Improving Prediction of Chemotherapy-Induced Nausea: Integrating Genes, Behavior, and the Microbiome

项目摘要 高达38%的接受中度或高度- 尽管国际止吐指南。化疗引起的恶心 与生活质量下降、医疗保健利用率增加和护理成本增加相关。先前 研究已经确定了恶心的临床和个人危险因素（例如，疾病阶段，致吐性 化疗，年龄，性别，晕动病史，焦虑，酒精使用），但基于风险预测算法 这些因素都有改进的余地。人类基因组研究的最新方法 和微生物组使我们第一次能够更全面地了解 化疗引起的恶心的病理生理学，并开发更好的算法。当前的目标 本研究旨在通过综合检查化疗引起的恶心风险， 遗传和微生物组变量，具有明确的临床和个人风险因素。我们将进行 化疗引起的恶心的第一个GWAS，然后使用途径分析将结果置于功能 上下文重要变异将与临床和个人因素一起纳入临床风险预测 算法这项研究也将是第一个研究肠道微生物组与 化疗引起的恶心重要的是，这项研究是第一个真正整合生物学， 临床和患者报告的数据来预测治疗毒性的风险。这项开创性的研究将 在化疗的其他副作用，如认知障碍，疲劳， 周围神经病变当前研究的更新风险算法将公开提供， 将为未来基于风险的止吐癌症护理的随机试验提供信息。积极的结果将 促使风险算法集成到电子医疗记录中，并提供警报以识别患者 有化疗引起恶心的风险研究前两年进行的微生物组分析 将提供关于其对化疗引起的恶心的贡献的快速知识。积极的结果将 进行额外的研究，以确定微生物操作是否可以预防化疗诱导的 恶心微生物组数据特别令人兴奋，因为它们关注的是一种全新的机制， 化疗相关毒性。总之，这项严格的，全面的研究提供了一个综合的新的 化疗引起的恶心的方法，预计将显着推进我们的理解 这一重要临床问题的病理生理学和风险。

PROJECT SUMMARY Moderate to severe nausea is reported by up to 38% of cancer patients receiving moderately- or highly- emetogenic chemotherapy despite international antiemetic guidelines. Chemotherapy-induced nausea is associated with worse quality of life, increased healthcare utilization, and greater costs of care. Previous research has identified clinical and personal risk factors for nausea (e.g., disease stage, emetogenicity of chemotherapy, age, sex, history of motion sickness, anxiety, alcohol use), but risk-prediction algorithms based on these factors demonstrate room for improvement. Recent methodologies for studying the human genome and microbiome enable us for the first time to develop a more comprehensive understanding of the pathophysiology of chemotherapy-induced nausea and develop better algorithms. The goal of the current study is to improve understanding of risk of chemotherapy-induced nausea through integrated examination of genetic and microbiome variables with well-established clinical and personal risk factors. We will conduct the first GWAS of chemotherapy-induced nausea, then use pathway analysis to place results into functional context. Significant variants will be incorporated with clinical and personal factors into a clinical risk prediction algorithm. This study will also be among the first to examine the association of the gut microbiome with chemotherapy-induced nausea. Importantly, this study is one of the first to truly integrate biological, clinical, and patient-reported data to predict risk of treatment toxicity. This groundbreaking study will be a model for similar efforts in other side effects of chemotherapy such as cognitive impairment, fatigue, and peripheral neuropathy. Updated risk algorithms from the current study will be made publicly available and will inform a future randomized trial of risk-based antiemetic cancer care delivery. Positive results will spur integration of the risk algorithms into the electronic medical record with provider alerts to identify patients at risk of chemotherapy-induced nausea. Microbiome analyses conducted in the first two years of the study will provide rapid knowledge about its contributions to chemotherapy-induced nausea. Positive results will generate additional studies to determine whether microbial manipulation can prevent chemotherapy-induced nausea. Microbiome data are particularly exciting because they focus on an entirely new mechanism in chemotherapy-related toxicity. In summary, this rigorous, comprehensive study provides an integrated new approach to chemotherapy-induced nausea that is expected to significantly advance our understanding of pathophysiology and risk of this important clinical problem.