A metagenome-wide association study of HIV disease progression in HIV controllers

iScience Article A metagenome-wide association study of HIV disease progression in HIV controllers Luis Miguel Real, Marı ´aE.Sa ´ez, Anais Corma- Go ´mez, ..., Mathias Lichterfeld, Ezequiel Ruiz- Mateos, the Swiss HIV Cohort Study [email protected] Highlights No SNP or gene was associated with the longterm non-progressor HIV control phenotype SNPs linked to LOC285696, RMI2,and chromosome 5 region showed suggestive association Process related to metallopeptidase activity showed suggestive significance SNPs previously associated with natural HIV control showed nominal association Real et al., iScience 26,107214 July 21, 2023 ª2023 The Authors. https://doi.org/10.1016/ j.isci.2023.107214 ll OPEN ACCESS iScience Article A metagenome-wide association study of HIV disease progression in HIV controllers Luis Miguel Real, 1,2,3,17 Marı ´aE.Sa ´ez, 4,17 Anais Corma-Go ´mez, 1,3 Antonio Gonzalez-Pe ´rez, 4 Christian Thorball, 5,6 Rocı ´o Ruiz, 7 Marı ´a Reyes Jimenez-Leon, 8 Alejandro Gonzalez-Serna, 1,3 Carmen Gasca-Capote, 8 Marı ´a Jose ´Bravo, 2 Jose ´Luis Royo, 2 Alberto Perez-Gomez, 8 Marı ´a Ine ´s Camacho-Sojo, 8 Isabel Gallego, 8 Joana Vitalle, 8 Sara Bachiller, 8,9 Alicia Gutierrez-Valencia, 8 Francisco Vidal, 3,10,11,12 Jacques Fellay, 5,6 Mathias Lichterfeld, 13,14,15,16 Ezequiel Ruiz-Mateos, 8,18, *and the Swiss HIV Cohort Study SUMMARY Some HIV controllers experience immunologic progression with CD4 + Tcell decline. We aimed to identify genetic factors associated with CD4 + T cell lost in HIV controllers. A total of 561 HIV controllers were included, 442 and 119 from the International HIV controllers Study Cohort and the Swiss HIV Cohort Study, respectively. No SNP or gene was associated with the long-term non-progressor HIV spontaneous control phenotype in the individual GWAS or in the meta-anal- ysis. However, SNPs previously associated with natural HIV control linked to HLA-B (rs2395029 [p = 0.005; OR = 1.70], rs59440261 [p = 0.003; OR = 1.78]), MICA (rs112243036 [p = 0.011; OR = 1.45]), and PSORS1C1 loci (rs3815087 [p = 0.017; OR = 1.39]) showed nominal association with this phenotype. Genetic factors associated with the long-term HIV controllers without risk of immunologic progression are those previously related to the overall HIV controller phenotype. INTRODUCTION HIV controllers are an extraordinary subset of individuals who are able to naturally control HIV replication in the absence of antiretroviral therapy. 1 In fact, this phenotype has been proposed as a model of functional cure. 2 The natural control of HIV infection has been considered a complex condition where host genetic factors could play a key role. For this reason, several genome-wide association studies (GWASs) have been published focused on this specific phenotype as well as in related ones such as viral load at set point and disease progression. 3,4 The SNPs more frequently associated with these related phenotypes in Caucasian individuals were rs2395029, 5–11 linked to HLA-B*5701 allele, and rs9264942, 6,7,10 linked to HLA-C locus. These findings pointed out the importance of the HLA region in all these phenotypes. However, different studies afterward revealed how some of these subjects showed clinical, immunological, and virological progression. 12,13 There are individuals eventually losing the virological control, the so-called transient controllers, opposed to persistent controllers who maintained virus control permanently. 14,15 Persistent controllers are characterized by having high HIV-specific T cell response, low viral diversity and HIV reservoir, low frequency of viral blips, and a peculiar proteomic, lipidomic, and metabolomic profiles compatible with low levels of inflammation. 15–18 In terms of immunological progression in HIV controllers, different immunological factors have been involved in CD4 + T cell loss, such as disturbance in T cell homeostasis, 19 with T cell activation 20,21 being one of the main proposed mechanisms. In relation to genetic factors involved in this specific phenotype, data are scarce. We have previously shown in a local and in a validation cohort from the International HIV controllers Study 22 that discrete genetic markers, commonly used in the clinic, such as HLA-B*57 and interferon lambda-4-related polymorphisms, were associated with protection against CD4 + Tcell loss in controllers. However, to our knowledge, there are no prior GWAS focused on this issue only taking into account the HIV controller population. 