Killer immunoglobulin-like receptor (KIR) genes are associated with the risk of episodes of high-level and detectable viremia among HIV controllers [version 1; peer review: awaiting peer review]

Background: HIV controllers (HICs) constitute a heterogeneous group of HIV-1 individuals able to suppress plasma viremia to low or undetectable levels in the absence of antiretroviral therapy. Host genetic factors may be involved in the sustained control of viral replication observed. We investigated the distribution and the potential impact of human leukocyte antigens (HLA)-B and -C alleles, killer immunoglobulin-like receptor (KIR) genes, single nucleotide polymorphisms (SNPs) of the NLRP3, CARD8 and IL-1β inflammasome genes, and CCR5Δ32 mutation on the viral control among HICs. Methods: In total, 28 HICs were categorized as persistent elite controllers (PECs, n = 7), ebbing elite controllers (EECs, n = 7), and viremic controllers (VCs, n = 14) according to the level of natural suppression of viremia. HLA alleles were assigned by sequencingbased typing, KIR alleles by polymerase chain reaction (PCR) sequence-specific amplification, SNPs by real-time PCR, and the CCR5 Δ32 mutation by PCR. Results: Significant differences were observed in the pairwise comparisons of protective HLA-B alleles, KIR Bx genotype, KIR2DL3 + C1 pair, KIR2DL5, and KIR2DS5 allelic carrier frequencies among the HIC groups. Multivariate models showed that HICs without the KIR2DL3 allele or without KIR2DL3 + C1/C2 pair, with the HLA-C*08 allele or with the NLRP3 rs10754558-G SNP had a higher mean hazard of a viral load above 2,000 copies/mL, while a lower mean hazard of this event was observed for HICs with KIR2DL5, KIR2DS1, KIR2DS5, Open Peer Review Reviewer Status AWAITING PEER REVIEW Any reports and responses or comments on the article can be found at the end of the article. Page 1 of 18 F1000Research 2021, 10:546 Last updated: 13 JUL 2021


Introduction
Different levels of viremia control are observed among human immunodeficiency virus (HIV)-1-infected individuals. Approximately 1% of the HIV-1-seropositive population suppresses viral replication to extremely low or undetectable levels in the absence of antiretroviral therapy and are termed HIV controllers (HICs) or elite controllers (ECs) (Deeks & Walker, 2007;Lambotte et al., 2005). HICs constitute a heterogeneous group of HIV-1-infected individuals, even when compared to persons with low-level viremia, they exhibit marked genetic and immunologic heterogeneity (Pereyra et al., 2008;Côrtes et al., 2015). Heterogeneity in viral load (VL), classification criteria and follow-up time to define the EC profile is also observed among the studies (Gurdasani et al., 2014;Navarrete-Muñoz et al., 2020). The mechanisms involved in the control of viral replication remain to be fully elucidated. Some studies point to the role of viral features in this phenomenon, while others focus on the role of host genetic in the efficient control of HIV-1 observed among HICs (Côrtes et al., 2015;Balasubramaniam et al., 2019).
