# A genetic fingerprint associated with durable HIV remission after interruption of antiretroviral treatment: ANRS VISCONTI/PRIMO

Asma Essat, Anaïs Chapel, Kahina Amokrane, Valérie Monceaux, Céline Didier, Adeline Melard, Elise Gardiennet, Véronique Avettand-Fenoel, Sylvie Orr, Faroudy Boufassa, et al.

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## To cite this version:

Asma Essat, Anaïs Chapel, Kahina Amokrane, Valérie Monceaux, Céline Didier, et al. A genetic fingerprint associated with durable HIV remission after interruption of antiretroviral treatment: ANRS VISCONTI/PRIMO. Med, 2025, 8 (6), pp.100670. 10.1016/j.medj.2025.100670. hal-05059741

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# A genetic fingerprint associated with durable HIV remission after interruption of antiretroviral treatment: ANRS VISCONTI/PRIMO

## Graphical abstract

<figure><img src="image_3.png" /></figure>

## Authors

Asma Essat, Anaïs Chapel,
Kahina Amokrane, ..., Asier Sáez-Cirión,
ANRS PRIMO cohort, VISCONTI study

## Correspondence

asier.saez-cirion@pasteur.fr

## In brief

Understanding the mechanisms underlying HIV-1 control after interruption of antiretroviral treatment may guide the development of immunotherapies aiming at HIV remission. Essat, Chapel et al. identified a fingerprint combining HLA-B*35 with NK cell-related immunogenetic traits that was associated with posttreatment HIV-1 control, supporting the role of NK cells in long-term HIV remission.

## Highlights

* Paradoxical frequency of HLA-B*35 alleles among HIV-1 posttreatment controllers

* HLA-B*35 linked to earlier ART start and higher chance of posttreatment control

* Bw4 and C2 KIR ligands are abundantly found in combination with HLA-B*35 in PTCs

* Genotype favoring KIR education of NK cells linked to posttreatment control

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## Article

# A genetic fingerprint associated with durable HIV remission after interruption of antiretroviral treatment: ANRS VISCONTI/PRIMO

Asma Essat,<fnref n="1" />,<fnref n="13" /> Anaïs Chapel,<fnref n="2" />,<fnref n="3" />,<fnref n="13" /> Kahina Amokrane,<fnref n="4" /> Valérie Monceaux,<fnref n="2" />,<fnref n="3" /> Céline Didier,<fnref n="5" /> Adeline Melard,<fnref n="6" />,<fnref n="7" />

Elise Gardiennet,<fnref n="6" />,<fnref n="7" /> Véronique Avettand-Fenoel,<fnref n="6" />,<fnref n="7" />,<fnref n="8" /> Sylvie Orr,<fnref n="1" /> Faroudy Boufassa,<fnref n="1" /> Olivier Lambotte,<fnref n="9" />

Michaela Müller-Trutwin,<fnref n="3" /> Camille Lécuroux,<fnref n="9" /> Antoine Chéret,<fnref n="7" />,<fnref n="10" /> Cécile Goujard,<fnref n="10" /> Christine Rouzioux,<fnref n="6" />

Sophie Caillat-Zucman,<fnref n="4" /> Laurent Hocqueloux,<fnref n="11" /> Daniel Scott-Algara,<fnref n="12" /> Laurence Meyer,<fnref n="1" /> Asier Sáez-Cirión,<fnref n="2" />,<fnref n="3" />,<fnref n="14" />,*
and ANRS PRIMO cohort, VISCONTI study

**CONTEXT AND SIGNIFICANCE** Current antiretroviral treatments efficiently block HIV-1 infection, but they need to be continued for life, as a rapid viral rebound occurs if the treatment is stopped. This study analyzed 27 extraordinary individuals who maintained the virus controlled for multiple years despite the interruption of the treatment. The scientists found genetic traits associated with NK cell education overrepresented in these individuals. The presence of these genetic factors was associated with decreased risk of viral rebound after treatment interruption in people who were diagnosed and treated in the first weeks following HIV-1 infection. These results support a key role of NK cells in the control of HIV-1 off antiretroviral treatment and may guide the development of new immunotherapies against HIV-1.

## SUMMARY

**Background:** There is currently no curative treatment for HIV-1 infection. However, some individuals (defined as posttreatment controllers) durably control viremia after the discontinuation of antiretroviral therapy (ART). Although the ability to achieve this HIV-1 remission status is enhanced by early treatment initiation, the mechanisms leading to posttreatment HIV-1 control remain unclear.

**Methods:** We retrospectively explored the immunogenetic characteristics of long-term posttreatment controllers from the ANRS VISCONTI study and persons monitored since primary HIV-1 infection in the ANRS PRIMO cohort and evaluated their influence on clinical parameters and outcome after ART discontinuation.

**Findings:** We identified a major histocompatibility complex (MHC)-related fingerprint favoring sustained HIV-1 remission. HLA-B*35 alleles, which are associated with rapid progression to AIDS during natural HIV-1 infection, were paradoxically overrepresented among posttreatment controllers and had a positive impact on outcome after treatment discontinuation in people who began therapy during primary infection. Specifically, the influence of HLA-B*35 alleles was observed when they were carried in combination with

<footnote n="1">¹Université Paris-Saclay, Inserm CESP U1018, AP-HP, Department of Public Health, Bicêtre Hospital, 94270 Paris-Saclay, France</footnote>

<footnote n="2">²Institut Pasteur, Université Paris Cité, Viral Reservoirs and Immune Control Unit, 75015 Paris, France</footnote>

<footnote n="3">³Institut Pasteur, Université Paris Cité, HIV Inflammation and Persistence Unit, 75015 Paris, France</footnote>

<footnote n="4">⁴AP-HP, Hôpital Saint-Louis, Université Paris Cité, Laboratoire d'Immunologie et Histocompatibilité, 75010 Paris, France</footnote>

<footnote n="5">⁵Institut Pasteur, Unité Régulation des Infections Rétrovirales, 75015 Paris, France</footnote>

<footnote n="6">⁶Université Paris Cité, Faculté de Médecine, 75015 Paris, France</footnote>

<footnote n="7">⁷INSERM U1016, CNRS UMR8104, Institut Cochin, 75014 Paris, France</footnote>

<footnote n="8">⁸Université d'Orléans, LI²RSO, CHU Orléans, Virologie, 45100 Orléans, France</footnote>

<footnote n="9">⁹Université Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological, Bacterial Diseases (IMVA-HB/IDMIT/UMRS1184), 94270 Le Kremlin Bicêtre, France</footnote>

<footnote n="10">¹⁰Université Paris-Saclay, AP-HP, Hôpital Bicêtre, DMU 7, Inserm U1018, CESP, 94270 Le Kremlin Bicêtre, France</footnote>

<footnote n="11">¹¹Centre Hospitalier Universitaire, Service des Maladies Infectieuses, 45100 Orléans, France</footnote>

<footnote n="12">¹²Institut Pasteur, Université Paris Cité, Lymphocyte Cell Biology Unit, 75015 Paris, France</footnote>

<footnote n="13">¹³These authors contributed equally</footnote>

<footnote n="14">¹⁴Lead contact</footnote>

<footnote>*Correspondence: asier.saez-cirion@pasteur.fr</footnote>

<footnote>https://doi.org/10.1016/j.medj.2025.100670</footnote>
other HLA class I alleles expressing Bw4 and C2 ligands of killer immunoglobulin-like receptors (KIRs) in a genetic context that favors KIR education of natural killer (NK) cells (Bw4TTC2 genotype). Accordingly, post-treatment controllers with HLA-B*35 alleles carry distinct KIR genotypes and NK cells.

**Conclusions:** The combination of HLA-B*35 with Bw4TTC2 genotype, associated with KIR education of NK cells, was abundant among posttreatment HIV-1 controllers and promoted viral control after interruption of early-initiated antiretroviral treatment. These results support a role of NK cells in sustained HIV-1 remission.

**Funding:** The VISCONTI study and the PRIMO cohort are funded by the ANRS-MIE.

## INTRODUCTION

Antiretroviral therapy (ART) has changed the HIV epidemic, increasing the life expectancy of people with HIV (PWH) to near normal levels. Unfortunately, ART cannot overcome barriers to HIV eradication, and new strategies are needed to mitigate the challenges of providing universal coverage and lifelong therapy to an increasing population of PWH. One possibility is to achieve HIV remission, where PWH can live for prolonged periods off ART without viral relapse.¹ The perspective of durable virological remission has been supported by the identification of posttreatment controllers (PTCs)²⁻⁵ (i.e., PWH in whom viremia control is maintained after treatment interruption [TI], even in the presence of replication-competent virus). The ANRS VISCONTI study characterized 14 long-term PTCs and suggested that early initiation of ART may favor HIV remission,⁴ a hypothesis that has been supported by independent studies⁶⁻⁹ and models of infection with simian immunodeficiency virus (SIV).¹⁰,¹¹

Understanding the factors associated with the PTC status is critical for developing interventions aiming for HIV remission. However, the underlying immunological mechanisms remain elusive and may differ from those identified in natural HIV controllers (HICs).⁴,¹² Although several mechanisms may explain how HICs achieve viral control without ever receiving ART, the development of a particularly efficient CD8⁺ T cell response has been most prominently purported.¹³,¹⁴ The role of CD8⁺ T cells in natural control is reinforced by the enrichment of human leukocyte antigen (HLA) class I alleles associated with low viremia, particularly HLA-B*57, HLA-B*27, and HLA-B*14, in different cohorts of HICs.¹⁵⁻¹⁷ Interestingly, these alleles have not been frequently found among PTCs. In contrast, we previously described a paradoxical abundance of HLA-B*35 alleles among the PTCs in the VISCONTI study.⁴ The HLA-B*35 allotype has been consistently associated with rapid progression to AIDS in the absence of ART.¹⁸⁻²⁵ Moreover, the negative impact of HLA-B*35 has been linked to the development of suboptimal HIV-specific CD8⁺ T cells with limited antiviral potential that are prone to exhaustion and targeting epitopes that allow rapid viral escape.²²,²⁶⁻²⁹ Therefore, one explanation for the high frequency of PTCs carrying HLA-B*35 alleles is that symptomatic and/or lower CD4⁺ T cell counts during primary HIV-1 infection (PHI) in PWH carrying HLA-B*35³⁰ prompt earlier HIV diagnosis and ART initiation, conferring an advantage toward posttreatment control.