1 Unidad Clı ´nica de Enfermedades Infecciosas y Microbiologı ´a, Hospital Universitario Virgen de Valme, Instituto de Biomedicina de Sevilla, IBIS, Sevilla, Spain 2 Departamento de Especialidades Quiru ´rgicas, Bioquı ´mica e Inmunologı ´a, Facultad de Medicina, Universidad de Ma ´laga, Ma ´laga, Spain 3 Centro de Investigacio ´n Biome ´dica en Red de Enfermedades Infecciosas (CIBERINFEC)-Instituto de Salud Carlos III, Madrid, Spain 4 Centro Andaluz de Estudios Bioinforma ´ticos (CAEBI, SL), Sevilla, Spain 5 School of Life Sciences, E ´cole Polytechnique Fe ´de ´rale de Lausanne, Lausanne, Switzerland 6 Precision Medicine Unit, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland 7 Departamento de Bioquı ´mica y Biologı ´a Molecular, Facultad de Farmacia, Universidad de Sevilla/Instituto de Biomedicina de Sevilla- Hospital Universitario Virgen del Rocı ´o/CSIC/Universidad de Sevilla, 41012 Sevilla, Spain 8 Institute of Biomedicine of Seville, IBiS/Virgen del Rocı ´o University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain 9 Department of Medical Biochemistry, Molecular Biology and Immunology, School of Medicine, Continued iScience 26, 107214, July 21, 2023 ª2023 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 1 ll OPEN ACCESS Identifying biological markers of HIV-1 controllers who are at risk for HIV-1 disease progression as defined by declining CD4 + T cell counts is an important objective, both for improving clinical care of these persons and for extending the conceptual understanding of immune mechanisms involved in persistent long-term non-progressor HIV spontaneous control (LTNP-C) as the right model of functional cure. Because of this, the aim of this study was to analyze genetic determinants, at a genome-wide association level, related to the LTNP-C phenotype in HIV controllers. RESULTS Study populations A total of 443 and 120 individuals from the International HIV controllers Study Cohort (ICSC) and the Swiss HIV Cohort Study (SHCS), respectively, fulfilled the inclusion criteria. Among them, 233 (52.7%) subjects in the ICSC and 59 (49.2%) subjects in the SHCS were LTNP-Cs. After quality controls, 442 and 119 subjects remained in the ICSC and SHCS cohorts, respectively. These individuals constituted the study populations. Among them, 233 (52.7%) individuals in the ICSC and 58 (48.7%) individuals in the SHCS were LTNP-Cs. Main characteristics of both populations are depicted in Tables 1 and 2. Single-locus association analyses and meta-GWAS A total of 477,986 and 9,829,427 SNPs were available in the ICSC and SHCS datasets, respectively. Among them, 5,766,421 SNPs passed the quality controls in the SHCS dataset. Regarding the ISCS dataset, 477,952 SNPs remained after the quality controls. Overall, a total of 7,597,066 SNPs were available for association studies after imputation. Principal component (PC) analysis performed among each dataset did not reveal population admixture (Figures S1A and S1B). Moreover, there was no overall inflation of the test statistic (ƛ%1.05) on each of them (Figures S2A and S2B), supporting that systematic confounding factors were unlikely in both populations. Results of single-locus genetic association analysis adjusted by PC vectors, age, sex, and the elite controller condition on each dataset did not reveal any marker associated with the LTNP-C phenotype in any of the two datasets analyzed. However, 28 suggestive signals (p < 10 5 )werefoundintheICSCpopulation (Table S1 and Figure S3). We analyzed combined data from both datasets using the meta-analysis tool in Plink. A total of 4,562,723 SNPs were common in both datasets. Again, there was no overall inflation of the test statistic (ƛ= 1.00) in this analysis (Figure S4). No SNP was associated with the LTNP-C phenotype at GWAS significant p value (Figure 1). Nevertheless, 17 SNPs, linked to LOC285696,RMI2 loci, and to an intergenic region within chromosome 5, showed suggestive association (Table 3). Table 1. Main characteristics of subjects selected