Influence of HLA‐C environment on the spontaneous clearance of hepatitis C in European HIV–HCV co‐infected individuals

N Legrand; G David; A Rodallec; A Gaultier; D Salmon; A Cesbron; L Wittkop; F Raffi; K Gendzekhadze; C Retière; C Allavena; K Gagne

doi:10.1111/cei.13562

. 2021 Feb 2;204(1):107–124. doi: 10.1111/cei.13562

Influence of HLA‐C environment on the spontaneous clearance of hepatitis C in European HIV–HCV co‐infected individuals

N Legrand ^1,^2,^¹, G David ^1,^2,^¹, A Rodallec ³, A Gaultier ⁴, D Salmon ⁵, A Cesbron ⁶, L Wittkop ⁷, F Raffi ⁸, K Gendzekhadze ⁹, C Retière ^1,^2,^10,^², C Allavena ^8,^², K Gagne ^1,^2,^10,^11,^✉

PMCID: PMC7944354 PMID: 33314121

Summary

Natural killer (NK) cell functions are regulated by diverse inhibitory and activating receptors, including killer cell immunoglobulin‐like receptors (KIR), which interact with human leukocyte antigen (HLA) class I molecules. Some KIR/HLA genetic combinations were reported associated with spontaneous clearance (SC) of hepatitis C virus (HCV) but with discordant results, possibly reflecting KIR and/or HLA gene polymorphism according to populations. KIR/HLA genetic combinations associated with both an exhaustive NK and T cell repertoire were investigated in a cohort of HIV–HCV co‐infected individuals with either SC (n = 68) or chronic infection (CI, n = 163) compared to uninfected blood donors [controls (Ctrl), n = 100]. Multivariate analysis showed that the HLA C2C2 environment was associated with SC only in European HIV–HCV co‐infected individuals [odds ratio (OR) = 4·30, 95% confidence interval = 1·57–12·25, P = 0·005]. KIR2D⁺ NK cell repertoire and potential of degranulation of KIR2DL1/S1⁺ NK cells were similar in the SC European cohort compared to uninfected individuals. In contrast, decreased frequencies of KIR2DS1⁺ and KIR2DL2⁺ NK cells were detected in the CI group of Europeans compared to SC and a decreased frequency of KIR2DL1/S1⁺ NK cells compared to controls. Regarding T cells, higher frequencies of DNAX accessory molecule‐1 (DNAM‐1)⁺ and CD57⁺ T cells were observed in SC in comparison to controls. Interestingly, SC subjects emphasized increased frequencies of KIR2DL2/L3/S2⁺ T cells compared to CI subjects. Our study underlines that the C2 environment may activate efficient KIR2DL1⁺ NK cells in a viral context and maintain a KIR2DL2/L3/S2⁺ mature T cell response in the absence of KIR2DL2 engagement with its cognate ligands in SC group of HCV–HIV co‐infected European patients.

Keywords: co‐infection, hepatitis C, HLA, KIR, spontaneous clearance

Some KIR/HLA genetic markers and specific lymphocyte subsets are significantly associated with spontaneous clearance (SC) of HCV in European HIV–HCV co‐infected patients. In particular, European HIV–HCV co‐infected individuals with SC of HCV are characterized by an increased frequency of C2C2 environment compared to chronically infected individuals. This HLA‐C environment may favor an effective KIR2DL1+ NK cell response induced by a down‐regulation of HLA‐C molecules mediated by HIV on the cell surface on infected cells. An increased frequency of KIR2DL2/L3/S2+/DNAM‐1+/CD57+ T cells is also observed in European HIV–HCV co‐infected individuals with SC of HCV.

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Introduction

Worldwide, approximately 71 million people are infected with hepatitis C virus (HCV), and 2 million are co‐infected with human immunodeficiency virus (HIV) [1]. Spontaneous clearance (SC) of hepatitis C virus (HCV) has been observed in up to 45% of HCV mono‐infected individuals, while its prevalence is lower in HCV–HIV co‐infected individuals [2]. In addition to clinical and socio‐demographic factors, SC of HCV has been associated with host genetic factors underlying the interindividual variability of HCV [3, 4]. While λ interferon 3 (IFN‐3) provides the most consistent genetic association with SC of HCV, other immune markers, such as HLA and killer cell immunoglobulin‐like receptor (KIR) polymorphic genes, play a role [3].

Although the mechanisms of SC remain not completely understood, both adaptive and innate immunity may contribute to the control of HCV. In particular, natural killer (NK) cells may play a role by their anti‐viral activity. NK cell functions are governed by diverse receptors, including KIR. KIR are clonally expressed on NK cells, and represent a family of inhibitory and activating receptors specific for HLA class I molecules [5]. KIR are also expressed at a low frequency on conventional T cells which exhibit a restricted KIR expression pattern, often dominated by a single KIR [6]. KIR2DL1 recognizes HLA‐Cw molecules from the C2 group (Lys⁸⁰), whereas KIR2DL2/L3, which segregate as alleles of a single locus, recognize remaining HLA‐Cw molecules from the C1 group (Asn⁸⁰) and some HLA‐Cw molecules belonging to the C2 group, such as HLA‐Cw4 [7]. All HLA‐Cw molecules classified as C1 or C2 groups thus represent KIR2DL ligands. KIR3DL1 recognizes the HLA‐Bw4 epitope carried by some HLA‐A and HLA‐B molecules and KIR3DL2 recognizes HLA‐A3/A11 molecules. KIR2DS1 and KIR2DS2, respectively, recognize the C2 and C1 group ligands as their inhibitory counterpart [7, 8]. The KIR3DS1 is the only KIR induced on activated NK cells [9] and its association with Bw4 molecules in controlling some viral infections has suggested a Bw4 specificity even if not clearly demonstrated [10]. More recently, HLA‐F has been demonstrated in vitro as a potential ligand for KIR3DS1 [11]. KIR/HLA class I interactions play a crucial role in the functional education of NK cells meaning that only KIR⁺ NK cells having encountered their KIR ligands are able to lyse HLA class I‐negative target cells [12]. The interaction of an activating KIR with its specific ligand induces the activation of NK cells. At the genetic level, 14 functional KIR genes have been identified. The number and nature of KIR genes vary between individuals defining different KIR haplotypes (A and B) and various KIR genotypes [13]. A large allelic polymorphism with a potential phenotypical and functional impact on NK cells has been also described [1415]. Overall, the functional KIR⁺ NK cell repertoire is defined not only by the KIR genotype but also by the immunological history of the individual and the HLA class I environment. Besides KIR, other NK cell receptors, such as CD94–NKG2A and its activating CD94–NKG2C counterpart, are involved in the sensing of HLA class I down‐regulation following viral infection and NK cell licensing [16]. Activating receptors such as DNAX accessory molecule‐1 (DNAM‐1) also modulate NK cell functions [17]. Lastly, inhibitory and activating receptor expression is strongly associated with the differentiation and maturation status of NK cells. In particular, KIR2D⁺NKG2C⁺ NK cells expressing CD57 define the late mature NK cell subset, which is expanded during CMV infection [18].

Since the last decade, different studies focusing upon KIR genes and HLA class I ligands with SC of HCV have been reported so far [3]. In a large sample size of predominantly HCV mono‐infected people, a major contribution of the KIR2DL3 gene and the corresponding C1 ligand, both at a homozygous status, was associated with SC of HCV in people who inject drugs [19]. These genetic data may suggest a protective KIR2DL3⁺ NK cell activity mediated through the lack of a strong NK cell inhibition, as weak interactions are usually observed between KIR2DL3 and C1 [20], but could also be related to an effect mediated by KIR⁺ T cells. Recent findings showed that inhibitory KIR strengthen the CD8⁺ T cell‐mediated control of HIV and HCV infection [21]. In particular, KIR2DL2 enhanced the protective effect of HLA‐B*57 on SC, as reported in large Caucasian and African cohorts of HCV mono‐infected individuals, suggesting that expression of KIR2DL2 on CD8⁺ T cells may prevent T cell exhaustion even if not demonstrated [22]. A few studies have confirmed the beneficial KIR2DL3/C1C1 genetic association with HCV outcome [23, 24] but many others did not, or reported other KIR/HLA genetic combinations associated with the outcome of HCV‐infected subjects without extensive functional data sustaining a role of KIR⁺ NK or T cells [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]. These inconsistencies may be related to the heterogeneity of the ethnic groups, HLA/KIR genotyping methods or different modes of inheritance for specific markers taken into account [3]. Moreover, most of these KIR/HLA immunogenetic studies assessing their role on the SC of HCV mainly concern only HCV mono‐infected or mixed HIV–HCV co‐infected and HCV mono‐infected subjects. Because beneficial KIR/HLA genetic combinations have been reported in HIV mono‐infected people [37], studies focusing upon HIV–HCV co‐infected subjects are needed. The role of NK cells on HCV infection outcome was mainly investigated in HCV mono‐infected people, but discrepancies remain according to the stage of the disease, the treatment and the methods of NK cell repertoire analysis [38, 39, 40]. Functional studies have also shown the role of T cell responses in the SC of HCV [41]. Here, we investigated for the first time the potential implication of both NK and T cells on SC of HCV in exclusively HIV–HCV co‐infected individuals, taking into account KIR/HLA genetic in investigating NK and T cell compartments in comparison to healthy unaffected controls and chronically infected counterparts.

