Literature DB >> 29253674

Complex patterns of Hepatitis-C virus longitudinal clustering in a high-risk population.

Rebecca Rose1, Susanna L Lamers1, Guido Massaccesi2, William Osburn2, Stuart C Ray2, David L Thomas2, Andrea L Cox2, Oliver Laeyendecker3.   

Abstract

We investigated longitudinal viral clustering among and within subjects in a highly networked cohort of people who inject drugs (PWID). All subjects had estimated dates of infection and two or more E1 sequences (bp 943-1288 relative to H77) with 1 to 14years of follow up. Two methods (HIV-TRACE and PhyloPart) were used to determine clusters. Genetic distance thresholds were determined by comparing intra-and inter-host distances. Additional phylogenetic analysis was performed on subjects with complicated viral histories. At the optimal threshold of 3.9%, HIV-TRACE found 77 clusters and PhyloPart found 63 clusters, of which 27 and 32 contained multiple subjects, respectively. Furthermore, 1/3 of the subjects had sequences in different clusters over the course of the study, including some cases in which a later-sampled sequence matched a cluster detected much earlier in the infection, despite being separated by RNA-negative lab visit and detection of sequences in different clusters. A detailed phylogenetic analysis of four subjects with such patterns showed that in all four cases, the earlier and later variants grouped closely on the tree, and did not group with concurrent sequences from any other subject. These observations suggest that subjects are either experiencing rapid and recurring infection-clearance-reinfection cycles from the same source, or a single transmission event produces a chronic infection that may go undetected and/or co-circulate with different viruses from separate transmission events. Furthermore, our results show the utility of using longitudinal sampling to obtain a more comprehensive view of the viral linkages in high-risk populations. Published by Elsevier B.V.

Entities:  

Keywords:  Clustering; Epidemiology; HCV; Linkage; Phylogenetic

Mesh:

Substances:

Year:  2017        PMID: 29253674      PMCID: PMC5807204          DOI: 10.1016/j.meegid.2017.12.015

Source DB:  PubMed          Journal:  Infect Genet Evol        ISSN: 1567-1348            Impact factor:   3.342


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