from the International HIV controllers Study Cohort Variables LTNP-C (n = 233) Non-LTNP-C (n = 209) p; OR (95%CI) Female, n (%) 42 (18.0) 38 (18.2) 0.95; 1.02 [0.63–1.65] Age at HIV diagnosis, years a 32 [26–28] 35 [29–41] <0.001; 0.96 [0.94–0.98] Calendar year of HIV diagnosis, n (%) 1980–1989 97 (41.6) 19 (9.1) Ref. 1990–1999 100 (42.9) 43 (20.7) <0.001; 20.71 [11.22–38.20] 2000–2008 36 (15.5) 146 (70.2) <0.001; 9.43 [5.66–15.72] PWID, n (%) 24 (10.3) 14 (6.7) 0.19; 1.59 [0.80–3.17] Elite, n (%) 83 (35.6) 51 (24.4) 0.01; 1.70 [1.13–2.60] PWID, people who have ever injected drugs; LTNP-C, long-term non-progress controllers; OR, Odds ratio; CI, confidence interval. Ref., reference variable. a Median (quartile 1 – quartile 3). Data available in 440 individuals. University of Seville, Seville, Spain 10 Hospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain 11 Institut Investigacio ´ Sanita `ria Pere Virgili (IISPV), Tarragona, Spain 12 Universitat Rovira i Virgili (URV), Tarragona, Spain 13 Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA 14 Harvard Medical School, Boston, MA, USA 15 Infectious Disease Division, Massachusetts General Hospital, Boston, MA, USA 16 Infectious Disease Division, Brigham and Women’s Hospital, Boston, MA, USA 17 These authors contributed equally 18 Lead contact *Correspondence: [email protected] https://doi.org/10.1016/j.isci. 2023.107214 ll OPEN ACCESS 2iScience 26, 107214, July 21, 2023 iScienc e Article Gene-based association and enrichment analyses The results obtained in the meta-analysis were analyzed with the Magma software for carrying a genebased association analysis. A total of 18,173 genes were ranked, but none of them reached the threshold p value stablished after multiple testing correction. Despite this, the RMI2 gene reached suggestive statistical significance (p_SNPwise_mean value = 7.52 310 6 )(Table S2). We analyzed if the best 200 ranked genes obtained in the gene-based association study (Table S2)were significantly aggregated in specific categories of Gene Ontology for biological processes. The process related to metallopeptidase activity reached the FDR p value threshold stablished (Table 4). Analysis of SNPs previously associated with the HIV control or related phenotypes Table 5 shows those SNPs previously associated at GWAS p value significant level with HIV controllers, viral load at set point, and/or disease progression reported in GWAS performed in Caucasians that were Figure 1. Manhattan plot of meta-analysis of the two GWAs carried out in selected subjects from the Swiss HIV Cohort Study and from the International HIV controllers Study Cohort Horizontal lines correspond to 1 310 5 and 5 310 8 p values, respectively. Table 2. Main characteristics of subjects selected from the Swiss HIV Cohort Study Variables LTNP-C (n = 58) Non-LTNP-C (n = 61) p; OR (95%CI) Female, n (%) 23 (39.7) 25 (41.0) 0.88; 1.06 [0.51–2.12] Age at HIV diagnosis, years a 31 [24–37] 30 [26–38] 0.33; 0.98 [0.95–1.02] Calendar year of HIV diagnosis, n (%) 1980–1989 14 (24) 8 (13.1) Ref. 1990–1999 24 (41.4) 34 (55.7) 0.35; 1.66 [0.57–4.86] 2000–2008 20 (34.5) 19 (31.1) 0.34; 0.67 [0.30–1.52] PWID, n (%) 15 (25.9) 20 (32.8) 0.41; 1.40 [0.63–3.10] Elite, n (%) 18 (31) 13 (21.3) 0.23; 1.70 [0.73–3.80] PWID, people who have ever injected drugs; LTNP-C, long-term non-progress controllers; OR, Odds ratio; CI, confidence interval. Ref., reference variable. a Median (quartile 1 – quartile 3). ll OPEN ACCESS iScience 26, 107214, July 21, 2023 3 iScienc e Article available in our meta-analysis. Four of them showed nominal association with the LTNP-C phenotype in the same direction that previously was reported (Table 5). DISCUSSION This study shows that those genetic factors previously associated with the spontaneous HIV control in the overall HIV controller population seem to be also involved in the long-term maintenance of CD4 + Tcellsin HIV controllers. However, neither single-locus association analyses nor gene-based association analyses yielded statistically significant results at the p value thresholds stablished. Taken together, these facts could suggest that non-genetic factors or genetic-environment interactions could have a more important role in the protection against the CD4 + TcelllossinHIVcontrollersthan genetic factors. According to this hypothesis, we previously identified differences in virological and immune factors between subjects with persistent control of viral replication and controllers who lost virological control. 