# NK Count and Natural Cytotoxicity in Immune Nonresponders Versus Responders Living With HIV

Charlotte Silvestre, Edouard Tuaillon, Maël-morvan Duroyon, Magali Abrantes, Jenny-constanza Thibout, Martin Villalba, Marie-Christine C Picot, Antoine Gross, Alain Makinson

► To cite this version:

Charlotte Silvestre, Edouard Tuaillon, Maël-morvan Duroyon, Magali Abrantes, Jenny-constanza Thibout, et al.. NK Count and Natural Cytotoxicity in Immune Nonresponders Versus Responders Living With HIV. Journal of Medical Virology, 2025, 97 (2), pp.301-307. 10.1002/jmv.70170. hal-04955232

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RESEARCH ARTICLE

OPEN ACCESS

# NK Count and Natural Cytotoxicity in Immune Nonresponders Versus Responders Living With HIV

Charlotte Silvestre<fnref n="1" /> ID | Edouard Tuillon² | Maël-Morvan Duroyon³ | Magali Abrantes<fnref n="1" /> | Jenny-Constanza Thibout⁴ |
Martin Villalba⁵ | Marie-Christine Picot³ | Antoine Gross<fnref n="1" /> ID | Alain Makinson⁶ ID

**Correspondence:** Antoine Gross (antoine.gross@cnrs.fr) | Alain Makinson (a-makinson@chu-montpellier.fr)

**Received:** 30 August 2024 | **Revised:** 28 November 2024 | **Accepted:** 5 January 2025

**Funding:** This work and CS were supported by Sidaction, a French association fighting against HIV and AIDS, the FHU-InCh (University Hospital Federation of Chronic Infections), and CHU de Montpellier, France.

**Keywords:** cytotoxicity | HIV | immune nonresponse | natural killer cells

## ABSTRACT

Despite viral suppression with antiretroviral therapy, immune nonresponders (INR) among people living with HIV (PLWH) still have a higher risk of developing AIDS-related and non-AIDS-related complications. Our study aimed to investigate the phenotype and functions of Natural Killer (NK) cells in INR, to better understand underlying mechanisms of immune nonresponse. Our cross-sectional study included PLWH aged over 45 with an undetectable HIV viral load sustained for at least 2 years. Participant CD4⁺ T-cell counts exceeded 500 cells/mm³ for IR or below 350 cells/mm³ for INR. We characterized NK cell subsets, performed natural cytotoxicity and ADCC assays, and phenotyped NK cells before and after functional assays. Median CD4 levels were 247.5 (IQR, 208.8–286.3) cells/mm³ and 768.5 (IQR, 673.3–957.8) cells/mm³ in the INR (n = 20) and IR (n = 40), respectively. NK cell counts were lower in INR (p = 0.00066), but the percentages were similar between IR and INR. NKG2A was the only differentially expressed marker between groups, showing higher expression in INR. Additionally, NK cell natural cytotoxicity was elevated in the INR group. Multivariate analyses associated CD4 nadir and low NK cell count with immune nonresponse. Our results do not indicate a clear role for NK-mediated ADCC in immune nonresponse. We did not objectify an association between CD8 hyperactivation and INR.

## 1 | Introduction

People living with HIV (PLWH) are expected to achieve an undetectable HIV viral load under antiretroviral therapy (ART) to restore CD4⁺ T-cell levels. However, 10%–40% of treated PLWH fail to achieve immune reconstitution despite viral suppression [1–5]. These immune nonresponders (INR) are at increased risk of developing AIDS-related and non-AIDS-related comorbidities, such as cardiovascular and neurological diseases, cancers, and death [1, 6–10]. Factors associated with

INR include older age [11–13], a low CD4 nadir [14], a diminished CD4/CD8 ratio at baseline [15], and suboptimal virological response following initiation of ART [16].

The mechanisms behind immune nonresponse remain insufficiently understood [17]. Hypotheses include impaired production or maturation of CD4 cells and chronic immune activation. Microbial translocation, gut impairment, and coinfections with hepatitis B virus (HBV) [18], hepatitis C virus (HCV) [19], or cytomegalovirus (hCMV) [11, 20] may contribute to an altered

<footnote n="1">¹IRIM, Université de Montpellier, CNRS, Montpellier, France | ²Virology Department, University Hospital Montpellier & Inserm U1058, University Montpellier, Montpellier, France | ³Epidemiology and Clinical Research Unit, University Hospital Montpellier, Montpellier, France | ⁴Infectious Diseases Department, University Hospital Montpellier, Montpellier, France | ⁵IRMB, INSERM, CNRS, University Hospital Montpellier, University Montpellier, Montpellier, France | ⁶Infectious Diseases Department, University Hospital Montpellier & INSERM U1175, University Montpellier, Montpellier, France</footnote>

<footnote>Antoine Gross and Alain Makinson had equally contributed to this work and should be considered as joint senior authors.</footnote>

<footnote>This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.</footnote>

<footnote>© 2025 The Author(s). *Journal of Medical Virology* published by Wiley Periodicals LLC.</footnote>
inflammatory environment even among PLWH receiving ART. Immune senescence may also play an active role in INR.

Natural killer (NK) cells, a subset of innate lymphoid cells, play a crucial role in eliminating stressed, tumor, or infected cells. They exert their cytotoxic activity through direct cell-mediated cytotoxicity and via antibody-dependent cellular cytotoxicity (ADCC), wherein antibodies allow infected cell recognition [21]. NK cells are a heterogeneous cell type composed of various subpopulations distinguished by their receptors, maturation states, and functions. With effective ART and CD4 T-cell restoration, NK cells CD56 and CD16 expression normalized though other markers remained dysregulated [22, 23]. Upon chronic HIV and/or hCMV infection, NK cells exhibit increased maturation, characterized by higher levels of CD57 and NKG2C expression [24]. They also display a more exhausted phenotype, indicated by elevated expression of exhaustion markers such as PD1, Tim3, and TIGIT [25].

NK cells have been investigated in INR, but most studies have primarily focused on describing NK subsets and the phenotypes of NK cells [26–28]. Few studies have explored mechanisms involving natural cytotoxicity and ADCC in NK cells that might contribute to CD4 T-cell depletion [29–31]. We aimed to study the differences in terms of NK cell phenotypes and functions in INR and IR in a well-matched study.

# 2 | Materials and Methods

## 2.1 | Ethics Approval

The INKASE study was approved by the Ethics Committee Sud-Est 1, France (study no. 2021-A02470-41), registered in [ClinicalTrials.gov](https://ClinicalTrials.gov) (Identifier: NCT05243381) and complied with the Helsinki Declaration. All volunteers gave informed consent.

