Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana

Abstract

BackgroundCross-sectional, biomarker methods to determine HIV infection recency present a promising and cost-effective alternative to the repeated testing of uninfected individuals. We evaluate a viral-based assay that uses a measure of pairwise distances (PwD) to identify HIV infection recency, and compare its performance with two serologic incidence assays, BED and LAg. In addition, we assess whether combination BED plus PwD or LAg plus PwD screening can improve predictive accuracy by reducing the likelihood of a false-recent result.MethodsThe data comes from 854 time-points and 42 participants enrolled in a primary HIV-1C infection study in Botswana. Time points after treatment initiation or with evidence of multiplicity of infection were excluded from the final analysis. PwD was calculated from quasispecies generated using single genome amplification and sequencing. We evaluated the ability of PwD to correctly classify HIV infection recency within <130, <180 and <360 days post-seroconversion using Receiver Operator Characteristics (ROC) methods. Following a secondary PwD screening, we quantified the reduction in the relative false-recency rate (rFRR) of the BED and LAg assays while maintaining a sensitivity of either 75, 80, 85 or 90%.ResultsThe final analytic sample consisted of 758 time-points from 40 participants. The PwD assay was more accurate in classifying infection recency for the 130 and 180-day cut-offs when compared with the recommended LAg and BED thresholds. A higher AUC statistic confirmed the superior predictive performance of the PwD assay for the three cut-offs. When used for combination screening, the PwD assay reduced the rFRR of the LAg assay by 52% and the BED assay by 57.8% while maintaining a 90% sensitivity for the 130 and 180-day cut-offs respectively.ConclusionPwD can accurately determine HIV infection recency. A secondary PwD screening reduces misclassification and increases the accuracy of serologic-based assays.

Estimating time of HIV-1 infection from next-generation sequence diversity

“…As the iSNV [7]. NGS diversity even 291 compared favorably with combinations of PwD and BED or LAg [7]. Furthermore, the 292 ROC characteristics of our method was similar to those reported for Hamming distances 293 calculated from SGS data from the env [6].…”

“…Such estimates would be much easier if the time since HIV-1 the number of hidden, undiagnosed infected persons, the magnitude of the problem 5 referred to as "late presentation" and other important aspects of HIV-1 spread. 6 Several biomarkers that classify patients as recently or long-term infected have been 7 used to estimate HIV-1 incidence in populations [1][2][3][4][5][6][7]. These biomarkers can be divided 8 into three main categories: (i) serological incidence tests, (ii) CD4+ T-lymphocyte 9 (CD4)-based estimates and (iii) sequence-based estimates.…”

“…The supplementary materials contain similar tables for the two 258 other diversity measures (S1 Table and S2 Table), as well as for the case when all codon 259 positions are taken into account (S3 Table, S4 Table and S5 Table). As the iSNV [7]. NGS diversity even 291 compared favorably with combinations of PwD and BED or LAg [7].…”

“…Kouyos et al [17] showed that time since infection findings [18,19]. This idea was expanded to other measures of sequence diversity, such 22 as mean Hamming distance [6,7,20] and high-resolution melting (HRM) [21]. These 23 studies (except HRM) used sequences generated by traditional Sanger population 24 sequencing often performed as part of routine HIV-1 resistance testing.…”

“…One then defines sensitivity as the probability of correctly classifying a 237 recent infection as recent (true positive rate), and specificity as the probability of 238 correctly identifying long-term infection (true negative rate). The results can be 239 characterized using the receiver operating characteristic (ROC) curve [7], shown in using NGS that can identify and quantify minority iSNVs.…”