TY - JOUR
T1 - Complex patterns of Hepatitis-C virus longitudinal clustering in a high-risk population
AU - Rose, Rebecca
AU - Lamers, Susanna L.
AU - Massaccesi, Guido
AU - Osburn, William
AU - Ray, Stuart C.
AU - Thomas, David L.
AU - Cox, Andrea L.
AU - Laeyendecker, Oliver
N1 - Publisher Copyright:
© 2017
PY - 2018/3
Y1 - 2018/3
N2 - 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 14 years 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.
AB - 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 14 years 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.
KW - Clustering
KW - Epidemiology
KW - HCV
KW - Linkage
KW - Phylogenetic
UR - http://www.scopus.com/inward/record.url?scp=85038837519&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85038837519&partnerID=8YFLogxK
U2 - 10.1016/j.meegid.2017.12.015
DO - 10.1016/j.meegid.2017.12.015
M3 - Article
C2 - 29253674
AN - SCOPUS:85038837519
SN - 1567-1348
VL - 58
SP - 77
EP - 82
JO - Infection, Genetics and Evolution
JF - Infection, Genetics and Evolution
ER -