## 2.2 | Participant Enrolment

The study was conducted at the Infectious and Tropical Diseases Department of Montpellier Hospital University. PLWH were proposed to participate in the study if they fulfilled the following criteria: age over 45 years, sustained undetectable HIV viral load for at least 2 years, and at least two CD4⁺ T-cell count measurements within the past 2 years. IR were defined as individuals with a CD4 lymphocyte count exceeding 500 cells/mm³, and INR as individuals with a CD4 lymphocyte count below 350 cells/mm³, both groups fulfilling all other inclusion criteria. Noninclusion criteria were an absence of ART, immunosuppressive medication, ongoing or history of cancer within 5 years of inclusion, pregnancy or breastfeeding, adult protection by law, or absence of social security. Immunosuppressive medication and a history of cancer during the last 5 years were considered as specific conditions of INR and NK disturbances, and PLWH with these conditions were excluded.

We planned to include 20 INR PLWH matched on age (per 5-year classes), gender, and duration of HIV undetectability (2–8 years and > 8 years) with 40 PLWH with IR. After obtaining informed consent, blood samples of 20 mL in EDTA tubes were collected from each volunteer.

## 2.3 | Isolation of NK Cells in PBMC

All samples were processed within 4 h of blood collection. After PBMC isolation by density gradient, the percentage of NK cells was determined as live cells within PBMC negative for lineage markers ($CD3^+$, $CD4^+$, $CD14^+$, $CD19^+$) and positive for CD56 and CD16 markers.

NK cells were isolated using the human NK cell isolation kit (Miltenyi Biotec) following the manufacturer's protocol. Isolated NK cells and plasmas were stored at -80°C for further analysis.

## 2.4 | NK Cell Phenotype

Isolated NK cells from the cohort were thawed and phenotyped with two antibody panels (Table S1) and a viability marker (FVS510, BD Biosciences). The panels shared a backbone composed of a negative lineage (CD3-FITC, CD4-FITC, CD14-FITC, and CD19-FITC), CD56-BV786, CD16-PerCP-Vio700, CD57-BV605, NKG2C-PE-Vio770, NKG2D-BV711, NKp30-PE, Tim3-PE-Cy5, and CD107a-BV-421. NKG2A-APC-VioBrightR720 and IFNγ-APC were added to Panel 1, whereas NKp46-APC-VioBrightR720 and CD3ζ-APC were added to Panel 2. After performing functional assays (natural cytotoxicity and ADCC assays), NK cell phenotypes were assessed with an effector-to-target (E/T) ratio of 1:1.

## 2.5 | Flow Cytometry Data Acquisition and Analysis

The data were acquired on a BD LSR Fortessa cytometer. Data was firstly cleaned with FlowJo v10.10 using FlowAI plugin (the gating strategy is presented in Figure S5). Then, calculations, representations, and statistics were done using R v4.3.2 (https://www.R-project.org/) with the Bioconductor packages Catalyst 1.28.0 (https://github.com/HelenaLC/CATALYST) and diff cyt 1.24.0 (Weber (2024), https://github.com/lmweber/diff cyt). All cytometry data from both panels and participants, including phenotyping after functional tests, are included in FlowSOM clusterization. After a first clusterization with 100 clusters based on CD16, CD56, CD57, NKG2C, NKG2D, and NKp30 expressions, an 8-metaclusterization was performed according to the delta area graph depicted in Figure S4 and package instructions. The Uniform Manifold Approximation and Projection (UMAP) was used to represent a dimensional reduction of NK cells. For subsequent analyses, the single-cell experiment object produced by CATALYST was parsed as required. We established three levels of expression for the different markers, based on the tertiles of each marker: high expression (high, expression: > 66%), intermediate level (int, expression: 33%–66%), and low expression (low, expression: 0%–33%).

## 2.6 | Natural Cytotoxicity Assay

To evaluate the natural cytotoxicity of NK cells, target K562 cells [32] were stained with Carboxyfluorescein succinimidyl ester (CFSE, Thermofisher) and cocultured with NK cells at different ratios (E/T: 1/1; 0.5/1; 0.25/1; 0.125/1) during 5 h at 37°C. Cell mortality was evaluated after staining with FVS700.
<table><caption>TABLE 1 | Characteristics of PLWH included in the study. INR and IR groups were matched on age, gender, and duration of HIV aviremia.</caption><thead><tr><th></th><th>INR group (n = 20)</th><th>IR group (n = 40)</th><th>p value</th></tr></thead><tbody><tr><td>Age (years)</td><td>64 [56.5–69.75]</td><td>63.5 [54.75–69]</td><td>0.951<sup>†</sup></td></tr><tr><td>Men</td><td>17 (85%)</td><td>34 (85%)</td><td>&gt; 0.999<sup>‡</sup></td></tr><tr><td>HIV aviremia duration (years)</td><td>10.2 [6.1–8.1]</td><td>10 [8.1–14]</td><td>0.499<sup>†</sup></td></tr><tr><td>History of AIDS</td><td>11/20 (55%)</td><td>11/40 (27.5%)</td><td>0.037<sup>§</sup></td></tr><tr><td>Anti-hCMV antibodies</td><td>18/20 (90%)</td><td>34/40 (85%)</td><td>0.707<sup>‡</sup></td></tr><tr><td>Anti-HCV antibodies</td><td>3/20 (15%)</td><td>3/40 (7.5%)</td><td>0.390<sup>‡</sup></td></tr><tr><td>HBs antigen</td><td>3/20 (15%)</td><td>4/40 (10%)</td><td>0.676<sup>‡</sup></td></tr><tr><td>CD4 count (cells/mm³)</td><td>247.5 [208.8–286.3]</td><td>768.5 [673.3–957.8]</td><td>&lt; 0.001<sup>¶</sup></td></tr><tr><td>CD4 percentage (%)</td><td>23.5 [17.25–29.95]</td><td>39.5 [32.63–46.03]</td><td>&lt; 0.001<sup>†</sup></td></tr><tr><td>CD8 count (cells/mm³)</td><td>420 [318.8–614.5]</td><td>772 [474.3–1028]</td><td>0.011<sup>¶</sup></td></tr><tr><td>CD8 percentage (%)</td><td>42.2 [34.03–49]</td><td>33.7 [26.85–41.8]</td><td>0.009<sup>†</sup></td></tr><tr><td>CD4/CD8 ratio</td><td>0.585 [0.4–0.695]</td><td>1.1 [0.8–1.675]</td><td>&lt; 0.001<sup>¶</sup></td></tr><tr><td>CD4 nadir (cells/mm³)</td><td>35.09 [24.25–106.6]</td><td>287.5 [106.3–399]</td><td>&lt; 0.001<sup>¤</sup></td></tr></tbody></table>

Note: The values presented for continuous variables are median and IQR.