Human leukocyte antigens (HLA) class I molecules have a crucial role in the cytotoxic T-lymphocyte (CTL) response. Genes that encode these molecules have been consistently associated with distinct patterns observed in the dynamics of HIV-1 infection (McLaren & Carrington, 2015), among which we can highlight the protective role attributed to the HLA-B*27 and B*57 alleles in EC cohorts (Lécuroux et al., 2014;Migueles et al., 2000;Fellay et al., 2007;Pereyra et al., 2010). However, the presence of HLA-B*27 and B*57 cannot be directly related to viral control, since some HIV-1infected individuals who harbor these alleles present absence of viremia control (Pereyra et al., 2008;Emu et al., 2008). While HLA-B alleles are well-reported markers of HIV disease progression and control (McLaren & Carrington, 2015), HLA-C alleles have been neglected. HLA-C alleles were generally considered inferior in restricting CTLs responses compared to HLA-A and -B (Kulpa & Collins, 2011). On the other hand, they act as excellent ligands for killer immunoglobulin-like receptor (KIR) receptors on natural killer (NK) cells and protect target cells from lysis mediated by NK cells (Kulpa & Collins, 2011). In this context, the HLA-C locus emerged as an important host genetic determinant of HIV infection outcomes. The HLA-C*08 and HLA-C*18 alleles have already been associated with better disease control in a study of HIV controllers (Lazaryan et al., 2011), and the HLA-C*15 allele was a protective factor in a cohort of exposed uninfected infants (Bardeskar et al., 2018). Moreover, a single-nucleotide polymorphism 35 kb upstream the HLA-C locus (rs9264942) showed the most significant association with viral load (VL) control (Fellay et al., 2007;Thørner et al., 2016;Malnati et al., 2017). This variant has been associated with high HLA-C mRNA (messenger ribonucleic acid) levels and higher surface expression of HLA-C alleles (Fellay et al., 2007;Thørner et al., 2016;Malnati et al., 2017).
Inflammasomes are cytosolic multiprotein complexes of the innate immune system responsible for activating inflammatory responses (Rathinam & Fitzgerald, 2016). These complexes regulate the maturation of cytokines of the IL-1 family, including IL-1β and IL-18 (Rathinam & Fitzgerald, 2016). Activation of the inflammasome during HIV-1 infection mainly contributes to immune hyperactivation, which is the main pathogenic mechanism of HIV-1 progression (Marín-Palma et al., 2018). However, the relationship between inflammasome single nucleotide polymorphisms (SNPs) and viral load control in the context of HIV-1 infection is still unclear. The genetic restriction to HIV-1 infection caused by polymorphisms in the chemokine receptor CCR5 is another important factor that can modulate HIV-1 dynamics. Homozygosity for a 32 base-pair deletion in the CCR5 gene (Δ32 mutation) is considered as a resistant phenotype leading to the protection of individuals against infection with HIV-1 R5 tropic lineages (Dean et al., 1996;Liu et al., 1996;Samson et al., 1996;Marmor et al., 2011), while heterozygosity may result in in slower progression to acquired immune deficiency syndrome (AIDS) (Huang et al., 1996;Sullivan et al., 2001).
Innate immunity mechanisms also participate in the sustained control of viral replication observed among ECs, mainly effector responses mediated by NK cells (Tomescu et al., 2012). The activity of these cells contributes to reduce viral replication in acute infection, thereby cooperating to the ability of ECs to control viremia (O'Connell et al., 2009). Consistent associations between KIR genesexpressed on the surface of NK cellsand viral control have already been described, highlighting the protective role conferred by KIR3DL1 associated with HLA-B molecules carrying the Bw4 motif (Martin et al., 2007). The inhibitory KIR2DL1, 2DL2, and 2DL3 recognize HLA-C ligands (Kulkarni et al., 2008), but no consistent association between HLA-C/KIR alleles and viral control has been described so far. Other innate immunological mechanisms have also been studied in ECs cohorts, including the ability of NK cells to induce cell death by antibody-dependent cellular cytotoxicity (ADCC) (Lambotte et al., 2013).
Studies with HICs may provide novel insights regarding host mechanisms of virus control (Hatano et al., 2009). Different from previous studies with HICs from the United States and Europe (Lambotte et al., 2005;Pereyra et al., 2008;Walker & Yu, 2013;Pernas et al., 2018), here, we have the opportunity to examine the role of these genetic markers in a HICs cohort that contains a high degree of miscegenation, which characterizes the Brazilian population. Besides this, other geneticrelated particularities can be observed among Brazilians, such as the association of HLA-B*52 with the non-progression to AIDS (Teixeira et al., 2014). Therefore, in this study, we analyzed the distribution of HLA-B and -C, KIR, CCR5 genes, as well as selected SNPs to investigate their impact on the viral control observed in a cohort of Brazilian HICs.

