in Japan and in Mexico [33]. These studies suggest that there may be distinct mechanisms underlying the association of low viral load in this Thai cohort with HLA-B*35:05. Of note, distinct from other HLA-B*35 alleles including those in the PY group, which share Ile (I) as HLA residues 94 and 95, and Arg (R) at residue 97, HLA-B*35:05 has Thr (T) at 94, Leu (L) at 95, and Ser (S) at 97 [4] (Fig. 3). Among these three residues, an association between sequence variants at residue 97 and HIV viral control has been previously reported and summarized in a European ancestry GWAS [17,18]. In the present study, we showed that the Arg (R) at residue 97 in HLA-B*35:01 protrudes into the peptide-binding groove, and conferred longer distances between α-helixes compared to Ser (S) at residue 97 in HLA-B*35:05. We propose that these results suggest Arg (R) has a dual role of an adhesive for epitope binding and a prop for a wider α-helix structure. Related with structure difference in peptide-binding groove of HLA and epitope variants, the difference between HLA-B*44:02 and HLA-B*44:03, with single amino acid difference of Asp (D) at residue 156 in HLA-B*44:02, and Leu (L) at residue 156 in HLA-B*44:03, was previously reported [40]. Although HLA-B*44:02 and HLA-B*44:03 shared more than 95% of their peptide repertoire in the examination of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDITOF MS), HLA-B*44:03 with wider groove also presented more unique peptides compared to HLA-B*44:02. Indeed, HLA-B*35:01 has binding motif of Tyr (Y), Phe (F), Met (M), Leu (L), Ile (I), or no specificity at F pocket, whereas HLA-B*35:05 has binding motif of Phe (F) only, according to the Los Alamos database (HIV HLA Anchor Residue Motifs. These data are consistent with the hypothesis proposed by Kosmrlj et al. [20] that HLA molecules with a more restricted peptide-binding repertoire, such as HLA-B*27 and HLA-B*57, and in this case, HLA-B*35:05, are more likely to be protective. In support of our hypothesis, we observed selection of D260E escape mutations within the Gag 253–262 NPPIPVGDIY (NY10) HLA-B*35:01-positive individuals and not in HLA-B*35:05-positive individuals.

In contrast to the consistent association between HLA-B*57 alleles and low viral load in this Thai cohort, as well as in clade B-infected and C-infected cohorts previously reported [6,8,9], the closely related allele HLA-B*58:01 was not protective in this Thai cohort. This contrasted with clade C-infected Native Africans and B-infected whites [6,8,9], but was consistent with subtype B-infected African–Americans [7]. HLA-B*58:01 was the fourth most prevalent HLA-B allele in this cohort, 17.6% by population frequency, higher than in Africans (6%) and whites (less than 2%) [7]. It is plausible, therefore, that the dominant virus in this population has already adapted to the immune pressure imposed on it by this allele [41]. Indeed, in our previous report, 15 of 20 (75%) of HLA-B*58:01-positive patients possessed the T242N escape mutation in Gag p24, and six of 15 (40%) of them already had at least one of the compensatory mutations, namely, H219Q, M228I, or G248A [27]. Among HLA-B*58:01 positives, a significantly higher viral load was identified among individuals with these compensatory mutations, compared with the ones without these mutations. However, among HLA-B*57:01, all (3/3) the individuals expressing this allele possessed T242N, but in none of the three there were compensatory mutations present at Gag residues 219/223/228. Although numbers are low, such a high frequency of compensatory mutations in the HLA-B*58:01-positive individuals suggests that it be easier for CRF01_AE's to adapt to immune pressure exerted by this allele.

In conclusion, our study has identified several protective HLA alleles, which affect viral control in HIV-infected individuals in Thailand. This represents a milestone in the study of HIV and HLA alleles from south-east Asia, as our data strongly indicate the existence of a protective effect of HLA-B*57 across ethnic groups, and also highlight for the first time HLA-B*35:05 as an allele protective in this cohort [42]. The identification of protective alleles in each endemic area provides the opportunity to better define the nature of HLA-mediated immune control and, therefore, will be valuable for further CTL vaccine development.

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The authors would like to thank Dr Naho Tsuchiya, Ms Phattaraporn Orataiwun, Ms Suthira Kasemsuk, Ms Sripai Saneewong-na-Ayuthaya, Ms Katkaew Thamachai, Ms Anongnard Suyasarojna, Ms Nutira Boonna, and Mr Praphan Wongnamnong for their excellent technical assistance at the Lampang hospital. This study was supported in part by JSPS KAKENHI Grant Number 25860367 (Japan), Ministry of Health, Labour and Welfare Grants-in-Aid (US-Japan Cooperative Medical Science Program), and by Imai Memorial Trust for AIDS Research (Japan).