(BD Biosciences) by determining the percentage of CFSE-posFVS700-pos cell in CFSE-pos cells on a Novocyte cytometer and Novoexpress software (Agilent). For each individual, the natural cytotoxicity index was computed as follows: $Index = \max(\frac{\% \text{ of dead cells}}{E / \text{Tratio}})$.

## 2.7 | ADCC Assay

To evaluate ADCC, CEM.NKR-CCR5 [33] (NIH AIDS Reagent Program) cells were stained with CFSE. The labeled cells were incubated with a dose of 0.33 µg/mL of recombinant GP120 Bal (HRP_20082, NIH AIDS Reagent Program) as a virological target before being incubated with serum. The plasma of PLWH or referenced antibodies HIVIG (ARP-3957, NIH AIDS Reagent Program) were added before the coculture with NK cells at different ratios (E/T: 1/1; 0.5/1; 0.25/1; 0.125/1) for 5 h at 37°C. Cell mortality was evaluated after staining with FVS700 by determining the percentage of CFSE-posFVS700-pos cells in CFSE-pos cells on a Novocyte cytometer. The ADCC index was computed as follows: $ADCC Index = \max(\frac{\% \text{ of dead cells} \times \text{antibody dilution}}{E / \text{Tratio}})$. The normalized ADCC index was computed as follows: Normalized $ADCC Index = \frac{ADCC Index with PLWH plasma}{ADCC Index with reference antibody}$.

## 2.8 | Data Collection

Biological data, including CD4 cell count and percentage, CD8 cell count and percentage, CD4/CD8 ratio, and CD4 nadir, were collected. Clinical data, such as history of AIDS and coinfections with hCMV, HBV, or HCV, were also recorded. Coinfections with hCMV were defined based on the presence of anti-CMV antibodies, while HBV and HCV coinfections were defined by the presence of HBs antigen and anti-HCV antibodies, respectively.

## 2.9 | Statistical Analysis

All statistical analyses were performed using R (version 4.3.1), with a significance level set at *p* < 0.05. The tests performed in accordance with their conditions of application are indicated in table and figure legends. The adjusted *p* values were computed with Holm's method. The analyses with CATALYST/diff cyt package used diff cyt/edgeR method for cluster abundance and diff cyt/limma method for marker expression, both with significance for *fdr* < 0.05. The association of parameters with immune nonresponse is analyzed using multivariable logistic regression with *glm* function.

## 3 | Results

### 3.1 | Clinical Characteristics of Enrolled Participants

The matching criteria of age, proportion of men, and duration of HIV aviremia were similar in both groups (Table 1). Median CD4 levels were 247.5 (IQR, 208.8–286.3) and 768.5 (IQR, 673.3–957.8) cells/mm³ in the INR group and IR group, respectively (Table 1). History of AIDS was significantly more frequent in INR (55% vs. 27.5%). Coinfection with CMV, HCV, or HBV did not differ between groups. Percentage of CD4 counts, absolute count, and CD4/CD8 ratio were significantly lower in INR than in IR.

### 3.2 | NK Cell Counts

There was a significantly lower count of NK cells in INR compared to IR (*p* = 0.00066), but no significant differences in percentages (*p* = 0.52). The median NK cell counts and percentages were 124

<footnote>†Two-sample *t*-test.</footnote>

<footnote>‡Fisher's exact test.</footnote>

<footnote>§Pearson's $\chi^2$ test.</footnote>

<footnote>¶Wilcoxon rank-sum test.</footnote>

<footnote>¤Wilcoxon rank-sum exact test.</footnote>
cells/mm³ (IQR, 75.1–160) and 11.1% of total leukocytes, respectively, in INR and 194 cells/mm³ (IQR, 153–252) and 10.5% of total leukocytes in the IR (Figure 1a,b). The age distribution analysis

<figure><img src="image_2.png" /></figure>

(Figure S1a) did not reveal a significant depletion trend of NK cells with increasing age in IR and INR. NK cell counts correlated with CD4 T-cell counts ($R = 0.34, p = 0.0075$) in all volunteers (Figure 1c), but not in groups of IR and INR, despite a trend in INR (Figure 1d). The percentage of NK cells (Figure 1e,f) relative to the percentage of CD4 cells remained stable globally and in each group. In contrast, the percentages of NK and CD4 cells were inversely correlated with CD8 percentages (Figure 1g,j) in all volunteers ($R = -0.72, p < 0.0001$ and $R = -0.36, p = 0.0051$, respectively) and within each group. There was a positive correlation between NK and CD4 cell counts and CD8 cell counts (Figure S1b–e). There was also no difference in the percentage of hyperactivated CD8 lymphocytes ($CD38^+CD8^+$) between the two groups (Figure S1f).

## 3.3 | Expressions of NK Cell Markers

Expression levels of phenotypic NK markers showed differences in INR and IR groups in the expression of CD57 and NKG2A (Figure 2a). NKG2A was significantly higher in INR (adjusted $p = 0.042$). The immune checkpoint markers Tim3 and TIGIT, as well as the activation marker CD69, were similarly highly expressed in both groups. Correlations between the expression levels of phenotypic markers are depicted in Figure 2b. Positive correlations included TIGIT and CD57, CD69 and TIGIT, Tim3 and NKp46, CD57 and NKp30, and NKG2A and NKp46. Conversely, the most notable negative correlations were CD16 and NKG2D, IFNγ and NKp46, and IFNγ and Tim3. The negative correlation between CD16 and NKG2D is illustrated in Figure 2c. Both INR and IR cells exhibited similar correlation factors ($R = -0.72$ and $-0.80$, respectively).

## 3.4 | NK Cell Clustering

Figure 3a shows the UMAP graphs resulting from NK cell meta-clustering from all INKASE participants, categorized by groups. The abundance of eight clusters is evaluated (Figure 3b), with Clusters 1, 2, 3, 4, and 8 being the most abundant. Clusters 5, 6, and 7 collectively represent only 1.5% of total NK cells. Diff cyt/EdgeR analysis did not detect differences in cluster abundances between INR/IR groups. Figure 3c depicts a heatmap of marker expression levels (for UMAP graph projections of each marker expression, see Figure S2). Clusters 1 and 2 express high levels of CD16, which were associated with heightened cytotoxicity subsets. They shared many markers but can be differentiated by the CD57 expression