13,15,17,18 Moreover, it has been reported that viral genetic variation has also a key role in the progression of the disease in Caucasian subjects. 26 Despite this, some suggestive signals were observed in our meta-analysis that deserve attention. Most of them were linked to LOC285696,alsoknownasBASP1 antisense RNA 1 (BASP1-AS1). BASP1-AS1 regulates the expression of its adjacent coding gene, BASP1, which seems to be involved in Th17 cells differentiation. 27 This subtype of CD4 + T cells are especially susceptible to HIV infection and, for that reason, this subpopulation appear depleted in infected individuals, but not in elite controllers. 28 In addition, it has also been suggested that the expression of BASP1 might be involved in modulation of the transcriptional program during T cell apoptosis. 29 Similarly, some of the better signals were reached by SNPs linked to RMI2 gene. Moreover, this gene was the top signal in the gene-based association analyses. RMI2 is a component of a protein complex together with BLM and topoisomerase IIIa(OMIM * 612426). This complex is involved in the regulation of genome integrity, a key process in lymphocyte proliferation. 30 Interestingly, the metalloprotease activity was the only biological processes associated with the LTNP-C phenotype in our study. The HIV infection has been related to the matrix metalloproteinase dysregulation. Table 3. Best single locus results (p < 10 5 ) using the meta-analysis tool in Plink CHR SNP BP A1 P P(R) OR OR(R) Q I ANNOT 5 rs2261514 17145620 A 1.75 310 6 4.58 310 6 2.19 2.18 0.306 4.33 LOC285696 16 rs35578928 11467777 A 2.33 310 6 2.33 310 6 2.28 2.28 0.432 0 RMI2 a 5 rs11739746 17147118 C 3.15 310 6 3.15 310 6 2.17 2.17 0.571 0 LOC285696 5 rs2624417 17148318 A 3.15 310 6 3.15 310 6 2.17 2.17 0.571 0 LOC285696 5 rs2731804 17146261 C 3.60 310 6 3.60 310 6 2.13 2.13 0.354 0 LOC285696 5 rs2652674 17152228 G 5.01 310 6 5.01 310 6 2.12 2.12 0.476 0 LOC285696 5 rs2170525 17132500 T 5.33 310 6 2.71 310 6 2.04 1.95 0.201 38.84 LOC285696 5 rs2731796 17153618 G 5.63 310 6 4.58 310 5 2.09 2.06 0.289 10.93 LOC285696 5 rs2731795 17154626 A 5.63 310 6 4.58 310 5 2.09 2.06 0.289 10.93 LOC285696 5 rs2652666 17119879 T 5.64 310 6 0.077 1.99 1.77 0.057 72.29 LOC285696 a 5 rs2731788 17130597 T 5.94 310 6 0.017 2.04 1.88 0.134 55.25 LOC285696 5 rs2624429 17142201 G 7.32 310 6 0.009 2.03 1.90 0.167 47.43 LOC285696 5 rs2624431 17136611 G 8.63 310 6 6.81 310 5 2.02 2.01 0.290 10.38 LOC285696 5 rs2731806 17141956 A 8.63 310 6 6.81 310 6 2.02 2.00 0.290 10.38 LOC285696 16 rs4508435 11478703 G 9.11 310 6 9.11 310 6 1.99 1.99 0.740 0 RMI2 a 5 rs67834917 62282963 G 9.70 310 6 9.70 310 6 0.49 0.49 0.446 0 . 5 rs72756740 62286523 T 9.70 310 6 9.70 310 6 0.49 0.49 0.446 0 . CHR, Chromosome; SNP, Single-nucleotide polymorphism; BP, Base pair position according to UCSC genome browser (NCBI37/hg19) and dbSNP build 142; A1, Reference allele (minor allele); p, Fixed-effects p value; p(R), Random-effects p value; OR, Fixed-effects odds ratio (for LTNP-C condition); OR(R), Random-effects OR; Q, p value for heterogeneity of OR; I, effect size for heterogeneity of OR. Gene names are shown in italics. a Closer gene within 200 kilobases. ll OPEN ACCESS 4iScience 26, 107214, July 21, 2023 iScienc e Article In fact, the increment of metalloprotease activity has been associated with both the HIV dissemination and HIV-related pathology progression. 31 However, its specific role in the LTNP-C phenotype is not known. All these results warrant future validations in independent studies. Among those SNPs previously associated with the natural HIV control or related phenotypes analyzed in our study, four were associated with the LTNP-C phenotype. One of the strongest associations was observed with the rs2395029 marker within the HCP5 gene and linked to the HLA-B*5701 allele. This SNP was previously associated with viral load at set point, 6,7 HIV-1 disease progression, 6 and HIV-1 controller phenotype. 