Materials and methods

Study population

We included subjects from the French national cohort (HEPAVIH ANRS CO13) of HIV–HCV co‐infected individuals with either chronic HCV infection (CI) (n = 79), cured after treatment (n = 72), or with a spontaneous clearance (SC) of HCV (n = 53). Inclusion criteria in the HEPAVIH cohort were adult HIV–HCV co‐infected individuals with either positive HCV RNA (active chronic HCV infection) with a possible negative viral burden during the follow‐up (cured at least 6 months after HCV treatment) or spontaneously negative HCV RNA at diagnosis without any HCV treatment (SC) whatever the date of HIV and HCV contamination and HBV status, and signed informed conse,nt. A second subset (VICKIR cohort) of HIV–HCV co‐infected subjects for which frozen peripheral blood mononuclear cells (PBMC) were available was enrolled into the Infectious Diseases Department of Nantes University Hospital, including people with SC of HCV (n = 15) and with failure to first‐generation treatment of HCV (n = 12) (Supporting information, Table S1). Overall, 68 pooled HIV–HCV co‐infected SC and 163 HIV–HCV co‐infected CI individuals were studied. Clinical and virological data of all HIV–HCV co‐infected individuals are presented in Table 1.

Table 1.

Associations between baseline clinical and biological characteristics and spontaneous clearance in HIV–HCV co‐infected individuals

		All individuals (N = 231)		SC individuals (n = 68)		CI individuals (n = 163)		Crude OR (95% confidence interval)	P *
		n/median	%/(IQR)	n/median	%/(IQR)	n/median	%/(IQR)	Crude OR (95% confidence interval)	P *
Age	Years	45·7	(42·7–48·9)	48·5	(44·9–52·4)	44·7	(42·1–47·6)	1·113 (1·056–1·177)	< 0·001
Age	Unknown	4	1·7	4	5·9
Gender	Male	163	71·8	43	67·2	120	73·6	1·000 (Ref)
	Female	64	28·2	21	32·8	43	26·4	1·363 (0·720–2·538)	0·333
	Unknown	4	1·7	4	5·9
Geographic origin	European	191	84·1	57	89·1	134	82·2	1·000 (Ref)
	African	36	15·9	7	10·9	29	17·8	0·567 (0·218–1·305)	0·208
	Unknown	4	1·7	4	5·9
Time since HIV diagnosis (1st positive serology)	Months	18·6	(13·5–21·3)	18·5	(12·2–24·3)	18·6	(13·8–20·9)	1·035 (0·989–1·086)	0·147
Time since HIV diagnosis (1st positive serology)	Unknown	5	2·2	4	5·9	1	0·6
Time since HCV diagnosis (1st positive serology)	Months	10·7	(5·9–15·3)	12·2	(7·2–16·8)	9·5	(4·9–13·5)	1·081 (1·028–1·139)	0·003
Time since HCV diagnosis (1st positive serology)	Unknown	8	3·5	4	5·9	4	2·5
HIV stage CDC	A	99	44	27	42·9	72	44·4	1·000 (Ref)
	B	61	27·1	19	30·2	42	25·9	1·206 (0·594–2·422)	0·599
	C	65	28·9	17	27	48	29·6	0·944 (0·459–1·906)	0·874
	Unknown	6	2·6	5	7·4	1	0·6
HIV contamination mode	Sexual	65	28·6	26	40·6	39	23·9	1·000 (Ref)
	IVDU	155	68·3	36	56·2	119	73	0·454 (0·244–0·846)	0·013
	Sexual and IVDU	2	0·9	0	0	2	1·2
	Other	5	2·2	2	3·1	3	1·8	1·000 (0·125–6·434)	1·000
	Unknown	4	1·7	4	5·9	0	0
HCV contamination mode	Sexual	25	12·2	12	18·8	13	9·2	1·000 (Ref)
	IVDU	146	71·2	39	60·9	107	75·9	0·395 (0·165–0·948)	0·035
	Other	34	16·6	13	20·3	21	14·9	0·671 (0·233–1·910)	0·454
	Unknown	26	11·3	4	5·9	22	13·5
On ART	No	5	2·2	4	5·9	1	0·6	1·000 (Ref)
On ART	Yes	226	97·8	64	94·1	162	99·4	0·099 (0·005–0·683)	0·040
Nadir CD4⁺ T cells	Cell/mm³	146	(66–244·5)	188	(84·5–251·5)	133	(60–232·8)	1·002 (1·001–1·004)	0·017
Nadir CD4⁺ T cells	Not available	16	6·9	5	7·4	11	6·7
% Nadir CD4⁺ T cells		17	(8–23·9)	18	(9–26)	16	(8–23·3)	1·021 (0·994–1·048)	0·135
% Nadir CD4⁺ T cells	Not available	35	15·2	11	16·2	24	14·7
HIV viral load	Copies/ml	40	(40–50)	40	(20–40)	40	(40–50)	1·000 (1·000–1·000)	0·984
HIV viral load	Not available	4	1·7	4	5·9	0	0
CD4⁺ T cells	Cell/mm³	455	(273–607·5)	521·5	(369·2–705·2)	419	(257·5–565·5)	1·001 (1·000–1·002)	0·019
CD4⁺ T cells	Not available	4	1·7	4	5·9	0	0
HCV genotype ^†	1	95	58·3	2	100	93	57·8
	2	1	0·6			1	0·6
	3	39	23·9			39	24·2
	4	28	17·2			28	17·4
	Not available	68	29·4	66	97·1	2	1·2
HCV RNA	UI/ml	70 987	(15–1 600 000)	15	(15–15)	134 124·5	(15–1 758 138·2)	1·000 (1·000–1·000)	0·304
HCV RNA	Undetectable	54	23·4	53	77·9	1	0·6
Fibroscan (kPa) ^†	F0–F3	127	72·6	17	70·5	110	89·5	1·000 (Ref)
	F4 > 12·5	48	27·4	2	29·5	46	10·5	0·281 (0·043–1·035)	0·10
	Not available	56		49		7
Anti‐HCV treatment ^†	Untreated	68	29·4	68	100
	Treated/resolved	72	31·2			72	44·2
	Treated/unresolved	91	39·4			91	55·8
IL‐28b genotype ^†	C/C	52	34·4			52	34·4
	C/T	79	52·3			79	52·3
	T/T	20	13·2			20	13·2
	Not available	80	34·6	68	100	12	7·4

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Anti‐HCV treatment = pegylated interferon + ribavirin or direct acting anti‐viral. P‐values = bivariate logistic regressions; CDC = Centers for Disease Control; CI = chronic infection; fibroscan ranging from F0 to F4; HCV = hepatitis C virus; HIV = human immunodeficiency virus; (RNA); IVDU = intravenous drug user; ART = anti‐retroviral treatment; kPa = kilopascal; SC = spontaneous clearance; IL = interleukin; IQR = interquartile range; OR = odds ratio.

^{^†}

P‐values not calculated because of unavailable data in SC individuals;

^{^††}

P‐values not relevant.

Significant associations found by bivariate analyses are highlighted in bold type.

Population control consisted of French healthy volunteer blood donors (n = 100), all HIV‐ and HCV‐negative and from European origin, recruited at the Blood Transfusion Center (EFS, Nantes, France). In accordance with the Declaration of Helsinki, informed signed consent was collected prior to the study in all HIV–HCV co‐infected subjects and controls. Declaration of the preparation and conservation of the controls biocollection (DC‐2014‐2340) has been submitted to the French Ministry of Research and had received agreement from IRB (2015‐DC‐1) since 2015.

PBMC and cell lines

PBMCs were isolated from citrate–phosphate–dextrose blood samples from controls and VICKIR subjects (Supporting information, Table S1), using Ficoll‐Hypaque density gradient centrifugation (Lymphoprep; Axis‐Shield, Oslo, Norway) and cryopreserved. The HLA class I‐deficient lymphoblastoid cell line 721.221, referred to as 221 cells (ATCC CRL‐1855), was used to assess the degranulation potential of NK cells. The 221‐cell line was cultured in RPMI‐1640 medium (Life Technologies, Paisley, UK) containing glutamine (Life Technologies) and penicillin–streptomycin (Life Technologies) supplemented with 10% heat‐inactivated fetal calf serum (FCS) (Life Technologies). Mycoplasma tests performed by polymerase chain reaction (PCR) were negative for this cell line.