**FIGURE 1** | The estimated number and percentage of natural killer (NK) cells. The estimated number (a) and percentage of NK cells among total leukocytes (b) in both the IR (green) and the INR (red) groups. The significant *p* value of the Wilcoxon rank-sum test is indicated on the graph. Correlation between the estimated number of NK cells and CD4 count in all enrolled individuals (c) and within each group (d). Correlation between NK cell percentage and CD4 percentage in all enrolled individuals (e) and within each group (f). Correlation between NK cell percentage and CD8 percentage in all enrolled individuals (g) and within each group (h). Correlation between CD8 cell percentage and CD4 percentage in all enrolled individuals (i) and within each group (j). Pearson's correlation estimates and *p* values are indicated on graphs.
<figure><img src="image_3.png" /><figcaption>**FIGURE 2** | Expression level of all markers in the IR and INR groups. Comparison of marker expression measured by flow cytometry in both IR (green) and INR (red) groups (a). \* indicate Wilcoxon rank-sum test adjusted *p* < 0.05. (b) Correlation matrix plot of marker expression. Significant correlations (Pearson's test adjusted *p* < 0.05) are indicated by circles, with color and size indicating correlation estimate levels. (c) Highlights of the negative correlation between CD16 and NKG2D levels in both IR and INR groups.</figcaption></figure>

level, which is higher in Cluster 1. Clusters 3 and 4 expressed intermediate levels of CD16 and high levels of CD3ζ and IFNγ. These clusters were differentiated by their level of maturation, with Cluster 3 showing higher expression of CD57. Cluster 8 exhibited high expression levels of most markers, except for CD16, CD3ζ, CD107a, and IFNγ, and so could have poor functional activity. Marker expression levels in clusters were compared between the two groups with diffcyt package. Among markers, NKG2A expression is consistently elevated among INR, with significant differences in Clusters 3 and 4 (Figure 3d).

## 3.5 | Natural Cytotoxicity and ADCC

The natural cytotoxicity activity of NK cells was higher in INR than IR (p = 0.033), as illustrated in Figure 4a. No significant differences were observed in the ADCC index with autologous plasma normalized to HIVIG between IR and INR groups (Figure 4b, p = 0.17) or in the ADCC index using the referenced antibody-pool HIVIG (Figure 4c, p = 0.35).

Figure 4d presents a heatmap comparing the abundance of clusters in both INR and IR groups before and after natural cytotoxicity

assays (pre/post-cytotoxicity) and ADCC assays (pre/post-ADCC) obtained through diffcyt/edgeR analysis. Clusters 1 and 2, expressing high levels of CD16, decreased after the functional assays, except for Cluster 2 in the INR group pre- versus post-ADCC comparison. Clusters 3 and 4, characterized by an intermediate level of CD16, were slightly enriched after ADCC assays and after natural cytotoxicity for the IR group. Clusters 7 and 8 were enriched after the functional assays, mainly after natural cytotoxicity activity with the exception of Cluster 7, which remained unchanged in the ADCC assay for the INR group. Figure 4e illustrates the variations showing slight depletion of Cluster 1 and concomitant enrichment of Cluster 3 in both groups.

The variations in marker expressions before and after natural cytotoxicity and ADCC assays are respectively presented in Figure S3.

## 3.6 | Association of Factors With Immune Nonresponse

Figure 5a presents a clustering heatmap illustrating factors of the previous analyses for the 60 PLWH enrolled in INKASE
<figure><img src="image_4.png" /><figcaption>**FIGURE 3** | Clusterization and expression levels of markers in the clusters. (a) Uniform Manifold Approximation and Projection (UMAP) representation of the 8-metaclusterization. (b) Frequencies of the clusters in the IR (green) and INR (red) groups. (c) Expression heatmap of all markers across the eight clusters in all individuals. (d) NKG2A expression levels considering clusters by groups. Statistically significant intergroup differences are indicated on graphs (*** for adjusted *p* value < 0.01 and ** for adjusted *p* value < 0.05, obtained after diff cyt/limma analysis).</figcaption></figure>

study and annotated the heatmap with group, CD4 count, and AIDS history. The cell counts, represented by CD4 nadir and NK count, clustered together. NKG2A expression in Clusters 3 and 4 grouped together. Functional indices calculated after natural cytotoxicity and ADCC assays formed the third group. The dendrogram of individuals (left of the heatmap) allowed the delineation of three distinct groups among the PLWH. The first group comprised 13 IR with a low natural cytotoxicity index and high NKG2A expression in NK cell Cluster 4. The second group predominantly consisted of INR (18 INR, representing 90% of the INR group) along with 8 IR individuals, characterized by a low CD4 nadir and high NKG2A expression in Clusters 3 and/or 4. The last group included 2 INR and 19 IR with low NKG2A expression in Clusters 3 and 4. The majority of the INR (18/20) were part of Group 2 related to a history of AIDS, known as an associated factor of immune nonresponse.

The forest plot of Figure 5b shows the association assessment of selected factors (excluding correlated parameters). Among the factors, only CD4 nadir and NK cell count were significantly associated with immune nonresponse. Refining the analysis (Figure 5c) shows that a CD4 nadir variation of 100 cells/mm³ is associated with an odds ratio (OR) of 7.64 (CI: 2.74–33.98, *p* = 0.001) and a variation of 100 NK/mm³ with an OR of 5.54 (1.80–25.79, *p* = 0.011).

4 | Discussion

We found that in INR, the absolute count of NK was lower than in IR. The percentages of NK were similar in both groups, in contrast with diminished percentages of CD4 T-cells and increased percentages of CD8 levels in INR. NKG2A expression was elevated in INR, particularly within Clusters 3 and 4 exhibiting an

intermediate level of CD16. We also highlighted a higher activity in natural cytotoxicity in INR compared to IR, but not significantly for ADCC. Ultimately, the CD4 nadir and NK cell count were independently associated with immune nonresponse.

The INKASE study stands out as one of the few investigations delving into the phenotype and functions of NK cells, in a well-matched and translational approach of IR and INR, and compared NK cell phenotypes following functional assays. To explore NK functions, we performed the assays using IL-2 unstimulated NK cells. This approach allowed us to preserve the basal activity of NK cells despite the thawing process.

There is no consensus definition of INR, and studies have chosen various definitions of INR, based on CD4/CD8 ratios and/or different CD4 cutoffs [1, 15]. However, we chose our cutoffs as CD4 levels < 350 cells/mm³ have been linked to AIDS and non-AIDS-related comorbidities and malignancies, including Kaposi syndrome, non-Hodgkin and Hodgkin lymphomas, and lung and liver cancers [34], and have been previously used in immunodiscordant studies [14]. We presumed that excluding PLWH with intermediate levels of CD4 recovery between 351 and 500 cells/mm³ would help to clearly distinguish differences in underlying immune mechanisms of INR. We chose not to define INR and IR with the CD4/CD8 ratio, as it can reflect either CD4 non-restoration (the aim of our study), but also CD8 increase.

