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Observational Study
. 2017 Feb;96(6):e6041.
doi: 10.1097/MD.0000000000006041.

Pairwise diversity and tMRCA as potential markers for HIV infection recency

Affiliations
Observational Study

Pairwise diversity and tMRCA as potential markers for HIV infection recency

Sikhulile Moyo et al. Medicine (Baltimore). 2017 Feb.

Abstract

Intrahost human immunodeficiency virus (HIV)-1 diversity increases linearly over time. We assessed the extent to which mean pairwise distances and the time to the most recent common ancestor (tMRCA) inferred from intrahost HIV-1C env sequences were associated with the estimated time of HIV infection. Data from a primary HIV-1C infection study in Botswana were used for this analysis (N = 42). A total of 2540 HIV-1C env gp120 variable loop region 1 to conserved region 5 (V1C5) of the HIV-1 envelope gp120 viral sequences were generated by single genome amplification and sequencing, with an average of 61 viral sequences per participant and 11 sequences per time point per participant. Raw pairwise distances were calculated for each time point and participant using the ape package in R software. The tMRCA was estimated using phylogenetic inference implemented in Bayesian Evolutionary Analysis by Sampling Trees v1.8.2. Pairwise distances and tMRCA were significantly associated with the estimated time since HIV infection (both P < 0.001). Taking into account multiplicity of HIV infection strengthened these associations. HIV-1C env-based pairwise distances and tMRCA can be used as potential markers for HIV recency. However, the tMRCA estimates demonstrated no advantage over the pairwise distances estimates.

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Conflict of interest statement

The remaining authors have no conflicts of interest to disclose.

Figures

Figure 1
Figure 1
Predicted times from infection using pairwise distance (top panels) or the time to the most recent common ancestor (tMRCA, bottom panels) versus estimated times from infection. The panels on the left represent predictions using all 164 measurements and those on the right represent predictions using a subset of 145 measurements excluding those with evidence for subclustering. The red lines are 45° lines passing origin, reflecting perfect prediction.

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