Non-R5-tropic HIV-1 in subtype A1 and D infections were associated with lower pretherapy CD4+ cell count but not with PI/(N)NRTI therapy outcomes in Mbarara, Uganda

Abstract

Background Previous studies suggest that infection with non-R5-tropic subtype B HIV-1, compared to R5, is associated with a more rapid decline in CD4 count, but does not affect PI/(N)NRTI therapy outcome. Here, we explored clinical correlates associated with viral tropism in subtype A1 and D infections. Methods HIV-1 subtype A1 (n=196) and D (n=143) pre-therapy plasma samples and up to 7.5 years of post-therapy virologic and CD4 data were collected from a cross-sectional cohort in Mbarara, Uganda. Tropism and subtype were inferred using env V3 (geno2pheno) and gp41 (RIP) Sanger sequences. For each subtype, R5 infection was compared with non-R5 in terms of: Pre-therapy viral load and CD4 count (Mann-Whitney tests), and therapy outcomes including time to virologic suppression, post-suppression virologic rebound, CD4 decline and CD4 recovery (Log-rank tests). Results 94% of all patients in this study achieved virologic suppression within median 3 months post-therapy. In both subtypes, non-R5 infection was associated with lower pre-therapy CD4 count (non-R5 versus R5; A: median 57 versus 147 cells/µL p=0.005; D: 80 versus 128 cells/µL p=0.006). Multivariable linear regression confirmed that tropism, not subtype nor the interaction between subtype and tropism, was a significant predictor of pre-therapy CD4 count (p<0.0001). None of pre-therapy viral load, time to virologic suppression, virologic rebound, CD4 decline nor CD4 recovery was significantly different (all p>0.09). Conclusion Regardless of HIV-1 subtype or tropism, the majority of patients in this Ugandan cohort responded to therapy, even though non-R5 infection was associated with lower pre-therapy CD4 count.

Net charge and position 22 of the V3 loop are associated with HIV-1 tropism in recently infected female sex workers in Nairobi, Kenya

“…[ 29 , 53 ] The confounding effects of net charge, amino acid at position 22 and the Kawangware SWOP clinic rendered CD4 + T cell count effect insignificant in our multivariable model despite it being a significant factor in univariable model as reported in other. [ 45 , 46 , 54 , 55 ]…”

“…[29,53] The confounding effects of net charge, amino acid at position 22 and the Kawangware SWOP clinic rendered CD4 + T cell count effect insignificant in our multivariable model despite it being a significant factor in univariable model as reported in other. [45,46,54,55] HIV-1 transmission is frequently characterized by the existence of numerous transmission clusters, thought to be critical for sustaining the epidemic. [16,17] Given that FSWs are one of the population groups most at risk for contracting HIV, this is even more crucial.…”

Prevalence and clinical impacts of HIV-1 intersubtype recombinants in Uganda revealed by near-full-genome population and deep sequencing approaches

“…The Uganda AIDS Rural Treatment Outcomes (UARTO) cohort consists of over 500 HIV-infected patients in Mbarara, Uganda, where HIV-1 subtypes A1 and D co-circulate [9–11]. Plasma samples were available before and after treatment initiation, and virologic and immunologic outcome data were collected for over seven years post-therapy.…”

HIV-1 subtype A1, D, and recombinant proviral genome landscapes during long-term suppressive therapy

“…Previous work has shown possible biological differences between HIV-1 subtypes, with subtype D being associated with faster disease progression, faster rate of CD4+ T-cell decline, lower pre-treatment CD4+ T-cell count, and higher mortality 6 – 10 . Subtype D HIV-1 has also been associated with greater replicative fitness, increased apoptosis of CD4+ T-cells, and higher frequencies of CXCR4 co-receptor usage relative to subtypes A1 and/or B 11 – 13 . Given HIV-1 subtype differences in pathogenesis and genetics, viral subtypes may have different proportions of defective proviruses and patterns of genomic areas with deletions or hypermutation.…”