Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients

Abstract

Background: The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission. While compensatory mutations increase fitness during treatment, their presence may also modulate viral fitness and virulence in absence of therapy and major resistance mutations. We previously designed a modeling technique that quantifies genotypic footprints of in vivo treatment selective pressure, including both drug resistance mutations and polymorphic compensatory mutations, through the quantitative description of a fitness landscape from virus genetic sequences.

Results: Genotypic correlates of viral load and CD4 cell count were evaluated in subtype B sequences from recently diagnosed treatment-naive patients enrolled in the SPREAD programme. The association of surveillance drug resistance mutations, reported compensatory mutations and fitness estimated from drug selective pressure fitness landscapes with baseline viral load and CD4 cell count was evaluated using regression techniques. Protease genotypic variability estimated to increase fitness during treatment was associated with higher viral load and lower CD4 cell counts also in treatment-naive patients, which could primarily be attributed to well-known compensatory mutations at highly polymorphic positions. By contrast, treatment-related mutations in reverse transcriptase could not explain viral load or CD4 cell count variability.

Conclusions: These results suggest that polymorphic compensatory mutations in protease, reported to be selected during treatment, may improve the replicative capacity of HIV-1 even in absence of drug selective pressure or major resistance mutations. The presence of this polymorphic variation may either reflect a history of drug selective pressure, i.e. transmission from a treated patient, or merely be a result of diversity in wild-type virus. Our findings suggest that transmitted drug resistance has the potential to contribute to faster disease progression in the newly infected host and to shape the HIV-1 epidemic at a population level.

Figure 1

Association between the number of compensatory mutations, estimated fitness and clinical parameters. Compensatory mutations, polymorphic in subtype B protease and modeled by the fitness model F_PI, are likely candidates to explain the observed association of viral fitness estimated under drug selective pressure with clinical parameters. For patients with no indications of acute infection and TDR (n = 962), the number of compensatory mutations (13V, 36I, 60E, 62V, 63P, 71V, 71T, 77I or 93L) in the protease sequence is calculated for each patient [21]. The following parameters are grouped by mutation count: log₁₀ viral RNA copies/ml (1a), square-root transformed CD4 cell counts (1b) and increased estimated fitness for protease log₁₀F_PI−m(1c). The distribution of the respective parameter is shown for each group using boxplots. The horizontal line (bold) within the boxplot represents the median value, with box boundaries indicating the interquartile range. Upper and lower ends of striped lines denote the most extreme data point which is no more than 1.5 times the IQR range from the box. An increased mutation number significantly correlated with 1a) increased log₁₀ viral RNA copies/ml (p-value < 0.01), 1b) decreased square-root transformed CD4 cell counts (p-value < 0.01) and 1c) increased estimated fitness for protease log₁₀F_PI−m(p-value < 0.01). A fitted line going through the median values (lowess smooth) is shown in red. The number of patients for each group is shown above each bin.