Factors associated with phylogenetic clustering of hepatitis C among people who inject drugs in Baltimore

Abstract

Background The availability of effective, oral direct acting antivirals (DAAs) for hepatitis C virus (HCV) treatment has put elimination of HCV as a public health challenge within reach. However, little is known about the characteristics of transmission networks of people who inject drugs (PWID). Methods Sequencing of a segment of the HCV genome was performed on samples collected from a community-based cohort of PWID between August 2005 and December 2016. Phylogenetic trees were inferred, and clusters were identified (70% bootstrap threshold; 0.04 maximum genetic distance threshold). We describe sex, race, age difference, and HIV infection status of potential transmission partners. Logistic regression was used to assess factors associated with being in an HCV cluster. Results Of 508 HCV genotype 1 viremic PWID, 8% (n = 41) were grouped into 20 clusters, consisting of 19 pairs and 1 triad. In adjusted analyses, female sex (odds ratio [OR] 2.3 [95% confidence interval (CI) 1.2–4.5]) and HIV infection (OR 5.7 [CI 2.7–11.9]) remained independently associated with being in an HCV infection cluster. Conclusions Molecular epidemiological analysis reveals that, in this cohort of PWID in Baltimore, HIV infection and female sex were associated with HCV clustering. Combination HCV prevention interventions targeting HIV infected PWID and addressing HCV infection prevention needs of women have potential to advance HCV elimination efforts.

Molecular and spatial epidemiology of HCV among people who inject drugs in Boston, Massachusetts

“…12 A study from Baltimore, concurrent with ours, found no evidence of genotype 3a. 13 Our study population was substantially younger than those in the other two studies, consistent with our aim to recruit a younger sample, but differences in genotype were not associated with age. However, there were two subtypes (1b and 2b) that were restricted to older individuals.…”

Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action

“…43 Through phylogenetic analysis, they were able to identify both drug use and sexual HIV transmission networks linking SSP clients with individuals outside of this group. 43 Falade-Nwulia et al found that, among HCV-positive PWID in Baltimore, women and HIVpositive individuals were more likely to be associated with an HCV transmission cluster, 44 showing that phylogenetic approaches can help identify individuals at higher risk of infection. Further Zhou et al present a novel molecular analysis to identify recent infections and drug resistance mutations among new HIV diagnoses.…”

Temporal trends of hepatitis C virus transmission in internally displaced people who inject drugs in Odessa, Ukraine

“…We used ClusterPicker [23] to identify possible transmission clusters defined as clades with >90% bootstrap support and within-clades genetic distance <3%. Other previously published cluster-defining criteria were considered [14], but did not affect our findings (Supplementary Materials).…”

“…Amplicon ends were prepared for ligation with the NEBNext Ultra II End Repair/dA-Tailing Module (NEB). Unique barcodes from the Oxford Nanopore Native Barcoding Expansion kits EXP-NBD104 (1-12) and EXP-NBD114 (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24) were ligated to each sample using the NEBNext Ultra II Ligation Module (NEB). Following barcoding, reactions were pooled together in equal volumes and purified with SPRI beads (x0.4 ratio).…”

“…Molecular epidemiology, the study of how epidemiological and evolutionary factors shape viral phylogenies [13], is increasingly utilised in public health settings due to the widespread availability of pathogen genetic sequences and has been used to identify HCV transmission clusters, thus improving our understanding of infection transmission chains [14, 15]. We previously used molecular epidemiology methods to show that internal displacement following war in eastern Ukraine triggered a geographic redistribution of existing HIV infections: migration from high prevalence regions in the east to lower prevalence regions in the west [16].…”