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Association of complement C3d receptor 2 genotypes with the acquisition of HIV infection in a trial of recombinant glycoprotein 120 vaccine

Meza, Giovannaa,b,*; Expósito, Almudenaa,*; Royo, José L.c; Ruiz-García, Celiaa; Sánchez-Arcas, Beatriza; Marquez, Francisco J.a; Gómez-Vidal, María A.d; Omar, Mohamedd; Sinangil, Faruke; Higgins, Keithe; Forthal, Donaldf; Real, Luis M.c,g; Caruz, Antonioa

Author Information
doi: 10.1097/QAD.0000000000002401



Host genetics may impact HIV-1 susceptibility and immune response to vaccination [1]. The immunogenetics of HIV-1 vaccine efficacy is a poorly explored issue, and only four loci have been identified so far [2–5]. The discovery of new biomarkers associated with response to HIV-1 vaccination in clinical trials can contribute to a better understanding the molecular mechanism of protection, improving vaccines design and vaccinees selection according to the individual's genetic profile.

In a previous candidate gene association study, we identified complement C3d receptor 2 (CR2) as a host genetic factor associated with innate resistance to HIV-1 in intravenous drug users as well as serodiscordant couples [6]. The HIV-protective CR2 haplotype displays lower levels of total CR2 mRNA as well as altered isoform expression [6].

The CR2 gene encodes a membrane protein which functions as the main receptor for C3d/iC3. CR2 together with CD19, CD81, and CD225 forms the B-cell coreceptor complex on the surface of B-lymphocytes. The binding of CR2 with immune complexes coated with C3 results in enhanced B-lymphocyte proliferation and up regulation of costimulatory molecules. On follicular dendritic cells CR2 captures C3 coated antigens, apparently to hold them on the surface for long periods of time, facilitating a prolonged immune response [7]. In the mouse model, Cr2 expression on follicular dendritic cells is necessary for the generation of a robust antigen-specific IgG response [8]. In addition, inhibition of mouse Cr2 with mAb or soluble Cr2 decreases primary antibody response to antigens [9].

CR2 function can be subverted by some viruses that use antibodies and complement for a highly efficient entry into target cells; in a process known as antibody-dependent enhancement of viral infection.

Three types of antibody-dependent enhancement have been described in the context of HIV-1. The first one depends on the interaction between antibody and FcR, particularly FCGR3A [2]. The second type of enhancement is mediated by anti-HIV antibodies by inducing alllosteric changes in HIV-1 envelope that increases viral interaction with cellular receptors [10]. Finally, antibody-dependent complement activation can boost infection of dendritic cells and monocytes/macrophages [11]. This mechanism is dependent on the CR2/CR1 expression on the target cells [11,12] and is probably mediated by and increased adhesion of the virus–antibody–complement complexes to CR2 on the target-cell surface. In other viral infections such as those caused by dengue virus, severe acute respiratory syndrome-related coronavirus or feline immunodeficiency virus, antibody-dependent enhancement plays an important role in the vaccine efficacy [13–15].

No immune-related phenotype has been explored in relation with CR2 variants, but it is likely that CR2 functional polymorphisms could modulate the range of IgG response. In this context, we hypothesize that CR2 genotypes can affect the rate of infection with HIV-1 after vaccination with recombinant gp120.