5,9–11 Likewise, other markers linked to the HLAB locus such as rs59440261, in partial linkage disequilibrium with rs2395029, 25 and rs9266409, located in the 30region of HLA-B, all of them previously associated with viral load at set point, 6 were also associated, or tended to be associated, with the LTNP-C phenotype in our study. These results are in agreement with our previous study that found an association between the HLA-B*57 allele and protection against CD4 + Tcelllossin controllers. 22 Interestingly, rs112243036 within MICA genealsoshowedassociationwiththeLTNP-Cphenotypeinour study. This marker was previously independently associated with HIV controllers. 23 It has been proposed that the rs2395029G-rs112243036A-rs9264942C haplotype significantly favors the viral load control and the non-progressor phenotype. 23 However, the SNP rs9264942, linked to HLA-C locus and previously associated with viral load at set point and with the non-progressor phenotype, 6,7,10 was not associated with the LTNP-C phenotype in our study. Therefore, our results partially support the hypothesis that the effect of rs9264942 could be only observed in the context of rs2395029G-rs112243036A haplotype as Le Clerc et al. proposed. 23 Takentogether,allthesedatapointedoutthepossibleroleoftheHLAB and MICA loci in the maintenance of CD4 + T cell levels within HIV controllers. The fact that the most replicated genetic associations with the HIV controller phenotype are also observed in our work suggests that in previous studies, the overall HIV controller population was enriched in the LTNP-C phenotype analyzed herein. Therefore, these genetic factors could help to refine the true HIV controller phenotype characterized by the long-term HIV remission or low viral loads and absence of HIV disease progression which in the case of elite participants is similar to those previously defined as exceptional or persistent HIV controllers. 15,18,32,33 In this sense, non-LTNP-C phenotype may behave as non-controllers justifying the association of the LTNP-C phenotype with classical SNPs associated with spontaneous HIV control, such as those in HLAB and MICA loci. In conclusion, we have performed the first meta-GWAS focused in the long-term maintenance of CD4 + T cells in HIV controllers. Our results suggest that genetic factors previously associated with the overall HIV controller phenotype, mainly those linked to PSORS1C1,HLAB,andMICA loci, seem to have a role in this complex trait. In this study, we also have identified suggestive signals that deserve a validation in the future. However, GWAS and meta-GWAS analysis in larger samples, deep-sequencing of candidate genes as well as both gene-gene and genetic-environment interactions analyses will be needed to identify all the genetic variants involved in the maintenance of the non-immunological progressor HIV controller phenotype and what their real effects are. The results of the present study could help us to refine the best definition for HIV controllers. Consequently, these HIV controllers should be considered as the best model of functional cure. The study of this specific phenotype could help us to design new strategies for preventing HIV progression, not necessarily associated with antiretroviral treatment, in those subjects who show CD4 + T cell loss. Table 4. Categories of Gene Ontology (GO) (http://www.geneontology.org/) for biological processes that were enriched using the top 200 ranked genes obtained in the gene-based association analysis GO category Description Category Size Genes included p value FDR Genes included GO:0008237 metallopeptidase activity 185 9 1.29 310 5 0.015 TRHDE; NAALAD2; ASTL; ZMPSTE24; CPO; KEL; ADAMTS10; MMP20; ADAM9 FDR, False discovery rate. Gene names are shown in italics. ll OPEN ACCESS iScience 26, 107214, July 21, 2023 5 iScienc e Article Limitations of the study Our work has some limitations. First, due to the low number of individuals included on each dataset, the powerfordetectingGWASsignificantsignalscouldbelow.Giventhesamplesizeandthecase-controlra- tio in the ICSC and a minor allele frequency of a causative SNP of 0.25, this GWAS had an 80% power to detect OR>3.8 at the p value stablished in these studies. However, our meta-analysis had 80.0% power to detect OR = 3.2 at the same p value. Therefore, our study was powered to detect robust signals but not genetic factors with modest effect. However, the fact of our study was performed on a rare phenotype Table 5. Main SNPs previously associated at GWAS-p value significant with natural HIV control, HIV disease progression, or viral load set point in Caucasian populations that has been analyzed in our study CHR Linked Gene SNP Allele Reported effect Reference P p (R) OR OR (R) Q I ICSC p; OR (95%CI) SHCS p; OR (95%CI) 6HLA-C rs9264942 C Protective Fellay et al., International HIV Controllers Study, et al. 6,7,10 0.089 0.826 1.24 1.07 0.060 71.52 0.020; 1.38 (1.05–1.83) 0.317; 0.73 (0.40–1.34) 6HCP5 rs2395029 G Protective Dalmasso et al.; Fellay et al.; Le Clerc et al.; Limou et al.; International HIV Controllers Study et al.; Guergnon et al. 5–11 0.005 0.005 1.70 1.70 0.561 0 0.006; 1.81 (1.18–2.77) 0.442; 1.37 (0.60–3.22) 6MICA rs112243036 A Protective Le Clerc et al. 23 0.011 0.011 1.45 1.45 0.582 0 0.012; 1.52 (1.09–2.11) 0.515; 1.24 (0.64–2.38) 6TRIM10 rs9468692 T Not Known Fellay et al. 6 0.883 0.883 0.96 0.96 0.427 0 0.584; 0.84 (0.47–1.52) 0.553; 1.32 (0.47–3.35) 6HLA-B rs9266409 C Protective Fellay et al. 6 0.051 0.051 1.33 1.33 0.719 0 0.124; 1.29 (0.93–1.80) 0.211; 1.49 (0.80–2.69) 6PSORS1C3 rs3131018 A Protective International HIV Controllers Study et al. 10 0.898 0.898 0.98 0.98 0.693 0 0.763; 0.94 (0.67–1.34) 0.776; 1.09 (0.58–2.05) 6PSORS1C1 rs3815087 T Protective Limou et al. 9 0.017 0.017 1.39 1.39 0.316 0,55 0.091; 1.29 (0.95–1.76) 0.051; 1.84 (0.99–3.40) 6ZNRD1 rs9261174 C Not Known Fellay et al. 6 0.761 0.761 1.06 1.06 0.960 0 0.796; 1.05 (0.71–1.54) 0.867; 1.08 (0.44–2.61) 6RNF39 rs2074480 G Not Known Fellay et al. 6 0.760 0.760 1.06 1.06 0.960 0 0.795; 1.05 (0.71–1.54) 0.867; 1.08 (0.44–2.61) 6RNF39 rs2301753 T Not Known Fellay et al. 6 0.760 0.760 1.06 1.06 0.960 0 0.795; 1.05 (0.71–1.54) 0.867; 1.08 (0.44–2.61) 6ZNRD1 rs9261129 C Not Known Fellay et al. 6 0.760 0.760 1.06 1.06 0.960 0 0.795; 1.05 (0.71–1.54) 0.867; 1.07 (0.45–2.61) 3CXCR6 rs2234358 T Non Protective Limou et al. 24 0.188 0.188 0.84 0.84 0.330 0 0.470; 0.89 (0.65–1.99) 0.142; 0.66 (0.38–1.15) 6HLA-B rs59440261 A Protective McLearn et al. 25 0.003 0.003 1.78 1.78 0.657 0 0.005; 1.87 (1.21–2.90) 0.305; 1.52 (0.68–3.92) 3CCRL2 rs1015164 A Protective McLearn et al. 25 0.516 0.516 0.91 0.91 0.618 0 0.422; 0.89 (0.67–1.20) 0.866; 1.05 (0.55–2.00) CHR. Chromosome; SNP. Single Nucleotide Polymorphism; A1. Reference allele (minor allele); P. Fixed-effects p value; P(R): Random-effects p value; OR. Fixedeffects Odds Ratio (for being LTNP-C); SHCS. Swiss HIV Cohort Study; ICSC. International HIV controllers Study Cohort; Q: p value for heterogeneity of OR; I. effect size for heterogeneity of OR; OR(R); Random-effects Odds ratio; CI, Confidence interval. Common SNPs found significant in our dataset are shown in bold. Gene names are shown in italics. ll OPEN ACCESS 6iScience 26, 107214, July 21, 2023 iScienc e Article using two very well characterized cohorts are strengths of our work. Second, since meta-analysis was performed with those SNPs genotyped in both datasets, it is possible that some SNPs associated with the LTNP-C phenotype were excluded in our study. It was the case of the rs12980275 marker linked to IL28B gene, a SNP in strong linkage disequilibrium with the causative variant rs368234815 in Caucasian individuals, 34 that was previously associated with LTNP-C by us. 22 This marker was not included or imputed in theSHCSdatasetanditcouldnotbeanalyzedinthemeta-analysis.Similarly,someofthemarkers previously associated with related genotypes could not be analyzed because they have not been genotyped or imputed in one or both datasets (Table S3). However, although the possibility to exclude important SNPs exists, the inclusion of more than 4 million of SNPs in the meta-analysis minimalizes this risk. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: dKEY RESOURCES TABLE dRESOURCE AVAILABILITY BLead contact BMaterials availability BData and code availability dEXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS dMETHOD DETAILS BGenotype quality controls and genotype imputation BSingle locus association study and meta-analysis BGene-based association study and enrichment analyses dQUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.isci.2023.107214. ACKNOWLEDGMENTS This work was supported by grants from the Consejerı ´a de Salud de la Junta de Andalucı ´a (PI-0001/2017); Plan Nacional de I + D + I cofinanced by ISCIII-Subdireccio ´n General de Evaluacio ´n and Fondo Europeo de Desarrollo Regional (FEDER) co-funded by the European Union (www.red.es/redes/inicio) (RD16/0025/ 0040, RD12/0017/0012). E.R.