Study subjects and ethical issues
The individual description of the HICs analyzed in this study had already been published (de Azevedo et al., 2017;Côrtes et al., 2018;Caetano et al., 2020). Individuals who fulfilled the criteria of HICs were identified in a cohort of HIV-1 seropositive individuals followed at the Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz (INI/FIOCRUZ), Rio de Janeiro, Brazil. These individuals were defined as subjects over 18 years old with documented HIV-1 infection for >3 years and RNA viral load below the detection limit (40 or 80 copies/mL, depending on the year of inclusion) in the absence of antiretroviral treatment. As this is a longitudinal study, these individuals were/have been followed up and classified under one of the categories of viral control.
After 12 years of follow up, a cohort of 28 HICs could be composed including HIV-1-infected individuals classified in three categories according to the plasmatic viral load (VL): (1) persistent elite controllers (PECs) if 100% of VL measures were below the limit of detection (< LD; 50-80 copies/mL) for the respective available commercial assays (n = 7); (2) ebbing elite controllers (EECs) if subjects had occasional (≤ 30%) episodes of transient low-level (> LD to 400 copies/mL) viremia (n = 7); and (3) viremic controllers (VCs) if most (≥ 70%) of VL determinations were between 51 and 2,000 copies/mL (n = 14). Occasional VL measurements above the upper limits were accepted for the EECs and VCs. Participants were followed at least once every 6-12 months, starting in November 2008, to perform HIV-RNA VL quantification and CD4 + T lymphocytes counts. In each visit, whole blood was collected into an ethylenediaminetetraacetic acid (EDTA)-containing tube, and 1 mL was stored at -20°C until use. At this moment, from the 28 individuals [median follow-up = 9.02 years (interquartile range (IQR) = 6.46)], 11 are currently being followed up and 17 are no longer study participants due to cART entry (n = 09) or loss of follow up (n = 08).
Genomic DNA extraction DNA was extracted from whole blood using the QIAamp DNA Blood Mini Kit (QIAGEN, Hilden, Nordrhein-Westfalen, Germany) according to the manufacturer's instructions. The DNA concentration was determined using the Thermo Scientific Nanodrop 2000 (Thermo Fisher Scientific, Waltham, Massachusetts, USA), and the filtrates containing the isolated DNA were stored at À20°C until used for genomic analysis.

Single nucleotide polymorphism selection and genotyping
We selected four single nucleotide polymorphisms (SNPs) in 3 inflammasome genes based on previously published data (Pontillo et al., 2013) and considering the relevance of each gene in the inflammasome pathway: CARD8 (Caspase Activation and Recruitment Domains-8) rs2043211 and rs6509365; NLRP3 (Nucleotide oligomerization domain-Like Receptor family, Pyrin domain-containing protein-3) rs10754558; and IL-1β rs1143634. Besides that, we selected HLA-C rs9264942 C>T (TaqMan ® genotyping assay C_29901957_10) based on the association of this SNP with a lower HIV-1 viral load (Fellay et al., 2007(Fellay et al., , 2009Wei et al., 2015). SNP genotyping was performed using commercially available TaqMan assays (Applied Biosystems/AB and Life Technologies) using the ABI7500 Real-Time platform (AB). Allelic discrimination was carried out by means of the Thermo Fisher Connect Software ® version 1.
CCR5 genotyping DNA samples were PCR amplified to determine the presence of the CCR5 Δ32 mutation. Primers (CCR5-F: GCT GTC TTT GCG TCT CTC CCA GGA and CCR5-R: CTC ACA GCC CTG TGC CTC TTC TTC) were used to amplify a 239 base-pair (bp) fragment covering the Δ32 mutation region. The cycling conditions were: 1 cycle 94°C 5 minutes; 30 cycles 94°C 1 minute, 60°C 30 seconds, 72°C 2 minutes; 1 cycle 72°C 10 minutes. The PCR amplified products (5 ul) were separated by agarose gel electrophoresis and visualized by ethidium bromide staining. A single band of 239 bp indicated the CCR5/CCR5 wild-type genotype, while the heterozygous genotype CCR5/Δ32 was detected by 239 and 207 bp bands, and the homozygous genotype Δ32/Δ32 by a single band of 207 bp.