KIR and HLA class I genotyping

KIR genotyping were performed by multiplex PCR using KIR specific primers [42] on genomic DNAs from all HIV–HCV co‐infected subjects (n = 231) and controls (n = 100). KIR genotypes were assigned following the presence or absence of activating KIR genes: the AA KIR genotype defined by the presence of only KIR2DS4 as activating KIR genes, the AB KIR genotypes defined by the presence of several activating KIR genes, including KIR2DS4, and the BB KIR genotypes defined by the presence of several activating KIR genes except KIR2DS4. Typing of HLA‐A, ‐B and ‐C genes were performed on all HIV–HCV co‐infected subjects and controls by Luminex technology (Thermo Fisher Scientific, Waltham, MA, USA). HLA‐A, ‐B and ‐C typing were further divided in terms of specific KIR ligands: HLA‐A3/A11⁺ for KIR3DL2, HLA‐A and/or HLA‐B Bw4+ for KIR3DL1/S1, C1C1⁺, C1C2⁺ and C2C2⁺ for KIR2DL1/2/3/S1/S2. HLA‐C*04 was included in the C2 group except when KIR2DL2/L3/HLA‐C interactions were considered, as KIR2DL2/L3 interacts with the HLA‐Cw4 molecule in addition to all HLA‐C molecules belonging to group C1 [7].

Phenotyping of lymphocyte subsets by multi‐color flow cytometry

PBMCs were isolated as previously described [7, 43, 44, 45, 46]. The phenotypes of living NK (CD3⁻CD56⁺), T (CD3⁺CD56⁻) and CD56⁺ T (CD3⁺CD56⁺) cells were gated from PBMC based on side‐scatter/forward‐scatter (SSC/FSC) parameters by multi‐color flow cytometry (MFC, eight colors) using the following monoclonal antibodies (mAbs): anti‐CD3‐peridinin chlorophyll (PerCP) (SK7; BD Biosciences, San José, CA, USA), anti‐CD56‐allophycocyanin‐cyanin 7 (APC‐Cy7) (HCD56; Biolegend, San Diego, CA, USA), anti‐CD56‐phycoerythrin (PE) (HCD56; Biolegend), anti‐KIR2DL1‐fluorescein isothiocyanate (FITC) (143211; R&D Systems, Minneapolis, MN, USA), anti‐KIR2DL1/S1‐PE (EB6; BD Biosciences), anti‐KIR2DL1/S1‐APC (EB6; BD Biosciences), anti‐KIR2DL2/L3/S2‐PC7 (GL183; BD Biosciences), anti‐KIR2DL3‐FITC (180701; R&D Systems), anti‐KIR2DS4‐APC (p50) (FES172; BD Biosciences), anti‐KIR3DL1/S1‐PE (Z27; BD Biosciences), anti‐KIR3DL1‐FITC (DX9; Biolegend), anti‐KIR2DL3/S2‐AF647 (1F12; EFS, Nantes, France) [47], anti‐NKG2A‐PC7 (Z199; BD Biosciences), anti‐NKG2C‐PE (134591; R&D Systems), anti‐CD57‐FITC (HNK1; Biolegend) and anti‐DNAM‐1‐BV510 (11A8; Biolegend). MFC phenotypical data were collected using a eight‐color flow cytometry (FACSCanto II; BD Biosciences) and analyzed with FlowJo version 10.2 software (Tree Star Inc. LLC, Ashland, OR, USA).

CD107a mobilization assay detected by flow cytometry

Briefly, PBMC were preincubated with the anti‐CD107a‐BV421 (H4A3; Biolegend) mAb at 37°C. NK cell degranulation was assessed after incubation for 5 h alone (control) or with 221 target cells (E/T ratio = 1 : 1) with brefeldin A (Sigma, St Louis, MO, USA) at 10 µg/ml for the last 4 h. Experiments were carried out in duplicate for each condition. After a membrane staining to target different NK cell subsets, MFC data were collected on a FACSCanto II instrument and analyzed with FlowJo version 10.2 software (Tree Star). Representative values of CD107a⁺ NK cells after stimulation with 221 target cells was obtained by subtracting the control.

Statistical analysis

For demographic characteristics of HIV–HCV co‐infected subjects (Table 1), descriptive analyses were performed. Categorical data were presented as numbers and frequencies of each modality and the quantitative data with their median and interquartile range. Frequencies of KIR genes, KIR ligands and KIR/KIR ligand genetic combinations were compared between controls (Ctrl), HIV–HCV co‐infected SC and CI subjects. Statistical differences in KIR–KIR ligand frequencies were analyzed with unpaired t‐tests or the one‐way analysis of variance (anova) test for multiple comparisons using GraphPad Prism version 6.0 software (San Diego, CA, USA). All KIR/KIR ligand genotypical data obtained were compared with variables taken into account; namely, patient‐related parameters and the evaluation criteria such as HIV viral load, duration of HIV disease, the number and nadir of CD4⁺ T cells and HCV genotypes. The role of KIR–HLA combinations was explored, taking into account response to anti‐HCV therapy, HCV and HIV viremia, CD4 T cell counts, interleukin (IL)‐28B, age and gender. The description of the different variables was first carried out on all HIV–HCV co‐infected individuals, according to the group of individuals (SC versus CI), then restricted only to individuals of European origin. Bivariate analyses were performed on individuals of European origin to compare the characteristics of SC and CI individuals. A multivariate analysis using a logistic regression, also to compare the characteristics of SC and CI, was then carried out, integrating the variables having a P‐value less than 0·2, and then removing the different non‐informative variables according to the Akaike information criterion (AIC). The results of these analyses are presented as odds ratios (ORs), with their associated 95% confidence interval. All statistical analyses were performed using r version 3.4.3 software.

Frequencies of NK, T, CD56⁺ T cells and CD107a⁺ NK cells between HIV–HCV co‐infected subjects (SC and CI) and controls (Ctrl) were analyzed with the one‐way anova test for multiple comparisons using GraphPad Prism version 6.0 software. P‐values < 0·05 were considered statistically significant.

Results

Clinical and immunovirological characteristics of HIV–HCV co‐infected individuals

In the population of HIV–HCV co‐infected adults (n = 231), including subjects with SC of HCV (n = 68) and CI (n = 163), SC were significantly older at HCV diagnosis, with a longer duration of known HCV infection, less frequently intravenous drug users (IVDU), a higher CD4⁺ T cell nadir and CD4⁺ T cell counts compared to CI individuals (Table 1). Gender, geographical origin and HIV Centers for Disease Control and Prevention (CDC) stage were not different within the two groups.

Association of C2C2 KIR ligand with spontaneous clearance of HCV in European HIV–HCV co‐infected individuals

Worldwide population studies have reported that KIR gene, KIR genotype and KIR ligand frequencies differ between populations [48]. In this study, HIV–HCV co‐infected individuals were either from European (84·1%) or African (15·9%) geographic origin. To highlight any potential KIR–KIR ligand genetic combinations associated with SC of HCV, polymorphic KIR and HLA class I genes were first assigned in the entire cohort of HIV–HCV co‐infected subjects. KIR/KIR ligand frequencies were similar between SC and CI and between HIV–HCV co‐infected individuals and unaffected healthy blood donors (Ctrl), all from French origin (data not shown).

