Molecular tools for studying HIV transmission in sexual networks

Abstract

Purpose of review Phylogenetics is frequently used for studies of population-based HIV transmission. The purpose of this review is to highlight current utilities and limitations of phylogenetics in HIV epidemiological research from sample collection through data analysis. Recent findings Studies of HIV phylogenies can provide critical information about HIV epidemics that are otherwise difficult to obtain trough traditional study design such as transmission of drug resistant virus, mixing between demographic groups, and rapidity of viral spread within populations. However, recent results from empirical and theoretical studies of HIV phylogenies challenge some of the key assumptions and interpretations from phylogenetic studies. Recent findings include lack of transmission bottlenecks in men who have sex with men and injection drug, evidence for preferential transmission of HIV virus in heterosexual epidemics, and limited evidence that tree topologies correlate with underlying network structures. Other challenges include a lack of a standardized definition for a phylogenetic transmission cluster and biased or sparse sampling of HIV transmission networks. Summary Phylogenetics is an important tool for HIV research, and offers opportunities to understand critical aspects of the HIV epidemic. Like all epidemiological research, the methods used and interpretation of results from phylogenetic studies should be made cautiously with careful consideration.

Molecular epidemiology of HIV-1 in Iceland: Early introductions, transmission dynamics and recent outbreaks among injection drug users

“…Incomplete and biased sampling is a caveat in studies using phylogenetic inference to depict the transmission dynamics of HIV-1 epidemics (Grabowski and Redd, 2014). Although our sampling was generally high (77% during the entire study period), the first quarter (1985)(1986)(1987)(1988)(1989)(1990)(1991) was represented only by 40% of the diagnosed patients.…”

Phylodynamic and Phylogeographic Profiles of Subtype B HIV-1 Epidemics in South Spain

“…Another aspect to consider is that the phylogenetic cluster definition vastly varies in the literature. Most studies have used node statistical support, genetic distance or time depth [58]. We relied on a bootstrap value in the ML analysis, combined with posterior probabilities in the Bayesian approach.…”

Impacts and shortcomings of genetic clustering methods for infectious disease outbreaks

“…Instead, these decisions are based on the genetic or evolutionary distances between the sequences. However, the specific criteria used to derive clusters from this information tend to vary from one study to the next (Grabowski and Redd 2014). Figure 1 displays a dendrogram generated from a hierarchical clustering analysis of a binary character state matrix for nine categories of nonparametric clustering methods (Supplementary Table S1).…”