Statistical analyses
Direct count estimated the frequencies of HLA, KIR, SNPs and CCR5 alleles and genotypes. Kruskal-Wallis ANOVA by Ranks test was used to compare the sociodemographic, clinical, and laboratory characteristics among the different HICs groups for continuous numerical variables. In contrast, for categorical nominal variables, Fisher's exact test was used in the evaluation of frequencies among the different HICs groups. Tests of equal proportions were used to evaluate the allele carriers' relative frequencies among the HICs groups. For comparative purposes, HLA-B genomic distribution data from the general Brazilian population were extracted from REDOME (National Registry of Bone Marrow Donors, Brazilian Ministry of Health) data (Rede Brasil de Imunogenética, 2018), and for HLA-C we used data available at Allele Frequencies Net Database.
To estimate the hazard of a transitory loss of virological control, defined as the observation of the first VL determination above 2,000 copies/mL, we calculated person-years (pY) at risk for each patient between HIV diagnosis and the occurrence of an event. Individuals were censored either at the time of final observation, death, cART (combined antiretroviral therapy) initiation, or the last follow-up visit/exam, whichever occurred first. The effect of various risk factors on the outcome was assessed using hazard ratios (HR) and corresponding 95% confidence intervals (CI), which were estimated through the Cox proportional hazard model (Therneau & Grambsch, 2000).
To evaluate the occurrence of multiple events of VL blips, herein defined as the number of detectable viral loads counted after HIV diagnosis and until cART initiation, we calculated the incidences/rates of the number of viral loads per pY for each patient, and 95% CI were estimated according to asymptotic standard errors calculated from a Gamma distribution (Lehmann & Casella, 1998). The effect of various risk factors on the outcome was assessed by relative risks (RR) and corresponding 95% CI were estimated employing the Negative Binomial (NB) models. Individual exposure time (in years) was used as an offset in the NB models (Hilbe, 2011).
Two-tailed levels of significance ≤ 0.01, 0.05 and 0.1 were considered "highly significant", "significant" and "suggestive", respectively. All statistical analysis was performed using the R statistical software package, version 3.4.1 (R Development Core Team, 2017). Table 1 depicts the main clinical and epidemiological characteristics of the HICs cohort distributed according to the viral control groups (de Sá & Teixeira, 2021). Overall, we found a similar frequency of females and males (16 [57.1%] and 12 [42.9%], respectively), while 21 (75%) of the individuals have identified themselves as heterosexual and 6 (21.4%) as men who have sex with men (MSM). Most heterosexual male (75%) and MSM subjects (83.3%) belonged to the VCs group. The ethnic background composition was diverse, with an unequal distribution of White, Brown, and Black participants among groups of HICs (P = 0.04). Participants had a median age of 32 (IQR 10.4) years old, with a similar median age observed among the PECs (33 years old; IQR 6.9), EECs (37 years old; IQR 13.9), and VCs (30 years old; IQR 9.8) groups.

Clinical and epidemiological characteristics of HICs
All HICs groups displayed a median CD4 + T cells count above 800 cells/μL (IQR 431). Further details about immunological and virological characteristics of most HICs of this study were depicted in previous studies from our group (Bello et al., 2009;Côrtes et al., 2015Côrtes et al., , 2018de Azevedo et al., 2017;Caetano et al., 2020).
