Implementation of Ghost for Detection of HCV Transmission Network by Tennessee Department of Health

Author: Ramachandran Sumathi, Thomas Linda, Steece Richard, Wester Carolyn, Sizemore Lindsey, Rickles Michael, Baggett Asimwe, Kellem Rhonda, Thai Hong, Medrzycki Magdelena, Ganova-Raeva Lilia, Longmire Atkinson, Sims Seth, Xia Guoliang, Lin Yulin, Punkova Lili, Dimitrova Zoya, Sue Amanda, DeAnne Sharp, Lindsay Jolly, Erlendsson Jennifer, Shane Allen, Sanders Beverly, Krajnak Mike, Teshale Eyasu, Ward John, Khudyakov Yury

Theme: Epidemiology & Public Health Research Year: 2017

Background: States along the Appalachian region face a growing hepatitis C virus (HCV) epidemic associated with injection drug use. To scale up the HCV surveillance capacity in the state of Tennessee, a pilot project was launched in collaboration between the Division of Viral Hepatitis, Centers for Disease Control and Prevention (CDC) and Tennessee Department of Health (TDH) with an objective to improve HCV molecular surveillance by utilizing Global Hepatitis Outbreak and Surveillance Technology (GHOST). GHOST is a new cloud-based system that integrates laboratory, information technology, and state public health laboratory resources to gather molecular data and distill public health relevant information to guide intervention measures.
Methods: TDH collected samples from STD and Family Planning Clinics between June to October 2016 to be analyzed with the GHOST HCV transmission analysis pipeline. GHOST utilizes an amplicon-based Illumina Miseq sequencing protocol that targets the hypervariable region (HVR1) of the HCV genome. Raw MiSeq files generated by TDH were submitted to the GHOST portal, which automatically delivered results for genotype and transmission network inference. CDC provided GHOST on-site and off-site trainings, technical assistance and proficiency panel testing and also confirmed the validity of GHOST results by random testing of 25% of the total samples.
Results: Of 4,753 persons tested for HCV, 397 (8.4%) were anti-HCV positive. Of these, 294 (74.1%) were RNA positive, and 85% produced sequences. Genotype 1a (n=178) was the most common, followed by 3a (n=49), 1b (n=13), 2b (n=13), 2a (n=1), 4a (n=1), and mixed genotypes (n=6). Transmission network analysis showed that 21 cases were linked into 9 clusters (8%), with 6 of them being infected by HCV genotype 1a, and 3 with 3A. Identification of mixed-genotype infections and multiple transmission clusters indicates detection of cases from a transmission network associated with high-risk acquisition of HCV infection.
Conclusions: TDH use of GHOST allowed for the detection of cases from a high-risk transmission network, demonstrating the feasibility of using this novel technology to facilitate complex state-based HCV outbreak investigations and molecular surveillance.

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