Role of CCL3L1-CCR5 genotypes in the epidemic spread of HIV-1 and evaluation of vaccine efficacy

Abstract

Background: Polymorphisms in CCR5, the major coreceptor for HIV, and CCL3L1, a potent CCR5 ligand and HIV-suppressive chemokine, are determinants of HIV-AIDS susceptibility. Here, we mathematically modeled the potential impact of these genetic factors on the epidemic spread of HIV, as well as on its prevention.

Methods and results: Ro, the basic reproductive number, is a fundamental concept in explaining the emergence and persistence of epidemics. By modeling sexual transmission among HIV+/HIV- partner pairs, we find that Ro estimates, and concordantly, the temporal and spatial patterns of HIV outgrowth are highly dependent on the infecting partners' CCL3L1-CCR5 genotype. Ro was least and highest when the infected partner possessed protective and detrimental CCL3L1-CCR5 genotypes, respectively. The modeling data indicate that in populations such as Pygmies with a high CCL3L1 gene dose and protective CCR5 genotypes, the spread of HIV might be minimal. Additionally, Pc, the critical vaccination proportion, an estimate of the fraction of the population that must be vaccinated successfully to eradicate an epidemic was <1 only when the infected partner had a protective CCL3L1-CCR5 genotype. Since in practice Pc cannot be >1, to prevent epidemic spread, population groups defined by specific CCL3L1-CCR5 genotypes might require repeated vaccination, or as our models suggest, a vaccine with an efficacy of >70%. Further, failure to account for CCL3L1-CCR5-based genetic risk might confound estimates of vaccine efficacy. For example, in a modeled trial of 500 subjects, misallocation of CCL3L1-CCR5 genotype of only 25 (5%) subjects between placebo and vaccine arms results in a relative error of approximately 12% from the true vaccine efficacy.

Conclusions: CCL3L1-CCR5 genotypes may impact on the dynamics of the HIV epidemic and, consequently, the observed heterogeneous global distribution of HIV infection. As Ro is lowest when the infecting partner has beneficial CCL3L1-CCR5 genotypes, we infer that therapeutic vaccines directed towards reducing the infectivity of the host may play a role in halting epidemic spread. Further, CCL3L1-CCR5 genotype may provide critical guidance for optimizing the design and evaluation of HIV-1 vaccine trials and prevention programs.

Figure 1. Conceptual model by which CCL3L1-CCR5 genotypes might influence the prevention and epidemic outgrowth of HIV infection.

(a) Classification system used to categorize the copy number of CCL3L1 (low or high) and genotypes of CCR5 (detrimental or nondetrimental) into three (low, moderate and high) risk categories. (b) Conceptual model by which the GRGs might affect epidemiological endpoints. The endpoint Pc has different components, and those that might be influenced by the GRGs are shown in green-colored letters, i.e., Ro, e and f. The model assumptions, parameters and methods are described in Supplementary Online Materials S1 (SOM), section 1 and Table S1. The conceptual model assumes a vaccine that requires the induction of CMI, in part, for protection. Here, the formula of Pc is from studies by Anderson and Blower . ?, indicates possible additional effects associated with CCL3L1-CCR5 GRGs that are unmeasured , .

Figure 2. Modeling studies assessing the influence of CCL3L1-CCR5 genotypes on epidemiological parameters relevant to the outgrowth and prevention of HIV-1.

(a) Nine population groups based on the CCL3L1-CCR5 GRG status of sexual partners. The estimated proportions (prevalence) of the GRGs in the general population are based on data from the HIV-positive WHMC cohort . L, M, and H denote low, moderate, and high GRG status, respectively. The color codes shown are used to illustrate the nine population groups (Grp) in panels b to g. (b) Estimates of Ro for the nine color-coded GRG-defined population groups. (c) Simulated epidemic growth in GRG-defined population groups. Methods are in SOM, section 1.9 online. (d to f) Attributable fractions (AF, panel d), critical response time (CRT, panel e) and Pc (f) in the nine population groups. The calculations for Pc (f) assume a vaccine efficacy of 50%. (g) Influence of varying vaccine efficacy estimates on Pc in the nine GRG-defined population. groups shown in panel a. Pc values greater than unity (dashed horizontal line) indicate the point at which repeated mass vaccination might be necessary. Pc for population group #1 was zero. Additional data relevant to these studies are shown in Table S2 online.

Figure 3. Influence of CCL3L1-CCR5 GRG status on vaccine efficacy.

(a) Estimated vaccine efficacy as a function of the percentage of subjects that are misallocated (m) with respect to their CCL3L1-CCR5 genotype across the placebo or vaccine trial arms. The model is for a preventive vaccine that has a true efficacy of 50%. The upper line in this plot depicts estimated vaccine efficacy as a function of misallocation of subjects with a low GRG towards the vaccine arm, resulting in a fallacious increase in the estimated vaccine efficacy. The lower line depicts the converse situation, i.e., misallocation of subjects with a low GRG towards the placebo arm, resulting in a fallacious decrease in the estimated vaccine efficacy. (b) Plots depict the difference (relative error) between the true and estimated vaccine efficacy as a percentage of the true vaccine efficacy for varying values of m. Methods are described in SOM, section 2.

Figure 4. CCL3L1 copy number (a) and CCR5 HHA haplotype frequency (b) in Pygmies (N = 51) and Cameroonians (N = 372).

The prevalence of the chimpanzee CCR5 HHA haplotype and the ortholog of human CCL3L1 in chimpanzee designated as CCL3L , is also shown (N = 83). Error bars in panel a denote 95% confidence interval.