Objectives To estimate prevalence, examine time trends, and test for clinical correlates and outcomes associated with HIV-1 intersubtype recombination under a full-genome sequencing context in a rural community in Mbarara, Uganda, where HIV-1 subtypes A1 and D co-circulate. Methods Near-full-genome HIV-1 Sanger sequence data was collected from plasma samples of 504 treatment-naïve individuals, who then received PI or NNRTI-containing regimens and were monitored for up to 7.5 years. Subtypes were inferred by Los Alamos RIP 3.0 and compared with Sanger/REGA and MiSeq/RIP. “Non-recombinants” and “recombinants” infections were compared in terms of pre-therapy viral load, CD4 count, post-therapy time to virologic suppression, virologic rebound, first CD4 rise above baseline and sustained CD4 recovery. Results Prevalence of intersubtype recombinants varied depending on the genomic region examined: gag (15%), prrt (11%), int (8%), vif (10%), vpr (2%), vpu (9%), GP120 (8%), GP41 (18%), and nef (4%). Of the 200 patients with near-full-genome data, prevalence of intersubtype recombination was 46%; the most frequently observed recombinant was A1-D (25%). Sanger/REGA and MiSeq/RIP yielded generally consistent results. Phylogenetic tree revealed most recombinants did not share common ancestors. No temporal trend was observed (all p>0.1). Subsequent subtype switches were detected in 27 of 143 (19%) subjects with follow-up sequences. Non-recombinant versus recombinants infections were not significantly different in any pre- nor post-therapy clinical correlates examined (all p>0.2). Conclusion Intersubtype recombination was highly prevalent (46%) in Uganda if the entire HIV genome was considered, but was not associated with clinical correlates nor therapy outcomes.
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.
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