The absence of associations of KIR/KIR ligand genetic combinations with SC of HCV in the entire cohort led us to restrict our analysis to European people, who were predominant (Table 1). Specific HLA‐A and HLA‐B Bw4 KIR ligand frequencies were not statistically different between SC and CI subjects (Fig. 1a). Interestingly, European SC were characterized by increased frequencies of HLA‐B Bw4 I80 and HLA‐A⁺HLA‐B Bw4 compared to Ctrl (P = 0·013 and P = 0·044, respectively) (Fig. 1a), suggesting a favored Bw4 environment. Conversely, the frequency of HLA‐B Bw4⁻Bw4⁻ was decreased in SC compared to Ctrl (P = 0·047) (Fig. 1a). European CI were characterized by a decreased frequency of HLA‐A Bw4 compared to Ctrl (P = 0·034) and increased frequencies of HLA‐A⁺HLA‐B Bw4 and HLA‐B Bw4⁻Bw4⁻ compared to Ctrl (P = 0·013 and P = 0·0095, respectively), as mentioned for SC subjects (Fig. 1a). Besides Bw4 ligands, European SC were characterized by an increased frequency of C2C2 (P = 0·05 and P = 0·025 HLA‐C*04 excluded) compared to CI (Fig. 1b). Interestingly, the frequency of C2C2 was particularly high in European SC versus Ctrl (Fig. 1b). Besides KIR ligands, although KIR3DL1⁺/Bw4 genetic combinations were not statistically different between SC and CI individuals (Fig. 1c), European SC exhibited a higher frequency of KIR3DS1⁺/HLA‐B Bw4 I80⁺ compared to CI (P = 0·044) (Fig. 1c). Due to a favored Bw4 environment, SC individuals showed a higher frequency of the KIR3DL1⁺/HLA‐A/B Bw4 genetic combination compared to Ctrl (P = 0·031) (Fig. 1c). Interestingly, in accordance with the predominance of C2C2 ligands, European SC were characterized by a higher frequency of KIR2DL1⁺/C2C2 (P = 0·023) and KIR2DL2/3⁺/C2C2 (P = 0·032 and P = 0·027 HLA‐C*04 excluded) genetic combinations (Fig. 1d). Conversely, a lower frequency of the KIR2DL2/3⁺/C1⁺ (i.e. C2C2⁻) genetic combination was observed in European SC (P = 0·032 and P = 0·041 HLA‐C*04 included) compared to European CI (Fig. 1d). European CI exhibited a higher frequency of KIR2DL2/3⁺/C1⁺ compared to Ctrl (P = 0·0004, HLA‐C*04 included) (Fig. 1d). These genetic KIR/HLA associations suggest in particular that NK cells from European SC preferentially evolved in a C2C2 environment. Bivariate analysis confirmed the beneficial associations of C2C2, KIR2DL1⁺/C2C2, KIR2DL2/3⁺/C2C2 and KIR3DS1⁺/HLA‐B Bw4 I80 genetic combinations with SC of HCV in European HIV–HCV co‐infected subjects (Table 2). Besides KIR/KIR ligand genetic combinations, European SC were significantly older, characterized by a lower proportion of IVDU HIV or HCV contamination and a higher number of nadir CD4⁺ T cells compared to European CI (Table 2). Multivariate analysis confirmed on a limited sample size that the C2C2 environment and, to a lesser extent, age and IVDU HIV contamination, were associated with SC of HCV in European HIV–HCV co‐infected subjects (Table 3).

Fig. 1 — C 2C2, killer‐cell immunoglobulin‐like receptor (KIR)2DL1⁺/C2C2, KIR2DL2/3⁺/C2C2 and KIR3DS1⁺/human leukocyte antigen (HLA)‐Bw4 I⁸⁰ genetic combinations associated with spontaneous clearance of hepatitis C virus (HCV) in European human immunodeficiency virus (HIV)–HCV co‐infected subjects. KIR ligand frequencies determined from HLA‐A, HLA‐B (a) and HLA‐C typing (b). KIR3DL1/S1/HLA‐A/B Bw4 (c) and KIR2DL1/2/3/S1/2/HLA‐C (d) genetic combination frequencies established in European HIV–HCV co‐infected subjects with spontaneous clearance (SC, n = 57) and with chronic infection (CI, n = 134) of HCV and in healthy volunteer blood donors [control (Ctrl), n = 100]. Statistical significance (*P ≤ 0·05; **P ≤ 0·01; ***P ≤ 0·005) between groups was determined using the χ² test.

Table 2.

Bivariate analysis of clinical, virological factors and KIR/KIR ligand genetic combinations associated with spontaneous clearance of HCV in European HIV–HCV co‐infected individuals

		European SC (n = 57)		European CI (n = 134)		OR (95% confidence interval)	P *
		n/median	%/(IQR)	n/median	%/(IQR)	OR (95% confidence interval)	P *
Age	Years	48·1	(44·8–51·3)	45	(42·2–47·6)	1·096 (1·038–1·636)	0·002
Gender	Male	38	66·7	94	70·1		Ref
Gender	Female	19	33·3	40	29·9	1·18 (0·60–2·27)	0·63
Time since HIV diagnosis	Months	19·8	(12·3–24·7)	18·8	(14·8–21·1)	1·033 (0·98–1·09)	0·20
Time since HIV diagnosis	Unknown	0		1	0·7
Time since HCV diagnosis	Months	12·7	(7–16·8)	9·5	(4·7–13·6)	1·078 (1·024–1·14)	0·005
Time since HCV diagnosis	Unknown	0		3	2·2
HIV CDC stage	A	25	44·6	62	46·6		Ref
	B	17	30·4	32	24·1	1·32 (0·62–2·78)	0·47
	C	14	25	39	29·3	0·89 (0·41–1·90)	0·77
	NA	1	1·8	1	0·7
HIV contamination mode	Sexual	23	40·4	30	22·4		Ref
	IVDU	32	56·1	101	75·4	0·41 (0·21–0·81)	0·010
	Sexual and IVDU		2	1·5
	Other	2	3·5	1	0·7	2·61 (0·24–58·19)	0·45
HCV contamination mode	Sexual	11	19·3	10	8·8		Ref
	IV	35	61·4	89	78·8	0·36 (0·14–0·92)	0·032
	Other	11	19·3	14	12·4	0·71 (0·22–2·29)	0·57
	Unknown	0		21	15·7
On ART	No	0		1	0·7
On ART	Yes	57		133	99·3
Nadir CD4⁺ T cells	Cell/mm³	188·5	(87·2–244·2)	130·5	(62·8–232)	1·00 (1·00–1·00)	0·041
Nadir CD4⁺ T cells	Not available	1	1·8	10	7·5
% Nadir CD4⁺ T cells		18	(9·1–24·8)	15	(8–23·1)	1·021 (0·99–1·05)	0·15
% Nadir CD4⁺ T cells	Not available	6	10·5	21	15·7
HIV viral load	Copies/ml	20	(20–40)	40	(40–50)	1·00 (1·00–1·00)	0·95
CD4⁺ T cells	Cell/mm³	499	(340–680)	432·5	(261–585·8)	1·00 (1·00–1·00)	0·087
HCV genotype ^†	1	2	100	79	59
	2
	3			27	20·1
	4			28	20·9
	Not available	55	96·5
HCV RNA	UI/ml	15	(15–15)	127 398	nn	1·00 (1·00–1·00)	0·38
HCV RNA	Undetectable/not available	43	75·4	1	0·7
Fibroscan (kPa) ^†	F4 > 12·5 kPa	17	100	42	32·8
Fibroscan (kPa) ^†	Not available	40	70·2	6	4·5
Anti‐HCV treatment^‡	Untreated	57	100	0
	Treated/resolved		54	40·3
	Treated/unresolved		80	59·7
IL28b genotype ^†	C/C			36	29
	C/T			71	57·3
	T/T			17	13·7
	Not available	57	100	10	7·5
C2C2⁺	No	40	70·2	106	84·1		Ref
	Yes	17	29·8	20	15·9	2·25 (1·07–4·74)	0·031
	Not available			8
C2C2⁺ (C*04 excluded)	No	44	77·2	113	89·7		Ref
	Yes	13	22·8	13	10·3	2·57 (1·10–6·03)	0·028
	Not available			8
2DL1⁺/C2⁺	No	20	35·1	47	37·6		Ref
	Yes	37	64·9	78	62·4	1·11 (0·58–2·17)	0·74
	Not available			9
2DL1⁺/C2C2⁺	No	41	71·9	108	86·4		Ref
	Yes	16	28·1	17	13·6	2·48 (1·14–5·39)	0·021
	Not available			9
2DL1⁺/C1C1⁺	No	40	70·2	84	67·2		Ref
	Yes	17	29·8	41	32·8	0·87 (0·43–1·70)	0·69
	Not available			9
2DL2 and/or 2DL3⁺/C1⁺	No	17	29·8	20	16·0		Ref
	Yes	40	70·2	105	84·0	0·45 (0·21–0·95)	0·034
	Not available			9
2DL2 and/or 2DL3⁺/C1⁺ (C*04 included)	No	13	22·8	14	11·2		Ref
	Yes	44	77·2	111	88·8	0·43 (0·18–0·99)	0·045
	Not available			9
2DL2 and/or 2DL3⁺/C2C2⁺	No	40	70·2	105	84·0		Ref
	Yes	17	29·8	20	16·0	2·23 (1·06–4·70)	0·034
	Not available			9
2DL2 and/or 2DL3⁺/C2C2⁺ (C*04 excluded)	No	44	77·2	112	89·6		Ref
	Yes	13	22·8	13	10·4	2·55 (1·09–5·97)	0·030
	Not available			9
2DL3‐2DL3⁺/C1C1⁺	No	48	84·2	102	81·6		Ref
	Yes	9	15·8	23	18·4	0·83 (0·34–1·88)	0·66
	Not available			9
2DL3‐2DL3⁺/C1C1⁺ (C*04 included)	No	45	78·9	91	72·8		Ref
	Yes	12	21·1	34	27·2	0·71 (0·33–1·48)	0·38
	Not available			9
3DL1⁺/HLA‐A and/or HLA‐B Bw4⁺	No	11	19·3	30	23·8		Ref
	Yes	46	80·7	96	76·2	1·31 (0·62–2·94)	0·50
	Not available			8
3DL1⁺/HLA‐A and/or HLA‐B Bw4‐	No	47	82·5	96	77·4		Ref
	Yes	10	17·5	28	22·6	0·72 (0·31–1·59)	0·44
	Not available			10
3DL1⁺/HLA‐B Bw4 80T⁺	No	38	66·7	76	61·3		Ref
	Yes	19	33·3	48	38·7	0·79 (0·40–1·52)	0·49
	Not available			10
3DL2⁺/HLA‐A3, A11⁺	No	40	70·2	79	62·2		Ref
	Yes	17	29·8	48	37·8	0·70 (0·35–1·35)	0·30
	Not available			7
2DS1⁺/C2⁺	No	48	84·2	101	80·8		Ref
	Yes	9	15·8	24	19·2	0·79 (0·33–1·78)	0·58
	Not available			9
2DS1⁺/C1C1⁺	No	46	80·7	112	89·6		Ref
	Yes	11	19·3	13	10·4	2·06 (0·85–4·94)	0·10
	Not available			9
2DS2⁺/C1⁺	No	33	57·9	69	55·2		Ref
	Yes	24	42·1	56	44·8	0·90 (0·47–1·68)	0·73
	Not available			9
2DS2⁺/C2C2⁺	No	48	84·2	115	92·0		Ref
	Yes	9	15·8	10	8·0	2·16 (0·81–5·68)	0·12
	Not available			9
3DS1⁺/HLA‐B Bw4⁺	No	42	73·7	95	76·6		Ref
	Yes	15	26·3	29	23·4	1·17 (0·56–2·38)	0·67
	Not available			10
3DS1⁺/HLA‐B Bw4‐	No	53	93·0	111	89·5		Ref
	Yes	4	7·0	13	10·5	0·64 (0·18–1·92)	0·46
	Not available			10
3DS1⁺/HLA‐B Bw4 I80⁺	No	44	77·2	110	88·7		Ref
	Yes	13	22·8	14	11·3	2·32 (1·00–5·36)	0·047
	Not available			10