Nevertheless, early ART initiation is not sufficient to achieve PTC status, as most PWH experience viral rebound even when ART is initiated during the early stages of infection.⁹,³¹ The presence of HLA-B*35 alleles might also have an as-yet-unknown, direct positive impact on outcome after TI. HLA class I molecules carry intrinsic motifs recognized by multiple receptors that regu-

late immune cells. The best example is natural killer (NK) cells, activity of which is regulated by complex interactions between activating and inhibitory receptors (such as killer cell immunoglobulin-like receptors [KIRs], immunoglobulin-like transcripts [ILTs], or NKG2 receptors) with ligands present in different HLA molecules.³² NK cells are “educated” to recognize the expression patterns of these ligands, and they release cytokines and cytotoxic granules in response to perturbed expression of HLA class I molecules in diseased cells.³³ NK cells are among the first cells mobilized following HIV infection. While NK cell cytotoxicity and the secretion of soluble factors are impaired early after HIV-1 infection,³⁴⁻³⁸ NK cells can contribute to control infection in some contexts, and the combination of KIR3DL1/S1 alleles with HLA-B alleles encoding the Bw4 epitope is strongly associated with delayed disease progression.³⁹⁻⁴³

To understand the impact of HLA-B*35 alleles on outcome after interruption of early-initiated ART, we studied an extended group of 27 PTCs who displayed long-term HIV remission (>12.8 [8.2–16.3] years) identified in the context of the VISCONTI study and 1,615 PWH monitored since PHI in the ANRS PRIMO cohort. Our results confirmed a higher probability of controlling viremia after TI in a group of PWH carrying HLA-B*35 alleles and revealed an immunogenetic fingerprint favoring durable posttreatment control. This genetic fingerprint is associated with a specific KIR genotype and the presence of NK cells with anti-HIV activity in PTCs.

## RESULTS

### Long-term posttreatment HIV-1 controllers frequently carry HLA-B*35 alleles

We reported that five of the 14 PTCs originally identified in the VISCONTI study carried one HLA-B*35 allele.⁴ Among the 27 PTCs included in the extended VISCONTI study (Table S1), nine carried one HLA-B*35 allele. The PTCs carrying HLA-B*35 alleles experienced a similarly long period off ART as did the PTCs carrying other alleles (median 14.4, interquartile range [IQR] [5.3–18.3] and 11.7 [8.5–15.9] years off ART, respectively; *p* = 0.71) and maintained similar CD4⁺ T cell counts (766 [654–1,084] and 751 [518–958], respectively; *p* = 0.71). The probability of loss of viremia control was similarly low for both groups of PTCs (Figure S1) (two PTCs with HLA-B*35 and three other PTCs who restarted ART during follow-up).

To assess the significance of the presence of HLA-B*35 alleles in PTCs, we compared HLA-B*35 allele frequencies in 27 PTCs, in a reference population in France (*N* = 6,094 individuals),⁴⁴ in a group of HICs from the ANRS CODEX cohort (*N* = 45),¹⁵ and in a group of PWH monitored since PHI in the PRIMO cohort (*N* = 1,615) (Figure 1A). The HLA-B*35 allele frequency was higher
in the PTCs than in the French reference population, but it was lower among HICs than in the reference population (Figure 1B), as previously reported.¹⁶ HLA-B*35 alleles can be divided into two groups depending on their peptide-binding specificity: HLA-B*35-PY alleles (HLA-B*3501 and HLA-B*3508) bind peptides with tyrosine at P9, and HLA-B*35-Px alleles (e.g., HLA-B*3502, HLA-B*3503) bind peptides containing any other amino acid at P9.¹⁹ Five PTCs carried HLA-B*35-PY alleles (four HLA-B*3501 and one1 HLA-B*3508), and four carried the HLA-B*3503-Px allele. Only HLA-B*3503 was found at a higher frequency among PTCs than among individuals in the reference population (odds ratio [OR] for carrying the allele, 3.76 [1.11–13]; *p* = 0.04) (Figure S2). Taken together, the HLA-B*35 alleles were enriched among PTCs and excluded among HICs when compared with the general population. In contrast, the frequency of HLA-B alleles typically associated with natural HIV control (i.e., HLA-B*57/58, HLA-B*27, and HLA-B*14) was not different among PTCs when compared with the reference population but was significantly higher among HICs (Figure 1). The HLA distribution was very similar between PWH monitored in the PRIMO cohort and those in the reference population (Figure 1B; Table S2). Overall, PTCs and HICs had distinct immunogenetic profiles (Figure 1C), which suggests that different immune mechanisms are involved in natural and posttreatment HIV-1 control. Our analyses reinforce, in an extended group of PTCs, our previous observation that HLA-B*35 risk alleles are abundant among people with durable posttreatment control of HIV-1 infection.

## The presence of HLA-B*35 alleles prompted ART initiation during primary infection

Although current guidelines recommend immediate ART initiation after HIV diagnosis, this was not common practice in the late 1990s, when most PTCs from the VISCONTI study were diagnosed. We evaluated whether the presence of HLA-B*35 alleles might have prompted a short delay in treatment initiation in PWH at that time. We compared the clinical characteristics during PHI of a subset of participants (N = 339) in the PRIMO cohort who were diagnosed before 2002, within the same period as PTCs from the VISCONTI study, carrying at least one HLA-B*35 allele, one HLA-B*27/57/58 allele, or none of these alleles. We found that PWH carrying HLA-B*35 were more often symptomatic and tended to have lower CD4⁺ T cell counts and higher cell-associated HIV DNA levels than did any other group (Table 1). In contrast, those carrying HLA-B*27/57/58 alleles presented higher CD4⁺ T cell counts, lower CD8⁺ T cell counts, higher CD4/CD8 ratios, lower viral loads, and lower cell-associated HIV DNA levels (Table 1). This recapitulates the deleterious or protective roles previously described for these alleles. In accordance with their less favorable clinical context, PWH carrying HLA-B*35 alleles began ART more frequently during PHI than other PWH did (*p* = 0.03) (Table 1). Therefore, although the differences were small, the presence of HLA-B*35 alleles prompted rapid ART initiation.

## The presence of HLA-B*35 alleles favored posttreatment control among PWH who began ART during primary infection

To evaluate the influence that HLA-B*35 alleles might have on posttreatment control beyond merely prompting early ART initi-

ation, we next focused on a subset of participants in the PRIMO cohort who began ART at the time of PHI diagnosis and who showed viremia suppression on ART but experienced TI later (PRIMO subcohort 1, N = 150). The delay between the estimated time of infection and ART initiation was similar for participants in this subcohort regardless of whether they carried HLA-B*35, HLA-B*27/57/58, or other HLA-B alleles (Table S3). The deleterious and protective effects of the HLA-B*35 and HLA-B*27/57/58 alleles were not obvious at PHI for this subcohort of early-treated participants except for higher levels of cell-associated HIV DNA in PWH carrying HLA-B*35 alleles (Figure 2A). All clinical parameters improved, and no differences were found between the groups based on their HLAs after a similar period on ART, except for a trend toward higher levels of cell-associated HIV DNA among HLA-B*35 participants than among those with HLA-B*27/57/58 alleles (Figure 2B). However, participants in this PRIMO subcohort 1 carrying HLA-B*35 alleles were more likely to maintain undetectable viremia after TI than those carrying HLA-B*27/57/58 alleles or other alleles (Figure 2C). Moreover, in six HLA-B*35 PWH, undetectable viremia was maintained for more than 1 year. Overall, seven participants in subcohort 1 of the PRIMO cohort exhibited viremia control to below 400 RNA copies/mL and were later included as PTCs in the VISCONTI study (IDs 063003, 084001, 090001, 093001, 098004, 200001, and 216001) (Table S1). No differences were found in CD4 T cell counts (median 795 [IQR 582–1460] vs. 738 [600–960] cells/mm³, *p* = 0.51), the CD4/CD8 ratio (1.45 [1.1–2] vs. 1.1 [0.8–1.4], *p* = 0.11), or cell-associated HIV DNA (2.6 [1.94–2.78] vs. 2.2 [1.7–2.65] log copies/10⁶ cells, *p* = 0.42) before TI between these individuals and the other PWH who did not control the virus. These results show that, even among PWH who begin ART at a similar early time, the presence of HLA-B*35 alleles to some degree favored posttreatment HIV-1 control.

## High frequency of HLA alleles containing the Bw4 epitope among HLA-B*35 PTCs

Analysis of the early-treated participants in the PRIMO subcohort 1 supported the positive impact of HLA-B*35 alleles on outcome after TI. However, only a fraction of HLA-B*35 participants achieved posttreatment control (Figure 2C). We therefore determined whether the HLA-B*35 PTCs from the VISCONTI study carried additional immunogenetic traits that might have promoted their capacity for durably controlling HIV-1 without ART. HLA-B alleles express either Bw4 or Bw6 motifs depending on residues 77–83 in the α1 domain,⁴⁵ and the presence of HLA alleles containing the Bw4 epitope recognized by KIRs on NK cells has been consistently associated with HIV control.⁴² HLA-B*35 alleles always contain a Bw6 motif. In contrast, we found that seven of nine (77.8%) HLA-B*35 PTCs in the VISCONTI study carried another HLA-B allele that contained the Bw4 epitope, a frequency that was higher than among the HLA-B*35 PWH in the complete PRIMO cohort (42.5%, *p* = 0.035) (Figure 3A). PTCs not carrying HLA-B*35 alleles (“other”) often carried at least one HLA-B molecule containing the Bw4 epitope (83.3%), but this was not different from other PWH in the PRIMO cohort (70.9%, *p* = 0.25). Among the HLA-B alleles containing the Bw4 epitope, HLA-B*35 PTCs
<figure><img src="image_5.png" /><figcaption>**Figure 1. HLA-B*35 alleles are overrepresented among PTCs**</figcaption></figure>

(A) Frequencies of favorable HLA-B*14, HLA-B*27, and HLA-B*57/58 alleles and of risk HLA-B*35 alleles among a reference population in France (N = 6,094 individuals), PWH from the ANRS PRIMO cohort (N = 1,615), posttreatment controllers (PTCs) from the ANRS VISCONTI study (N = 27), and HIV controllers (HICs) from the ANRS CODEX cohort (N = 45).

(B) Comparison of frequencies of HLA-B*35, HLA-B*14, HLA-B*27, and HLA-B*57/58 alleles among HICs, PWH from PRIMO, and PTCs relative to the reference population. Odds ratios and 95% confidence intervals are shown. (C) Comparison of HLA-B*35, HLA-B*14, HLA-B*27, and HLA-B*57/58 allele frequencies among PTCs relative to HICs.

p' represents values corrected for multiple comparisons.

from the VISCONTI study more frequently carried the HLA-B*13 allele (Table S4). In addition, a few HLA-A alleles (A*23, A*24, A*25, A*32) contain the Bw4 epitope. Among them, A*24 was frequently found in HLA-B*35 individuals from both VISCONTI and PRIMO (Table S5) and HLA-A*23 alleles were more frequently present in HLA-B*35 PTCs from the VISCONTI study than in HLA-B*35 PWH from the PRIMO cohort (Table S5). Overall, HLA-B*35 PTCs from the VISCONTI study more frequently carried several HLA-A or HLA-B alleles containing the Bw4 epitope (44.4%) than did HLA-B*35 PWH in the PRIMO cohort (16.4%, p = 0.028) (Figure 3B). A similar trend was observed for PTCs not carrying HLA-B*35 alleles (55.6% vs. 35% of PWH from PRIMO not carrying HLA-B*35, p = 0.072). Participants of non-European origin tended to be more frequently present among PTCs from the VISCONTI study than among the participants in the PRIMO cohort (22.2% vs. 10.6%, p = 0.06). However, HLA-B*35 alleles were mostly found in PTCs of European origin (88.9%), which was not different in the PRIMO cohort (91.6%, p = 0.56). Therefore, neither the high proportion of PTCs with HLA-B*35 alleles nor the differences found between people carrying these alleles in the VISCONTI and PRIMO cohorts could be explained by differences in their ethnic origin. These results reveal an extraordinary frequency of HLA molecules expressing the NK ligand Bw4 in HLA-B*35 PTCs from the VISCONTI study and a trend toward a high presence of multiple Bw4 alleles among PTCs in general.