-M. was supported by Consejo Superior de Investigaciones Cientı ´ficas (CSIC) and Consejerı ´a de Salud y Bienestar Social, Junta de Andalucı ´a through the Nicola ´sMonardesProgram (C-0032/17) and Fondo de Investigacio ´n Sanitaria, Instituto de Salud CarlosIII,FondosEuropeospara el Desarrollo Regional, FEDER, co-funded by the European Union grants PI16/00684, PI19/01127, PI22/ 01796, PI10/02635, PI13/0796, PI16/00503 and PI19/01337, ‘‘A way to make Europe’’/’’Investing in your future’’; RETICS, Red de Investigacio ´n en SIDA co-funded by the European Union (RD16/0025/0020, RD16/0025/0006-ISCIII-FEDER (Spain). Programa de Suport als Grups de Recerca AGAUR (2017SGR948); Gilead Fellowship Program GLD14/293 and GLD22/00147. F.V. is supported by grants from the Programa de Intensificacio ´n de Investigadores (l)-ISCIII. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This study would not have been possible without the collaboration of the patients, medical and nursery staff, and data managers who took part in the project. Members of the Swiss HIV Cohort Study: Anagnostopoulos A, Battegay M, Bernasconi E, Bo ¨ni J, Braun DL, Bucher HC, Calmy A, Cavassini M, Ciuffi A, Dollenmaier G, Egger M, Elzi L, Fehr J, Fellay J, Furrer H, Fux CA, Gu ¨nthard HF (President of the SHCS), Haerry D (deputy of ‘‘Positive Council’’), Hasse B, Hirsch HH, Hoffmann M, Ho ¨sli I, Huber M, Kahlert CR (Chairman of the Mother & Child Substudy), Kaiser L, Keiser O, Klimkait T, Kouyos RD, Kovari H, Ledergerber B, Martinetti G, Martinez de Tejada B, Marzolini C, Metzner KJ, Mu ¨ller N, Nicca D, Paioni P, Pantaleo G, Perreau M, Rauch A (Chairman of the Scientific Board), Rudin C, Scherrer AU (Head of Data Center), Schmid P, Speck R, Sto ¨ckleM(ChairmanoftheClinical and Laboratory Committee), Tarr P, Trkola A, Vernazza P, Wandeler G, Weber R, Yerly S. ll OPEN ACCESS iScience 26, 107214, July 21, 2023 7 iScienc e Article AUTHOR CONTRIBUTIONS Studydesign:L.M.R.,M.E.S.,E.R.M.;rawgenomic-datamanagement:C.T.,J.F.,M.L.,E.R.M.;dataquality controls and statistical analysis: L.M.R., M.E.S., A.G.P., R.R., E.R.M.; data interpretation: L.M.R., M.E.S., A.C.G., M.R.J.L., A.G.S., C.G.C., M.J.B., J.L.R., A.P.G., I.C.S., I.G., J.V., S.B., A.G.V., F.V., E.R.M.; writers: L.M.R., M.E.S., E.R.M. with contribution of all authors. All authors read and approved the final manuscript. DECLARATION OF INTERESTS The authors declare no competing interests. INCLUSION AND DIVERSITY We support inclusive, diverse, and equitable conduct of research. Received: April 4, 2023 Revised: May 19, 2023 Accepted: June 22, 2023 Published: June 26, 2023 REFERENCES 1. Lambotte, O., Boufassa, F., Madec, Y., Nguyen, A., Goujard, C., Meyer, L., Rouzioux, C., Venet, A., and Delfraissy, J.F.; SEROCOHEMOCO Study Group (2005). HIV controllers: a homogeneous group of HIV-1- infected patients with spontaneous control of viral replication. Clin. Infect. Dis. 41, 1053– 1056. https://doi.org/10.1086/433188. 2. Autran, B., Descours, B., Avettand-Fenoel, V., and Rouzioux, C. (2011). Elite controllers as a model of functional cure. Curr. Opin. HIV AIDS 6, 181–187. https://doi.org/10.1097/ COH.0b013e328345a328. 3. Le Clerc, S., Limou, S., and Zagury, J.F. (2019). Large-Scale "OMICS" Studies to Explore the Physiopatholgy of HIV-1 Infection. Front. Genet. 10, 799. https://doi.org/10.3389/ fgene.2019.00799. 4. Limou, S., and Zagury, J.F. (2013). Immunogenetics: Genome-Wide Association of Non-Progressive HIV and Viral Load Control: HLA Genes and Beyond. Front. Immunol. 4, 118. https://doi.org/10.3389/ fimmu.2013.00118. 5. Dalmasso, C., Carpentier, W., Meyer, L., Rouzioux, C., Goujard, C., Chaix, M.L., Lambotte, O., Avettand-Fenoel, V., Le Clerc, S., de Senneville, L.D., et al. (2008). Distinct genetic loci control plasma HIV-RNA and cellular HIV-DNA levels in HIV-1 infection: the ANRS Genome Wide Association 01 study. PLoS One 3, e3907. https://doi.org/10.1371/ journal.pone.0003907. 