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HLA = human leukocyte antigen; HIV = human immunodeficiency virus; HCV = hepatitis C virus; KIR= killer‐cell immunoglobulin‐like receptor; SC = spontaneous clearance; CI = chronic infection; CDC = Centers for Disease Control; (RNA); IVDU = intravenous drug user; ART = anti‐retroviral treatment; kPa = fibroscan ranging F4 kilopascal; anti‐HCV treatment = pegylated interferon + ribavirin or direct‐acting anti‐viral; IQR = interquartile range.

^{^†}

P‐values not calculated because of unavailable data in SC individuals; ^‡ P‐values not relevant.

Significant associations found by bivariate analyses are highlighted in bold type.

Table 3.

Multivariate analysis results of variables associated with spontaneous clearance of hepatitis C virus in European HIV–HCV co‐infected individuals

	Odds ratio	95% confidence interval	P‐value*
Age	1·10	1·033–1·18	0·0048
HIV contamination other mode than IVDU	1·00		Ref
IVDU HIV contamination	0·45	0·21–0·95	0·036
% Nadir CD4⁺ T cells	1·026	0·99–1·06	0·12
C2C2 presence versus absence	4·30	1·57–12·25	0·005
KIR2DS1/C1C1 presence versus absence	2·65	0·92–7·62	0·068

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IVDU = intravenous drug user; HIV = human immunodeficiency virus; HCV = hepatitis C virus.

Significant associations are highlighted in bold type.

Functional KIR2D+ NK cell repertoire in European HIV–HCV co‐infected subjects with spontaneous clearance of HCV

As C1 and C2 KIR ligands impact upon the phenotypical and functional composition of the KIR2D⁺ NK cell repertoire, we investigated the KIR⁺ NK cell phenotype in representative Ctrl, HIV–HCV co‐infected SC and CI subjects from the VICKIR cohort displaying different HLA‐C environmental and KIR genotypes (Supporting information, Table S1). Dates of first HIV‐positive serology were prior to those of first HCV‐positive serology for 10 of 14 SC and seven of 10 CI subjects (Supporting information, Table S1). The frequency of CMV⁺ was higher in SC versus CI subjects (62 versus 44%) (Supporting information, Table S1). Although a small sample size, C2C2 environment was more prevalent in SC (43%) compared to CI (30%) subjects (Supporting information, Table S1). A different combination of specific anti‐KIR mAbs gives us the opportunity to define mono‐specific KIR⁺ NK cell subsets in accordance with the KIR genotype (Fig. 2). European SC individuals exhibit the same frequencies of total NK cells (Fig. 2a), KIR⁺ (Fig. 2b–d), NKG2A⁺, NKG2C⁺ (Fig. 2e) and DNAM‐1⁺ (Fig. 2f) NK cell subsets compared to Ctrl. In contrast, CI exhibited decreased frequencies of KIR2DS1⁺/L1⁻ (P = 0·041 and P = 0·032 in CMV⁻ restricted individuals) and KIR2DL2⁺ (P = 0·034) NK cells compared to SC and of KIR2DL1/S1⁺ (P = 0·013), KIR2DL1⁺ (P = 0·024), KIR2DL1⁺/S1⁺ (P = 0·031), KIR2DL1/S1⁺/L2/3/S2⁻ (P = 0·039) NK cells compared to Ctrl (Fig. 2b,c). Both SC and CI showed a decreased frequency of CD57⁺ NK cells compared to Ctrl (P = 0·026 and P = 0·017, respectively), (Fig. 2f) suggesting fewer differentiated NK cells. A decreased frequency of CD57⁺ NK cells in SC compared to Ctrl (P = 0·038) was observed in CMV⁺ individuals, whereas a decreased frequency of CD57⁺ NK cells in CI compared to Ctrl (P = 0·0010) and an increased frequency of CD57⁺ NK cells in SC compared to CI (P = 0·0077) were observed in CMV⁻ individuals (Fig. 2f).

In addition to the unaltered KIR2D⁺ NK cell phenotype in SC compared to Ctrl KIR2DL1/S1⁺/L2/3/S2⁻ (Fig. 2g), KIR2DL2/3/S2⁺/L1/S1⁻ and KIR3DL1⁺ (data not shown) NK cells from SC individuals are functional in terms of degranulation and exhibit CD107a⁺ NK cell frequencies higher to Ctrl and to CI individuals, although results did not reach significance due to a limited sample size. Overall, SC of HCV in European HIV–HCV co‐infected subjects was associated with functional KIR2D⁺ NK cells sustaining a beneficial potential of degranulation of KIR2DL1⁺ NK, cells especially in a C2 environment.

Mature KIR2DL2/3/S2+ T cells as a hallmark of spontaneous clearance of HCV in European HIV–HCV co‐infected individuals

In addition to NK cells, a KIR impact on T cell‐mediated adaptive immunity and a role of KIR⁺ T cells in HIV and HCV infection has been reported [21]. KIR are expressed on non‐conventional CD56⁺ T cells, which have a particular phenotype potentially modulated by KIR being expressed at a high frequency. As the CD56⁺ T cell phenotype has never been investigated in HIV–HCV co‐infected individuals, we performed high‐resolution phenotyping of CD56⁺ T cells in European SC, CI and Ctrl from the same individuals (Supporting information, Table S1). No significant differences of CD56⁺ T cell phenotype were observed between SC, CI subjects and Ctrl (data not shown). In parallel, high‐resolution phenotyping of conventional T cells was investigated on European SC, CI and Ctrl. Although SC and Ctrl exhibit the same frequencies of T cells, CI subjects showed a decreased frequency of T cells compared to Ctrl (P = 0·038, Fig. 3a). KIR2DL1/S1⁺, KIR3DL1⁺ and KIR2DS4⁺ T cell subset frequencies were not statistically different in SC, CI and Ctrl, all at low frequencies (data not shown). Interestingly, KIR2DL2/3/S2⁺ T cell frequencies were significantly higher in SC compared to Ctrl (P = 0·042) and to CI (P = 0·015) (Fig. 3b). The expansion of KIR2DL2/3/S2⁺ T cells in SC compared to Ctrl and CI was confirmed in CMV⁺ individuals (P = 0·019 and P = 0·012, respectively) (Fig. 3b). The increase of KIR2DL2/3/S2⁺ T cells in SC patients could be linked to an increase of KIR2DL2⁺ T cells, especially in C2⁺ SC subjects compared to C2⁺ Ctrl (P = 0·02) and C2⁺ CI subjects (P = 0·040), although a limited sample size of KIR2DL2⁺ genotyped individuals was included (data not shown).

