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Related Experiment Video

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Prediction of HIV-1 Coreceptor Usage (Tropism) by Sequence Analysis using a Genotypic Approach

Prediction of HIV-1 Coreceptor Usage (Tropism) by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

A new pattern-based method for identifying recent HIV-1 infections from the viral env sequence.

Jing Yang¹, Xiayu Xia, Xiang He

¹Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, Beijing 100084, China.

Science China. Life Sciences

|May 9, 2012

Summary

Identifying recent HIV infections is difficult due to the long asymptomatic stage. A new genetic diversity method accurately detects recent HIV-1 infections, unaffected by advanced disease or ART treatment.

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Last Updated: May 22, 2026

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Area of Science:

* Virology
* Epidemiology
* Bioinformatics

Background:

* The asymptomatic stage of Human Immunodeficiency Virus (HIV) infection complicates the identification of recent cases.
* This diagnostic challenge hinders accurate HIV epidemic monitoring and the evaluation of national AIDS control programs.
* Current serological methods for detecting recent infections have limitations, including high false-positive rates in patients with advanced disease or on Antiretroviral Therapy (ART).

Purpose of the Study:

* To develop and validate a novel pattern-based method for assessing intra-patient viral genetic diversity to identify recent HIV infections.
* To estimate population incidence using this new genetic diversity approach.
* To provide a reliable tool for HIV surveillance in diverse epidemiological settings.

Main Methods:

* Development of a pattern-based method analyzing intra-patient viral genetic diversity.
* Validation using datasets of HIV-1 subtype B (424 samples) and CRF07_BC (77 samples) with known infection times.
* Comparison of genetic diversity patterns between recent and chronic infections.

Main Results:

* Significantly lower pattern-based genetic diversity was observed in recent HIV-1 infections compared to chronic infections.
* The method achieved high accuracy (90%-95%) with window periods of 200–350 days.
* Accuracy remained unaffected by advanced disease stages or ART treatment, unlike some serological assays.

Conclusions:

* The developed pattern-based genetic diversity method offers a reliable approach for identifying recent HIV infections.
* This method is supplementary to existing serological assays and can be used independently.
* The approach is suitable for HIV surveillance in both low and high epidemic regions, addressing limitations of current methods.