## High frequency of HLA-C alleles containing the C2 epitope among HLA-B*35 PTCs

In addition to the Bw4 epitope, other KIR ligands are present in HLA molecules. This is the case for the bimorphic C1/C2 epitopes, which are encoded by HLA-C alleles and distinguished by the presence of an asparagine or lysine at position 80 of the alpha-1 domain.⁴⁶ We found a higher frequency of C2 alleles among PTCs from the VISCONTI study (54.5%) than in the reference population (37.9%, p = 0.023) and a trend compared with PWH from the PRIMO cohort (42.1%, p = 0.097) (Figure 3C). This was related to the higher frequency of HLA-B*35 among PTCs. HLA-C*04 alleles, which express the C2 ligand, are in strong linkage disequilibrium with HLA-B*35 alleles.⁴⁷ Accordingly, HLA-C*04 molecules were frequently present among HLA-B*35 individuals from PRIMO and from VISCONTI (49% and 39% of HLA-C alleles, respectively) (Table S5). Although no difference in the overall frequency of C2 alleles was observed between HLA-B*35 PTCs from VISCONTI and HLA-B*35 PWH from PRIMO (72.2% and 63.4%, respectively) (Figure 3C), C2-containing C*06 alleles were more frequent among HLA-B*35 PTCs from VISCONTI (22.2 vs. 5.1% among HLA-B*35 PWH from PRIMO, p' = 0.026) (Table S5). Therefore, HLA-B*35 PTCs from the VISCONTI cohort are characterized by C2 allele abundance. These results, together with the elevated incidence of Bw4 alleles in HLA-B*35 PTCs, highlight the profusion of HLA alleles expressing specific KIR ligands in these individuals.
<table><caption>Table 1. Clinical characteristics during PHI of PWH enrolled before 2002 in the ANRS PRIMO cohort</caption><thead><tr><th></th><th>Other HLA<br>(N = 228)</th><th>HLA-B*35 (N = 67)<sup>a</sup></th><th>HLA-B*27/B*57/58<br>(N = 44)</th><th><i>p</i> value</th><th><i>p</i> value<br>(HLA-B*35 vs. other)</th></tr></thead><tbody><tr><td>Sex (M)<sup>b</sup></td><td>184 (80.7%)</td><td>61 (91%)</td><td>35 (79.6%)</td><td>0.11</td><td>0.06</td></tr><tr><td>ART initiation during PHI</td><td>167 (73.3%)</td><td>59 (88.1%)*</td><td>31 (70.5%)</td><td>0.02</td><td>0.01</td></tr><tr><td>Delay to ART (months)</td><td>1.64 [1.18–3.65]</td><td>1.28 [1.05–2.17]*</td><td>1.47 [1.08–3.29]</td><td>0.13</td><td>0.05</td></tr><tr><td>Symptomatic PHI</td><td>189 (82.9%)</td><td>63 (94%)*</td><td>36 (81.8%)</td><td>0.05</td><td>0.03</td></tr><tr><td>CD4 inclusion (cells/μL)</td><td>523 [392–682]</td><td>480 [312–630]</td><td>636 [467–854]*</td><td>0.01</td><td>0.07</td></tr><tr><td>CD8 inclusion (cells/μL)</td><td>1006 [723–1465]</td><td>922 [750–1414]</td><td>833 [630–1188]*</td><td>0.03</td><td>0.40</td></tr><tr><td>CD4/CD8 &lt; 1 inclusion</td><td>196 (86.7%)</td><td>58 (87.9%)</td><td>29 (65.9%)*</td><td>0.004</td><td>1</td></tr><tr><td>pVL<sup>c</sup> inclusion (log copies/mL)</td><td>5.18 [4.32–5.81]</td><td>5.15 [4.74–5.76]</td><td>4.24 [3.39–4.88]*</td><td>0.0004</td><td>0.91</td></tr><tr><td>HIV DNA inclusion<br>(log copies/10<sup>6</sup> PBMCs)</td><td>3.30 [2.86–3.64]</td><td>3.40 [3.17–3.74]</td><td>2.82 [2.30–3.24]*</td><td>&lt;0.0001</td><td>0.07</td></tr></tbody></table>

The asterisks identify the parameters driving the differences between the groups in post hoc tests.

<sup>a</sup>Participants carrying simultaneously one HLA-B*35 allele and one HLA-B*27 or HLA-B*57/58 allele were excluded from the analyses.

<sup>b</sup>M: male.

<sup>c</sup>pVL: plasma viral load.

## Genotype favoring KIR education of NK cells in all PTCs carrying HLA-B*35 alleles

The abundance among HLA-B*35 PTCs from the VISCONTI study of HLA class I alleles carrying specific KIR ligands suggests a role for NK cells in posttreatment HIV control. The activity of NK cells is regulated such that they can trigger an immune response against a damaged cell while maintaining tolerance to nondiseased cells. This education of NK cells can occur (1) through direct interaction between several activating or inhibitory KIRs with HLA ligands or (2) through interaction of complexes of HLA-E and class I peptides with inhibitory NKG2A/CD94.48 HLA-E expression is strongly determined by the interaction of HLA-E with a short leader sequence present in all HLA class I molecules.49 In particular, the anchor residue at position –21 (either a methionine or threonine) of HLA-A, HLA-B, or HLA-C molecules determines the quality of folding and surface expression of HLA-E complexes.48 Specifically, a –21M residue provides a good anchor, facilitates HLA-E expression and promotes NKG2A education, whereas –21T is an inferior anchor associated with poor expression of HLA-E and promotes KIR education in NK cells.48 The high frequency of HLA-B*35 PTCs carrying Bw4 and C2 alleles suggests that these PWH have HLA genotypes that favor KIR education. The most frequent HLA-B alleles have a –21T residue, which is the case for HLA-B*35 alleles.48 We found that, in general, PTCs from the VISCONTI study tended to more frequently carry two HLA-B molecules containing a T at position –21 (Figure 4A). This was specifically linked to HLA-B*35 PTCs but not to other PTCs. Notably, all HLA-B*35 PTCs in the VISCONTI study carried two HLA-B alleles with a –21T residue. This is not a general characteristic of people harboring HLA-B*35 alleles, as HLA-B alleles with –21M were found in 25.3% of HLA-B*35 PWH from the PRIMO cohort. These results further support the observation that HLA-B*35 PTCs have HLA genotypes that favor the KIR education of NK cells.

Overall, we found that all HLA-B*35 PTCs from the VISCONTI study carried at least one HLA-Bw4 allele, one HLA-C2 allele, and had two HLA-B alleles with a T residue at position –21 (Bw4TTC2 genotype). This Bw4TTC2 genotype present was detected

in only 39.4% of HLA-B*35 PWH from the PRIMO cohort ($p < 0.001$) (Figure 4B). The frequency of the Bw4TTC2 genotype did not differ between PTCs from VISCONTI and PWH from PRIMO not carrying HLA-B*35 alleles (Figure 4B). Overall, 33.3% (9 out of 27) of the PTCs we studied carried a combination of HLA-B*35 alleles and the Bw4TTC2 genotype, although the frequency was 7.9% (125/1588) for PWH from the PRIMO cohort (OR, 5.9 [2.5–13.1], $p < 0.0001$). This finding suggests a strong association of HLA-B*35 alleles plus the Bw4TTC2 genotype with long-term posttreatment control of HIV infection.

To further evaluate the impact of the Bw4TTC2 genotype on posttreatment control, we reanalyzed outcome after TI in PWH from PRIMO subcohort 1 for whom early-initiated ART was discontinued (Figure 2) while accounting for the absence or presence of Bw4TTC2. While no differences were observed in their baseline characteristics compared with those of people carrying other combinations (Table S3), the combination of HLA-B*35 alleles with the Bw4TTC2 genotype (but neither when considered alone) was associated with a higher probability of maintaining control after TI (Figure 4C). Therefore, the combination of HLA-B*35 with the Bw4TTC2 genotype identifies a genetic fingerprint associated with posttreatment HIV control.

## Selection of KIR Bx genotypes in PTCs carrying HLA-B*35 alleles

The Bw4TTC2 genotype reflects a combination of HLA molecules associated with KIR education of NK cells. We therefore assessed whether PTCs from the VISCONTI study might carry particular KIR repertoires. KIR haplotypes are defined based on the different numbers and polymorphisms of KIR genes,50,51 and are commonly divided into group A and group B KIR haplotypes. The group A haplotypes have a fixed gene content and encode mainly inhibitory KIRs (3DL1, 2DL1, and 2DL3) and activating KIR2DS4; the group B haplotypes have more variable gene content and encode more activating KIRs. We determined the KIR genotype52 for 19 PTCs from the VISCONTI study (eight carrying HLA-B*35 alleles) for whom material was available (Table S6). Unfortunately, the KIR genotype was not available
A

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B

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C

<figure><img src="image_14.png" /><figcaption>Figure 2. The presence of HLA-B*35 alleles is associ-
ated with a higher probability of maintaining undetect-
able viremia after ART interruption in PWH who initiate
treatment during PHI</figcaption></figure>

(A and B) CD4+ T cell counts, CD4/CD8 ratio, plasma viral load, and cell-associated HIV-1 DNA at PHI (A) and before TI (B) in PWH enrolled in the ANRS PRIMO cohort who began ART at the time of PHI diagnosis and for whom treatment was later interrupted. The participants were grouped based on the presence of at least one HLA-B*35 allele (N = 30), one HLA-B*27 or HLA-B*57/58 allele (N = 15), or neither the HLA-B*35 nor HLA-B*27/57 allele (other, N = 105). Cell-associated HIV DNA levels before TI were only available for a subset of these participants (HLA-B*35, N = 22; HLA-B*27/B*57/58, N = 9; other HLAs, N = 62). Participants carrying HLA-B*35 and HLA-B*27 or HLA-B*57/58 alleles simultaneously were excluded from the analyses. Individual values and medians and IQRs are presented for each group.