Besides KIR, SC showed an increased frequency of CD57⁺ T cells compared to Ctrl ( P = 0·005, Fig. 3c). This increase remained significant both in CMV⁺ and CMV⁻ individuals (P = 0·027 and P = 0·022, respectively, Fig. 3c). CI showed an increased frequency of CD57⁺ T cells compared to Ctrl, but only restricted to CMV⁺ individuals (P = 0·016, Fig. 3c). SC showed an increased frequency of DNAM‐1⁺ T cells compared to Ctrl ( P < 0·0001, Fig. 3d). Increased frequencies of DNAM‐1⁺ T cells in SC compared to Ctrl was observed both in CMV⁺ and CMV⁻ individuals (P = 0·010 and P = 0·0005, Fig. 3d). CI showed an increased frequency of DNAM‐1⁺ T cells compared to Ctrl (P < 0·0001, Fig. 3d). This increase was observed both in CMV⁺ and CMV⁻ individuals (P = 0·0078 and P ≤ 0·0001, Fig. 3d).

Overall, these phenotypical data sustain a beneficial impact of differentiated KIR2DL2/3/S2⁺/CD57⁺/DNAM‐1⁺ T cells in SC of HCV in HIV–HCV co‐infected individuals.

Discussion

Our study examined for the first time, to our knowledge, the role of KIR/HLA genetic combinations combined with NK, T, CD56⁺ T cell phenotyping and NK cell degranulation on the SC of HCV in French HIV–HCV co‐infected people. Although a limited sample size, multivariate analysis confirmed increased frequencies of C2C2 in SC compared to CI subjects only in those of European origin, underscoring the importance of both individual background and HLA class I environment associated with a specific KIR2D⁺ NK and T cell repertoire.

In a previous study involving a large cohort of UK and US HCV‐infected people, the presence of C1C1 in KIR2DL3 homozygous individuals was associated with the SC of HCV [19]. This protective KIR2DL3/C1C1 association was observed both in Caucasians and African Americans, but only in non‐transfused individuals [19]. More recently, the KIR3DL1/HLA‐B Bw4^80T genetic combination was found associated with SC of HCV in German people who injected drugs [33]. However, in these two studies, mixed HCV mono‐infected – who were predominant – and HIV–HCV co‐infected people were included, preventing any comparison. In our HIV–HCV co‐infected cohort, neither KIR2DL3/C1C1 nor KIR3DL1/HLA‐Bw4^80T genetic combinations were associated with SC of HCV. Individual background and mode of HIV and/or HCV contamination may account for these discordances. In addition to KIR/HLA polymorphism, one cannot exclude the role of the favorable IL‐28B CC genotype in SC of HCV [49] and the HCV genotype not taken into account, due to unavailable typing for SC individuals in this retrospective and multi‐centric study. Of note, HCV is not accessible in SC people. For this reason, genotyping for subtype and IL‐28B identification is not feasible.

Besides KIR/HLA genetic markers, we found that older age at the time of HCV diagnosis and less IVDU contamination were associated with SC of HCV. A recent meta‐analysis found that the likelihood of SC of HCV was lower in males, HIV‐infected individuals, absence of HBV co‐infection, asymptomatic infection, black race, non‐genotype 1 infection, older age and alcohol or drug problems [50]. Our results are similar except for age. However, we took into account the age at time of HCV diagnosis and not the age at time of SC, which may be several years apart and explain the difference.

In our study, no association of total NK cell frequencies with the SC of HCV or CI was found as reported [39]. Interestingly, we reported no alteration of both KIR2D⁺ NK cell phenotype and function in terms of degranulation in SC individuals. The preferential C2C2 environment of SC may sustain a preponderant role of licensed KIR2DL1⁺ NK cells. Indeed, KIR2DL1⁺ NK cells specifically interact with HLA‐Cw molecules of C2 specificity with a strong binding, whereas KIR2DL1/3⁺ NK cells interact with HLA‐Cw molecules of C1 specificity with a weak binding and also with some HLA‐Cw molecules belonging to the C2 group [7]. However, KIR2DL1⁺ NK cell functionality in SC individuals was only focused upon the degranulation potential in response to HLA class I‐deficient targets in our study, and not against viral antigens. Moreover, one cannot exclude an antibody‐dependent cellular cytotoxicity (ADCC) or a modulation of cytokine production by KIR⁺ NK cells in SC versus CI individuals, although these were not evaluated in our retrospective study due to limited cellular material. In contrast, lower frequencies of KIR2D⁺ NK cells in CI suggest a deleterious imprint of HCV and/or HIV on the NK cell repertoire in chronically infected HIV–HCV individuals. So far, few studies have analyzed KIR⁺ NK cell repertoire in HCV‐infected individuals. It has been shown that KIR3DL1⁺ NK cell functionality in terms of cytokine production and degranulation was associated with SC of HCV in HLA‐Bw4 80(T)⁺ people who injected drugs, predominantly HCV mono‐infected [33]. However, the NK cell response was restricted only to KIR3DL1⁺ NK cells, without taking into account the KIR2D⁺ NK cell repertoire [33]. In contrast, we did not report any impact of KIR3DL1⁺ NK cell functionality in terms of degranulation, even in a favored Bw4 environment, in HIV–HCV co‐infected individuals. The HLA class I environment, individual background not taken into account in the German cohort and mode of HIV and/or HCV contamination may account for these discordances.

Besides the KIR⁺ NK cell repertoire, HIV–HCV co‐infected people included in our study were characterized by a decreased frequency of CD57⁺ NK cells compared to controls. In contrast, a mature CD57⁺ NK cell expansion has been reported after HIV or HCV mono‐infected subjects as a consequence of cumulative lifetime exposure to infections [51]. In HIV–HCV co‐infected subjects, a higher frequency of CD57⁺, NKG2C⁺ NK cells compared to HIV and HCV mono‐infected people, and a lower frequency of NKG2A⁺ NK cells compared to controls, have been reported [38]. However, in this latter study there was no discrimination between SC, if any, and CI among HIV–HCV co‐infected subjects, and no resolutive KIR⁺ NK cell phenotype determination was performed, preventing any comparison [38]. Lastly, the impact of CMV on the NK cell repertoire was investigated in our study, as CMV‐driven NKG2C⁺ NK cell expansion with a specific KIR repertoire was observed in CMV⁺ healthy individuals [5253]. In our study, CMV infection did not modulate the NK cell repertoire in HIV–HCV co‐infected SC, as reported in mono‐infected HCV individuals [54]. However, the impact of CMV on the NK cell repertoire should be investigated in a larger cohort of HIV–HCV co‐infected SC individuals.

Regarding T cells, we reported an increased frequency of CD57⁺, DNAM‐1⁺ and KIR2DL2/3/S2⁺ T cells in SC compared to Ctrl. Chronic viral infections such as HIV and HCV offer some of the best examples of expansion of CD57⁺ CD8⁺ T cells [51]. CD57⁺ T cells are presumed to lack proliferative capacity and are known to increase in frequency with chronic immune activation as well as during normal aging. It has been shown that CD8⁺ T cells may up‐regulate CD57 and become senescent during CI with pathogens including HIV and HCV [51]. Moreover, expression of inhibitory markers as such as programmed cell death 1 (PD‐1) and T cell immunoglobulin mucin 3 (TIM3) is increased on effector memory T cells in HIV–HCV co‐infected compared to HCV or HIV mono‐infected subjects [55]. These expressions are usually associated with decreased proliferation and cytotoxicity in HIV–HCV co‐infection. The cytokine microenvironment could also play a role. Thus, systemic elevation of proinflammatory IL‐18 has been reported in HIV–HCV co‐infected versus HIV or HCV mono‐infected subjects [56]. We hypothesize that the presence of cytokines such as IL‐18 in HIV–HCV co‐infected individuals may increase KIR2DL2/3/S2⁺ T cell frequencies. An extended T cell phenotype in the presence of IL‐18 associated with functional assays on a larger sample size of HIV–HCV co‐infected individuals could confirm this hypothesis, as functional CD8 T cells play a key role in the SC of HCV.

