HCV Ghost Sequencing Center

项目概要： 美国正处于阿片类药物的巨大流行之中。2015年，超过52，000名美国人死亡， 由于药物过量，其中超过60%与处方或非法阿片类药物使用有关。鉴于 注射吸毒仍然是HCV传播的主要危险因素，同时美国已经观察到， 2010-2013年间，HCV发病率显著增加>150%，新发HCV增加364%。 2006年至2012年期间，阿巴拉契亚州的四个州感染了艾滋病毒，特别是在农村地区。因此， 迫切需要在国家层面上更具战略性地检测、预防、治疗和控制HCV。 在母公司的奖励下，我们建立了一个高质量，高通量的HCV下一代测序（NGS）平台 这使得能够从来自8个农村研究的1,000多个患者样本中生成HCV HVR 1序列， 网站，沿着与内部信息管道能够验证系统发育聚类确定的 CDC GHOST实验室NGS数据的传输网络分析表明， （可能直接传播）在研究中心之间差异很大，范围为10%至42%。跨所有 基因型1a（57%）最常见，其次为3a（30%）、2b（9%）、1b（4%） 混合基因型占不到5%。GHOST HCV分子检测系统的实施 监测技术表明，在农村社区进行HCV基因组监测是可行的， 潜在的因素可能会影响跨站点传输网络的规模。根据父母奖 我们还研究了使用干血斑（DBS）收集用于该应用的可行性。一项试点研究 包括14份血清样品的研究表明，DBS内的病毒群体在遗传上与 来自血浆的病毒群，证明DBS可以捕获可比的传播网络 以及从传统的血清样品收集中观察到的病毒多样性。因此，DBS可以增强传统的 在资源有限的地区，HCV监测方法是冷冻血浆的一种实用且具有成本效益的替代方法 比如农村人口。 由于SARS-CoV-2大流行对我们在Ragon研究所的实验室工作产生了重大影响， 在我们的UH 3合作者为我们的工作提供标本后，我们应用的许多最初目标 没有完成。我们的U24应用程序的此管理补充建议支持生成 并为CDC的GHOST中心分析额外的HCV NGS数据，以确定HCV在 注射毒品者（PWID）;验证用于采集和生成干血点的应用 管理艾滋病毒和丙型肝炎病毒血清样本的收集和储存， 根据RFA-DA-17-014从临床研究中心接收受感染的受试者;并将标本运送至CDC， 梅毒检测和HIV和HCV系统发育图谱。 我们计划使用这些资金来支付第六年的额外工作量，以实现我们项目的最初目标。这 包括，处理和分析最近到达的数百个新患者样本， 我们的临床研究中心，通过合并NGS数据与研究中心特定的RDS， 数据，并完成我们的DBS研究出版。

PROJECT SUMMARY: The United States is in the midst of an enormous opioid epidemic. In 2015, more than 52,000 American’s died due to a drug overdose, over 60% of which were associated with prescription or illicit opioid use. Given that injection drug use remains the major risk factor for HCV transmission, concomitantly the US has observed a striking >150% increase in the incidence of HCV between 2010-2013, and a 364% increase in new HCV infections between 2006 and 2012 in four Appalachian states, most notably in rural areas. As such, there is urgent need to more strategically detect, prevent, treat and control HCV on a national level. Under the parent award we built a high-quality, high-throughput HCV next-generation sequencing (NGS) platform that enabled the generation of HCV HVR1 sequences from over 1,000 patient samples derived from 8 rural study sites, along with an in-house informatics pipeline capable of validating phylogenetic clustering identified by the CDC GHOST laboratory. Transmission network analysis of the NGS data showed that the rate of clustering (likely direct transmission) varied considerably across study sites ranging from 10% to 42%. Across all geographical sites, genotype 1a (57%) was the most common followed by genotype 3a (30%), 2b (9%), 1b (4%) and mixed genotypes represented less than 5% of cases. The implementation of the GHOST HCV molecular surveillance technology illustrates that genomic surveillance of HCV in rural communities is feasible and suggest underlying factors may be influencing the size of transmission networks across sites. Under the parent award we also examined the feasibility of using dried blood spot (DBS) collection for this application. A pilot study comprising 14 serum samples revealed that viral populations within DBS were genetically indistinguishable from viral populations derived from plasma, demonstrating that DBS can capture comparable transmission networks and viral diversity observed from the traditional collection of serum samples. Thus, DBS can augment traditional HCV surveillance approaches as a practical and cost-effective alternative to frozen plasma in resource-limited settings such as rural populations. Due to the substantial impact of the SARS-CoV-2 pandemic upon both our laboratory work at the Ragon Institute, and upon our UH3 collaborators providing specimens for our work, many of the initial goals of our application were not completed. This Administrative Supplement to our U24 application proposes to support the generation and analysis of additional HCV NGS data for the CDC’s GHOST center to identify HCV transmission links among persons who inject drugs (PWID); validate the application of dried blood spots for the collection and generation of transmission links by NGS data; manage the collection and storage of serum samples from HIV- and HCV- infected participants from the clinical research sites under RFA-DA-17-014; and ship specimens to the CDC for syphilis testing and phylogenetic mapping for HIV and HCV. We plan to use these funds to cover additional workload in Year 6 to meet the original goals of our project. This includes, the processing and analysis of several hundred new patient samples that have recently arrived from our clinical sites, identify factors driving high rates of clustering by merging NGS data with site-specific RDS data, and completing our DBS study for publication.