HIV-1 dual infection (DI) and CXCR4 (X4) co-receptor usage are associated with accelerated disease progression but frequency and dynamics of co-receptor usage during DI is unknown. Ultradeep sequencing was used to interrogate for DI and infer co-receptor usage in longitudinal blood samples of 102 subjects. At baseline, X4 usage was high (23 subjects harbored X4 variants), and was not associated with infection duration or DI. Co-receptor usage changed over time in 12/47 participants, and X4 usage emerged in 4/41 monoinfections vs. 2/5 superinfections (p=0.12), suggesting a weak statistical trend towards occurrence of superinfection and acquiring X4 usage.
[Show abstract][Hide abstract] ABSTRACT: HIV-1 tropism needs to be determined before the use of CCR5 antagonist drugs such as maraviroc (MVC), which are ineffective against CXCR4-using HIV-1. This study assessed how different computational methods for predicting tropism from HIV sequence data performed in a large clinical cohort. The value of adding clinical data to these algorithms was also investigated.
PCR amplification and sequence analysis of the HIV-1 gp120 V3 loop region was performed on triple replicates of plasma viral RNA or proviral DNA extracted from peripheral blood monocytes (PBMCs) in 242 patients. Coreceptor usage was predicted from V3 sequences using seven bioinformatics interpretation algorithms, combined with clinical data where appropriate. An intention-to-treat approach was employed for exploring outcomes and performance for different viral subtypes was examined.
The frequency of R5 predictions varied by 22.6%, with all seven algorithms agreeing for only 75.3% of tests. The identification of individuals likely to fail was poor for all algorithms. The addition of clinical data improved this, but at the expense of their ability to predict success. The clinical algorithms varied across subtypes, whereas other algorithms were more consistent. Furthermore, individuals with discordant clonal and clinical predictions were more likely to fail MVC treatment.
Eligibility for MVC varied depending on the algorithm method used. The addition of clinical parameters alongside sequence data may help predict X4 emergence during treatment. It could be that V3 loop analysis in isolation may not be the best method for selecting individuals for MVC.
AIDS (London, England) 04/2014; 28(11). DOI:10.1097/QAD.0000000000000288 · 5.55 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To better understand the dynamics of HIV-specific neutralizing antibody (NAb), we examined associations between viral genetic diversity and the NAb response against a multi-subtype panel of heterologous viruses in a well-characterized, therapy-naïve primary infection cohort. Using next generation sequencing (NGS), we computed sequence-based measures of diversity within HIV-1 env, gag and pol, and compared them to NAb breadth and potency as calculated by a neutralization score. Contemporaneous env diversity and the neutralization score were positively correlated (p=0.0033), as were the neutralization score and estimated duration of infection (EDI) (p=0.0038), and env diversity and EDI (p=0.0005). Neither early env diversity nor baseline viral load correlated with future NAb breadth and potency (p>0.05). Taken together, it is unlikely that neutralizing capability in our cohort was conditioned on viral diversity, but rather that env evolution was driven by the level of NAb selective pressure.
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