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Conflicts of interest

There are no conflicts of interest.

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1. Goulder PJ, Watkins DI. Impact of MHC class I diversity on immune control of immunodeficiency virus replication. Nat Rev Immunol 2008; 8:619–630.
2. McMichael AJ, Borrow P, Tomaras GD, Goonetilleke N, Haynes BF. The immune response during acute HIV-1 infection: clues for vaccine development. Nat Rev Immunol 2010; 10:11–23.
3. Mungall AJ, Palmer SA, Sims SK, Edwards CA, Ashurst JL, Wilming L, et al. The DNA sequence and analysis of human chromosome 6. Nature 2003; 425:805–811.
4. Robinson J, Mistry K, McWilliam H, Lopez R, Parham P, Marsh SG. The IMGT/HLA database. Nucleic Acids Res 2011; 39:D1171–D1176.
5. Buonaguro L, Tornesello ML, Buonaguro FM. Human immunodeficiency virus type 1 subtype distribution in the worldwide epidemic: pathogenetic and therapeutic implications. J Virol 2007; 81:10209–10219.
6. Kiepiela P, Leslie AJ, Honeyborne I, Ramduth D, Thobakgale C, Chetty S, et al. Dominant influence of HLA-B in mediating the potential co-evolution of HIV and HLA. Nature 2004; 432:769–775.
7. Lazaryan A, Song W, Lobashevsky E, Tang J, Shrestha S, Zhang K, et al. The influence of human leukocyte antigen class I alleles and their population frequencies on human immunodeficiency virus type 1 control among African Americans. Hum Immunol 2011; 72:312–318.
8. Leslie A, Matthews PC, Listgarten J, Carlson JM, Kadie C, Ndung’u T, et al. Additive contribution of HLA class I alleles in the immune control of HIV-1 infection. J Virol 2010; 84:9879–9888.
9. O’Brien SJ, Gao X, Carrington M. HLA and AIDS: a cautionary tale. Trends Mol Med 2001; 7:379–381.
10. Gonzalez-Galarza FF, Christmas S, Middleton D, Jones AR. Allele frequency net: a database and online repository for immune gene frequencies in worldwide populations. Nucleic Acids Res 2011; 39:D913–919.
11. Kaslow RA, Carrington M, Apple R, Park L, Munoz A, Saah AJ, et al. Influence of combinations of human major histocompatibility complex genes on the course of HIV-1 infection. Nat Med 1996; 2:405–411.
12. Sette A, Sidney J. Nine major HLA class I supertypes account for the vast preponderance of HLA-A and -B polymorphism. Immunogenetics 1999; 50:201–212.
13. Sidney J, Peters B, Frahm N, Brander C, Sette A. HLA class I supertypes: a revised and updated classification. BMC Immunol 2008; 9:1.
14. Lazaryan A, Song W, Lobashevsky E, Tang J, Shrestha S, Zhang K, et al. Human leukocyte antigen class I supertypes and HIV-1 control in African Americans. J Virol 2010; 84:2610–2617.
15. Scherer A, Frater J, Oxenius A, Agudelo J, Price DA, Gunthard HF, et al. Quantifiable cytotoxic T lymphocyte responses and HLA-related risk of progression to AIDS. Proc Natl Acad Sci U S A 2004; 101:12266–12270.
16. Trachtenberg E, Korber B, Sollars C, Kepler TB, Hraber PT, Hayes E, et al. Advantage of rare HLA supertype in HIV disease progression. Nat Med 2003; 9:928–935.
17. Pereyra F, Jia X, McLaren PJ, Telenti A, de Bakker PI, Walker BD, et al. The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science 2010; 330:1551–1557.
18. McMichael AJ, Jones EY. Genetics. First-class control of HIV-1. Science 2010; 330:1488–1490.
19. Smith KJ, Reid SW, Harlos K, McMichael AJ, Stuart DI, Bell JI, et al. Bound water structure and polymorphic amino acids act together to allow the binding of different peptides to MHC class I HLA-B53. Immunity 1996; 4:215–228.
20. Kosmrlj A, Read EL, Qi Y, Allen TM, Altfeld M, Deeks SG, et al. Effects of thymic selection of the T-cell repertoire on HLA class I-associated control of HIV infection. Nature 2010; 465:350–354.
21. Fischer W, Ganusov VV, Giorgi EE, Hraber PT, Keele BF, Leitner T, et al. Transmission of single HIV-1 genomes and dynamics of early immune escape revealed by ultra-deep sequencing. PLoS One 2010; 5:e12303.