(C) Probability of participants in the different HLA groups maintaining viral load below the test detection level after ART interruption.
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A

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Odds ratio for carrying one HLA B Bw4 allele
relative to PRIMO

<figure><img src="image_32.png" /></figure>

B

Number of
Bw4 alleles

<figure><img src="image_33.png" /></figure>

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(legend on next page)
for the PRIMO cohort, and, to study KIR HLA epistasis, we used
as a reference previously reported data by Hanson and col-
leagues⁵³ based on a cohort of 12,214 healthy individuals of Eu-
ropean origin from the International Genetics of Ankylosing
Spondylitis (IGAS) consortium. The common KIR AA1 genotype,
found in 36.9% of individuals in the IGAS cohort, was present at
a relatively low frequency among PTCs from the VISCONTI study
and was completely absent in the eight PTCs carrying HLA-B*35
alleles analyzed herein (Figure 5A). Notably, the frequency of the
KIR AA1 genotype was similar among individuals in the IGAS
cohort regardless of whether they carried HLA-B*35 alleles.
Some KIR genes more consistently found in KIR AA genotypes
(KIR2DL1, KIR2DL3, and KIR2DS4) were, or tended to be, less
frequent among PTCs, particularly those carrying HLA-B*35 al-
leles (Figure 5B). This was also the case for KIR2DP1, which en-
codes a fossil KIR more frequently deleted in group B KIR
haplotypes.⁵⁴

In contrast to the low frequency of the KIR AA1 genotype, some uncommon KIR Bx genotypes were detected in PTCs from the VISCONTI study (Table S6). For example, the KIR Bx32 genotype is carried by only 60 individuals among 25,050 in the KIR genotype reference database (allelefrequencies.net/ kir.asp) (0.24%) but was carried by three of the 19 PTCs analyzed herein (15.8%, *p* < 0.0001): one carrying HLA-B*35 and two carrying HLA-B*5301, which is closely related to the HLA-B*35 family,<sup>55,56</sup> classed in the HLA-B*35-Px group and associated with rapid disease progression in the absence of ART.<sup>19</sup>

We next assessed whether PTCs carried cognate ligands for
their KIR repertoire. Most PTCs (and all of those with HLA-
B*35 alleles) carrying KIR3DL1 or KIR3DS1 had at least one
HLA Bw4 allele (Figure S3), while HLA-C1 alleles were more often
absent in HLA-B*35 PTCs carrying KIR2DL2 or KIR2DL3 (Fig-
ure S3). Overall, KIR3DL1/Bw4 and KIR3DS1/Bw4 combinations
tended to be more frequently detected in PTCs than in individ-
uals from the IGAS cohort, and a higher frequency of the
KIR2DS5/C2 combination was also observed among PTCs (Fig-
ure 5C). In contrast, the KIR2DL1/C2 combination was less
frequent in PTCs carrying HLA-B*35 alleles. Overall, these re-
sults demonstrate that HLA-B*35 PTCs from the VISCONTI
study have KIR repertoires that influence interactions with the
HLA ligands abundantly present in these individuals.

Immunogenetic traits influence the phenotype of NK cells of PTCs

We investigated whether the HLA-KIR profile of PTCs might
translate into differences in the phenotypes of their NK cells.
We analyzed the NK cell phenotypes of 15 PTCs (when already

controlling infection) and six individuals receiving ART (Table S7) in similar age ranges (54 [39–67] vs. 54 [50–60], *p* = 0.87), and with similar viral load levels (5.7 [5.2–6.6] vs. 4.8 [4.1–5.8], *p* = 0.1) and nadir CD4+ T cell counts (419 [361–830] vs. 264 [19–561], *p* = 0.22) before ART. No differences were observed in the frequency of total NK cells (*p* = 0.4) or classically defined NK cell subsets (Figure S4). We combined all the data collected and used uniform manifold approximation and projection (UMAP) for dimension-reduced visualization to identify differently distributed NK cell subsets (Figures 6A and S4). UMAP revealed that a distinct cluster (cluster 1) was more abundant in PTCs than in people on ART (*p* = 0.029, Figure 6A). This cluster was CD16+CD56dim, suggestive of a cytotoxic subset, and it was characterized by high expression of KIR3DL1/S1 and CD57 and low expression of KIR2DL2/L3, KIR2DL1/S1, LILRB1(CD85J), and NKG2C (Figures 6A and S4).

We more thoroughly compared NK cell subsets using Boolean gating considering the markers with greater variability in our analyses (CD57, NKG2C, KIR3DL1/S1, KIR2LD2/S2/L3, KIR2DL1/S1, LILRB1) (Figures 6B and S5). Among the 64 phenotypes defined, four were more frequent in PTCs (b10 *p* = 0.029, b26 *p* = 0.029, b30 *p* = 0.042, b41 *p* = 0.029). The b10, b26, and b30 phenotypes were characterized by negative expression of NKG2C and positive expression of CD57 and KIR3DL1/S1, in agreement with the cluster identified through UMAP visualization. In contrast, the b16 phenotype, which was characterized by the expression of CD57 and LILRB1 in the absence of NKG2C and KIRs, was more frequent among PWH on ART than among PTCs (*p* = 0.047). Another phenotype, b39 (NKG2C+KIR2DL1/S1+LILRB1+), was also found more frequently among PWH on ART (Figure S5). We found that three phenotypes, all of which were characterized by combined expression of KIR2DL2/S2/L3 and LILRB1, were more frequent among HLA-B*35+ PTCs than among the other individuals analyzed (b9 *p* = 0.006, b41 *p* = 0.007, b44 *p* = 0.043) (Figure 6C). Taken together, these results confirmed the enrichment of distinct NK cell subsets among PTCs. At least some of these subsets appear to be influenced by the HLA-B*35 background in these individuals.

NK cells from PTCs have anti-HIV activity

We next analyzed the ex vivo capacity of NK cells from PTCs to inhibit HIV-1 infection of autologous CD4+ T cells. Overall, NK cells from PTCs showed a superior capacity to control HIV-1 infection than NK cells from people without HIV (*p* = 0.02) (Figure 6D). This difference appeared to be driven mostly by a greater capacity to inhibit infection by NK cells from HLA-B*35 PTCs (*p* = 0.01 vs. HIV negative). Although limited by the number

Figure 3. Alleles containing the Bw4 and C2 KIR ligands are overrepresented in PTCs with HLA-B*35

(A) Proportion of individuals carrying HLA-B alleles containing the Bw4 or Bw6 domain among PWH from the ANRS PRIMO cohort (N = 1,615) and PTCs from the ANRS VISCONTI study (N = 27) (top panels). The proportions of individuals carrying at least one HLA-B*35 allele or not (other) are depicted in the middle and bottom panels, respectively.

(B) Frequencies of individuals with no (0), one (1), or two or more (>1) HLA-A or HLA-B alleles containing the Bw4 epitope among PWH from the ANRS PRIMO cohort (N = 877) and PTCs from the ANRS VISCONTI study (N = 27), carrying HLA-B*35 alleles (B35) or not (other).

(C) Frequency of HLA-C alleles containing the C1 or C2 domain in the French reference population (n = 12,188 alleles), PWH from the ANRS PRIMO cohort (n = 3,212 alleles), and PTCs from the ANRS VISCONTI study (n = 44 alleles) (top panels). The frequencies of individuals carrying at least one HLA-B*35 allele or not are depicted in the middle and bottom panels, respectively. HLA-C information was not available for 5 PTCs not carrying HLA-B*35.

(A–C) Odds ratios and 95% confidence intervals are shown for PTCs relative to the PRIMO cohort.
<figure><img src="image_39.png" /></figure>

A

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B

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C

<figure><img src="image_53.png" /></figure>

(legend on next page)
of individuals analyzed, our results suggest that anti-HIV NK cell activity is increased in PTCs and may be favored by the presence of HLA-B*35 alleles.

DISCUSSION

Efforts to develop strategies for HIV-1 remission have been hampered by the lack of known mechanisms associated with posttreatment viral control. Here, we show that HLA-B*35 alleles in combination with other HLA-A, -B, and -C alleles that express Bw4 and C2 KIR ligands are remarkably frequent among PTCs from the VISCONTI study with prolonged HIV-1 remission. These PTCs also frequently have KIR Bx genotypes, which influence the phenotype of NK cells. Moreover, we identified a major histocompatibility complex (MHC) genotype (Bw4TTC2), congruent with the KIR education of NK cells, that was present in all HLA-B*35 PTCs from the VISCONTI study and associated with a high probability of sustained undetectable viremia after TI in early-treated PWH carrying HLA-B*35 alleles. These results support a role for NK cells in posttreatment HIV-1 control.

Since our observation of the unexpected abundance of HLA-
B*35 alleles among the initial 14 PTCs in the VISCONTI study,⁴
cases of PTCs carrying HLA-B*35 alleles have been
described.⁶,⁵⁷,⁵⁸ We further confirmed this finding in the
enlarged group of PTCs studied herein. Given the association
of these alleles with rapid progression to AIDS,¹⁸ a possible con-
founding factor is the potential earlier diagnosis and ART initia-
tion for PWH carrying HLA-B*35 alleles with symptomatic pri-
mary infection, a possibility that was confirmed in this study
among PRIMO participants diagnosed during the same period
than PTCs from VISCONTI. However, the impact of HLA-B*35 al-
leles extended beyond prompting slightly earlier ART initiation,
as we found a higher probability of undetectable viremia mainte-
nance after TI in PWH carrying HLA-B*35 alleles, compared with
other PWH with an equivalent short delay until ART initiation
(PRIMO subcohort 1) even if they carried favorable HLA-B*27/
57 alleles. Therefore, the impact of immunogenetic traits after
early ART discontinuation may differ from what is observed dur-
ing natural history.

Contrary to favorable HLA-B*27/57 alleles, HLA-B*35 alleles have been shown to restrict poor CD8+ T cell responses. It was therefore unclear how HLA-B*35 might contribute to post-treatment control, particularly because most early-treated HLA-B*35 PWH in the PRIMO subcohort 1 rapidly lost control after TI. HLA-B*35 PTCs from the VISCONTI study were characterized by an abundance of HLA molecules carrying Bw4 and C2

KIR ligands, with all being homozygous for a threonine at the –21 residue of the leader sequence of HLA-B alleles, which has been associated with the KIR education of NK cells. The resulting Bw4TTC2 genotype was found in all HLA-B*35 PTCs from VISCONTI. Moreover, the combination of HLA-B*35 alleles and the Bw4TTC2 genotype, but not the presence of HLA-B*35 alleles alone, was associated with a higher probability of maintaining control for at least 1 year after TI in our analysis of PRIMO subcohort 1.

Although each of the immunogenetic traits identified here (abundance of Bw4 and C2 alleles and –21TT homozygosity) may favor posttreatment viral control on its own, their combination may further enhance this outcome. Epidemiological studies have linked HIV-1 control with homozygosity for HLA-B alleles expressing Bw4 epitopes⁴² or the combination of Bw4 alleles with the presence of KIR3DS1/L1 alleles.³⁹,⁴⁰ We found that this combination was common among PTCs. Moreover, we found a higher frequency of NK cells expressing KIR3DS1/L1 among PTCs than among other PWH. These results extend the association of KIR3DS1/L1 and Bw4 with HIV-1 control to the context of post-ART interruption. Beyond this interaction, the protective effect of Bw4 HLA-B alleles may be reinforced by their linkage disequilibrium with the –21T residue in these alleles.⁴⁸,⁵⁹,⁶⁰ Similarly, the C2 ligand is rarely present in –21M haplotypes. In general, –21T/T individuals express high levels of Bw4, C1, and C2 KIR ligands and are characterized by the presence of a large population and high surface expression of NKG2A on NK cells.⁴⁸ Although the interaction between NKG2A and HLA-E provides an inhibitory signal, the presence of the –21T residue is associated with diminished expression of HLA-E. In contrast, Bw4 and C2 ligands can potentially interact with both activating and inhibitory KIRs.⁶¹ Moreover, T/T genotypes are associated with elevated frequencies of NK cells that coexpress a limited number of inhibitory KIRs in comparison with NK cells in M/M or M/T individuals.⁴⁸ In this context, another finding of our study was the absence of the common KIRAA1 genotype in the HLA-B*35 PTCs analyzed, which was not the case for other individuals with HLA-B*35 alleles. One consequence is that the KIR2DL1 gene was less frequently found among HLA-B*35 PTCs than among other HLA-B*35 individuals (six out of eight HLA-B*35 PTCs carried this gene, 75% vs. 98.8% in the reference cohort). Moreover, we detected increased frequencies of several NK cell subsets characterized by the expression of KIR2DL2/S2/L3 in the absence of KIR2DL1 among HLA-B*35 PTCs. Although the antibody used did not allow us to discriminate precisely, there was a trend

<caption>Figure 4. The presence of the Bw4TTC2 genotype in individuals with HLA-B*35 on ART since PHI is associated with a strong probability of maintaining durable undetectable viremia after ART interruption</caption>

(A) Frequency of individuals homozygous for HLA-B alleles containing a threonine at position –21 (–21TT), homozygous for HLA-B alleles containing a methionine at position –21 (–21MM), or heterozygous (–21MT) among PWH from the ANRS PRIMO cohort (N = 1,615 individuals) and PTCs from the ANRS VISCONTI study (N = 27 individuals) (top panels).

(B) Frequency of individuals carrying the MHC-related Bw4TTC2 genotype among PWH from the ANRS PRIMO cohort (N = 1,588 individuals) and PTCs from the ANRS VISCONTI study (N = 22 individuals) (top panels).

(A and B) The frequencies of individuals carrying at least one HLA-B*35 allele or not (other) are depicted in the middle and bottom panels, respectively. Odds ratios and 95% confidence intervals are shown for PTCs vs. PRIMO cohort.

(C) Probability for PWH enrolled in the ANRS PRIMO subcohort 1, who began ART at the time of PHI diagnosis and interrupted their treatment, to maintain a viral load below the test detection level based on the simultaneous presence of HLA-B*35 alleles and Bw4TTC2, one, or neither of these traits.
A

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B

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Odds ratio for carrying gene
relative to IGAS cohort

<figure><img src="image_62.png" /></figure>

Odds ratio for carrying gene
relative to IGAS cohort B35

<figure><img src="image_63.png" /></figure>

Odds ratio for carrying genotype
relative to IGAS cohort

C

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Odds ratio for combination relative to IGAS cohort

<figure><img src="image_68.png" /></figure>

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Odds ratio for combination relative to IGAS cohort

(legend on next page)
toward more frequent presence of KIR2DL2/S2 alleles and less frequent presence of KIR2DL3 alleles among HLA-B*35 PTCs, suggesting that the NK cells common among these individuals might predominantly express KIR2DL2/S2. Additionally, the expression of KIR2DL2 epistatically reduces the expression of KIR2DL1.⁶² Therefore, although HLA-B*35 PTCs present high C2 allele frequencies, which typically provide a strong inhibitory signal through KIR2DL1, the KIR haplotypes present in these individuals abrogate this effect. On the other hand, both KIR2DL2 and KIR2DL3 can provide an inhibitory signal that is weaker than the KIR2DL1-C2 pair upon interaction with C1 molecules⁶³; however, C1 molecules are rare among HLA-B*35 PTCs. Because KIR2DS2 is in linkage disequilibrium with KIR2DL2⁶³ and the antibody that we used can recognize both KIR2DS2 and KIR2DL2, we cannot exclude the possibility that the NK cell subsets frequently found among HLA-B*35 PTCs are characterized by expression of the activating receptor. Overall, our results suggest that the NK cell subsets frequently present among HLA-B*35 PTCs may favor activating signals during infection. The presence of activating KIRs has a beneficial effect on several viral infections, including HIV-1.³⁵,³⁹,⁶⁴ Similarly, reduced relapse of cytomegalovirus infection following transplantation has been observed in the presence of multiple activating KIRs or in the absence of inhibitory KIR-ligand pairs.⁶⁵⁻⁶⁷ This may explain why the Bw4TTC2 genotype was associated with a greater probability of achieving posttreatment control in the presence of HLA-B*35 alleles but not other alleles.

Other factors may also contribute to this association. For example, HLA-B*35-Px alleles strongly bind LILRB2 on DCs and limit their capacity to stimulate T cells.⁶⁸ This is also the case for other alleles (i.e., HLA-A*24, HLA-C*06), which we found to be frequently present among HLA-B*35 PTCs.⁶⁹ The presence of these alleles may therefore favor a more tolerogenic context that limits T cell activation and inflammation after TI. Although this may be deleterious during acute infection, such a “silent” environment may allow maintenance of the repression of the latent viral reservoir after the interruption of promptly initiated ART.¹² NK cells may be optimal means for maintaining silent control after TI in this context due to their capacity to react to expression of stress peptides on infected cells⁷⁰ before viral antigen production.

Overall, our results argue that posttreatment control, at least among HLA-B*35 PTCs, is associated with the selection of HLA and KIR genotypes that favor the antiviral activity of NK cells, although the precise mechanisms remain to be determined. The role of NK cells during HIV-1 infection has been extensively studied,³²,⁷¹,⁷² and NK cells have been associated with protection from HIV-1 acquisition⁷³,⁷⁴ or AIDS³⁹,⁷⁵ or with control of viremia.⁷¹ Recent reports also suggest a potential

role for NK cells in posttreatment control.⁷⁶,⁷⁷ NK cells are able to counteract HIV-1 *in vitro* through different effector functions, including the release of soluble antiviral factors and direct or antibody-dependent cytotoxic mechanisms. NK cells from T/T donors have superior capacity *in vitro* to inhibit HIV-1 infection of autologous CD4⁺ T cells.⁷⁸,⁷⁹ A previous study revealed that KIR2DL2+ NK cells, such as those we found in HLA-B*35 PTCs, are activated and exert enhanced antiviral activities in response to HIV-infected CD4⁺ T cells and can select for viral escape variants *in vivo*.⁸⁰ NK cells expressing activating KIRs are expanded during acute infection, particularly in PWH who carry the KIR-specific ligands.⁸¹ Early treatment might “freeze” the status of these expanded cells, which later might be better prepared to counteract viral rebound after TI. In contrast, continuous exposure to the virus leads to expansion of cells carrying inhibitory receptors, reducing their capacity to control HIV.³⁵,⁷²,⁸¹ Recently, a higher frequency of an NK cell subset with “memory-like” characteristics has been reported in PWH undergoing PHI.⁸² These NK cells possess increased antiviral potential when reencountering viral antigens or receiving cytokine stimulation. Whether the expansion of NK cells with trained immunity might have been favored by early ART in PTCs deserves further exploration. It is also unknown whether the combination of HLA-B*35 alleles with the Bw4TTC2 genotype may favor posttreatment control when ART is initiated during the chronic phase of infection.

Although our results revealed a stronger association with post-treatment control in the presence of HLA-B*35, KIR HLA interactions may also contribute to posttreatment control in other PTCs. The KIRAA1 genotype tended to be rare, even among PTCs not carrying HLA-B*35, who often carried multiple HLA alleles containing Bw4 epitopes and NK cells expressing KIR3DL1/S1. A deeper study of KIR alleles and copy number variation may provide valuable information concerning the role of NK cells in these PTCs. Additionally, it is likely that multiple mechanisms contribute to posttreatment control. Early treatment initiation may favor the optimal development of an adaptive response against HIV, favoring a more efficient secondary-like response against the virus after ART interruption in some PTCs, as has been recently suggested by others and us.¹¹,⁷⁷,⁸³

Here, we provide insight into durable HIV-1 remission. The identification of an MHC-related fingerprint potentially associated with posttreatment HIV-1 control has several implications. The contribution of immunogenetic traits should be carefully considered when interpreting results from HIV cure trials with analytical TI, particularly because beneficial MHC alleles might differ from those classically associated with natural control. Our results also identify NK cells as potentially important contributors to durable HIV remission. Therapies based on NK cells are

<caption>**Figure 5.** KIR Bx genotypes are overrepresented among PTCs</caption>

(A) Frequency of individuals carrying KIR AA genotypes (two KIR A haplotypes) or KIR Bx genotypes (at least one KIR B haplotype) among participants in a cohort of healthy individuals of European origin from the International Genetics of Ankylosing Spondylitis (IGAS) consortium (IGAS cohort) (N = 14,844 individuals)⁵⁵ and PTCs from the ANRS VISCONTI study (N = 19 individuals) (top panels). The frequencies of individuals carrying at least one HLA-B*35 allele or not (other) are depicted in the middle and bottom panels, respectively.

(B and C) Comparison of the frequencies of the presence of KIR genes (B) or the combined presence of KIR genes with cognate HLA-related ligands (C) among PTCs (all or carrying HLA-B*35) relative to IGAS cohort participants.

(A–C) Odds ratios and 95% confidence intervals are shown in PTCs relative to IGAS cohort participants. *p* represents values corrected for multiple comparisons.
A

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KIR3DL1/S1

<figure><img src="image_75.png" /></figure>

NKG2C

<figure><img src="image_76.png" /></figure>

B

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<figure><img src="image_83.png" /></figure>

D

<figure><img src="image_84.png" /></figure>

(legend on next page)
increasingly being explored as treatments for cancer.⁸⁴,⁸⁵ Such therapies are based on the activation of NK cells with small molecules, blockade of inhibitory receptors, or adoptive transfer of allogenic or autologous NK cells after (1) expansion of particular subsets, (2) cell reprogramming, or (3) genetic modification to induce the expression of activating receptors or chimeric antigen receptors. The results of our study encourage therapies harnessing NK cells in HIV cure strategies, and some of these approaches (such as the use of TLR7 and TLR9 agonists, interferon [IFN]α, interleukin [IL]-15, or IL-21) are already being explored in HIV remission clinical studies or SIV preclinical models.⁸⁶⁻⁸⁸

## Limitations of the study

The low number of PTCs that we could analyze led to a high level of uncertainty for some analyses. In addition, we compared the KIR genotype to available data from the IGAS cohort and we cannot exclude the possibility that some of the differences observed between the PTCs and this cohort may have been driven by factors such as HIV infection and ethnic background. However, HLA-B*35 is found mainly among people of European background and KIR AA1 (infrequent among PTCs) is the most abundant genotype in populations of African and European origin, in both people with and without HIV-1.⁸⁹,⁹⁰ Finally, the analyses of NK cells from people with HIV on ART allowed us to compare the cells in a situation of durable posttreatment vs. ART mediated viral control. However, we could not compare the NK cell phenotype and antiviral activity to those of other people with similar HLA and/or KIR backgrounds or people who did not control infection after ART interruption. Therefore, the specific traits and activities of NK cells that might be associated with posttreatment control and how they are determined by NK cell education or affected by early ART initiation remain unclear. Moreover, it is unknown whether NK cells may exert their potential protective effect by shaping the viral reservoir and other immune responses early after infection or by facilitating posttreatment control after ART interruption. Future prospective studies in people with different immunogenetic backgrounds and monitoring of NK cells after PHI, during ART and after ART interruption, are needed to address these questions and better understand the implications of NK cells on posttreatment control.

## RESOURCE AVAILABILITY

### Lead contact

Further information and requests for resources and reagents should be directed to the lead contact, Asier Sáez-Cirión (asier.saez-cirion@pasteur.fr).