Distribution of HLA-B, -C, KIR, and CCR5 genes among HICs Table 2 describes the relative frequencies of HLA-B and -C, KIR, and CCR5Δ32 alleles carriers found in the different HICs groups. Due to the dependence between the genotypes, we did not perform this comparative analysis for the SNPs included in this study. However, the complete genetic characterization of the analyzed markers is depicted in Table 3. We observed significant differences between PECs and EECs for protective HLA-B alleles, KIR Bx genotype, KIR2DL5, and KIR2DS5 allelic carrier frequencies. Among EECs and VCs, the frequencies of KIR Bx genotype, KIR2DL3 + C1 pair, KIR2DL2, KIR2DL5, and KIR2DS2 alleles carriers were also significantly distinct. The only genetic marker with significantly different frequencies between PECs and VCs was KIR2DS5. It is noticeable that HLA-B protective alleles (HLA-B*27, B*52, and/or B*57) were found in 71% of the PECs, 43% of the VCs, and only 14% of the EECs.
To check for an enrichment of protective HLA alleles in our cohort, we compared the classical protective HLA-B and -C frequencies here obtained with those from the general Brazilian population, and with HIV-1-infected individuals who progressed to AIDS (Teixeira et al. 2014;Biberg-Salum et al., 2018), considered as HIV non-controllers (HIV-NC) ( Table 4). For HLA-B, we noted that the frequency of carriers of these alleles in our HICs cohort (0.464; n = 13) is on average 3.34-fold higher (P < 0.001) than in the overall Brazilian population (0.139; n = 396,740) and 3.22-fold higher (P = 0.014) in the HIV non-controllers group (0.144; n = 29). Similarly, for HLA-C we noted that the frequency of carriers of these alleles in our HICs cohort (0.571; n = 16) is on average 3.60-fold higher (P < 0.001) than in the overall Brazilian population (0.159; n = 42) and 3.50-fold higher (P < 0.001) than in the HIV non-controllers group (0.161; n = 26). Only   two PECs carried the CC genotype in the HLA-C rs9264942 polymorphism. The KIR Bx genotype was found in 86% of PECs, 79% of the VCs, and 29% of EECs. The KIR3DL1+Bw4 genotype was detected in only two VCs, and the KIR3DS1+Bw4 genotype in four participants (one PEC, one EEC, and two VCs). All PECs and EECs had the KIR2DL3 allele. The CCR5Δ32 mutation was found in four heterozygous (WT/Δ32) participants (one PEC, one EEC, and two VCs), resulting in an overall allelic frequency of 7.1%, and no homozygous (Δ32/Δ32) participants were identified in this cohort. Therefore, we cannot assign any relation between this genetic marker and the distinct patterns of viremia control observed in these HICs.

Episodes of high-level and detectable viremia among HICs
To test the potential relevance of genetic host factors in the risk of a transitory loss of virological control in some HICs, we conducted Cox proportional hazard multivariate analysis to identify factors associated with the occurrence of the high-level viremia (> 2,000 copies/mL) (  Protective HLA-C alleles included HLA-C*08, C*15, and C*18 alleles. Abbreviations: HICs = HIV controllers; HIV-NC = HIV non-controllers; BGP = Brazilian general population; N = number of individuals; n = observed number of an allele carriers; Freq = relative frequency of carriers for each allele, calculated as the number of carriers/N; NC = not calculated. P = 0.006] had less risk of undergoing VL blips within the same normalized period than those participants without this allele. Conversely, HICs without the KIR2DL3 allele ); P = 0.03] had a mean higher risk of experiencing VL blips within the same normalized period than those with this allele. The results of Cox's proportional hazard multivariate analysis and Negative Binomial (NB) models of the HLA-C and inflamassome SNPs are depicted in Tables 7 and 8. Our results point to a protective role for KIR2DL3 and KIR2DS5 alleles since the absence of the former was associated both with a higher risk of a transitory loss of virological control and to a higher risk of any event of detectable viremia (VL blip); while the presence of the latter was associated to a lower risk of these events. Epidemiological features were a Levels = 0 (absent); 1 (present). b First HIV-1 VL determination above 2,000 copies/mL. c pY: person-years at risk were calculated for each patient between HIV diagnosis and the occurrence of an event. d Hazard ratios were adjusted by gender and education whenever applicable, which were variables associated with an uncontrolled viremic event in bivariate analysis (P < 0.2). Abbreviations: HR = hazard ratios; aHR = adjusted hazard ratios.
introduced in the multivariate models for controlling bias in the statistical analysis. The limited sample size and the study design do not allow us to explore the associations involving these epidemiological features depicted in Tables 5 and 6.

