CROI 2019 Abstract eBook

Abstract eBook

Poster Abstracts

593 PHYLOGENETIC EVIDENCE FOR INTERCITY HCV CLUSTERS OF PEOPLE WHO INJECT DRUGS IN INDIA Steven J. Clipman 1 , Mary A. Rodgers 2 , Shanmugam Saravanan 3 , Priya Duggal 1 , Shruti H. Mehta 1 , Aylur K. Srikrishnan 3 , Muniratnam S. Kumar 3 , Allison M. McFall 1 , Gregory M. Lucas 4 , Thomas C. Quinn 4 , Gavin Cloherty 2 , Sunil S. Solomon 4 1 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 2 Abbott Labs, Abbott Park, IL, USA, 3 YR Gaitonde Center for AIDS Research and Education, Chennai, India, 4 Johns Hopkins University School of Medicine, Baltimore, MD, USA Background: Little data exist on HCV phylodynamics and transmission networks among people who inject drugs (PWID), especially from low- and middle-income countries (LMICs). HCV epidemics in a city can be considered a series of sub-epidemics caused by phylogenetically distinct viral lineages. Mapping these lineages to generate transmission clusters and overlaying epidemiologic data can be used to identify factors associated with clustering. Methods: PWID were recruited via respondent driven sampling in 2016-17. Participants completed a survey and blood draw. HCV 5’UTR-core sequencing was performed on 486 HCV RNA positive samples from 4 cities (Amritsar [n=126], Delhi [n=128], Kanpur [n=138], Imphal [n=94]). Sequences were aligned using Multiple Sequence Comparison by Log-Expectation. The most appropriate nucleotide substitution model was determined using jModelTest and phylogenetic inference was carried out using Maximum Likelihood methods in RaXML with 500 bootstrap replications. Clusters were identified using ClusterPicker with posterior support and genetic distance thresholds of 70% and 4.5%, respectively. Given the large number of covariates of interest, a machine learning model utilizing the Boruta wrapper of the random forest algorithmwas constructed to identify features predictive of clustering, as well as differences between clusters. Results: Median age was 33 years, 99%were male and HIV prevalence was 75%. Mean p-distance for all sequences was 0.075. A total of 251 sequences fell into 19 transmission clusters (Fig). Mean cluster size was 7.4 (range: 2-49); 8 clusters were dyads. There were 6 large clusters comprised of >10 samples. 7 of the 19 clusters contained samples frommultiple cities. Machine learning based analysis revealed that no history of HIV testing and living with friends were predictive of clustering (both p<0.05), and that state, residential zip code, injection zip code, time spent away from home, and buprenorphine injection could be predictive of membership in a given cluster (all p<0.05). Age, gender, and HIV status did not predict clustering. Conclusion: These are among the first data from a LMIC setting to demonstrate clustering across multiple cities. The median size of the clusters identified were also larger than self-reported injection networks in India. Treatment as prevention efforts for HCV have emphasized network-based approaches for PWID, and these data suggest that networks may need to be defined by space (zip code) as opposed to egocentric injection networks.

594 PHYLODYNAMICS OF ACUTE HCV INFECTION IN MEN HAVING SEX WITH MEN Gonché Danesh 1 , Victor Virlogeux 2 , Christophe Ramiere 2 , Caroline Charre 2 , Samuel Alizon 1 , Laurent Cotte 2 1 Université de Montpellier, Montpellier, France, 2 Hospices Civils de Lyon, Lyon, France Background: Opioid substitution and syringes exchange programs have drastically reduced HCV spread in France, while HCV sexual transmission in men who have sex with men (MSM) has recently arose as a significant phenomenon. Epidemiological data such as prevalence and incidence rates can quantify an epidemic at its chronic stage but are less meaningful at its early stages or if the transmission of the pathogen only occurs in a subgroup of individuals. Phylodynamic inferences use both pathogen phylogenies based on genetic sequences and epidemiological data to describe infectious diseases transmission dynamic. We used a phylodynamic approach to estimate key epidemiological parameters such as the reproduction number (R0) and the infectious period duration of acute HCV infection (AHI) in French MSM. Methods: A birth-death epidemiological model with 2 host types corresponding to respectively the “classic” HCV epidemic (mostly IVDU-blood product recipients) and the “new” epidemic in MSM was implemented. Two periods (< and >1997) were considered for the classic epidemic. 30,000 simulated phylogenies were first generated under a variety of parameter set. These simulations were then used to “feed” a regression model and to infer epidemiological parameters using an approximate Bayesian computation approach. The model was then run on the true HCV phylogeny from AHI and chronic HCV infections, to infer R0, infectious period and assortativity estimates (the extent to which virus transmission is random or occurs mostly within groups) for both epidemics. The validity of the results was estimated using a parametric bootstrap approach. Results: 213 NS5B sequences from HCV genotype 1a infections were analyzed (68 from AHI in MSM, 145 from chronic infections in non-MSM patients). Estimates of the beginning dates for the classic and the new epidemics were 1983 (95%CI 1981-1983) and 2000 (95%CI 1999-2002) respectively. Estimates of R0 for the classic epidemic >1997 and for the new epidemic were 1.5 (IQR 1.3-1.7) and 1.7 (IQR 1.4-2.1) respectively. Estimates for the infectious period duration for the classic and the new epidemics were 2.3 years (IQR 1.6-3.1 years) and 0.4 years (0.4-0.5 years) respectively. Conclusion: AHI epidemic in French MSM was characterized by a similar R0, but a much shorter infectious period and a greater transmission rate per unit of time than the classic epidemic. These result shows how phylodynamic can help to understand the transmission dynamics of an epidemic spreading in different populations. 595 VALIDATION OF A GENOTYPE-INDEPENDENT HEPATITIS C WHOLE- GENOME SEQUENCING ASSAY Hope R. Lapointe 1 , Weiyan Dong 2 , Winnie W. Dong 2 , Don Kirkby 2 , Conan K. Woods 2 , Art Poon 3 , Anita Y. Howe 2 , P. Richard Harrigan 1 , Chanson J. Brumme 2 1 University of British Columbia, Vancouver, BC, Canada, 2 British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada, 3 Western University, London, ON, Canada Background: Recent development of direct-acting antiviral agents (DAA) has dramatically improved the effectiveness and tolerability of treatments for hepatitis C virus (HCV), resulting in >95% sustained virologic response (SVR) rates. However, cases of treatment failure have been associated with the emergence of resistance-associated substitutions (RAS). To better guide clinical decision-making, we developed and validated a near-whole-genome, HCV genotype (GT)-independent sequencing strategy on the Illumina MiSeq next- generation sequencing (NGS) platform. Methods: HCV GT1-6 samples from treatment-naïve HCV-infected individuals as well as DAA-treated persons who did not achieve SVR were included. Viral RNA was extracted on a Biomerieux easyMag and underwent nested reverse- transcription-PCR. Libraries prepared by Nextera XT were sequenced on the MiSeq. NGS data were processed by an in-house pipeline that incorporates HCV reference sequence selection and an iterative mapping process for paired- end reads. Nucleotide consensus sequences were aligned to appropriate FDA reference strain sequences for downstream identification of RAS. Sequences were compared to data obtained from a previously validated in-house assay optimized for HCV GT1. A minimal threshold for minority species detection was estimated from the coefficient of variation of minor species quantification.

Poster Abstracts

CROI 2019 224