Background

A better understanding of HIV transmission dynamics among populations at high risk is important for development of prevention strategies. We determined HIV transmission networks from infected individuals enrolled in the pre-exposure prophylaxis (PrEP) IPERGAY trial in combination with the ANRS PRIMO and Montreal PHI cohorts to identify and characterize active clusters of transmission in this high-risk population.

Methods

Genotypic resistance tests were performed on plasma samples from 31 IPERGAY participants. Reverse transcriptase sequences were analyzed in combination with unique HIV pol sequences from 1351 individuals enrolled in the PRIMO ANRS cohort (1999-2014) and 511 individuals enrolled in the Montreal PHI cohort (1996-2016). Network analyses were performed to infer putative relationships between all participants.

Results

Overall, 1893 participants were included. Transmission network analyses revealed that 14 individuals (45.2%) from the IPERGAY trial were involved in 13 clusters sampled over a median period (interquartile range) of 2 (0.3-7.8) years, including 7 dyads and 6 larger clusters ranging from 4 to 28 individuals. When comparing characteristics between clustering individuals enrolled in the PRIMO cohort (n = 377) and in IPERGAY (n = 14), we found that IPERGAY participants had a higher viral load (5.93 vs 5.20 log₁₀ copies/mL, P = .032) and reported a higher number of partners in the last 2 months (P < .01).

Conclusions

These results demonstrate high rates of HIV transmission clustering among young high-risk MSM enrolled in the IPERGAY trial. In-depth sampling of high-risk populations may help to uncover unobserved transmission intermediaries and improve prevention efforts that could be targeted to the most active clusters.

Phylogenetics has been advanced as a structural framework to infer evolving trends in the regional spread of HIV-1 and guide public health interventions. In Quebec, molecular network analyses tracked HIV transmission dynamics from 2002-2020 using MEGA10-Neighbour-joining, HIV-TRACE, and MicrobeTrace methodologies. Phylogenetics revealed three patterns of viral spread among Men having Sex with Men (MSM, n = 5024) and heterosexuals (HET, n = 1345) harbouring subtype B epidemics as well as B and non-B subtype epidemics (n = 1848) introduced through migration. Notably, half of new subtype B infections amongst MSM and HET segregating as solitary transmissions or small cluster networks (2-5 members) declined by 70% from 2006-2020, concomitant to advances in treatment-as-prevention. Nonetheless, subtype B epidemic control amongst MSM was thwarted by the ongoing genesis and expansion of super-spreader large cluster variants leading to micro-epidemics, averaging 49 members/cluster at the end of 2020. The growth of large clusters was related to forward transmission cascades of untreated early-stage infections, younger at-risk populations, more transmissible/replicative-competent strains, and changing demographics. Subtype B and non-B subtype infections introduced through recent migration now surpass the domestic epidemic amongst MSM. Phylodynamics can assist in predicting and responding to active, recurrent, and newly emergent large cluster networks, as well as the cryptic spread of HIV introduced through migration.

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types.