The previously known factors associated with immune non-response, such as a history of AIDS [35], a low CD4 nadir [14, 35], and a low CD4/CD8 ratio [1, 15, 35], were also observed in our study as expected. Multivariable analyses showed that, in our study, a history of AIDS had no impact on immune non-response taking account the nadir. Nevertheless, the two
(a)

<figure><img src="image_5.png" /></figure>

(b)

<figure><img src="image_6.png" /></figure>

(c)

<figure><img src="image_7.png" /></figure>

(d)

Clusters

<figure><img src="image_8.png" /></figure>

(e)

<figure><img src="image_9.png" /></figure>

**FIGURE 4** | Natural cytotoxicity and ADCC functional assays in the IR and INR groups. Natural cytotoxicity index (a), normalized ADCC index (b), and referenced HIVIG ADCC index (c) in the IR (green) and INR (red) groups; *p* values from the Wilcoxon rank-sum test are indicated on graphs. (d) and (e): Variations in cluster abundance before and after natural cytotoxicity and ADCC assays are presented on heatmap (d) with a focus on Clusters 1 and 3 (e). Heatmap colors indicated abundance fold changes; significances computed by diff cyt/EdgeR method are indicated by NS (adjusted *p* value > 0.05), \* (adjusted *p* value < 0.05), \*\* (adjusted *p* value < 0.01), and \*\*\* (adjusted *p* value < 0.001).

parameters are closely associated since AIDS appears primarily
with low CD4 counts.

In addition to nadir, a low NK cell count was significantly
associated with immune nonresponse in our study. This has
never been formally described before. Interestingly, *Luo* et al.

[30] described similar nonsignificant trends, in 13 IR, 11 INR, and 12 healthy controls. IR had an NK cell population at similar levels of healthy controls and INR exhibited a lower NK cell count, as in our study. The sample size and participant homogeneity, ensured by matching criteria, allowed us to characterize the associations in our study.
The INR of INKASE cohort displayed significant decreases in CD8 lymphocyte counts compared to IR (median CD8 count of 420 and 772 cells/mm³, respectively). In contrast to decreased CD4 percentage and stable NK cell percentage in INR and IR, CD8 percentages were significantly increased in INR (33.7% in the IR group and 42.2% in the INR group). However, this CD8

increase did not signify increased CD8 activation, as the percentage of activated CD8⁺CD38⁺ lymphocytes was low and similar in both groups. Thus, our study does not highlight CD8 activation as a correlate of INR. Negredo et al. [14] also described a decrease in CD8 counts in INR, but in contrast with our study a decrease in CD8 percentage and a significant increase in CD8 hyperactivation. However, in that same study, CD8 activation remained low between groups (12.4% in INR vs. 8.2% in IR), with differences in values which may not be clinically relevant. Our results need confirmation, and additional studies should determine whether the increased risk of AIDS and non-AIDS related events objectified in cohorts of INR with low CD4/CD8 [10] is due, in INR, to low CD4 counts or NK counts, rather than CD8 activation, or both.

The clusters representing different NK subtypes showed similar abundance in both groups, indicating that the reduction of NK cell counts is not solely due to the depletion of a specific NK subpopulation. Cluster analysis divided close clusters (Cluster 1 vs. Cluster 2, Cluster 3 vs. Cluster 4) based on CD57 expression levels, with CD57⁺ cells being relatively frequent among participants. This could be linked to the documented increase of CD57⁺ NK cells associated with chronic HIV infection and the high prevalence of CMV infection in the study population [36]. The increase in cytotoxic NK cells (Clusters 1–4) might be enhanced by HIV infection and contribute to higher natural cytotoxicity in INR. However, the abundance of clusters did not differ between the two groups, suggesting that NK cell diversity is not influenced by immune nonresponse and does not participate in it.

NK cells from INR exhibited higher activity in natural cytotoxicity compared to IR. The expression levels of common markers of NK cells were mostly similar between the two groups, except for the inhibitory receptor NKG2A. NKG2A was significantly higher in the INR group, particularly in two clusters within Cluster 3 and Cluster 4, which were characterized by an intermediate level of CD16 and high levels of CD3ζ and IFNγ. NKG2A is an inhibitory receptor of NK activity, and its overexpression could be the result of increased natural NK-mediated cytotoxicity in INR as the expression of CD16 and NKG2A have been described as opposites [37]. Moreover, NKG2A⁺ NK cells exhibit a higher cytotoxic response against the K562 cells and HIV-infected CD4 cells [38]. Negredo et al. [14] identified ex vivo CD4 T-cell death during PBMC culture as predictors of immune nonresponse concurrently to nadir CD4 cells. It would be interesting to determine whether increased NK natural cytotoxicity was implicated in the CD4 death in INR.

<figure><img src="image_10.png" /></figure>

<table><thead><tr><th>Variable</th><th>N</th><th>Odds Ratio</th><th>OR (CI)</th><th>p-value</th></tr></thead><tbody><tr><td>Nadir (100 CD4/mm3)</td><td>60</td><td></td><td>9.06 (2.54, 59.54)</td><td>0.005</td></tr><tr><td>History of AIDS</td><td>No 38<br>Yes22</td><td></td><td>Reference<br>1.02 (0.12, 9.00)</td><td>0.989</td></tr><tr><td>NK cells (100 NK/mm3)</td><td>60</td><td></td><td>6.53 (1.64, 44.93)</td><td>0.023</td></tr><tr><td>NKG2A in cluster 3</td><td>60</td><td></td><td>0.45 (0.11, 1.26)</td><td>0.189</td></tr><tr><td>Cytotoxicity (Index)</td><td>60</td><td></td><td>1.00 (1.00, 1.00)</td><td>0.344</td></tr></tbody></table>

<table><thead><tr><th>Variable</th><th>N</th><th>Odds Ratio</th><th>OR (CI)</th><th>p-value</th></tr></thead><tbody><tr><td>Nadir (100 CD4/mm3)</td><td>60</td><td></td><td>7.64 (2.74, 33.98)</td><td>0.001</td></tr><tr><td>NK cells (100 NK/mm3)</td><td>60</td><td></td><td>5.54 (1.80, 25.79)</td><td>0.011</td></tr></tbody></table>

**FIGURE 5** | Factors associated with immune nonresponse. (a) Clustering heatmap of previous significant factors associated with immune nonresponse. Each row corresponds to an individual. Left annotations: Group, CD4 count, and AIDS history are not included in clustering. The heatmap is horizontally split regarding dendrogram of individuals (left) and vertically split regarding factor dendrogram (below). Forest plots illustrate the impact of each factor on immune nonresponse status (b), highlighting those associated with immune nonresponse status (c). Odds ratio (OR) and their confidence intervals (CIs) and *p* value obtained with multivariable logistic regression are indicated on graphs.
There was no significant difference in ADCC function between the two groups when using either autologous plasma antibodies or the referenced HIVIG antibody pool, arguing against a specific mechanism of NK ADCC in immune nonresponse physiology. Indeed, functional activities were associated with cluster variations post-functional assays in the most abundant clusters but did not differ between INR and IR. However, a recent study has shown that in PLWH with elevated levels of soluble GP120 (sGP120), the CD4⁺ T-cell count is inversely correlated with the level of anti-GP120 antibodies targeting the cluster A region [39]. Through its circulation, sGP120 might contribute to CD4⁺ T-cell depletion via ADCC in vivo. Measuring sGP120 in INR would be relevant and could help anticipate whether Fostemsavir might mitigate the involvement of GP120 and ADCC in INR [40].

