Disentangling human tolerance and resistance against HIV

Abstract

In ecology, "disease tolerance" is defined as an evolutionary strategy of hosts against pathogens, characterized by reduced or absent pathogenesis despite high pathogen load. To our knowledge, tolerance has to date not been quantified and disentangled from host resistance to disease in any clinically relevant human infection. Using data from the Swiss HIV Cohort Study, we investigated if there is variation in tolerance to HIV in humans and if this variation is associated with polymorphisms in the human genome. In particular, we tested for associations between tolerance and alleles of the Human Leukocyte Antigen (HLA) genes, the CC chemokine receptor 5 (CCR5), the age at which individuals were infected, and their sex. We found that HLA-B alleles associated with better HIV control do not confer tolerance. The slower disease progression associated with these alleles can be fully attributed to the extent of viral load reduction in carriers. However, we observed that tolerance significantly varies across HLA-B genotypes with a relative standard deviation of 34%. Furthermore, we found that HLA-B homozygotes are less tolerant than heterozygotes. Lastly, tolerance was observed to decrease with age, resulting in a 1.7-fold difference in disease progression between 20 and 60-y-old individuals with the same viral load. Thus, disease tolerance is a feature of infection with HIV, and the identification of the mechanisms involved may pave the way to a better understanding of pathogenesis.

Figure 1. Quantifying tolerance and resistance.

(A) The tolerance of a group of individuals can be measured as the change of fitness across varying levels of parasite burden. Fitness is inversely related to the virulence of the infection. The difference in resistance between groups can be quantified simply as the difference in the mean parasite burden. (B) In the context of HIV, virulence can be quantified by measuring the CD4+ T-cell decline in an infected individual, and the set-point viral load is a good proxy for the “parasite burden”. (C) and (D) show conceivable outcomes of a tolerance-resistance analysis for the HIV resistance genes, such as classic protective HLA-B alleles. In the scenario entitled “pure resistance” (C), the reduction of viral load that the resistance genes confers fully explains the reduction in disease progression. Alternatively, resistance genes could additionally confer tolerance, as shown in plot (D).

Figure 2. Relationship between CD4+ T-cell decline and set-point viral load in our study population.

(A) Calculation of the set-point viral load and CD4+ T-cell decline, illustrated for a single individual. The set-point viral load (red line) is calculated as the geometric mean of the viral load measurements (after primary infection and before treatment). The decline of CD4+ T cells is determined as the regression slope (blue line) of CD4+ T-cell counts against time. The CD4+ T-cell counts and virus load measurements of three randomly selected individuals are shown in Figure S1. (B) Nonlinear tolerance curve characterizing the relationship between CD4+ T-cell decline and set-point viral load in our study population (n = 3,036). The black line shows the quadratic regression line. Blue crosses indicate individuals that were identified as viremic nonprogressors in a previous study .

Figure 3. Investigating associations of tolerance with sex, age at infection, and HLA-B alleles.

(A) Tolerance does not differ significantly between sexes in a univariate analysis. (B) Young age at infection is strongly associated with tolerance. The data are plotted stratified by age. The younger, the redder. The three curves show the relationships between set-point viral load and CD4+ T-cell decline when infected at age 20, 40, and 60. (C) Classic protective HLA-B alleles induce pure resistance. The tolerance curves do not differ significantly for individuals with (red, n = 416) and without (blue, n = 507) protective HLA-B alleles. Protectiveness is defined according to the data presented in table 1 of (see Materials and Methods). (D) HLA-B homozygosity is associated with tolerance. Homozygotes also have significantly higher set-point viral loads—that is, are more resistant than heterozygotes.

Figure 4. Variation of tolerance associated with HLA-B genotype.

(A) Frequencies of the HLA-B genotypes in our study population of 923 individuals. Approximately half of the genotypes are represented by only one individual. (B) Visualizing the random effect of the mixed effect modeling approach. Estimated tolerance curves for each HLA-B genotype, based on best linear unbiased predictions, are shown. We estimated a mean tolerance parameter (red curve), and a deviation of the random effects, , of (see Text S1).