APOBEC3G expression is dysregulated in primary HIV-1 infection and polymorphic variants influence CD4+ T-cell counts and plasma viral load

Abstract

Objectives: In the absence of HIV-1 virion infectivity factor (Vif), cellular cytosine deaminases such as apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3G (APOBEC3G) inhibit the virus by inducing hypermutations on viral DNA, among other mechanisms of action. We investigated the association of APOBEC3G mRNA levels and genetic variants on HIV-1 susceptibility, and early disease pathogenesis using viral load and CD4 T-cell counts as outcomes.

Methods: Study participants were 250 South African women at high risk for HIV-1 subtype C infection. We used real-time PCR to measure the expression of APOBEC3G in HIV-negative and HIV-positive primary infection samples. APOBEC3G variants were identified by DNA re-sequencing and TaqMan genotyping.

Results: We found no correlation between APOBEC3G expression levels and plasma viral loads (r = 0.053, P = 0.596) or CD4 T-cell counts (r = 0.030, P = 0.762) in 32 seroconverters. APOBEC3G expression levels were higher in HIV-negative individuals as compared with HIV-positive individuals (P < 0.0001), including matched pre and postinfection samples from the same individuals (n = 13, P < 0.0001). Twenty-four single nucleotide polymorphisms, including eight novel, were identified within APOBEC3G by re-sequencing and genotyping. The H186R mutation, a codon-changing variant in exon 4, and a 3' extragenic mutation (rs35228531) were associated with high viral loads (P = 0.0097 and P < 0.0001) and decreased CD4 T-cell levels (P = 0.0081 and P < 0.0001), respectively.

Conclusion: These data suggest that APOBEC3G transcription is rapidly downregulated upon HIV-1 infection. During primary infection, APOBEC3G expression levels in peripheral blood mononuclear cells do not correlate with viral loads or CD4 T-cell counts. Genetic variation of APOBEC3G may significantly affect early HIV-1 pathogenesis, although the mechanism remains unclear and warrants further investigation.

Figure 1

Outline of study cohort and experiments. HIV+ve samples are indicated by pink blocks and HIV−ve samples are indicated by blue blocks

Figure 2

Comparison of APOBEC3G mRNA levels between (a) HIV-uninfected and HIV-infected participants, (b) pre-infection and post-infection samples of HIV-infected individuals, (c) persistently seronegative subjects and pre-infection samples of seroconverters and (d) longitudinal post-infection samples.

Figure 3

Comparison of viral loads (a) and CD4+ T cell counts (b) between H186R genotypes over 0–12 months post infection using a LOWESS model. Measurements were classified into 0–3 months post infection and 3–12 months post infection time intervals to identify differences between the genotypes during acute infection and early chronic infection. Confidence intervals are shown by the vertical lines and overall P values are indicated. A Kaplan-Meier survival curve (c) performed to assess the difference between the genotype groups in the event of a CD4+ T cell count less than 350 cells/3l for more than two consecutive visits. Cox Regression was used to acquire Hazard Ratios.