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Updated: Aug 30, 2025
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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
Published on: December 27, 2010
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Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification
Erik Lundgren1, Ethan Romero-Severson1, Jan Albert2,3
1Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Plos Computational Biology
|August 26, 2022
Summary
New epidemiological techniques using multi-biomarker phylogenetic inference can improve identification of human immunodeficiency virus (HIV) transmission chains. This method enhances accuracy in reconstructing HIV transmission histories, aiding public health prevention strategies.
Area of Science:
- Epidemiology
- Phylogenetics
- Biostatistics
Background:
- Identifying and interrupting active human immunodeficiency virus (HIV) transmission chains is crucial for public health.
- Current epidemiological techniques may require enhancement for accurate reconstruction of HIV transmission histories.
- Phylogenetic inference is a powerful tool for understanding pathogen evolution and transmission.
Purpose of the Study:
- To develop and evaluate a multi-biomarker augmentation to phylogenetic inference for reconstructing HIV transmission history.
- To assess the impact of incorporating biomarker data on the accuracy of transmission chain identification.
- To provide a tool for more effective, locally informed HIV prevention strategies.
Main Methods:
- Developed a multi-biomarker model incorporating serological assays, HIV sequence data, and target cell counts.
- Utilized a mixed effects framework and Markov Chain Monte Carlo (MCMC) methods for model fitting.
- Integrated probabilistic infection time estimates into phylogenetic tree reconstruction.
Main Results:
- Biomarker-augmented phylogenetics achieved up to 90% accuracy in idealized scenarios.
- In realistic scenarios with within-host evolution, accuracy averaged around 50% in transmission clusters.
- Biomarker data improved reconstruction accuracy by an average of 16 percentage points compared to phylogeny alone.
Conclusions:
- Multi-biomarker augmentation significantly enhances the accuracy of reconstructing HIV transmission histories.
- The method is robust to incomplete sampling and improves reconstructions of real-world HIV-1 transmission events.
- This technology offers potential for developing more targeted and effective HIV prevention programs.