We do acknowledge several limitations in our study. First, our study comprised only 20 INR and may not be totally representative of PLWH with INR or IR. In our study, we analyzed individuals several years (3–23 years) after their last detected HIV viremia and do not describe events occurring during (or involved in) the immune nonresponse onset. Second, we did not perform a long-term follow-up to determine which parameters are predictive of clinical events, as our study was a cross-sectional study. Third, in our NK cell functional assays, we used two referenced cell lines, K562 and CEM.NKR-CCR5. We used cell lines as target cells instead of autologous CD4 T-cells and identical numbers of NK cells from INR and IR, which may not reflect in vivo NK depletion in INR. These approaches were used to enable comparison of NK functions across all volunteers. Lastly, we characterized NK cells after thawing using two antibody panels, though some NK-specific markers were lacking. Since no standardized panel exists for NK cell characterization—beyond the commonly used CD56 and CD16 markers, which we used to determine NK counts on PBMCs isolated directly from blood—this made direct comparisons with other studies challenging. As an example, we opted to examine the expression of Tim3 and TIGIT instead of PD-1 and DNAM-1. The only inhibitory receptor included was NKG2A, for which we observed a difference between the two groups, and the analysis of KIR receptors and NKp44 and NKp80 would have been important.

The higher natural cytotoxicity in the INR group is associated with increased NKG2A expression in certain NK clusters. Therefore, it would be pertinent to investigate these phenomena alongside markers expressed by CD4 lymphocytes, such as activation markers (HLA-DR and CD38), cellular exhaustion markers (PD1), the NKG2A-ligand HLA-E and its functional interaction with NKG2A, and the expression CMH-I molecules and other activating ligands for NK cells [28, 35, 41, 42]. This would be valuable for better understanding the relationship between these two cell populations, specifically whether NKG2A expression could confer CD4 lymphocyte resistance to increased NK activity or by opposition that NK ligand expression would have a deleterious on CD4 lymphocyte survival and if the heightened NK cytotoxicity is influenced by CD4 lymphocyte.

In conclusion, in this well-matched study of INR and IR, we found that NK cells were less abundant but had similar

percentages in INR and exhibited a higher natural cytotoxicity response, but not an increased NK ADCC. We did not objectify an association between CD8 hyperactivation and immune nonresponse. Our results do not highlight a clear role of NK-mediated ADCC in immune nonresponse and suggest limited efficacy of strategies limiting NK ADCC to restore CD4 cell levels. Our results merit confirmation in other studies of INR.

## Author Contributions

**Charlotte Silvestre:** experimental design, experiment, formal analysis, writing—original draft. **Edouard Tuillon:** medical investigator, experimental design, review. **Maël-Morvan Duroyon:** biostatistics. **Magali Abrantes:** experiment. **Jenny-Constanza Thibout:** methodology. **Martin Villalba:** experimental design. **Marie-Christine Picot:** methodology, biostatistics. **Antoine Gross:** conceptualization, funding acquisition, experimental design, biostatistics, writing—original draft. **Alain Makinson:** conceptualization, principal medical investigator, funding acquisition, methodology, writing—original draft.

## Acknowledgments

We thank all PLWH who gave their consent to participate in the INKASE study. This work and CS were supported by Sidaction, a French association fighting against HIV and AIDS, the FHU-InCh (University Hospital Federation of Chronic Infections), and CHU de Montpellier, France. We thank Myriam Boyer-Clavel and Stéphanie Viala from Montpellier Ressources Imagerie (MRI) facility for their assistance and training in flow cytometry acquisition and analysis. We also thank Nicolas Tessandier for his help with unsupervised flow cytometry analyses. We would like to thank Charlotte Kaan, Sylvine Brochot, and Hélène Lenden-Hasse for all their help with the administrative formalities. We thank all medical investigators: René Baglioni, Marie Bistoquet, Jean-Marc Jacquet, Jordan Lejeune, Vincent Le Moing, Corinne Merle de Boever, Ana Montoya, Nathalie Pansu, Lucas Perez, and Jacques Reynes. We thank nurses, Christine Merlo, Corinne Aleu, and Virginie Monnier, for blood sampling.

## Ethics Statement

The INKASE study was approved by the Ethics Committee Sud-Est 1, France (study no. 2021-A02470-41), registered in [ClinicalTrials.gov](https://ClinicalTrials.gov) (Identifier: NCT05243381) and complied with the Helsinki Declaration.

## Consent

All volunteers gave informed consent.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Data Availability Statement

The authors have nothing to report.

## References

1. C. Mussini, P. Lorenzini, A. Cozzi-Lepri, et al., "CD4/CD8 Ratio Normalisation and Non-AIDS-Related Events in Individuals With HIV Who Achieve Viral Load Suppression With Antiretroviral Therapy: An Observational Cohort Study," *Lancet HIV* 2, no. 3 (2015): e98-e106, https://doi.org/10.1016/S2352-3018(15)00006-5.

2. X. Yang, B. Su, X. Zhang, Y. Liu, H. Wu, and T. Zhang, "Incomplete Immune Reconstitution in HIV/AIDS Patients on Antiretroviral Therapy: Challenges of Immunological Non-Responders," *Journal of Leukocyte Biology* 107, no. 4 (2020): 597-612, https://doi.org/10.1002/JLB.4MR1019-189R.
3. I. Rosado-Sánchez, I. Herrero-Fernández, A. I. Álvarez-Ríos, et al., "A Lower Baseline CD4/CD8 T-Cell Ratio is Independently Associated With Immunodiscordant Response to Antiretroviral Therapy in HIV-Infected Subjects," *Antimicrobial Agents and Chemotherapy* 61, no. 8 (2017): e00605-17, https://doi.org/10.1128/AAC.00605-17.

4. Y. Kong, Y. Tian, Y. Hao, et al., "Two Types of Poor Immunological Responder Showing Distinct Responses to Long-Term Haart," *International Journal of Infectious Diseases* 86 (2019): 178-187, https://doi.org/10.1016/j.ijid.2019.07.037.

