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

Abstract

Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Existing biomarkers for the recent infection are relatively imprecise. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection.Virus diversity increased linearly with time, particularly at 3rd codon positions, with little inter-patient variation. The precision of the TI estimate improved with increasing sequencing depth, showing the superiority of NGS over counting polymorphic sites in Sanger sequences, which is one of the alternative biomarkers. The full advantage of the high sequencing resolution of NGS was utilized with continuous diversity measures, average Hamming distance or site entropy, rather than the fraction of polymorphic sites. The precision depended on the genomic region and codon position and was highest when 3rd codon positions in the entire pol gene was used. For these data TI estimates had a mean absolute error of around 1 year. The error increased only slightly from around 0.6 years at a TI of 6 months to around 1.1 year at 6 years. In addition, NGS diversity compared favorably with other biomarkers for binary classification of patients as being recently or long-term infected.Our results show that virus diversity determined by NGS can be used to estimate time since HIV-1 infection with a precision that is better than most alternative biomarkers. Importantly, TI can be estimated many years after infection. We provide regression coefficients that can be used for TI estimation.

Viral Diversity Based on Next-Generation Sequencing of HIV-1 Provides Precise Estimates of Infection Recency and Time Since Infection

“… The remaining patients were required to have maximally 2 years between the last negative and first positive HIV-1 test, and the date of infection was taken as the midpoint between these dates, as used by [21].…”

“…Variants are reported along with their frequency in the sample, rather than a position simply being marked as ambiguous, which increases the amount of quantitative information returned from NGS sequencing compared to Sanger population sequencing. Puller et al [21] present a simple method based on NGS sequences for predicting TSI from viral diversity, using average pairwise diversity (APD) as a predictor, and showed a good correlation of NGS-diversity with TSI.…”

Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers

“…preexposure prophylaxis) 31,32 . The method can easily be adapted to other biomarkers like the LAg avidity assay and viral diversity [33][34][35] .…”

Estimating the Age at HIV Infection Retroactively in Limited Resource Settings: <i>A Case Study of Tanzania</i>

“…Previous scholars have demonstrated different methods for estimating the HIV infection time through biological approaches and statistical methods [1,3,5,[7][8]10]. For those who used biological approaches they assessed some common biomarkers and tests that can tell whether a person was recently infected or not.…”

“…Likewise, a study to estimate the time to HIV-1 Infection from Next Generation Sequence (NGS) diversity was conducted in Sweden by using dataset obtained from 11 untreated HIV-1 patients with known infection dates [8]. The selection of patients who were included in this study required among other criteria, to have a relatively well-defined time of infection or a negative HIV test obtained less than two years before first positive test.…”