Overall, our data suggest a role of mature T cells and KIR2D⁺ NK on the SC of HCV in European HIV–HCV co‐infected individuals (Fig. 4). This may imply a regulation of cell surface expression of HLA‐C molecules on infected cells. The modulation of HLA‐C expression by HCV remains unclear, but the down‐regulation of HLA‐Cw molecule expression following HIV infection [57] suggests a down‐regulation of HLA‐Cw molecules on infected cells in HIV–HCV co‐infected individuals. In a specific C2C2 environment, our data confirm that the SC of HCV in European HIV–HCV co‐infected individuals may be driven by an efficient KIR2DL1⁺ NK cell response, given the restricted C2 specificity and the strong interactions occurring between KIR2DL1 and C2 molecules.

Disclosures

The authors declare that they have nothing to disclose regarding funding or conflicts of interest with respect to this manuscript. All the authors approved the manuscript.

Author contributions

N. L.: genomic DNA extractions of all healthy blood donors and HIV–HCV co‐infected individuals, acquisition of KIR and HLA class I genotyping on all samples, drafting of manuscript. G. D.: peripheral blood mononuclear cell (PBMC) preparation of healthy blood donors, acquisition of phenotypical and functional tests on all healthy blood donors, drafting of manuscript. A. R.: sample collection of HIV–HCV co‐infected individuals from the VICKIR cohort, PBMC preparation of HIV–HCV co‐infected individuals, acquisition of phenotypical and functional tests on HIV–HCV co‐infected individuals, drafting of manuscript. A. G.: multivariate statistical analyses, drafting of manuscript. D. S.: sample collection from the national HEPAVIH cohort, drafting of manuscript. A. C.: HLA class I typing, drafting of manuscript. L. W.: sample collection from the national HEPAVIH cohort and drafting of manuscript. F. R.: sample collection from the VICKIR cohort, drafting of manuscript. K. Ge.: contribution to KIR genotyping, drafting of manuscript. C. R.: concept and design, analysis of phenotypical/functional data, drafting of manuscript. C. A.: concept and design for clinical input, sample collection, drafting of manuscript. K. G.: concept and design, analysis of KIR/HLA genetic and phenotypical/functional data, statistical analysis, drafting of manuscript.

Supporting information

Table S1. HLA class I, KIR genotyping, CMV status and time between HIV/HCV infection and sample date of French healthy blood donors (Crtl, n = 20), European HIV‐HCV co‐infected subjects with spontaneous clearance of HCV (SC, n = 14) and with chronic infection (CI, n = 10) included in NK and T cell repertoire analysis.

Click here for additional data file.^{(57KB, xls)}

Acknowledgements

This work was financially supported by the EFS Centre Pays de la Loire and by grants from Janssen (VX‐950HHC001). The CO13 HEPAVIH cohort was supported by ANRS (France Recherche Nord et Sud Sida‐HIV Hépatites). We are grateful to all the volunteer blood donors and HIV–HCV co‐infected subjects for participating in this study. We thank K. Gendzekhadze (City of Hope, National Medical Center, Duarte, California) for her help with English language editing, C. Volteau (Department of Biostatistics, CHU Hotel Dieu, Nantes, France) for advice on statistical analysis and L. Esterle (UMR 1219, ISPED, University of Bordeaux, France) for data management from the HEPAVIH ANRS CO13 cohort. We also thank HEPAVIH ANRS C013 centers participating in this study including: Scientific Committee: D. Salmon (co‐Principal Investigator), L. Wittkop (co‐Principal Investigator and Methodologist), P. Sogni (co‐Principal Investigator), L. Esterle (project manager), P. Trimoulet, J. Izopet, L. Serfaty, V. Paradis, B. Spire, P. Carrieri, M. A. Valantin, G. Pialoux, J. Chas, I. Poizot‐Martin, K. Barange, A. Naqvi, E. Rosenthal, A. Bicart‐See, O. Bouchaud, A. Gervais, C. Lascoux‐Combe, C. Goujard, K. Lacombe, C. Duvivier, , D. Neau, P. Morlat, F. Bani‐Sadr, L. Meyer, F. Boufassa, B. Autran, A. M. Roque, C. Solas, H. Fontaine, D. Costagliola, L. Piroth, A. Simon, D. Zucman, F. Boué, P. Miailhes, E. Billaud, H. Aumaître, D. Rey, G. Peytavin, V. Petrov‐Sanchez and D. Lebrasseur‐Longuet; Clinical Centers: APHP Hôpitaux Universitaires Paris Centre, Paris (D. Salmon, R. Usubillaga, P. Sogni, B. Terris, P. Tremeaux), APHP Pitié‐Salpétrière, Paris (C. Katlama, M.A. Valantin, H. Stitou, A. Simon, P. Cacoub, S. Nafissa, Y. Benhamou, F. Charlotte, S. Fourati), APHM Sainte‐Marguerite, Marseille (I. Poizot‐Martin, O. Zaegel, H. Laroche, C. Tamalet), APHP Tenon, Paris (G. Pialoux, J. Chas, P. Callard, F. Bendjaballah, C. Amiel, C. Le Pendeven), CHU Purpan, Toulouse (B. Marchou, L. Alric, K. Barange, S. Metivier, J. Selves, F. Larroquette), CHU Archet, Nice (E. Rosenthal, A. Naqvi, V. Rio, J. Haudebourg, M. C. Saint‐Paul, A. De Monte, V. Giordanengo, C. Partouche), APHP Avicenne, Bobigny (O. Bouchaud, A. Martin, M. Ziol, Y. Baazia, V. Iwaka‐Bande, A. Gerber), Hôpital Joseph Ducuing, Toulouse (M. Uzan, A. Bicart‐See, D. Garipuy, M. J. Ferro‐Collados, J. Selves, F. Nicot), APHP Bichat Claude‐Bernard, Paris (A. Gervais, Y. Yazdanpanah, H. Adle‐Biassette, G. Alexandre, G. Peytavin), APHP Saint‐Louis, Paris (C. Lascoux‐Combe, J. M. Molina, P. Bertheau, M. L. Chaix, C. Delaugerre, S. Maylin), APHP Saint‐Antoine (K. Lacombe, J. Krause, P. M. Girard, D. Wendum, P. Cervera, J. Adam, C. Viala), APHP, Hôpitaux Paris Sud, Bicêtre, Paris (D. Vittecocq, C. Goujard, Y. Quertainmont, E. Teicher, C. Pallier), APHP Necker, Paris (O. Lortholary, C. Duvivier, C. Rouzaud, J. Lourenco, F. Touam, C. Louisin, V. Avettand‐Fenoel, E. Gardiennet, A. Mélard), CHU Bordeaux Hôpital Pellegrin, Bordeaux (D. Neau, A. Ochoa, E. Blanchard, S. Castet‐Lafarie, C. Cazanave, D. Malvy, M. Dupon, H. Dutronc, F. Dauchy, L. Lacaze‐Buzy, A. Desclaux, P. Bioulac‐Sage, P. Trimoulet, S. Reigadas), CHU Bordeaux Hôpital Saint‐André, Bordeaux (P. Morlat, D. Lacoste, F. Bonnet, N. Bernard, M. Hessamfar, F. Paccalin, C. Martell, M. C. Pertusa, M. Vandenhende, P. Mercié, D. Malvy, T. Pistone, M. C. Receveur, M. Méchain, P. Duffau, C Rivoisy, I. Faure, S. Caldato, P. Bioulac‐Sage, P. Trimoulet, S. Reigadas, P. Bellecave, C. Tumiotto), CHU Bordeaux Hôpital du Haut‐Levêque, Bordeaux (J.L. Pellegrin, J.F. Viallard, E. Lazzaro, C. Greib, P. Bioulac‐Sage; Virologie: P. Trimoulet, S. Reigadas), Hôpital FOCH, Suresnes (D. Zucman, C. Majerholc, M. Brollo, E. Farfour), APHP Antoine Béclère, Clamart (F. Boué, J. Polo Devoto, I. Kansau, V. Chambrin, C. Pignon, L. Berroukeche, R. Fior, V. Martinez, S. Abgrall, M. Favier, C. Deback), CHU Henri Mondor, Créteil (Y. Lévy, S. Dominguez, J. D. Lelièvre, A. S. Lascaux, G. Melica), CHU Nantes Hôpital Hôtel Dieu, Nantes (E. Billaud, F. Raffi, C. Allavena, V. Reliquet, D. Boutoille, C. Biron, M. Lefebvre, N. Hall, S. Bouchez, A. Rodallec, L. Le Guen, C. Hemon), Hôpital de la Croix Rousse, Lyon (P. Miailhes, D. Peyramond, C. Chidiac, F. Ader, F. Biron, A. Boibieux, L. Cotte, T. Ferry, T. Perpoint, J. Koffi, F. Zoulim, F. Bailly, P. Lack, M. Maynard, S. Radenne, M. Amiri, F. Valour, J. Koffi, F. Zoulim, F. Bailly, P. Lack, M. Maynard, S. Radenne, C. Augustin‐Normand, C. Scholtes, T. T. Le‐Thi), CHU Dijon, Dijon (L. Piroth, P. Chavanet M. Duong Van Huyen, M. Buisson, A. Waldner‐Combernoux, S. Mahy, R. Binois, A. L. Simonet‐Lann, D. Croisier‐Bertin, A. Salmon Rousseau, C. Martins), CH Perpignan, Perpignan (H. Aumaître, Virologie: S. Galim); CHU Robert Debré, Reims (F. Bani‐Sadr, D. Lambert, Y Nguyen, J. L. Berger, M. Hentzien, V. Brodard); CHRU Strasbourg (D. Rey, M. Partisani, M. L. Batard, C. Cheneau, M. Priester, C. Bernard‐Henry, E. de Mautort, P. Gantner, S. Fafi‐Kremer). Data collection: F. Roustant, P. Platterier, I. Kmiec, L. Traore, M.‐K. Youssouf, A. Benmammar, M.‐G. Tateo, S. Lepuil, Pomes Chloé V. Sicart‐Payssan, S. Anriamiandrisoa, C. Pomes, F. Touam, C. Louisin, M. Mole, P. Catalan, M. Mebarki, A. Adda‐Lievin, P. Thilbaut, Y. Ousidhoum, F. Z. Makhoukhi, O. Braik, R. Bayoud, C. Gatey, M. P. Pietri, V. Le Baut, R. Ben Rayana, F. Barret, C. Chesnel, D. Beniken, M. Pauchard, S. Akel, S. Caldato, T. Rojas‐Rojas, C. Debreux, L. Chalal, J. Zelie, A. Soria, M. Cavellec, S. Breau, P. Fisher, C. Charles, D. Croisier‐Bertin, S. Ogoudjobi, C. Brochier, V. Thoirain‐Galvan, M. Le Cam; Management, statistical analyses: P. Carrieri, M. Chalouni, V. Conte, L. Dequae‐Merchadou, M. Desvallees, L. Esterle, C. Gilbert, S. Gillet, R. Knight, T. Lemboub, F. Marcellin, L. Michel, M. Mora, C. Protopopescu, P. Roux, B. Spire, S. Tezkratt, T. Barré, T. Rojas, M. Baudoin, M. Santos V. Di Beo, M.Nishimwe and L. Wittkop.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Click here for additional data file.^{(57KB, xls)}

