Identification of Genetically Related HCV Infections Among Self-Described Injecting Partnerships

Author:

Tully Damien C12,Hahn Judith A3,Bean David J4,Evans Jennifer L5,Morris Meghan D5,Page Kimberly6,Allen Todd M4

Affiliation:

1. Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom

2. Center for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom

3. Department of Medicine, University of California, San Francisco, California, USA

4. Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA

5. Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA

6. Department of Internal Medicine, University of New Mexico Health Center, Albuquerque, New Mexico, USA

Abstract

Abstract Background The current opioid epidemic across the United States has fueled a surge in the rate of new hepatitis C virus (HCV) infections among young persons who inject drugs (PWIDs). Paramount to interrupting transmission is targeting these high-risk populations and understanding the underlying network structures facilitating transmission within these communities. Methods Deep sequencing data were obtained for 52 participants from 32 injecting partnerships enrolled in the U-Find-Out (UFO) Partner Study, which is a prospective study of self-described injecting dyad partnerships from a large community-based study of HCV infection in young adult PWIDs from San Francisco. Phylogenetically linked transmission events were identified using traditional genetic-distance measures and viral deep sequence phylogenies reconstructed to determine the statistical support of inferences and the direction of transmission within partnerships. Results Using deep sequencing data, we found that 12 of 32 partnerships were genetically similar and clustered. Three additional phylogenetic clusters were found describing novel putative transmission links outside of the injecting relationship. Transmission direction was inferred correctly for 5 partnerships with the incorrect transmission direction inferred in more than 50% of cases. Notably, we observed that phylogenetic linkage was most often associated with a lower number of network partners and involvement in a sexual relationship. Conclusions Deep sequencing of HCV among self-described injecting partnerships demonstrates that the majority of transmission events originate from outside of the injecting partnership. Furthermore, these findings caution that phylogenetic methods may be unable to routinely infer the direction of transmission among PWIDs especially when transmission events occur in rapid succession within high-risk networks.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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