### Materials availability

Requests for biological samples will be evaluated by the corresponding author and scientific committee of the ANRS VISCONTI study and ANRS PRIMO cohort and will be fulfilled based on availability and upon the establishment of a material transfer agreement subjected to ANRS policy.

### Data and code availability

Three previously reported datasets were used as a reference in this study. HICs were participants in the ANRS CO21 CODEX cohort and naive to antiretroviral treatment, with the last five consecutive plasma HIV RNA values being below 400 copies/mL; the HLA for the group studied herein (N = 45) was reported previously.¹⁵ The HLA allele distribution in a group of 6,094 French volunteer bone marrow donors is available through www.allelefrequencies.net (population ID = 2429).⁴⁴ For analyses of KIR genotype and KIR HLA epistasis, we used data generated by Hanson and colleagues based on a cohort of 12,214 healthy individuals of European origin from the IGAS consortium.⁵³ All the data generated during this study are included in this published article (and its supplementary information files). External requests for additional data will be evaluated by the corresponding author and scientific committee of the ANRS VISCONTI study and ANRS PRIMO cohort and may be subjected to ANRS policy.

This paper does not report original code. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

## CONSORTIA

ANRS VISCONTI study: Valérie Artizzu, Firouzé Bani-Sadr, Frédéric Bastides, Anne-Cécile Beaudrey, Jean-Luc Berger, Louis Bernard, Philippe Blanche, Olivier Bourgault, Guillaume Brouillet, Pascal Chavanet, Anne Conrad, Pauline Cornavin, Laurent Cotte, Barbara De Dieuleveult, Yasmine Debab, Jeannine Delgado Bertaut, Marie-Josée Dulucq, Jane Foucoin, Cindy Godard, Matthieu Godinot, Sandrine Gohier, Emilie Goncalves, Maxime Hentzien, Gilles Hittinger, Laurent Hocqueloux, Thomas Huleux, Christine Jacomet, Zélie Julia, Corinne Jung, Marina Karmochkine, Isabelle Kmiec, Véronique Lambry, Sophie Le Nagat, Franco Maggiolo, Djamila Makhloufi, Sophie Matheron, Mohamed Meghadecha, Agnès Meybeck, Patrick Miailhes, Jean-Michel Molina, Safa Nasri, Stanislas Ogoudjbi, Sophie Pailhes, Christia Palacios, Jean Paul Viard, Gilles Pialoux, Gilles Pichancourt, Marie-Pierre Piétri, Lionel Piroth, Diane Ponscarme, Thierry Prazuck, Jürgen Rockstroh, Dominique Salmon-Ceron, Martin Siguier, Olivier Taulera, David Théron, Laurence Weiss, Yazdan Yazdanpanah. ANRS PRIMO cohort: Sylvie Abel, Sophie Abgrall, Pierre Abgueguen, Bruno Abraham, Anne Adda Lievin, Nouara Agher, Emmanuelle Aissi, Faïza Ajana, Isabelle Alcaraz, Clotilde Allavena, Thierry Allegre, Christophe Allienne, Muriel Alvarez, Naouel Amirat, Marc Antoine Valentin, Odile Antoniotti,

<caption>**Figure 6.** PTCs have NK cell phenotypes distinct from those of PWH on ART</caption>

(A) UMAP plot of NK cell phenotypes from concatenated analysis of NK cells from PTCs (N = 15) and individuals on ART (N = 6). UMAP visualization allowed us to identify one cluster of cells whose frequency differed between PTCs and people on ART (center panel). The fluorescence intensity of various markers characterizing the cluster is shown.
(B) Frequencies (median and IQR) of NK cells with 64 phenotypes defined by Boolean gating (CD57, NKG2C, KIR3DL1/S1, KIR2DL2/L3, KIR2DL1/S1, and LILRB1) in PTCs (dark cyan symbols) and people on ART (orange symbols). Individual frequencies are shown for NK cells with b10, b26, and b30 phenotypes, which were more frequently found among PTCs.
(C) Individual frequencies of NK cells with b9, b41, and b44 phenotypes were more frequently found among PTCs with HLA-B*35 alleles. Differences between groups were analyzed using the Mann-Whitney test and were not adjusted for multiple comparisons.
(D) Capacity of NK cells from PTCs (N = 17) and HIV-negative donors from Établissement Français du Sang (EFS) (N = 19) to inhibit HIV-1 infection in a viral suppression assay (ratio of NK:CD4 1:1). Individual levels, medians, and IQRs are depicted. The filled green symbols represent PTCs with HLA-B*35 alleles (N = 6).
Sylvie Aprelon, Christian Aquilina, Cédric Arvieux, Alexandre Aslan, Assi Assi, Nadine Atoui, Hugues Aumaitre, Antoine Bach- elard, Véronique Baclet, Vincent Baillat, Stéphanie Balausine, Florence Balsarin, Jonas Bantsimba, Claudine Barbuat, Frédéric Bastides, Anne-Sophie Batala, Dominique Batisse, Joanie Ba- vay, Christine Bazin, Abdelmoula Becharef, Charles Beck, Agathe Becker, Coralie Becquart, Linda Belarbi, Saadia Ben Ab- dallah, Raida Ben Rayana, Dalila Beniken, Samir Benkouiten, Meryem Benomar, Julie Berge, Jean-Luc Berger, Noëlle Ber- nard, Valérie Berrebi, Laura Bertin, Michel Besnier, Claude Beus- cart, Sybille Bevilacqua, Noemie Biezunski, Eric Billaud, Arnaud Blanc, Martine Bloch, Laurent Blum, Loïc Bodard, Diane Bollens, Manuela Bonmarchand, Fabrice Bonnet, Bénédicte Bonnet, Eli- sabeth Botelho-Nevers, Julie Bottero, Olivier Bouchaud, Celia Boucheraine, Sabelline Bouchez, Celia Bouhnik, Marie-Pierre Bouillon, Catherine Bourdeaux, Ghania Bouteria, David Bou- toille, Laurence Boyer, Sophie Breaud, Sylvie Bregigeon, Guil- laume Brouillet, Cecile Brunet, Marielle Buisson, Martin Buisson, Rodolphe Buzele, André Cabie, Ornella Cabras, Fabienne Caby, Isabelle Cahitte, Johann Cailhol, Sabrina Caldato, Pauline Campa, Pauline Caraux Paz, Claudia Carvalho, Philippe Castel, Guylaine Castor Alexandre, Morane Cavellec, Charles Caza- nave, Benoit Cazenave, Christophe Cerland, Amélie Chabrol, Eka Chakvetadze, Lynda Chalal, Hélène Champagne, Jean- Marc Chapplain, Carole Charles, Julie Chas, Sami Chaussee, Soumia Chenakeb, Christine Cheneau, Antoine Cheret, Pierre Chiarello, Catherine Chirouze, François Clavel, Nathalie Colin De Verdiere, Lio Collias, Guillaume Conort, François Cordonnier, Pauline Cornavin, Agnés Cros, Eric Cua, Lise Cuzin, Vincent Da- neluzzi, Corinne Daniel, Jean Daniel Lelievre, Iuliana Darasteanu, Frédéric Dauchy, Perrine Dayle, Arnaud De La Blanchardiere, Nathalie De Castro, Pierre De Truchis, Alicia De Castro, Yasmine Debab, Alexa Debard, Nathalie Decaux, Barbara De-Dieuleveut, Isabelle Delacroix, Jeannine Delgado, Sophie Delllion, Pierre De- lobel, Jean Derouineau, Georges Diab, Kevin Diallo, Myriam Die- mer, Denis Dondia, Régine Donesco, Anabèle Dos Santos, Martine Dubois, Pierre Duffau, Marie-Josée Dulucq, Gilles Du- mondin, Brigitte Dunais, Régine Dupin, Michel Dupont, Matthieu Dupont, Martin Duracinsky, Jacques Durant, Christine Duronea, Hervé Dutronc, Claudine Duvivier, Orélia Eden, Brigitte Elharrar, Murielle Eliazevitch, Jean-Luc Esnault, Jean-Marie Estavoyer, Nicolas Ettahar, Amina Fadli, Olivia Faucher, Jean-François Faucher, Christine Faudon, Isabelle Faure, Samuel Ferret, Mila- gros Ferreyra, Pascale Fialaire, Fabien Fily, Patricia Fischer, Adeline Foltzer, Laurent Fonquernie, Clotilde Fontier, Alais Fre- lat, Anne Fresard, Eric Froguel, Valérie Gaborieau, Amandine Gagneux-Brunon, Valérie Galvan, Daniel Garipuy, Valérie Gar- rait, Barbara Gasse, Caroline Gatey, Catherine Gaud, Sandrine Gazaignes, Brigitte Gbaguidi, Loïc Geoffray, Claire Genet, Lau- rence Gerard, Juliette Gerbe, Jade Ghosn, Jacques Gilquin, Véronique Godard, Claire Godin Collet, Sandrine Gohier, Emilie Goncalves, Cécile Goujard, Jeanne Goupil De Bouille, Florence Gourdon, Marie Gousseff, Gersendé Grain, Guillaume Gras, Alix Greder Belan, Loïc Guillevin, Thomas Guimard, Blanka Ha- dacek, Jean-Michel Halna, Latifa Hamour, Paul Henri Consigny, Marie-Cécile Herve, Mojgan Hessamfar, Emmanuel Hiraux, Gilles Hittinger, Laurent Hocqueloux, Thomas Huleux, Cylia Im- ekhlaf, Flore Isard, Françoise Itoua, Alena Ivanova, Christine Ja-

comet, Stéphane Jaureguiberry, Didier Jayle, François Jean- blanc, Noëlle Jeunet, Marina Karmochine, Mohamed Kassim Youssouf, Christine Katlama, Myriam Kirstetter, Isabelle Kmiec, Joseph Koffi, Pascale Kousignan, Jessica Krause, Marion La- casse, Karine Lacombe, Matthieu Lafaurie, Erik Lafon, Sandra Lagarrigue, Laetitia Laine, Julie Lamarque, Isabelle Lamaury, Véronique Lambry, Fanny Lanternier, Hélène Laroche, Anne- Sophie Lascaux, Caroline Lascoux-Combe, First Last, Odile Launay, Manuela Le Cam, Pascal Le Bret, Stéphanie Le Grand, Sophie Leantez-Nainville, Catherine Lechiche, Catherine Le- clerc, Benedicte Lefebvre, Agnès Lefort, Adrien Lemaignan, Vin- cent Lemoing, Ludovic Lenclume, Anne Leplatois, Annie Lep- retre, Nathalie Lerolle, Helene Leroy, Didier Leureillard, Yves Levy, Marie Lise Lecapitaine, Jean-Michel Livrozet, Carole Loui- sin, Jeremy Lourenco, Marie-Laure Lucas, Joelle Lux, Odile Luycx, Zoha Maakaroun, Moise Machado, Didier Magba, Rezak Mahrez, Sophie Mahy, Catherine Majerholc, Djiamila Makhloufi, Alain Makinson, Véronique Manceron, Jean Marc Jacquet, Jean Marie Chennebault, Cédric Martell, Benoit Martha, Martin Martinot, Patrice Massip, Jean-Marc Mauboussin, Thierry May, Julien Mazet, Mouniya Mebarki, Line Meddeb, Marie Medus, Céline Melounou, Corinne Merle, Agnès Meybeck, Flory Mfutila, Kaykay, Patrick Miailhes, Christophe Michau, Catherine Michel, Christian Michelet, Mahsa Mohseni Zadeh, Jean-Michel Molina, Bénédicte Montoya, Philippe Moreau, Pascale Morineau-Le Houssine, Philippe Morlat, Emmanuel Mortier, Anaïs Mothes, Mourad Mouhadjer, Anne-Lise Munier, Alissa Naqvi, Safa Nasri, Didier Neau, Ségolène Neuville, Valérie Nivet, Martine Obadia, Stanislas Ogoudjobi, Laurence Onnis, Zineb Ouazene, François Paccalin, Anne Pachart, Christia Palacios, François Parcelier, Er- nesto Paredes Manyari, Sylvie Parlier, Maria Partisani, Solène Patra-Delon, Juliette Pavie, Pauline Penot, Delphine Peretti, Phil- ippe Perre, Pauline Perreau, Véronique Perrone, Jean-Michel Peter, Patrick Philibert, Bao Phung, Gilles Pialoux, Gilles Pichan- court, François Pichon, Sandrine Pierre-Francois, Marie-Pierre Pietri, Laetitia Pinheiro, Claire Pintado, Adriana Pinto, Lionel Pir- oth, Thierry Pistone, Sandrine Poirier, Diane Ponscarme, Lydie Porte, Nathalie Pouhaut, Christian Pradier, Thierry Prazuck, François Prevoteau Du Clary, Michèle Priester, Christina Pso- mas, Yann Quertainmont, Denis Quinsat, Valérie Rabier, Emilie Racamier, François Raffi, Agathe Rami, Isabelle Ravaux, Sami Rehaiem, Véronique Reliquet, Matthieu Revest, David Rey, Jac-ques Reynes, Carole Ricaud, Anne Ricci, Laurent Richier, Anne- Suzel Ritleng, Olivier Robineau, Roland Rodet, Véronique Ronat, Eric Rosenthal, Isabelle Rouanet, Hicham Roukas, Elisabeth Rouveix, Willy Rozenbaum, Mathieu Saada, Ketty Samar, Sarah Sanit Marc, Fabienne Sauser, Carmele Sautron, Jean-Luc Schmit, Elodie Schneider, Luminita Schneider, Sophie Seang, Olivier Segeral, Jean-Christophe Seghezzi, Valérie Seguin, Benjamin Silbermann, Anne Simon, Phlippe Simon, Anne- Marie Simonpoli, Mathilde Six, Thibaut Sixt, Laurence Slama, Alain Sobel, Anne Sophie Lascaux, Albane Soria, Albert Sotto, Faouzi Souala, Hind Stitou, Tassadit Tahi, Sylvie Tassi, Pierre Kattevin, Olivier Taulera, Serge Tempesta, Audrey Therby, David Theron, Mathilde Thierry, Nugyen Thu-Huyn, Fatima Touam, Muriel Tourneur, Marie-Pierre Treilhou, Roland Tubiana, Isabelle Turpault, Agnès Uludag, Michel Valette, Nadia Valin, Dorothée Vallois, Marie-Anne Vandenhende, Marc-Olivier Vareil, Renaud
Verdon, Jean-François Viallard, Jean-Paul Viard, Nathalie Viget, Antoine Villadero, Jocelyne Vivent, Jean-Luc Vourch, Guillaume Wartel, Laurence Weiss, Yves Welker, Charlotte Wemmert, Gaëtane Wirth, Yazdan Yazdanpanah, Olivier Zak Dit Zbar, Ai-Feng Zeng, Fatima Zohra Daikh, David Zucman.

## ACKNOWLEDGMENTS

The authors wish to thank the study participants for their generous contribution to the research. The authors wish to thank Pierre Versmisse and Marine Fillion for technical support. The authors thank members of ANRS RHIVIERA consortium and ERASE Collaboratory for helpful discussion. This study was conducted with funds from the ANRS-MIE and NIH through P01 grants P01AI131365 and UM1AI64562. A. Chapel and A.M. received salary support from the ANRS-MIE. The VISCONTI study and the CO6 PRIMO and CO21 CODEX cohorts are sponsored and funded by the ANRS-MIE.

## AUTHOR CONTRIBUTIONS

A. Chapel, V.M., K.A., C.D., C.L., A.M., E.G., and V.A.-F. performed the experiments. A.E. D.S.-A., A. Chapel, V.M., K.A., V.A.-F., S.C.-Z., L.M., and A.S.-C. analyzed the data. A.E., L.M., and A.S.-C. performed statistical analyses. S.O., F.B., O.L., A. Chéret, C.G., and L.H. provided key reagents or contributed to the inclusion of the study participants and obtained and validated the clinical information. D.S.-A., M.M.-T., O.L., C.R., L.H., L.M., and A.S.-C. contributed to the conception and discussion of the study. A.S.-C. designed the study. L.M. and A.S.-C. supervised the study and had unrestricted access to all data. A.S.-C. drafted the article. All authors critically reviewed the manuscript and approved the final article and take responsibility for its content.

## DECLARATION OF INTERESTS

The authors declare that they have no competing interests.

## STAR★METHODS

Detailed methods are provided in the online version of this paper and include the following:

* KEY RESOURCES TABLE

* EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

* METHOD DETAILS

* Genomic DNA extraction and HLA typing

* KIR genotyping by multiplex PCR-SSP (sequence-specific primer)

* Cell staining and flow cytometry acquisition

* Capacity of NK cells to suppress HIV infection of autologous CD4⁺ T cells

* QUANTIFICATION AND STATISTICAL ANALYSIS

## SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.medj.2025.100670.

Received: August 9, 2023

Revised: December 27, 2024

Accepted: March 19, 2025

Published: April 28, 2025

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## STAR★METHODS

### KEY RESOURCES TABLE

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3"><strong>Antibodies</strong></td></tr><tr><td>KIR2DL2/L3/S2- BUV395 (clone CH-L)</td><td>BD Biosciences</td><td>Cat#743456 RRID: AB_2741521</td></tr><tr><td>KIR2DL1/S1/S3/S5- BUV496 (clone HP-MA4)</td><td>BD Biosciences</td><td>Cat#752510 RRID: AB_2917501</td></tr><tr><td>CD25<sup>-</sup> BUV661 (clone M-A251)</td><td>BD Biosciences</td><td>Cat#741608 RRID: AB_2871016</td></tr><tr><td>CD56<sup>-</sup> BUV737 (clone NCAM16.2)</td><td>BD Biosciences</td><td>Cat#612767 RRID: AB_2860005</td></tr><tr><td>CD14<sup>-</sup> V450 (clone M5E2)</td><td>BD Biosciences</td><td>Cat#561390 RRID: AB_10611582</td></tr><tr><td>CD19<sup>-</sup> V450 (clone HIB19)</td><td>BD Biosciences</td><td>Cat#560353 RRID: AB_1645564</td></tr><tr><td>NKG2A- BV605 (clone 131411)</td><td>BD Biosciences</td><td>Cat#747921 RRID: AB_2872382</td></tr><tr><td>CD69<sup>-</sup> BV650 (clone FN50)</td><td>BD Biosciences</td><td>Cat#563835 RRID: AB_2738442</td></tr><tr><td>DNAM-1 - BV711 (clone DX11)</td><td>BD Biosciences</td><td>Cat#564796 RRID: AB_2738956</td></tr><tr><td>NKG2C- BV786 (clone 134591)</td><td>BD Biosciences</td><td>Cat#748170 RRID: AB_2872631</td></tr><tr><td>CD57<sup>-</sup> FITC (clone NK-1)</td><td>BD Biosciences</td><td>Cat#555619 RRID: AB_395986</td></tr><tr><td>CD85j/LILRB1- PE (clone REA998)</td><td>Miltenyi</td><td>Cat#130-116-615 RRID: AB_2727624</td></tr><tr><td>NKG2D- PE-Vio 615 (clone REA1228)</td><td>Miltenyi</td><td>Cat#130-124-344 RRID: AB_2811657</td></tr><tr><td>KIR3DL1/S1- PerCP-Vio 700 (clone REA168)</td><td>Miltenyi</td><td>Cat#130-123-910 RRID: AB_2857645</td></tr><tr><td>NKp46- PE Cy7 (clone 9E2)</td><td>BD Biosciences</td><td>Cat#562101 RRID: AB_10894195</td></tr><tr><td>NKp30- APC (clone REA823)</td><td>Miltenyi</td><td>Cat#130-112-431 RRID: AB_2657621</td></tr><tr><td>CD3<sup>-</sup> AF700 (clone UCHT1)</td><td>BD Biosciences</td><td>Cat#557943 RRID: AB_396952</td></tr><tr><td>CD16<sup>-</sup> APC Cy7 (clone 3G8)</td><td>BD Biosciences</td><td>Cat#557758 RRID: AB_396864</td></tr><tr><td colspan="3"><strong>Bacterial and virus strains</strong></td></tr><tr><td>HIV-1 BaL</td><td>NIH AIDS reagent program</td><td>Cat#510</td></tr><tr><td colspan="3"><strong>Biological samples</strong></td></tr><tr><td>Cryopreserved PBMCs from VISCONTI and PRIMO cohorts</td><td>ANRS</td><td>N/A</td></tr><tr><td>Blood samples from VISCONTI cohort</td><td>ANRS</td><td>N/A</td></tr><tr><td>Blood samples from blood donors</td><td>EFS</td><td>N/A</td></tr><tr><td colspan="3"><strong>Chemicals, peptides, and recombinant proteins</strong></td></tr><tr><td>LIVE/DEAD® Fixable Aqua Dead Cell Stain Kit, for 405 nm excitation</td><td>Life technologies</td><td>Cat# L34957</td></tr><tr><td>RPMI 1640 GlutaMAX</td><td>Life Technologies</td><td>Cat# 61870-010</td></tr><tr><td>Fetal calf serum</td><td>Eurobio</td><td>Cat# CVFSVF00-01</td></tr><tr><td>Lymphocyte Separation Medium</td><td>Lonza Bioscience</td><td>Cat# 17-829E</td></tr><tr><td>Penicillin-Streptomycin</td><td>Gibco</td><td>Cat# 15140122</td></tr><tr><td>Interleukine 15, IL-15</td><td>Miltenyi Biotec</td><td>Cat# 130-095-760</td></tr><tr><td>Interleukine 2, IL-2</td><td>Miltenyi Biotec</td><td>Cat# 130-097-745</td></tr><tr><td>PHA-L</td><td>Sigma</td><td>Cat# L4144</td></tr><tr><td>Platinum Taq polymerase</td><td>Invitrogen</td><td>Cat#15966005</td></tr><tr><td>10xPCR buffer</td><td>Roche</td><td>Cat#11699105001</td></tr><tr><td colspan="3"><strong>Critical commercial assays</strong></td></tr><tr><td>DNAeasy Blood and Tissue kit</td><td>Qiagen</td><td>N/A</td></tr><tr><td>MiSeq Reagent Kits v2</td><td>Illumina</td><td>Cat# MS-102-2002</td></tr><tr><td>EasySep Human CD4 Positive Selection Kit II</td><td>Stemcell technologies</td><td>Cat# 17852</td></tr><tr><td>EasySep Human NK Enrichment Kit</td><td>Stemcell technologies</td><td>Cat# 19055</td></tr><tr><td>HIV-1 p24 ELISA kit</td><td>XpressBio</td><td>Cat# XB-1000</td></tr></tbody></table>

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Continued

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3"><strong>Deposited data</strong></td></tr><tr><td>HLA allele distribution in French bone marrow donors (population id = 2429)</td><td>Allele Frequency Net Database</td><td>http://www.allelefrequencies.net/hla6006a.asp?hla_population=2429</td></tr><tr><td>KIR and HLA from healthy individuals from the International Genetics of Ankylosing Spondylitis (IGAS) consortium</td><td>Hanson et al., 2020<sup>53</sup></td><td>https://doi.org/10.1371/journal.pgen.1008906.s005</td></tr><tr><td colspan="3"><strong>Oligonucleotides</strong></td></tr><tr><td>Primers for KIR genotyping, full description in Table S8</td><td>Kulkarni et al., 2009<sup>91</sup></td><td>Custom</td></tr><tr><td colspan="3"><strong>Software and algorithms</strong></td></tr><tr><td>NGSengine, IMGT/HLA database version 3.37.0</td><td>GenDx</td><td>https://www.gendx.com/product_line/ngsengine/</td></tr><tr><td>GenSys V1.4.1.0</td><td>Syngene</td><td>https://www.syngene.com/software/</td></tr><tr><td>FlowJo cytometry analysis software v10.8.1 and v10.9</td><td>BD Biosciences</td><td>https://www.flowjo.com/</td></tr><tr><td>Prism v9</td><td>GraphPad</td><td>https://www.graphpad.com/</td></tr><tr><td colspan="3"><strong>Other</strong></td></tr><tr><td>Nanodrop 2000c</td><td>Thermo Scientific</td><td>N/A</td></tr><tr><td>MiSeq instrument</td><td>Illumina</td><td>N/A</td></tr><tr><td>G:BOX Chemi</td><td>Syngene</td><td>N/A</td></tr><tr><td>LSRFortessa X20 flow cytometer</td><td>BD Biosciences</td><td>N/A</td></tr><tr><td>RoboSep</td><td>Stemcell technologies</td><td>N/A</td></tr></tbody></table>

EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

Posttreatment controllers (PTC) (N = 27) were recruited among PWH followed-up in French hospitals in the context of the ANRS Viro-Immunological Sustained CONTrol after Treatment Interruption (VISCONTI) study and the ANRS CO21 CODEX cohort. Some of the PTCs included in the present study have been previously described,³⁻⁵ and seven had been previously included in the ANRS CO6 PRIMO cohort (see the Results section and Figure S6). PTCs were defined as PWH who had a viral load >2000 RNA copies/ml at ART initiation, were on ART for at least 12 months with suppressed viremia, and maintained a viral load below 400 RNA copies/ml for more than 1 year after treatment discontinuation, with at least two viral load determinations during this period. The HIV-1 status and main clinical characteristics of the participants are summarized in Table S1.

HLA-typed participants in the ANRS CO6 PRIMO cohort (N = 1615) were monitored since PHI, which was determined by one of the following criteria: (1) incomplete western blotting (i.e., absence of anti-p68 and/or anti-p34); (2) detectable p24 antigenemia or detectable plasma viral load (VL) associated with either a negative or weakly reactive enzyme-linked immunosorbent assay (ELISA) or a negative western blot; or (3) an interval <3 months between a negative and positive ELISA. The participants in the cohort were ART naive at enrollment. The delay to treatment initiation was calculated accounting for the estimated date of infection, as described previously.⁹² The decision to initiate ART was made by the physicians while considering the available guidelines. No specific guidelines were available for treatment initiation during PHI before 2002 (N = 339 participants were included during this period). Between 2002 and 2010, ART initiation was based on the presence of symptoms or CD4⁺ T-cell counts, with an increasing cutoff of 200–500 cells/µl in 2010. ART initiation has been recommended in French guidelines for all PHI diagnosed since 2013, regardless of the CD4⁺ T-cell count.⁹³ Different subsets of participants in the PRIMO cohort were studied based on the inclusion period, delay to ART initiation, or occurrence of ART discontinuation during follow-up (Figure S6). The specific characteristics of these groups are provided in Table 1, Figure 2 and Table S3. No differences in HLA allele distribution were found between these subsets and the complete PRIMO cohort. CD4⁺ and CD8⁺ T-cell counts and plasma VL were measured at months 1, 3, and 6 and every 6 months thereafter for all participants and were used to establish characteristics at PHI before TI and to determine the probability of maintaining viral control after TI in retrospective analyses.

All participants provided written informed consent. The ANRS VISCONTI study and the ANRS CO6 PRIMO (NCT03148964) and CO21 CODEX (NCT01520844) cohorts received approval from the French National Agency of Medicine and Health Products Safety (ANSM) and ethical committees (Comité de Protection des Personnes, CPP) Tours-region Centre-Ouest 1, Ile-de-France III or VII. Blood samples from HIV-negative donors were obtained from the French blood bank (Établissement Français du Sang, EFS) in the context of a collaboration with the Institut Pasteur.
# METHOD DETAILS

## Genomic DNA extraction and HLA typing

Genomic DNA was extracted from cryopreserved peripheral blood mononuclear cells (PBMCs) or CD4⁺ T cells using the DNeasy Blood and Tissue kit (Qiagen) following the manufacturer's protocol, and the concentration was determined using a NanoDrop 2000c (Thermo Scientific). High-resolution HLA typing was performed by NGS using the NGSgo Workflow from GenDx (www.gendx.com) for HLA amplification and library preparation, with subsequent sequencing using the MiSeq instrument from Illumina (www.illumina.com) and MiSeq V2 reagents with application of paired-end sequencing (2 × 151 bp). The final HLA allele calling was performed using NGSengine software from GenDx (www.gendx.com) based on the IMGT/HLA database version 3.37.0.

## KIR genotyping by multiplex PCR-SSP (sequence-specific primer)

KIR genotyping was performed on samples from 19 posttreatment controllers using the PCR-SSP method described by Kulkarni et al.⁹¹ Each DNA sample was amplified with 12 separate mixes of KIR genes (Table S8), allowing typing of the most common alleles of 16 human KIR genes. The DRB1 gene fragment was used as a positive internal control. PCR was performed with a 60-µL mixture containing 150 ng DNA (variable volume), 7.5 µL 10x PCR buffer, 2.25 µL MgCl2, 0.6 µL dNTPs, 0.375 µL Platinum Taq polymerase (Thermo Fisher) and nuclease-free water. The amplification was carried out as follows: 3 min at 94°C; 5 cycles of 15 s at 94°C, 15 s at 65°C and 30 s at 72°C; 21 cycles of 15 s at 94°C, 15 s at 60°C, and 30 s at 72°C; 4 cycles of 15 s at 94°C, 1 min at 55°C, and 2 min at 72°C; and a final 7-min extension step at 72°C. The PCR products were separated on a 3% agarose gel and visualized under UV light at 312 nm using the G:BOX Chemi apparatus and GeneSys V1.4.1.0 acquisition software (Syngene).

## Cell staining and flow cytometry acquisition

Frozen PBMCs were thawed and incubated overnight in RPMI supplemented with 10% FBS 1% Pen/strep and IL15 (0.1 ng/mL, Miltenyi Biotec). The cells were stained with a live/dead fixable Aqua dead cell stain kit (Life Technologies) followed by surface staining according to the manufacturer's instructions. Data were acquired using an LSRFortessa X20 flow cytometer (BD Biosciences) and analyzed using FlowJo cytometry analysis software v10.8.1 (Tree Star, Inc).

The gating schemes applied to identify NK cells are shown in Figure S4A. The NK cell FCS files were exported and concatenated for downstream analysis. The UMAP (v3.1) FlowJo plugin was used for dimension-reduced visualization of the data according to the following parameters: metric: Euclidian, nearest neighbors: 15, minimum distance: 0.5, number of components: 3. Boolean gating was performed with FlowJo (v10.9) and the following markers: CD57, NKG2C, KIR3DL1/S1, KIR2DL1/S1, and CD85j (Figure S5A). Figures were generated with Prism v9 (GraphPad software).

## Capacity of NK cells to suppress HIV infection of autologous CD4⁺ T cells

We implemented an NK cell viral inhibition assay based on an assay we previously developed for CD8⁺ T cells.⁹⁴ PBMCs were isolated from fresh peripheral blood by density gradient centrifugation. CD4⁺ T cells were purified by positive selection with antibody-coated magnetic beads (EasySep Human CD4 Positive Selection Kit II ref. 17852) and NK cells were sorted by negative selection (EasySep Human NK Enrichment Kit ref. 19055) using a RoboSep instrument (STEMCELL Technologies). Purified cells were cultured in RPMI 1640 medium supplemented with GlutaMAX, 10% FCS, penicillin (10 UI/ml) and streptomycin (10 µg/mL). After purification, the CD4⁺ T cells were activated for 3 days with 2 µg/mL of PHA-L (Sigma, Ref.L4144) and 200 IU/mL of IL-2 (Human IL-2 IS, premium grade, Miltenyi Biotec, ref. 130-097-745). During this period, NK cells were maintained in culture medium supplemented with 0.1 ng/ mL IL-15. This concentration of IL-15 allows the survival of NK cells without inducing activation. Activated CD4⁺ T cells were then seeded in a 96-U-well plate (100 µL at 10⁶/mL in triplicate) alone or in the presence of NK cells (1:1 ratio) and then challenged with the HIV-1<sub>BAL</sub> strain (R5) (10 ng p24/mL). The cells were spinoculated⁹⁵ at 1200 × g for 1 h. The cells were then incubated at 37°C and 5% CO₂ for 1 h and washed before being cultured for 72h in RPMI 1640 medium containing GlutaMAX, 10% FCS, penicillin (10 UI/ml) and streptomycin (10 µg/mL) and IL-2 (200 UI/ml). Viral replication was monitored in the culture supernatants at 3 and 7 days post-infection by an ELISA p24 assay (HIV-1 p24 ELISA kit, XpressBio, Ref.XB-1000). The viral inhibitory capacity of NK cells was calculated by comparing p24 levels on day 3 (when maximal NK cell activities were found in most cases) in the NK:CD4 cocultures to those in the CD4⁺ T cells cultured alone.

# QUANTIFICATION AND STATISTICAL ANALYSIS

The chi-square test was used to compare the frequency of discrete variables, and the Baptista-Pike method was used to test odd ratios to 1. The Bonferroni-Sidak method was used to correct for multiple comparisons in the analyses of alleles. The corrected values are presented as p' throughout the manuscript. The nonparametric Mann-Whitney test or ANOVA followed by the Kruskal-Wallis test was applied for comparisons of continuous variables between two or multiple groups, respectively. Kaplan-Meier survival curves were constructed to estimate the cumulative proportion of individuals with continued viral load control after treatment interruption; curves were compared via log rank tests.