Patients and method


The retrospective cross-sectional study was carried out in 675 peripheral blood mononuclear cells (PBMC) samples from males of European ancestry vaccinees or placebo recipients participating in the Vax004 trial ( Identifier: NCT00002441) [16]. The vaccine consisted of 300 μg each of 2 rgp120 envelope subunits derived from the subtype B isolates MN and GNE8 absorbed onto 600 μg of alum. Volunteers were randomized to receive vaccine or placebo (alum) by intramuscular injection at months 0, 1, 6, 12, 18, 24, and 30. Samples are from available volunteers that became infected with HIV during trial (n = 273) and from a random sample of volunteers that remained uninfected (n = 402). The median age of all volunteers was 35 (range 30–43) years old. The main epidemiological and clinical characteristics of these volunteers have been previously described [16,17]. Volunteers were classified as having low or high baseline risk on the basis of self reported behaviors during the 6 months before enrollment. These behaviors were highly predictive of HIV infection in men [16]. Behavioral risk scores ranged from 0 to 7 and was defined as the total number of risk factors reported from the following: unprotected receptive anal sex with an HIV-1-infected male partner; unprotected insertive anal sex with an HIV-1-infected male partner; unprotected receptive anal sex with an HIV-1-uninfected male partner; five or less acts of unprotected receptive anal sex with a male partner of unknown HIV-1 status; 10 or less sex partners; anal herpes; hepatitis A; use of poppers; and use of amphetamines. Dichotomization was conducted by collapsing the seven risk score categories into two binary categories with approximately equal sample size, risk score of 1 or less was categorized as low-risk and risk score at least 2 as high-risk behaviors.

Ethical approval

The study was designed and performed according to the Helsinki declaration and was approved by the Institutional Review Board of the Universidad de Jaen. All patients provided written informed consent to participate in the Vax004 trial.

Polymorphism selection and genotyping

Three single nucleotide polymorphisms (SNPs) within the CR2 gene were selected, they were previously associated with HIV-1 susceptibility among intravenous drug users [6] and autoimmune diseases [18,19]. The rs3813946 (minor allele frequency C = 0.20), is placed in the 5′UTR and alters CR2 transcription [20,21]; rs1567190 is located in the first intron (minor allele frequency C = 0.49) modulates the alternative splicing of CR2 [6] and rs17615 is placed in the coding region of exon 9 (minor allele frequency C = 0.29). rs17615 causes a nonsynonymous change in CR2 from serine to asparagine in the position 639, probably affecting the protein function according to the PolyPhen algorithm ( (Supplementary Fig. 1, The minor allele frequencies of these SNPs in European populations were obtained from the dbSNP (

DNA was extracted from frozen PBMC using the Tripure Reagent (Sigma-Aldrich, St. Louis, Missouri, USA). The polymorphic markers were genotyped using commercial Taqman assay (Applied Biosystems, Foster City, California, USA), according to the manufacturer's instructions, using the Eco thermocycler (Illumina, San Diego, California, USA).

Statistical analyses

For the comparison of SNP genotypic distributions between groups and to carry out the Hardy–Weinberg equilibrium test, we used the online resource at the Institute for Human Genetics, Munich, Germany ( [22], with the exception of rs381346 genotype distribution analysis in the placebo treated volunteers with high-risk score of HIV infection where the Fisher's exact test was used. Pairwise linkage disequilibrium (D′) was calculated using Haploview V4.1 software (Broad Institute, Cambridge, Massachusetts, USA) [22]. Block structure was considered for marker pairs showing D′ more than 0.8, following the solid-spine block definition. The genetic models selected for association analyses were those previously described or those that reached the lowest P values.

Logistic regression models were elaborated including variables with a univariate P value less than 0.20, as well as age, to obtain adjusted P and odds ratio (OR) values and to detect independent risk factors associated with HIV-1 infection after vaccination. To explore prespecified baseline risk behavior subgroups, we introduced the interaction terms in the models including the rs3813946 genotype.

Breslow–Day test was used to test homogeneity of the ORs in the stratified analyses. Kaplan–Meier estimates of the cumulative probability of HIV-1 infection were calculated using the log-rank test. Those variables with a P value of 0.2 or less on univariate analyses were entered in multivariate Cox models. Again, to explore genotype-risk behavior interaction we introduced the interaction terms in the models. The study of the effect of CR2 genotypes separately on HIV acquisition in the vaccine and placebo group was a post-hoc decision. All these calculations were carried out using the SPSS statistical software package release 23.0 (IBM Corporation, Somers, New York, USA). To correct for multiple comparisons, a P value less than 0.017 was considered significant (0.05/no. loci). All the P values were two-tailed.