Discussion
In the present study, we characterized the distribution of HLA-B, HLA-C, KIR, SNPs of the NLRP3, CARD8, IL-1β, and CCR5Δ32 mutation in a cohort of HICs with different levels of virological control. Our results show that host genes classically associated with protective mechanisms are present in our HICs cohort. Despite the small number of participants analyzed, we observed a higher frequency of HLA-B protective alleles in this cohort than in the general Brazilian population and Brazilian HIV non-controllers (Teixeira et al., 2014), confirming the results of many studies showing enrichment of protective B*27 and B*57 alleles in HICs (Migueles et al., 2000;Fellay et al., 2007;Pereyra et al., 2010;Lécuroux et al., 2014). We also observed that B*27 and B*57 allele carriers' frequencies were not different among HICs groups. However, when considered together with HLA-B*52 composing the 'protective HLA-B alleles' group, a significant difference of these alleles frequencies between PECs and EECs was observed (P = 0.002, Table 2). In this study, multivariate models showed that some genetic markers were associated with a transitory loss of virological control and/or of an event of detectable viremia (VL blip). A lower mean hazard for the risk of transitory loss of virological control was observed for KIR2DL5, KIR2DS1, KIR3DS1, and KIR2DS5 alleles. In contrast, the HLA-C*08 allele and the absence of KIR2DL3 and KIR3DL3+C1/C2 alleles were associated with an increased risk of this event (Table 5). Additionally, KIR2DL3 allele absence was also associated with a higher risk of an event of detectable viremia (VL blip), and KIR2DS5 was also associated with a lower risk of these events (Table 6), pointing to a protective role of these alleles. Interestingly, no association was found for the CC genotype in the HLA C rs9264942 polymorphism with either the hazard of an uncontrolled viremic event or the risk of undergoing VL blips. This variant (CC genotype) has been associated with a higher viral load control (VL) in previous studies (Fellay et al., 2007;Thørner et al., 2016;Malnati et al., 2017).
Studies have been associated KIR2DL3 receptor and its ligand HLA-C1 with a lower VL and a higher CD4 + T cell count (Körner et al., 2014). In agreement with these studies, we observed an increased HR of a high-level viremic event and a higher risk of experiencing VL blips in HICs without KIR2DL3. Inhibitory KIR receptors (KIR2DL2/KIR2DL3 heterozygosity) were associated with resistance to HIV-1 infection among female sex workers in the absence of their respective HLA ligands. These results indicate that absence of these ligands may reduce the threshold for NK cell activation via activating KIR, resulting in NK cytotoxic activity and early elimination of HIV-1 infected cells (Jennes et al., 2006).