5. R. Rb-Silva, A. Goios, C. Kelly, et al., "Definition of Immunological Nonresponse to Antiretroviral Therapy: A Systematic Review," *Journal of Acquired Immune Deficiency Syndromes* 82, no. 5 (2019): 452-461, https://doi.org/10.1097/QAI.0000000000002157.

6. G. Lapadula, L. Chatenoud, A. Gori, et al., "Risk of Severe Non AIDS Events Is Increased Among Patients Unable to Increase Their CD4+ T-Cell Counts >200+/µl Despite Effective HAART," *PLoS One* 10, no. 5 (2015): e0124741, https://doi.org/10.1371/journal.pone.0124741.

7. F. N. Engsig, J. Gerstoft, G. Kronborg, et al., "Long-Term Mortality in HIV Patients Virally Suppressed for More Than Three Years With Incomplete CD4 Recovery: A Cohort Study," *BMC Infectious Diseases* 10 (2010): 318, https://doi.org/10.1186/1471-2334-10-318.

8. F. Caby, M. Guiguet, L. Weiss, et al., "CD4/CD8 Ratio and the Risk of Kaposi Sarcoma or Non-Hodgkin Lymphoma in the Context of Efficiently Treated Human Immunodeficiency Virus (HIV) Infection: A Collaborative Analysis of 20 European Cohort Studies," *Clinical Infectious Diseases* 73, no. 1 (2021): 50-59, https://doi.org/10.1093/cid/ciaa1137.

9. J. L. Castilho, A. Bian, C. A. Jenkins, et al., "CD4/CD8 Ratio and Cancer Risk Among Adults With HIV," *JNCI: Journal of the National Cancer Institute* 114, no. 6 (2022): 854-862, https://doi.org/10.1093/jnci/djac053.

10. F. Chammartin, A. Mocroft, A. Egle, et al., "Measures of Longitudinal Immune Dysfunction and Risk of AIDS and Non-AIDS Defining Malignancies in Antiretroviral-Treated People With Human Immunodeficiency Virus," *Clinical Infectious Diseases* 78, no. 4 (2024): 995-1004, https://doi.org/10.1093/cid/ciad671.

11. V. Appay, S. Fastenackels, C. Katlama, et al., "Old Age and Anti-Cytomegalovirus Immunity are Associated with Altered T-Cell Reconstitution in HIV-1-Infected Patients," *AIDS* 25, no. 15 (2011): 1813-1822, https://doi.org/10.1097/QAD.0b013e328346406e.

12. J. Chen, K. Titanji, A. N. Sheth, et al., "The Effect of Age on CD4+ T-Cell Recovery in HIV-Suppressed Adult Participants: A Sub-Study From AIDS Clinical Trial Group (ACTG) A5321 and the Bone Loss and Immune Reconstitution (BLIR) Study," *Immunity & Ageing* 19, no. 1 (2022): 4, https://doi.org/10.1186/s12979-021-00260-x.

13. R. T. Gandhi, J. Spritzler, E. Chan, et al., "Effect of Baseline- and Treatment-Related Factors on Immunologic Recovery After Initiation of Antiretroviral Therapy in HIV-1-positive Subjects: Results From ACTG 384," *Journal of Acquired Immune Deficiency Syndromes* 42, no. 4 (2006): 426-434, https://doi.org/10.1097/01.qai.0000226789.51992.3f.

14. E. Negredo, M. Massanella, J. Puig, et al., "Nadir CD4 T Cell Count as Predictor and High CD4 T Cell Intrinsic Apoptosis as Final Mechanism of Poor CD4 T Cell Recovery in Virologically Suppressed HIV-Infected Patients: Clinical Implications," *Clinical Infectious Diseases* 50, no. 9 (2010): 1300-1308, https://doi.org/10.1086/651689.

15. F. Caby, A. Guihot, S. Lambert-Niclot, et al., "Determinants of a Low CD4/CD8 Ratio in HIV-1-Infected Individuals Despite Long-Term Viral Suppression," *Clinical Infectious Diseases* 62, no. 10 (2016): 1297-1303, https://doi.org/10.1093/cid/ciw076.

16. F. Raffi, V. Le Moing, A. Assuied, et al., "Failure to Achieve Immunological Recovery in HIV-Infected Patients With Clinical and Virological Success After 10 Years of Combined Art: Role of Treatment Course," *Journal of Antimicrobial Chemotherapy* 72, no. 1 (2017): 240-245, https://doi.org/10.1093/jac/dkw369.

17. M. Massanella, E. Negredo, B. Clotet, and J. Blanco, "Immunodiscordant Responses to HAART—Mechanisms and Consequences," *Expert Review of Clinical Immunology* 9, no. 11 (2013): 1135-1149, https://doi.org/10.1586/1744666X.2013.842897.

18. M. Anderson, S. Gaseitsiwe, S. Moyo, et al., "Slow CD4+ T-Cell Recovery in Human Immunodeficiency Virus/Hepatitis B Virus-Coinfected Patients Initiating Truvada-Based Combination Antiretroviral Therapy in Botswana," *Open Forum Infectious Diseases* 3, no. 3 (2016): ofw140, https://doi.org/10.1093/ofid/ofw140.

19. J. van Griensven, L. Phirum, K. Choun, S. Thai, A. De Weggheleire, and L. Lynen, "Hepatitis B and C Co-Infection Among HIV-Infected Adults While on Antiretroviral Treatment: Long-Term Survival, CD4 Cell Count Recovery and Antiretroviral Toxicity in Cambodia," *PLoS One* 9, no. 2 (2014): e88552, https://doi.org/10.1371/journal.pone.0088552.

20. E. Gómez-Mora, E. García, V. Urrea, et al., "Preserved Immune Functionality and High CMV-Specific T-Cell Responses in HIV-Infected Individuals With Poor CD4+ T-Cell Immune Recovery," *Scientific Reports* 7, no. 1 (2017): 11711, https://doi.org/10.1038/s41598-017-12013-2.

21. E. Scully and G. Alter, "NK Cells in HIV Disease," *Current HIV/AIDS Reports* 13 (2016): 85-94, https://doi.org/10.1007/s11904-016-0310-3.

22. N. Q. Zhao, A. M. Ferreira, P. M. Grant, S. Holmes, and C. A. Blish, "Treated HIV Infection Alters Phenotype but Not HIV-Specific Function of Peripheral Blood Natural Killer Cells," *Frontiers in Immunology* 11 (2020): 829, https://doi.org/10.3389/fimmu.2020.00829.

23. F. Bisio, F. Bozzano, F. Marras, A. Di Biagio, L. Moretta, and A. De Maria, "Successfully Treated HIV-Infected Patients Have Differential Expression of NK Cell Receptors (NKp46 and NKp30) According to AIDS Status at Presentation," *Immunology Letters* 152, no. 1 (2013): 16-24, https://doi.org/10.1016/j.imlet.2013.03.003.

