HIV-1 Transmission Clustering and Phylodynamics Highlight the Important Role of Young Men Who Have Sex with Men

Dennis, Ann M.; Volz, Erik; Frost, Simon D. W.; Hossain, Mukarram; Poon, Art F. Y.; Rebeiro, Peter F; Vermund, Sten H.; Sterling, Timothy R.; Kalish, Marcia L.

doi:10.1089/aid.2018.0039

Cited by 27 publications

(35 citation statements)

References 30 publications

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“…This analysis supports the hypothesis that there has been a recent and rapid rise of HIV transmissions among young MSM in Tennessee and in particular among young black MSM. This interpretation is mostly in agreement with the original study (Dennis et al 2018), but we find that black MSM are a group at greater risk than young white MSM.…”

Section: Resultssupporting

confidence: 93%

“…Finally, we applied phylodynamic analysis methods to see if the partition structure supported the previously published findings that young MSM were transmitting at a higher rate (Dennis et al 2018). To estimate N e through time, we used the nonparametric skygrowth R package (Volz and Didelot 2018).…”

Section: Resultsmentioning

confidence: 64%

“…We reanalysed a time-scaled phylogeny reconstructed from 2068 partial pol HIV-1 subtype B sequences collected from Tennessee between 2001 and 2015 (Dennis et al 2018). Each lineage within this phylogeny corresponds to a single HIV patient sampled at a single time point, and various clinical and demographic covariate data concerning these patients can be associated with each lineage.…”

Section: Resultsmentioning

confidence: 99%

“…Each lineage within this phylogeny corresponds to a single HIV patient sampled at a single time point, and various clinical and demographic covariate data concerning these patients can be associated with each lineage. In the original study, these sequence data were used to show high rates of transmission among young (age < 26.4) men who have sex with men (MSM) (Dennis et al 2018). Clustering by threshold genetic distance is often used in HIV epidemiology (Dennis et al 2014) and indicated that young white MSM had the highest odds of clustering.…”

Section: Resultsmentioning

confidence: 99%

“…A time-scaled phylogeny estimated from HIV-1 pol sequences in Tennessee (Dennis et al 2018). The colours correspond to the ten partitions identified using the treestructure algorithm.…”

Section: Resultsmentioning

confidence: 99%

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Identification of hidden population structure in time-scaled phylogenies

Volz

Wiuf

Grad

et al. 2019

Preprint

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17Population structure influences genealogical patterns, however data 18 pertaining to how populations are structured are often unavailable or 19 not directly observable. Inference of population structure is highly 20 important in molecular epidemiology where pathogen phylogenetics is 21 increasingly used to infer transmission patterns and detect outbreaks. 22 Discrepancies between observed and idealised genealogies, such as those 23 generated by the coalescent process, can be quantified, and where 24 significant differences occur, may reveal the action of natural selection, 25 host population structure, or other demographic and epidemiological 26 heterogeneities. We have developed a fast non-parametric statistical test 27 for detection of cryptic population structure in time-scaled phylogenetic 28 trees. The test is based on contrasting estimated phylogenies with the 29 theoretically expected phylodynamic ordering of common ancestors in 30 two clades within a coalescent framework. These statistical tests have 31 also motivated the development of algorithms which can be used to 32 quickly screen a phylogenetic tree for clades which are likely to share a 33 distinct demographic or epidemiological history. Epidemiological 34 applications include identification of outbreaks in vulnerable host 35 populations or rapid expansion of genotypes with a fitness advantage.36To demonstrate the utility of these methods for outbreak detection, we 37 applied the new methods to large phylogenies reconstructed from 38 thousands of HIV-1 partial pol sequences. This revealed the presence of 39 clades which had grown rapidly in the recent past, and was significantly 40 concentrated in young men, suggesting recent and rapid transmission in 41 that group. Furthermore, to demonstrate the utility of these methods 42 for the study of antimicrobial resistance, we applied the new methods to 43 a large phylogeny reconstructed from whole genome Neisseria 44 gonorrhoeae sequences. We find that population structure detected 45 using these methods closely overlaps with the appearance and expansion 46 of mutations conferring antimicrobial resistance. 48 diversity is a longstanding problem in population genetics. When information 49 about how lineages are sampled is available, primarily geographic location, a 50 variety of statistics are available for describing the magnitude and role of 51 population structure (Hartl et al. 1997). In pathogen phylogenetics, such 52 geographic 'meta-data' has been instrumental in enabling the inference of 53 transmission rates over space (Dudas et al. 2017), host species (Lam et al. 54 2015), and even individual hosts (De Maio et al. 2018). Population structure 55 shapes genetic diversity, but can the existence of structure be inferred directly 56 from genetic data in the absence of structural covariates associated with each 57 lineage, such as if the geographic location or host species of a lineage is 58 unknown? 59 The problem of detecting and quantifying such 'cryptic' population 60 structure has become a pr...

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 64%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…A time-scaled phylogeny estimated from HIV-1 pol sequences in Tennessee (Dennis et al 2018). The colours correspond to the ten partitions identified using the treestructure algorithm.…”

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations