Longitudinal typing of molecular HIV clusters in a statewide epidemic

Abstract

Background: HIV molecular epidemiology is increasingly integrated into public health prevention. We conducted cluster typing to enhance characterization of a densely sampled statewide epidemic towards informing public health. Methods:We identified HIV clusters, categorized them into types, and evaluated their dynamics between 2004 and 2019 in Rhode Island. We grouped sequences by diagnosis year, assessed cluster changes between paired phylogenies, t 0 and t 1 , representing adjacent years and categorized clusters as stable (cluster in t 0 phylogeny ¼ cluster in t 1 phylogeny) or unstable (cluster in t 0 6 ¼ cluster in t 1 ). Unstable clusters were further categorized as emerging (t 1 phylogeny only) or growing (larger in t 1 phylogeny). We determined proportions of each cluster type, of individuals in each cluster type, and of newly diagnosed individuals in each cluster type, and assessed trends over time.Results: A total of 1727 individuals with available HIV-1 subtype B pol sequences were diagnosed in Rhode Island by 2019. Over time, stable clusters and individuals in them dominated the epidemic, increasing over time, with reciprocally decreasing unstable clusters and individuals in them. Conversely, proportions of newly diagnosed individuals in unstable clusters significantly increased. Within unstable clusters, proportions of emerging clusters and of individuals in them declined; whereas proportions of newly diagnosed individuals in growing clusters significantly increased over time.Conclusion: Distinct molecular cluster types were identified in the Rhode Island epidemic. Cluster dynamics demonstrated increasing stable and decreasing unstable clusters driven by growing, rather than emerging clusters, suggesting consistent in-state transmission networks. Cluster typing could inform public health beyond conventional approaches and direct interventions.

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 ].…”

“…Large cluster networks may also reflect the natural selection favouring more transmissible, infectious, or replicatively fit viral species [ 33 , 41 , 42 , 43 ]. Overall, 2.5% of viral variants have contributed to over half of infections.…”

“…Overall, 2.5% of viral variants have contributed to over half of infections. Our studies suggest that large cluster viruses may reflect a shift to evolutionary fit variants showing lower genetic diversity, higher viral loads, and extended high viremia [ 33 , 41 , 42 , 43 ]. Analysis of the distinct genotypic and phenotypic features of super-spreader viral lineages is warranted.…”

“…Our findings show “short-lived” small cluster lineages epidemiologically resemble solitary transmissions while being distinct from “super-spreader” larger cluster variants. Stable large cluster lineages have been recently shown to fuel the Rhode Island, North Carolina, and New York statewide epidemics and may contribute to more transmissible drug-resistant epidemics [ 16 , 27 , 33 , 41 ].…”

“…This shorter genetic distance is estimated to evolve over approximately 2–3 years [ 44 ]. Our findings found that this lower cut-off may not always assist in forecasting cluster growth [ 26 , 27 , 33 ]. Analyses at genetic distances of 1.5% and 2.5% thresholds assisted in distinguishing patterns of spread of large cluster networks implicated in the Quebec epidemic.…”