Features of the study population

All individuals participating in this study were male of European ancestry who were vaccinated (n = 392) or treated with placebo (n = 283) in the setting of the Vax004 trial. All of them were followed for 3 years after enrollment. All the available samples from vaccinees that become HIV-1 infected were included in this study, n = 189 (48.2%) and a random sample of n = 202 uninfected vaccinees (51.8%). A total of n = 194 vaccinees (49.2%) were classified as having high-risk baseline behavior for infection (risk score ≥2). We included all the placebo-treated individuals that became infected during the trial with available samples, n = 84 (29.5%) and a random sample of placebo-treated uninfected individuals n = 200 (70.5%). A total of 161 of placebo recipients (56.6%) were classified as having high-risk behavior for infection (risk score ≥2).

Genetic and sexual behavioral factors associated with HIV-infection after vaccination

The genotyping call rate in the entire sample was 99% for the three selected polymorphisms. All of them were in high linkage disequilibrium (Supplementary Fig. 1, The genotypic distributions for the three SNPs in the entire population were in accordance with the Hardy–Weinberg equilibrium law (P value >0.1 in all cases) and similar to those reported for European populations. Table 1 depict the overall genotypic distributions of these SNPs in the vaccinated and placebo-treated population according to the HIV-infection status after the end of the follow-up. None of these genetic markers were associated with HIV-1 infection in the population of vaccinees or placebo-treated volunteers (Table 1).

Table 1
Table 1:
Risk factors associated with HIV infection in vaccines (a) and placebo treated volunteers (b).

In vaccinated individuals the genotypic counts were in accordance with the Hardy–Weinberg equilibrium law for rs1590167 and rs17615 (P > 0.1 in both cases) but not for rs3813946. The genotypic distribution of this SNP in the group of volunteers that become infected during the trial was deviated from the Hardy-Weinberg equilibrium (P value = 0.008) due to an excess of CC genotypes.

Sexual behavior measured by the baseline risk score was the factor more strongly associated with HIV-1 infection after vaccination in the univariate analysis (Table 1a). Significantly, the rs3813946 genetic marker showed a trend to significant statistical association. Sexual behavior, use of drugs and the prevalence of other sexually transmitted infections are risk factors associated with HIV-1 infection rates in several studies. These environmental factors could interact with the genotype to modify susceptibility to HIV-1 infection [2,23]. To test it, we applied general lineal models analysis and it was observed evidence of interaction (Table 1). Both, the rs3813946 genetic marker and the baseline risk score were independent risk factor for HIV infection in that model (Table 1a). In contrast, these effects were not observed in the placebo-treated population (Table 1b).

Stratified genetic association analyses and prevalence of HIV-1 infection

Because the interaction observed between the rs3813946 genetic marker and the baseline risk score, we analyzed the effect of rs3813946 in the subgroups of volunteers classified according to the risk score preassigned during the Vax004 trial [16]. A total of 199 volunteers were classified as having low-risk behaviors (risk score ≤1) and 194 volunteers with high-risk behaviors (risk score ≥2). There were a higher proportion of CC individuals (C minor allele) and fewer CT heterozygous individuals in the vaccinated low-risk volunteers that become infected during the trial compared with the high-risk group (Table 2); P value = 0.006; OR [95% confidence interval (CI)] = 5.58 (1.43–21.70) versus P value = 0.41; OR [95% CI) = 0.59 (0.16–2.12), respectively (Breslow–Day test P value = 0.014). In addition, the genetic distribution of this marker among HIV-1 infected volunteers with low-risk behavior strongly deviated from the Hardy-Weinberg equilibrium law (P value = 0.0006).

Table 2
Table 2:
Genetic factors associated with HIV infection in vaccines stratified according to sexual risk behavior (a) high-risk score and (b) low-risk score.