22. Turnbull EL, Lopes AR, Jones NA, Cornforth D, Newton P, Aldam D, et al. HIV-1 epitope-specific CD8+ T cell responses strongly associated with delayed disease progression cross-recognize epitope variants efficiently. J Immunol 2006; 176:6130–6146.
23. Ode H, Nakashima M, Kitamura S, Sugiura W, Sato H. Molecular dynamics simulation in virus research. Front Microbiol 2012; 3:258.
24. Reboul CF, Meyer GR, Porebski BT, Borg NA, Buckle AM. Epitope flexibility and dynamic footprint revealed by molecular dynamics of a pMHC-TCR complex. PLoS Comput Biol 2012; 8:e1002404.
25. Ode H, Yokoyama M, Kanda T, Sato H. Identification of folding preferences of cleavage junctions of HIV-1 precursor proteins for regulation of cleavability. J Mol Model 2011; 17:391–399.
26. Wichukchinda N, Nakayama EE, Rojanawiwat A, Pathipvanich P, Auwanit W, Vongsheree S, et al. Protective effects of IL4-589T and RANTES-28G on HIV-1 disease progression in infected Thai females. AIDS 2006; 20:189–196.
27. Gesprasert G, Wichukchinda N, Mori M, Shiino T, Auwanit W, Sriwanthana B, et al. HLA-associated immune pressure on Gag protein in CRF01_AE-infected individuals and its association with plasma viral load. PLoS One 2010; 5:e11179.
28. Storey JD. A direct approach to false discovery rates. J Royal Stat Soc 2002; 64:479–498.
29. Carlson JM, Brumme ZL, Rousseau CM, Brumme CJ, Matthews P, Kadie C, et al. Phylogenetic dependency networks: inferring patterns of CTL escape and codon covariation in HIV-1 Gag. PLoS Comput Biol 2008; 4:e1000225.
30. Alter G, Heckerman D, Schneidewind A, Fadda L, Kadie CM, Carlson JM, et al. HIV-1 adaptation to NK-cell-mediated immune pressure. Nature 2011; 476:96–100.
31. Kloverpris HN, Stryhn A, Harndahl M, Carlson JM, Leslie AJ, Chen F, et al. HLA-A*68:02-restricted Gag-specific cytotoxic T lymphocyte responses can drive selection pressure on HIV but are subdominant and ineffective. AIDS 2013; 27:1717–1723.
32. Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, et al. Scalable molecular dynamics with NAMD. J Comput Chem 2005; 26:1781–1802.
33. Matthews PC, Koyanagi M, Kloverpris HN, Harndahl M, Stryhn A, Akahoshi T, et al. Differential clade-specific HLA-B*3501 association with HIV-1 disease outcome is linked to immunogenicity of a single Gag epitope. J Virol 2012; 86:12643–12654.
34. Lazaryan A, Lobashevsky E, Mulenga J, Karita E, Allen S, Tang J, et al. Human leukocyte antigen B58 supertype and human immunodeficiency virus type 1 infection in native Africans. J Virol 2006; 80:6056–6060.
35. Gao X, Nelson GW, Karacki P, Martin MP, Phair J, Kaslow R, et al. Effect of a single amino acid change in MHC class I molecules on the rate of progression to AIDS. N Engl J Med 2001; 344:1668–1675.
36. Jin X, Gao X, Ramanathan M, Deschenes GR, Nelson GW, O’Brien SJ, et al. Human immunodeficiency virus type 1 (HIV-1)-specific CD8+-T-cell responses for groups of HIV-1-infected individuals with different HLA-B*35 genotypes. J Virol 2002; 76:12603–12610.
37. Huang J, Goedert JJ, Sundberg EJ, Cung TD, Burke PS, Martin MP, et al. HLA-B*35-Px-mediated acceleration of HIV-1 infection by increased inhibitory immunoregulatory impulses. J Exp Med 2009; 206:2959–2966.
38. Willberg CB, Garrison KE, Jones RB, Meiklejohn DJ, Spotts G, Liegler TJ, et al. Rapid progressing allele HLA-B35 Px restricted anti-HIV-1 CD8+ T cells recognize vestigial CTL epitopes. PLoS One 2010; 5:e10249.
39. Singh P, Kaur G, Sharma G, Mehra NK. Immunogenetic basis of HIV-1 infection, transmission and disease progression. Vaccine 2008; 26:2966–2980.
40. Macdonald WA, Purcell AW, Mifsud NA, Ely LK, Williams DS, Chang L, et al. A naturally selected dimorphism within the HLA-B44 supertype alters class I structure, peptide repertoire, and T cell recognition. J Exp Med 2003; 198:679–691.
41. 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; 296:1439–1443.
42. Goulder PJ, Walker BD. HIV and HLA class I: an evolving relationship. Immunity 2012; 37:426–440.

HIV-1 CRF01_AE; HLA-B*35; PY; residue 97; south-east Asia

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