BioProject

Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. More...

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. Less...