Applying an 'omics' approach to predict hepatic decompensation events and hepatocellular carcinoma in veterans after HCV cure with direct acting antiviral therapy

退伍军人事务部是美国最大的丙型肝炎病毒感染卫生保健提供者。 美国的自2014年引入直接作用抗病毒药物治疗HCV感染以来，VA已 治愈了超过10万名退伍军人由于退伍军人中合并症的发生率很高，包括艾滋病毒合并症， 感染、饮酒、肥胖和代谢综合征、DAA治疗前严重肝纤维化的发生率 很高，即使治愈也可能持续存在。而持续病毒学应答（SVR），一种病毒学替代物， HCV治愈与肝失代偿风险降低相关（即，自发性细菌性腹水 腹膜炎（SBP），肝性脑病（HE），食管静脉曲张出血），肝细胞癌（HCC）， 和肝脏相关的死亡率，在治愈之前患有严重肝纤维化的退伍军人仍然处于此类事件的高风险中， 全因死亡率到目前为止，还没有可靠的实验室检查或生物标志物来区分患有 SVR后失代偿事件、HCC和肝脏相关死亡的风险最大。我们发现了一群 脂质和脂质相关代谢物，可准确预测HIV感染者的肝脏相关并发症风险 和HCV合并感染，发生事件前约2年。我们建议验证这种生物标志物 在一组已经治愈HCV的患者中。一旦得到验证，我们建议在真实的- 世界退伍军人队列，以确保普遍性。代谢产物谱的成功验证将支持 转化研究，以了解与代谢物相关的基础生物学 以及纤维化和HCC治疗靶点的潜在途径。对于目标1，我们将验证以下生物特征： 循环脂质和脂质相关代谢物，可预测偶发肝代偿失调事件， DAA治疗达到HCV治愈的肝硬化患者的HCC。我们将进行嵌套病例对照 一项研究，利用了一个预先存在的HCV和肝硬化患者队列，这些患者通过DAA疗法治愈 并对肝脏相关并发症进行前瞻性随访。我们将有针对性地进行全面的 代谢组学分析以验证预后代谢谱。为了实现目标2，我们将开发集成的“临床- “代谢”模型结合临床变量和代谢物生物标志物，最大限度地识别退伍军人 DAA治疗实现HCV治愈后肝失代偿事件和HCC的风险。我们将招收 患有严重肝病的退伍军人进入一项前瞻性观察性研究，在两个VA中心进行，DAA后， 诱导HCV治愈使用巢式病例对照设计，我们将完成全面的靶向代谢物 分析以开发优化模型来预测肝脏相关事件。对于目标3，我们将使用集成的高- 外周血和肝组织的三维生物学方法，以优化基于血液的预测模型， 研究退伍军人中SVR后发生的HCC，并确定新的生物学途径，为未来的治疗目标提供信息 发展使用DAA治疗HCV治愈后发生HCC的退伍军人的肝组织 我们将整合转录组学，代谢组学和蛋白质组学分析，以确定新的生物途径， 可以开发血浆中的哪些代谢物生物标志物。这项试点研究将产生生物学知识， 这些通路将作为疾病生物标志物和未来研究的新疗法的靶点。

The Department of Veterans Affairs is the single largest hepatitis C virus infection health care provider in the United States. Since the introduction of direct acting antivirals for the treatment of HCV infection in 2014, VA has cured over 100,000 Veterans. Due to the high rate of comorbidities in the veteran population, including HIV co- infection, alcohol use, and obesity and metabolic syndrome, rates of severe liver fibrosis prior to DAA therapy are high and likely to persist despite cure. While sustained virologic response (SVR), a virologic surrogate of HCV cure, is associated with decreased risk of hepatic decompensation (i.e., ascites, spontaneous bacterial peritonitis (SBP), hepatic encephalopathy (HE), esophageal variceal bleed), hepatocellular carcinoma (HCC), and liver-related mortality, Veterans with severe liver fibrosis prior to cure remain at high risk for such events and all-cause mortality. To date there are no reliable laboratory tests or biomarkers to differentiate patients with the greatest risk of post-SVR decompensation events, HCC, and liver-related death. We have discovered a group of lipid and lipid-related metabolites that accurately predict risk of liver-related complications in people with HIV and HCV co-infection, approximately 2 years prior to the incident event. We propose to validate this biomarker in a cohort of patients who have achieved HCV cure. Once validated, we propose to test the biomarker in a real- world Veteran cohort to ensure generalizability. Successful validation of the metabolite profile will support translational investigations to gain an understanding of the fundamental biology associated with the metabolites and potential pathways for therapeutic targets of fibrosis and HCC. For Aim 1 we will validate a biosignature of circulating lipid and lipid-related metabolites that is predictive of incident hepatic decompensation events and HCC in patients with cirrhosis who achieve HCV cure with DAA therapy. We will conduct a nested case-control study, leveraging a pre-existing cohort of patients with HCV and cirrhosis who achieved cure with DAA therapies and are followed prospectively for liver-related complications. We will perform comprehensive targeted metabolomic profiling to validate a prognostic metabolic profile. For Aim 2 we will develop integrated “clinico- metabolic” models incorporating clinical variables and metabolite biomarkers that identify Veterans at greatest risk of hepatic decompensation events and HCC after achieving HCV cure with DAA therapy. We will enroll Veterans with severe liver disease into a prospective, observational study, conducted at two VA sites, after DAA- induced HCV cure. Using a nested case-control design we will complete comprehensive targeted metabolite profiling to develop optimized models to predict liver-related events. For Aim 3 we will use an integrated high- dimensional biology approach of peripheral blood and liver tissue to optimize blood-based predictive models of post-SVR incident HCC in Veterans and identify novel biologic pathways to inform future therapeutic target development. Using liver tissue from Veterans who develop incident HCC after HCV cure with DAA therapies we will integrate transcriptomic, metabolomic, and proteomic profiling to identify novel biologic pathways for which metabolite biomarkers in the plasma can be developed. This pilot study will generate knowledge of biologic pathways that will serve as the target for disease biomarkers and novel therapeutics for future study.