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

改善化疗引起恶心的预测：整合基因、行为和微生物组

• 批准号: 10166795
• 负责人: HEATHER S.L. JIM
• 金额: $ 68.35万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10166795
• 关键词: Acute; Adult; Age; Alcohol consumption; Algorithms; Antiemetics; Anxiety; Area; Behavior; Benefits and Risks; Bioinformatics; Biological; Cancer Center; Cancer Patient; Characteristics; Clinical; Computerized Medical Record; Data; Data Collection; Data Reporting; Diarrhea; Disease; Evolution; Fatigue; Fright; Functional disorder; Future; Genes; Genetic; Genetic Variation; Goals; Guidelines; Heritability; Hour; Human; Human Genome; Human Microbiome; Impaired cognition; Infusion procedures; International; Intravenous; Knowledge; Malignant Neoplasms; Medicine; Metagenomics; Methodological Studies; Microbe; Microbial Genetics; Modeling; Motion Sickness; Mucositis; Nausea; Oncology; Outcome Study; Outpatients; Participant; Pathway Analysis; Pathway interactions; Patient risk; Patients; Peripheral Nervous System Diseases; Protocols documentation; Provider; Quality of life; Recording of previous events; Reporting; Research; Risk; Risk Factors; Risk Management; Role; Sampling; Serotonin; Severities; Time; Toxic effect; Toxicity due to chemotherapy; Translating; Treatment-related toxicity; Update; Variant; base; cancer care; cancer therapy; care costs; care delivery; chemotherapy; clinical care; clinical predictors; clinical risk; experience; gastrointestinal; genetic risk factor; genetic testing; genetic variant; genome wide association study; gut microbiome; hangover; health care service utilization; high risk; improved; innovation; insight; microbial; microbiome; microbiome analysis; microbiome composition; novel strategies; prediction algorithm; prevent; randomized trial; recruit; risk prediction; sample collection; sex; side effect; stool sample; treatment risk

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.

项目摘要 据报道，多达38％的癌症患者中等至重度恶心 尽管国际抗过敏指南，但取消化疗。化学疗法引起的恶心为 与生活质量较差，医疗保健利用率增加以及更高的护理成本相关。以前的 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，突出性 化学疗法，年龄，性别，运动病史，焦虑，饮酒），但风险预测算法基于 在这些因素上证明了改进的余地。研究人类基因组的最新方法 微生物组首次使我们能够对 化学疗法引起的恶心并发展更好的算法的病理生理。电流的目标 研究是通过整合检查化疗引起的化疗引起恶心的风险的理解 具有良好临床和个人危险因素的遗传和微生物组变量。我们将进行 化学疗法引起的恶心的第一个GWA，然后使用途径分析将结果置于功能上 语境。重大变体将与临床和个人因素合并为临床风险预测 算法。这项研究还将是最早检查肠道微生物组与 化学疗法引起的恶心。重要的是，这项研究是最早真正整合生物学的研究之一 临床和患者报告的数据以预测治疗毒性的风险。这项开创性的研究将 成为化学疗法其他副作用（例如认知障碍，疲劳和 周围神经病。当前研究的更新风险算法将公开可用， 将为未来的基于风险的抗癌症护理提供的随机试验提供信息。积极的结果将会 刺激风险算法与提供者警报识别患者的风险算法进入电子病历 有化疗引起的恶心的风险。在研究的前两年进行的微生物组分析 将提供有关其对化学疗法引起的恶心的贡献的快速知识。积极的结果将会 生成其他研究以确定微生物操纵是否可以防止化学疗法诱导 恶心。微生物组数据特别令人兴奋，因为它们专注于一个全新的机制 化学疗法相关的毒性。总而言之，这项严格，全面的研究提供了一个综合的新 化学疗法引起的恶心的方法，预计将显着提高我们对 病理生理学和这一重要临床问题的风险。