6. Fellay, J., Ge, D., Shianna, K.V., Colombo, S., Ledergerber, B., Cirulli, E.T., Urban, T.J., Zhang, K., Gumbs, C.E., Smith, J.P., et al. (2009). Common genetic variation and the control of HIV-1 in humans. PLoS Genet. 5, e1000791. https://doi.org/10.1371/journal. pgen.1000791. 7. Fellay, J., Shianna, K.V., Ge, D., Colombo, S., Ledergerber, B., Weale, M., Zhang, K., Gumbs, C., Castagna, A., Cossarizza, A., et al. (2007). A whole-genome association study of major determinants for host control of HIV-1. Science 317, 944–947. https://doi.org/10. 1126/science.1143767. 8. Le Clerc, S., Limou, S., Coulonges, C., Carpentier, W., Dina, C., Taing, L., Delaneau, O., Labib, T., Sladek, R., ANRS Genomic Group, et al. (2009). Genomewide association study of a rapid progression cohort identifies new susceptibility alleles for AIDS (ANRS Genomewide Association Study 03). J. Infect. Dis. 200, 1194–1201. https://doi.org/10.1086/ 605892. 9. Limou, S., Le Clerc, S., Coulonges, C., Carpentier, W., Dina, C., Delaneau, O., Labib, T., Taing, L., Sladek, R., Deveau, C., et al. (2009). Genomewide association study of an AIDS-nonprogression cohort emphasizes the role played by HLA genes (ANRS Genomewide Association Study 02). J. Infect. Dis. 199, 419–426. https://doi.org/10.1086/ 596067. 10. International HIV Controllers Study, Pereyra, F., Jia, X., McLaren, P.J., Telenti, A., de Bakker, P.I.W., Walker, B.D., Ripke, S., Brumme, C.J., Pulit, S.L., et al. (2010). The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science 330, 1551–1557. https://doi.org/10. 1126/science.1195271. 11. Guergnon, J., Dalmasso, C., Broet, P., Meyer, L., Westrop, S.J., Imami, N., Vicenzi, E., Morsica, G., Tinelli, M., Zanone Poma, B., et al. (2012). Single-nucleotide polymorphism-defined class I and class III major histocompatibility complex genetic subregions contribute to natural long-term nonprogression in HIV infection. J. Infect. Dis. 205, 718–724. https://doi.org/10.1093/infdis/ jir833. 12. Leon, A., Perez, I., Ruiz-Mateos, E., Benito, J.M., Leal, M., Lopez-Galindez, C., Rallon, N., Alcami, J., Lopez-Aldeguer, J., Viciana, P., et al. (2016). Rate and predictors of progression in elite and viremic HIV-1 controllers. AIDS 30, 1209–1220. https://doi. org/10.1097/QAD.0000000000001050. 13. Chereau, F., Madec, Y., Sabin, C., Obel, N., Ruiz-Mateos, E., Chrysos, G., Fidler, S., Lehmann, C., Zangerle, R., Wittkop, L., et al. (2017). Impact of CD4 and CD8 dynamics and viral rebounds on loss of virological control in HIV controllers. PLoS One 12, e0173893. https://doi.org/10.1371/journal.pone. 0173893. 14. Dominguez-Molina, B., Leon, A., Rodriguez, C., Benito, J.M., Lopez-Galindez, C., Garcia, F., Del Romero, J., Gutierrez, F., Viciana, P., Alcami, J., et al. (2016). Analysis of Non-AIDS- Defining Events in HIV Controllers. Clin. Infect. Dis. 62, 1304–1309. https://doi.org/10. 1093/cid/ciw120. 15. Pernas, M., Taranco ´n-Diez, L., Rodrı ´guez- Gallego, E., Go ´mez, J., Prado, J.G., Casado, C., Dominguez-Molina, B., Olivares, I., Coiras, M., Leo ´n, A., et al. (2018). Factors Leading to the Loss of Natural Elite Control of HIV-1 Infection. J. Virol. 92, e01805-17. https://doi. org/10.1128/JVI.01805-17. 16. Canouı ¨, E., Le ´curoux, C., Avettand-Fenoe ¨l, V., Gousset, M., Rouzioux, C., Saez-Cirion, A., Meyer, L., Boufassa, F., Lambotte, O., Noe ¨l, N., et al. (2017). A Subset of Extreme Human Immunodeficiency Virus (HIV) Controllers Is Characterized by a Small HIV Blood Reservoir and a Weak T-Cell Activation Level. Open Forum Infect. Dis. 4, ofx064. https://doi.org/ 10.1093/ofid/ofx064. 17. Rodrı ´guez-Gallego, E., Taranco ´n-Diez, L., Garcı ´a, F., Del Romero, J., Benito, J.M., Alba, V., Herrero, P., Rull, A., Dominguez-Molina, B., Martinez-Madrid, O., et al. (2019). Proteomic Profile Associated With Loss of Spontaneous Human Immunodeficiency Virus Type 1 Elite Control. J. Infect. Dis. 219, 867–876. https://doi.org/10.1093/infdis/ jiy599. 18. Tarancon-Diez, L., Rodrı ´guez-Gallego, E., Rull, A., Peraire, J., Vilade ´s, C., Portilla, I., Jimenez-Leon, M.R., Alba, V., Herrero, P., Leal, M., et al. (2019). Immunometabolism is a key factor for the persistent spontaneous elite control of HIV-1 infection. EBioMedicine 42, ll OPEN ACCESS 8iScience 26, 107214, July 21, 2023 iScienc e Article