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

[cei13562-bib-0001] 1. Alter MJ. Epidemiology of viral hepatitis and HIV co‐infection. J Hepatol 2006; 44 S6–9. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0002] 2. Islam N, Krajden M, Gilbert M et al. Role of primary T‐cell immunodeficiency and hepatitis B coinfection on spontaneous clearance of hepatitis C: the BC Hepatitis Testers Cohort. J Viral Hepat 2017; 24:421–9. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0003] 3. Gauthiez E, Habfast‐Robertson I, Rüeger S et al. A systematic review and meta‐analysis of HCV clearance. Liver Int 2017; 37:143145. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0004] 4. Tillmann HL, Thompson AJ, Patel K et al. A polymorphism near IL28B is associated with spontaneous clearance of acute hepatitis C virus and jaundice. Gastroenterology 2010; 139:1586–92, 1592.e1. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0005] 5. Béziat V, Hilton HG, Norman PJ, Traherne JA. Deciphering the killer‐cell immunoglobulin‐like receptor system at super‐resolution for natural killer and T‐cell biology. Immunology 2017; 150:248–64. [DOI] [PMC free article] [PubMed] [Google Scholar]

[cei13562-bib-0006] 6. Björkström NK, Béziat V, Cichocki F et al. CD8 T cells express randomly selected KIRs with distinct specificities compared with NK cells. Blood 2012; 120:3455–65. [DOI] [PMC free article] [PubMed] [Google Scholar]

[cei13562-bib-0007] 7. David G, Djaoud Z, Willem C et al. Large spectrum of HLA‐C recognition by killer Ig‐like receptor (KIR)2DL2 and KIR2DL3 and restricted C1 specificity of KIR2DS2: dominant impact of KIR2DL2/KIR2DS2 on KIR2D NK cell repertoire formation. J Immunol 2013; 191:4778–88. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0008] 8. Morvan M, David G, Sébille V et al. Autologous and allogeneic HLA KIR ligand environments and activating KIR control KIR NK‐cell functions. Eur J Immunol 2008; 38:3474–86. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0009] 9. Morvan M, Willem C, Gagne K et al. Phenotypic and functional analyses of KIR3DL1+ and KIR3DS1+ NK cell subsets demonstrate differential regulation by Bw4 molecules and induced KIR3DS1 expression on stimulated NK cells. J Immunol 2009; 182:6727–35. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0010] 10. Martin MP, Gao X, Lee J‐H et al. Epistatic interaction between KIR3DS1 and HLA‐B delays the progression to AIDS. Nat Genet 2002; 31:429–34. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0011] 11. Garcia‐Beltran WF, Hölzemer A, Martrus G et al. Open conformers of HLA‐F are high‐affinity ligands of the activating NK‐cell receptor KIR3DS1. Nat Immunol 2016; 17:1067–74. [DOI] [PMC free article] [PubMed] [Google Scholar]

[cei13562-bib-0012] 12. Anfossi N, André P, Guia S et al. Human NK cell education by inhibitory receptors for MHC class I. Immunity 2006; 25:331–42. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0013] 13. Uhrberg M, Valiante NM, Shum BP et al. Human diversity in killer cell inhibitory receptor genes. Immunity 1997; 7:753–63. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0014] 14. Gagne K, Willem C, Legrand N et al. Both the nature of KIR3DL1 alleles and the KIR3DL1/S1 allele combination affect the KIR3DL1 NK‐cell repertoire in the French population. Eur J Immunol 2013; 43:1085–98. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0015] 15. Gardiner CM, Guethlein LA, Shilling HG et al. Different NK cell surface phenotypes defined by the DX9 antibody are due to KIR3DL1 gene polymorphism. J Immunol 2001; 166:2992–3001. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0016] 16. Björkström NK, Riese P, Heuts F et al. Expression patterns of NKG2A, KIR, and CD57 define a process of CD56dim NK‐cell differentiation uncoupled from NK‐cell education. Blood 2010; 116:3853–64. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0017] 17. Cifaldi L, Doria M, Cotugno N et al. DNAM‐1 activating receptor and its ligands: how do viruses affect the NK cell‐mediated immune surveillance during the various phases of infection? Int J Mol Sci 2019; 20:3715. [DOI] [PMC free article] [PubMed] [Google Scholar]

[cei13562-bib-0018] 18. Gumá M, Angulo A, Vilches C, Gómez‐Lozano N, Malats N, López‐Botet M. Imprint of human cytomegalovirus infection on the NK cell receptor repertoire. Blood 2004; 104:3664–71. [DOI] [PubMed] [Google Scholar]

[cei13562-bib-0019] 19. Khakoo SI, Thio CL, Martin MP et al. HLA and NK cell inhibitory receptor genes in resolving hepatitis C virus infection. Science 2004; 305:872–4. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Influence of HLA‐C environment on the spontaneous clearance of hepatitis C in European HIV–HCV co‐infected individuals

N Legrand

G David

A Rodallec

A Gaultier

D Salmon

A Cesbron

L Wittkop

F Raffi

K Gendzekhadze

C Retière

C Allavena

K Gagne

Summary

Introduction

Materials and methods

Study population

Table 1.

PBMC and cell lines

KIR and HLA class I genotyping

Phenotyping of lymphocyte subsets by multi‐color flow cytometry

CD107a mobilization assay detected by flow cytometry

Statistical analysis

Results

Clinical and immunovirological characteristics of HIV–HCV co‐infected individuals

Association of C2C2 KIR ligand with spontaneous clearance of HCV in European HIV–HCV co‐infected individuals

Fig. 1.

Table 2.

Table 3.

Functional KIR2D+ NK cell repertoire in European HIV–HCV co‐infected subjects with spontaneous clearance of HCV

Fig. 2.

Mature KIR2DL2/3/S2+ T cells as a hallmark of spontaneous clearance of HCV in European HIV–HCV co‐infected individuals

Fig. 3.

Discussion

Fig. 4.

Disclosures

Author contributions

Supporting information

Acknowledgements

Data Availability Statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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