Assessing the role of transmission chains in the spread of HIV-1 among men who have sex with men in Quebec, Canada

Abstract

Background Phylogenetics has been used to investigate HIV transmission among men who have sex with men. This study compares several methodologies to elucidate the role of transmission chains in the dynamics of HIV spread in Quebec, Canada. Methods The Quebec Human Immunodeficiency Virus (HIV) genotyping program database now includes viral sequences from close to 4,000 HIV-positive individuals classified as Men who have Sex with Men (MSMs), collected between 1996 and early 2016. Assessment of chain expansion may depend on the partitioning scheme used, and so, we produce estimates from several methods: the conventional Bayesian and maximum likelihood-bootstrap methods, in combination with a variety of schemes for applying a maximum distance criterion, and two other algorithms, DM-PhyClus, a Bayesian algorithm that produces a measure of uncertainty for proposed partitions, and the Gap Procedure, a fast non-phylogenetic approach. Sequences obtained from individuals in the Primary HIV Infection (PHI) stage serve to identify incident cases. We focus on the period ranging from January 1st 2012 to February 1st 2016. Results and conclusion The analyses reveal considerable overlap between chain estimates obtained from conventional methods, thus leading to similar estimates of recent temporal expansion. The Gap Procedure and DM-PhyClus suggest however moderately different chains. Nevertheless, all estimates stress that longer older chains are responsible for a sizeable proportion of the sampled incident cases among MSMs. Curbing the HIV epidemic will require strategies aimed specifically at preventing such growth.

The Role of Phylogenetics in Unravelling Patterns of HIV Transmission towards Epidemic Control: The Quebec Experience (2002–2020)

“…There have been debates as to which methodological approaches should be used to assign viral linkage, i.e., clustering, and reconstruct transmission networks [ 26 , 33 , 34 , 35 , 36 ]. We applied MEGA7/10 phylogenetic analyses across the viral reverse transcriptase (RT) and protease regions based on strict criteria of high bootstrap support and short genetic distance [ 34 , 35 , 36 ]. Our cluster group assignment was supported using multiple phylogenetic, genetic-distance, and Bayesian-based approaches [ 34 , 35 , 36 ].…”

Phylogenetic Clustering among Asylum Seekers with New HIV-1 Diagnoses in Montreal, QC, Canada

“…HIV-1 genotyping was carried out as previously described to generate partial pol sequences, spanning the viral protease and the reverse transcriptase, HXB2 nucleotide positions 2253→2549 and 2550→3870, respectively [ 15 , 16 ]. All available HIV-1 pol sequences from the provincial genotyping database were aligned to consensus HXB2 sequences, removing gaps and cutting to identical sequence lengths (921 base pairs) using BioEdit.…”

“…Genetic distance was computed using Kimura-2-parameter methods and in units of number of base units per site. The rate variation among sites was modeled with a gamma distribution (shape parameter = 1) [ 16 ]. Subtype B and non-B subtype trees were rooted against subtype K or N consensus sequences (accession numbers AJ24935 and AJ006022, respectively) to visually depict patterns of spread.…”

“…Phylogenetic analysis, a form of molecular epidemiology, has been increasingly used to characterize HIV transmission and tailor potential prevention responses to better inform public health [ 15 , 16 ]. Recent studies using phylogenetic analysis found that small heterosexual clusters among migrants were commonly composed of people living with HIV from a single birth country [ 10 , 17 ].…”

HIV Care Prioritization using Phylogenetic Branch Length

“…Molecular epidemics suggest an alternative method: prioritizing PLWHs for intervention solely based on patterns of transmission inferred from HIV sequence data (Bbosa et al, 2019; Villandré et al, 2019; Oster et al, 2018; Ragonnet-Cronin et al, 2019; Wertheim et al, 2018, 2011, 2014; Smith et al, 2009). The inference of transmission networks using phylogenetic or distance-based methods has been the subject of much research (e.g.…”