KIR2DS5 allele carriers had a lower mean hazard of high-level viremia (> 2,000 copies/mL) events and, in the mean, less VL blip events than those without the allele (Table 5). This activating gene was associated with the protection against HIV-1 infection of exposed uninfected infants (Chavan et al., 2016) and reducing HIV-1 transmission from mother to child (Omosun et al., 2018). It remains unclear what mechanisms at the KIR2DS5 allele might result in this protection. We speculate that the presence of activating mechanisms driven by this gene could impact viral control. This mechanism may be due to the activation signal delivered to NK cells when activating receptors bind their ligand on the target cell surface, leading to the activation of these cells and eliminating the pathogen (Srivastava et al., 2003). The relevance of NK cell function regarding the HIC status has been suggested by genetic studies (Martin et al., 2002(Martin et al., , 2007. The effect of the combination of KIR3DS1 + NK cells with the Bw4 epitope reduces the susceptibility to HIV-1 infection, improves viremia control, and decreases CD4 + T cells depletion (Martin et al., 2002;Alter et al., 2007Alter et al., , 2009. Moreover, in agreement with our results, the KIR3DS1 gene has been indicated as a protective factor in the resistance to HIV in different routes of exposure (Boulet et al. 2008;Chavan et al. 2014;Habegger de Sorrentino et al. 2013;Tallon et al. 2014). KIR2DL5 has already been associated with a reduced risk of HIV-1 infection and reduced HIV-1 transmission among Africans (Jennes et al., 2006;Omosun et al., 2018), but there is no previous report associating this allele with virological control. The KIR2DS1 gene bind HLA-C molecules of the C2 group (Folley et al., 2008). It has already been significantly associated with a lower viral load in HIV-1 patients from India (Chavan et al., 2014) and South Africa (Wong et al., 2010).
The HLA-C*08 allele and the rs10754558 G allele were associated with an increased risk of transitory loss of virological control in this study. Several researchers have reported the positive influence of these alleles in HIV disease course (Lazaryan et al., 2011;Shepherd et al., 2015;Mhandire et al., 2018;Pontillo et al., 2010Pontillo et al., , 2012. The presence of the C*08 allele has already been associated with a high CD4 + T cell count (Mhandire et al., 2018), and this allele was enriched First HIV-1 VL determination above 2,000 copies/mL. b pY: person-years at risk were calculated for each patient between HIV diagnosis and the occurrence of an event. c Hazard ratios were adjusted by gender and education whenever applicable, which were variables associated with an uncontrolled viremic event in bivariate analysis. Abbreviations: HR = hazard ratios; aHR = adjusted hazard ratios; NC = not calculated.
among HIV controllers (Lazaryan et al., 2011) and long-term non-progressors (LTNPs) (Shepherd et al., 2015). The NLRP3 rs10754558-G SNP has already been described as a protective factor against HIV-1 infection in different ethnic groups (Pontillo et al., 2010(Pontillo et al., , 2012. Moreover, in vitro assays showed that rs10754558 was associated with NLRP3 mRNA stability since the PBMCs isolated the CG and GG patients increase the NLRP3 expression approximately 2-fold Relative risks were adjusted by gender, age at HIV diagnosis, education and skin color whenever applicable, which were variables associated with multiple events of viral load blips in the bivariate analysis (P < 0.2). Abbreviations: RR = risk ratios or relative risk; aRR = adjusted relative risk; NC = not calculated.
when compared to CC patients (Ravimohan et al., 2018). These results indicate that the protection to the disease exerted by the variant possibly depends on the stable expression of the NLRP3. Although our findings do not corroborate previous studies, it is relevant to note that the current study has some limitations, as the lack of a functional NK cell characterization of HICs and the limited number of participants enrolled in our cohort. EC cohorts are difficult to establish and maintain, given that they represent a rare group of individuals. Therefore, to obtain more reliable results, additional studies with larger populations and functional studies are needed to better understand the importance and role of the HLA-C*08 and the rs10754558 G allele in the context of HIV infection.
In conclusion, our results showed an association between the absence and presence of host immunogenetic markers with the frequencies of high-level viremia episodes and the frequency of VL blips in our HICs cohort, highlighting the protective role of KIR2DL3 and KIR2DS5. Besides, we confirmed that protective HLA-B and HLA-C allelic frequencies are higher in HICs than in HIV-1 non-controllers and in the general population. Although the limitations of this study, the results presented here provide an essential contribution to understanding the genetic factors that can modulate viral control in these individuals. Additional studies aiming to identify the role of host genetics in persistent vs. transient control of HIV-1 replication in HICs will undoubtedly help a more efficient clinical management of this particular cohort.