Neither the SNP rs17615 located in the coding region of CR2 nor the intronic rs1590167 showed association with HIV-1 infection after vaccination in the global population (Table 1) or stratified according to baseline risk behavior (Table 2).

When the same analysis was carried out in the placebo group it was not observed any association of these polymorphisms with HIV-1 infection susceptibility neither in the high-risk score nor low-risk score subgroups (Table 3).

Table 3
Table 3:
Genetic factors associated with HIV infection among placebo recipients stratified by sexual risk behavior (a) high-risk score and (b) low-risk score.

Factors associated with the rate of HIV-1 acquisition after vaccination

In the univariate analyses only the risk score was associated with the probability of HIV infection in the vaccinated population during the follow-up (Table 4). Significantly, the rs3813946 genetic marker again showed a trend to significant statistical association. And again, it was observed interaction between that genetic marker and the baseline risk score in the multivariate Cox analysis (P = 0.01), being both of them independently associated with a shorter time to be infected by HIV-1. (Table 4). The analysis restricted to the low-risk behavior group revealed that rs3813946 CC genotype was strongly associated with the rate of HIV-1 infection [hazard ratio (95% CI) = 3.38 (1.61–7.09), P = 0.001], this association was not observed in the vaccinated high-risk group (P = 0.30) (Fig. 1) neither among the individuals treated with placebo (data not shown).

Table 4
Table 4:
Independent predictor factors associated with time to HIV infection in vaccinees during the follow-up.
Fig. 1
Fig. 1:
Association of CR2 rs3813946 genotypes with the rate of HIV-1 infection after vaccination.(a) Volunteer with baseline low sexual risk behavior. (b) Volunteer with baseline high sexual risk behavior.


In this study, we found an association between a SNP at rs3813946 in the CR2 gene and susceptibility to infection by HIV-1 among gp120-vaccinated individuals with low-risk-behavior. We found no such association among placebo recipients.

Other SNPs in the same gene previously associated with resistance to HIV-1 infection [6] showed no association with HIV-1 acquisition either in vaccinees or placebo-treated volunteers, suggesting that the effect of this SNP is not related to innate resistance to HIV-1 infection. Rather, these findings suggest that CR2 could play a role in the sexual transmission of HIV-1 in the context of vaccine-induced antibodies, perhaps through enhancement of target cell infection in vivo.

Opsonization of HIV-1 with complement and antibodies leads to deposition of C3 and C3-degradation fragments onto the surface virions. Opsonized viruses interact with target cells (B lymphocytes, a subset of T-lymphocytes and follicular dendritic cells) using CR2 for leading a higher infection rate. Enhancement of HIV-1 infection by complement in the absence of antibodies has also been observed, mainly by direct interaction of C1q with HIV-1 envelope and sequential activation of the complement cascade [24].

As in other human vaccine trials, the Vax004 regimen overwhelming elicited nonneutralizing antibodies [25]. Enhancement of infection by nonneutralizing antibodies has been observed in several viral families including Flaviridae (Dengue, Zika, and Murray encephalitis viruses) [26–29], Paramyxoviridae (Respiratory syncytial virus, Measles) [30,31], Filoviridae (Marburg virus) [32], Herpesviridae (Cytomegalovirus) [33] and Retroviridae (HIV, FIV, EIAV, SIV) [11,34–37]. Although in many cases controversially or not well established in humans, enhancement has been described in the setting of antibodies elicited by vaccination [35] or natural infection [38] and in the context of transplacental [33] or passive acquision of antibody [34].

In the case of HIV-1, the best characterization of antibody-dependent enhancement in vitro using clinical isolates was reported by Willey et al.[11]. They observed that nonneutralizing antibodies produced early in HIV-1 infection could enhance viral infectivity dramatically to levels higher than 350-fold. They also confirmed that high-level of enhancement occurred through CR2 and demonstrated that the main effect was related to increase binding of opsonized viruses to target cells.