24. H. Kared, S. Martelli, S. W. Tan, et al., "Adaptive NKG2C+CD57+ Natural Killer Cell and Tim-3 Expression During Viral Infections," *Frontiers in Immunology* 9 (2018): 686, https://doi.org/10.3389/fimmu.2018.00686.

25. E. Vendrame, C. Seiler, T. Ranganath, et al., "Tigit is Upregulated by HIV-1 Infection and Marks a Highly Functional Adaptive and Mature Subset of Natural Killer Cells," *AIDS* 34, no. 6 (2020): 801-813, https://doi.org/10.1097/QAD.0000000000002488.

26. S. Sun, W. Kong, X. Cui, et al., "The Abnormal Distribution of NK Cell Subsets Before HAART Treatment May Be Related to the Level of Immune Reconstitution in HIV Patient," *International Immunopharmacology* 96 (2021): 107784, https://doi.org/10.1016/j.intimp.2021.107784.

27. Q. Y. Zhang, X. Zhang, B. Su, et al., "Increased Early Activation of CD56dim/CD16dim/- Natural Killer Cells in Immunological Non-Responders Correlates With CD4+ T-Cell Recovery," *Chinese Medical Journal* 133, no. 24 (2020): 2928-2939, https://doi.org/10.1097/CM9.0000000000001262.

28. A. Soria, F. R. Guerini, A. Bandera, et al., "KIR-HLA Genotypes in HIV-Infected Patients Lacking Immunological Recovery Despite Effective Antiretroviral Therapy," *PLoS One* 6, no. 11 (2011): e27349, https://doi.org/10.1371/journal.pone.0027349.

29. Z. Luo, Z. Li, L. Martin, et al., "Pathological Role of Anti-CD4 Antibodies in HIV-Infected Immunologic Nonresponders Receiving Virus-Suppressive Antiretroviral Therapy," *Journal of infectious diseases* 216, no. 1 (2017): 82-91, https://doi.org/10.1093/infdis/jix223.

30. Z. Luo, Z. Li, L. Martin, et al., "Increased Natural Killer Cell Activation in HIV-Infected Immunologic Non-Responders Correlates With CD4+ T Cell Recovery After Antiretroviral Therapy and Viral Suppression," *PLoS One* 12, no. 1 (2017): e0167640, https://doi.org/10.1371/journal.pone.0167640.
31. E. Muñoz-Muela, M. Trujillo-Rodríguez, A. Serna-Gallego, et al., "Anti-CD4 Autoantibodies in Immunological Nonresponder People With HIV: Cause of CD4 + T-Cell Depletion?," *AIDS (London, England)* 36, no. 9 (2022): 1207-1214, https://doi.org/10.1097/QAD.0000000000003264.

32. E. Klein, F. Vánky, H. Ben-Bassat, et al., "Properties of the K562 Cell Line, Derived From a Patient With Chronic Myeloid Leukemia," *International Journal of Cancer* 18, no. 4 (1976): 421-431, https://doi.org/10.1002/ijc.2910180405.

33. A. Trkola, J. Matthews, C. Gordon, T. Ketas, and J. P. Moore, "A Cell Line-Based Neutralization Assay for Primary Human Immunodeficiency Virus Type 1 Isolates That Use Either the CCR5 or the CXCR4 Coreceptor," *Journal of Virology* 73, no. 11 (1999): 8966-8974.

34. M. Guiguet, F. Boué, J. Cadranel, J. M. Lang, E. Rosenthal, and D. Costagliola, "Effect of Immunodeficiency, HIV Viral Load, and Antiretroviral Therapy on the Risk of Individual Malignancies (FHDH-ANRS CO4): A Prospective Cohort Study," *Lancet Oncology* 10, no. 12 (2009): 1152-1159, https://doi.org/10.1016/S1470-2045(09)70282-7.

35. W. A. J. W. Vos, A. Navas, E. M. G. Meeder, et al., "HIV Immunological Non-Responders Are Characterized by Extensive Immunosenescence and Impaired Lymphocyte Cytokine Production Capacity," *Frontiers in Immunology* 15 (2024): 1350065, https://doi.org/10.3389/fimmu.2024.1350065.

36. A. C. Hearps, J. Zhou, P. A. Agius, et al., "Adaptive NK Cells Rapidly Expand During Acute HIV Infection and Persist Despite Early Initiation of Antiretroviral Therapy," *Journal of Immunology* Published online April 1 212, no. 10 (2024): 1553-1563, https://doi.org/10.4049/jimmunol.2300523.

37. L. Lajoie, N. Congy-Jolivet, A. Bolzec, and G. Thibault, "Gradual Increase of FcγRIIIa/CD16a Expression and Shift Toward IFN-γ Secretion During Differentiation of CD56dim Natural Killer Cells," *Frontiers in Immunology* 8 (2017), https://doi.org/10.3389/fimmu.2017.01556.

38. I. Lisovsky, G. Isitman, R. Song, et al., "A Higher Frequency of NKG2A+ Than of NKG2A-NK Cells Responds to Autologous HIV-Infected CD4 Cells Irrespective of Whether or Not They Coexpress KIR3DL1," *Journal of Virology* 89, no. 19 (2015): 9909-9919, https://doi.org/10.1128/JVI.01546-15.

39. M. Benlarbi, J. Richard, C. Bourassa, et al., "Plasmatic HIV-1 Soluble gp120 is Associated With Correlates of Immune Dysfunction and Inflammation in ART-Treated Individuals With Undetectable Viremia," *Journal of Infectious Diseases* Published online November 30 229, no. 3 (2023): 763-774, https://doi.org/10.1093/infdis/jiad503.

40. J. Richard, J. Prévost, C. Bourassa, et al., "Tem savir Blocks the Immunomodulatory Activities of HIV-1 Soluble gp120," *Cell Chemical Biology* 30, no. 5 (2023): 540-552.e6, https://doi.org/10.1016/j.chembiol.2023.03.003.

41. L. M. S. Pereira, E. S. França, I. B. Costa, et al., "HLA-B*13, B*35 and B*39 Alleles Are Closely Associated With the Lack of Response to ART in HIV Infection: A Cohort Study in a Population of Northern Brazil," *Frontiers in Immunology* 13 (2022): 829126, https://doi.org/10.3389/fimmu.2022.829126.

42. M. El-Beeli, S. H. Al-Mahrooqi, R. M. Youssef, et al., "HLA-A68 and HLA-B15 Alleles Correlate With Poor Immune Response Among AIDS Patients on Combined Antiretroviral Therapy," *Human Immunology* 77, no. 6 (2016): 490-497, https://doi.org/10.1016/j.humimm.2016.04.009.

## Supporting Information

Additional supporting information can be found online in the Supporting Information section.