Using Primer-ID Deep Sequencing to Detect Recent Human Immunodeficiency Virus Type 1 Infection

Area of Science:

• Virology
• Genomics
• Infectious Disease Epidemiology

Background:

• Intrahost viral diversity is a key factor in understanding viral evolution and transmission.
• Accurate identification of recent infections is crucial for effective public health interventions and treatment strategies for Human Immunodeficiency Virus Type 1 (HIV-1).
• Next-generation sequencing (NGS) offers a powerful tool for analyzing complex viral genetic data.

Purpose of the Study:

• To evaluate the utility of intrahost viral sequence diversity in identifying recent HIV-1 infections.
• To assess the performance of Primer-ID NGS in analyzing genetic diversity across multiple genomic regions.
• To establish thresholds for viral diversity metrics that discriminate recent (<9 months) from established infections.

Main Methods:

• Sequencing of reverse transcriptase (RT) and env V1-V3 regions from HIV-1 infected individuals using Primer-ID NGS.
• Calculation of mean (π) and first quintile of pairwise diversity distributions over time.
• Analysis using receiver operating characteristic (ROC) curves to determine diagnostic accuracy (Area Under the Curve - AUC).

Main Results:

• Combined analysis of RT and V1-V3 regions demonstrated excellent discrimination of recent HIV-1 infections (<9 months).
• The mean diversity metric (π) achieved an AUC of 0.98 (threshold <1.03%), with 97% sensitivity and 89% specificity for single transmitted variants.
• The first quintile metric (including all variants) showed an AUC of 0.90 (threshold <0.60%), with 91% sensitivity and 92% specificity.

Conclusions:

• Primer-ID NGS-based assessment of intrahost viral diversity is a highly effective method for identifying recent HIV-1 infections.
• Specific diversity thresholds in RT and env V1-V3 regions can accurately classify infection status.
• This approach holds significant potential for epidemiological surveillance and clinical management of HIV-1.