Mechanisms other than enhancement of infection could also explain the association between CR2 SNP and HIV acquisition. CR2 genotypes could influence the range and amplitude of IgG or IgA production in response to rgp120 antigens. Risk of infection analysis in the RV144 vaccine efficacy trial demonstrated that plasma IgG against the HIV-1 envelope variable regions 1 and 2 inversely correlated with protection whereas HIV-1 Env-specific plasma IgA responses directly correlated with risk [39]. It was shown that HIV-1 Env IgA antibodies elicited by the RV144 vaccine could interfere with binding and functional activity of vaccine-induced IgG responses [40]. CR2 is involved in either the regulation of IgA production or the clearance of IgA immune complexes [41]. CR2 genotype could thus influence higher plasma IgA antibody levels which could attenuate the protective effect of vaccine-induced IgG responses.

The polymorphism rs3813946, located in the 5′UTR of CR2 gene, is known to have functional consequences. The SNP alters transcriptional activity in a non B-cell line as well as in stably transfected cell lines by altering transcription factor binding and affecting chromatin accessibility of the surrounding sequence [20]. In fact this SNP is associated with altered expression of CR2 in cell lines [20,21,42], suggesting that the higher CR2 levels, might be the responsible of the increased susceptibility to HIV-1 infection after vaccination in the individuals harboring the CC genotype. Moreover, the risk genotype identified in our study, is also associated with susceptibility to systemic lupus erytematosus, supporting its relevance in vivo[18,20,43]. However, the association reported in this study could be due to other functional SNPs in close linkage dissequilibrium with rs3813946 that may alter the transcription or alternative splicing of CR2 or other genes in the surrounding genomic region as CD55 or CR1. Further research is warranted to find out the precise immune phenotype associated to this polymorphism.

The fact that only the low behavioral risk group showed an association between CR2 genotype and HIV-1 acquisition may be due to a strong genotype–environment interaction wherein a threshold level of exposure overwhelms the impact of the genotype susceptibility.

The main limitations of our research are the sample size and the low-frequency of the risk genotype. Small random deviations in the number of volunteers with the risk genotype could have an influence on the statistical association. In addition, we only have access to the phenotypes related to the rate of infection. Correlations between CR2 genotypes and phenotypes related to vaccine-elicited immune responses would improve our understanding of the genetic association identified in this study.

In conclusion, our candidate gene association study provides evidence that CR2 genotype is a novel marker associated with HIV-1 infection after vaccination in those individuals with low-risk behavior. Analyses of the CR2 genotypes or expression levels in other HIV vaccine trials will be needed to confirm the potential role of CR2 in HIV-1 acquisition following vaccination.


The authors thank to the staff members of the Division of AIDS (National Institute of Allergy and Infectious Diseases, National Institutes of Health) as well as the company Precision for Medicine for assistance in the selection and management of the samples; we are greatly indebted to Dr Jon Warren (DAIDS) and Dr Karen Carter (PFM). This work was supported by grant SAF2016-80125-R (Ministerio de Economía, Industria y Competitividad, Spain) to A.C. and F.J.M. G.M. is recipient of a grant from AUIP (Asociación Universitaria Iberoamericana de Postgrado).

Authors’ contribution: A.C., F.S., F.J.M., K.H. and D.F. conceived and designed the study. G.M., A.E., C.R.G., B.S.A. performed sample processing. A.C., G.M., A.E., J.L.R., L.M.R. analyzed the data. M.A.G.V. and M.O. contribute to the data analysis and interpretation of the results. A.C. and L.M.R. wrote the article. A.C. guided and reviewed the research.

Conflicts of interest

Coauthors F.S. and K.H. are employees of GSID. Other coauthors declare conflicts of interest.


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* Giovanna Meza and Almudena Expósito contributed equally to the article.


Complement C3d receptor 2; complement; HIV-1; immunogenetics; rgp120; vaccine

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