Redefining C.difficile patient outcomes through network medicine

通过网络医学重新定义艰难梭菌患者的治疗结果

• 批准号: 10722290
• 负责人: Javier Andres Villafuerte Galvez
• 金额: $ 19.12万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10722290
• 关键词: Address; Admission activity; Advisory Committees; Asthma; Award; Awareness; Bacteria; Bioinformatics; Biological; Biological Markers; Biological Process; Biology; Blinded; Blood; Categories; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; Classification; Clinical; Clinical Research; Clostridium difficile; Colectomy; Colitis; Computing Methodologies; Critical Care; Data; Diagnosis; Diagnostic; Diarrhea; Digestive System Disorders; Disease; Educational Curriculum; Environment; Failure; Feces; Fellowship; Focus Groups; Foundations; Gastroenterologist; Goals; Grant; Grouping; Human; Immune; Immune response; Indolent; Infection; Inflammatory; Inflammatory Bowel Diseases; Israel; K-Series Research Career Programs; Knowledge; Life; Machine Learning; Mass Spectrum Analysis; Measures; Mediating; Medical center; Medicine; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Metabolic; Methodology; Methods; Modeling; Modernization; Outcome; Parkinson Disease; Pathway interactions; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Pattern; Phenotype; Postdoctoral Fellow; Practice Management; Public Health; Quality of Care; Quality of life; Recurrence; Recurrent disease; Research; Resolution; Risk; Sampling; Severities; Stratification; Symptoms; Therapeutic; Time; Training; Translational Research; Vertebral column; Writing; antitoxin; biobank; bioinformatics tool; biomarker identification; biomedical informatics; career; career development; catalyst; clinical predictors; clinical translation; clinically relevant; cohort; cytokine; design; diagnostic algorithm; drug development; drug quality; effective therapy; experience; fungus; gut inflammation; gut microbiome; improved; insight; instructor; machine learning algorithm; machine learning model; medical schools; microbial; mortality risk; novel; novel therapeutics; pathogen; patient advocacy group; patient oriented; predictive marker; prognostication; programs; prospective; recruit; skills; standard of care; tool; treatment response

PROJECT SUMMARY From asymptomatic carriage to life-threatening diarrhea and colitis, C.difficile interacts with humans through a range of phenotypes. The mechanisms underlying this spectrum are incompletely understood. Despite progress in the understanding of the disease and the advent of newer therapies, patient outcomes such as failure to respond promptly to therapy (~20%), recurrence (~21%), death, colectomy or need for critical care (severe outcomes, ~3 %) remain common. As patient-centered outcomes (PCOs) take center stage in clinical research, C.difficile Infection (CDI) will not be an exception. This Career Development proposal is based on the central hypothesis that integrated analysis of immune, microbial and metabolic data (IMM/d) from new and existing cohorts of CDI patients and carriers, by identifying biological markers and pathways, can transform patient outcomes (especially PCOs) and re-categorize the CDI to colonization continuum (CDI/cc). Javier A. Villafuerte Gálvez [JVG], MD is an Instructor at Harvard Medical School (HMS) and a gastroenterologist subspecialized in immune-mediated digestive disease at Beth Israel Deaconess Medical Center (BIDMC). He has gained substantial experience in clinical and translational research during his post-doctoral and T32 fellowships while proving commitment to a patient centered research career. This Award will provide the applicant with the opportunity to develop quantitative analysis skill while taking full advantage of mentored research opportunities to address knowledge gaps in prediction, classification and pathobiology of CDI. Dr. Ciarán P. Kelly, an expert in CDI and bowel inflammation will serve as mentor, along with Dr. Yang-Yu Liu, an expert in bioinformatics studying the dynamics of the human gut microbiome who will be co-mentor. The Advisory Committee composed by CDI and methodological experts (Drs. Garey, Pollock, Gerszten and Dubberke) will confer regularly with the applicant to evaluate progress. The K23 award will aid JVG to establish an independent research program applying bioinformatics tools to unmet needs in immune-digestive disorders, with CDI as a first model. The backbone of the curriculum will be the Master in Biomedical Informatics at HMS. Grant writing training and support through Harvard Catalyst will be critical. The first aim of this project is to identify fecal IMM/d biological markers and pathways at the time of CDI diagnosis associated with severe outcomes, recurrence and disease trajectory. Informed by this, we will recruit a new CDI cohort to measure PCOs (symptoms, quality of life) while collecting biospecimens, in order to identify IMM/d biological markers and pathways predicting and underlying PCOs. Finally, with IMM/d as substrate to machine learning algorithms blinded to standard diagnostics, we will re-categorize patients in the CDI/cc in new functional disease groupings. This research will answer critical questions in CDI diagnostics, prognostication and pathobiology while placing PCOs at the forefront, generating foundational data for R-level proposals.

项目概要 从无症状携带到危及生命的腹泻和结肠炎，艰难梭菌通过以下方式与人类相互作用： 表型范围。这一谱系背后的机制尚不完全清楚。尽管取得了进展 在对疾病的了解和新疗法的出现中，患者的结果，例如未能 对治疗（~20%）、复发（~21%）、死亡、结肠切除术或需要重症监护（严重 结果，~3%）仍然很常见。随着以患者为中心的结果 (PCO) 成为临床研究的中心舞台， 艰难梭菌感染 (CDI) 也不例外。本职业发展建议基于中央 假设对新的和现有的免疫、微生物和代谢数据（IMM/d）进行综合分析 通过识别生物标志物和途径，CDI 患者和携带者群体可以改变患者的生活方式 结果（尤其是 PCO）并将 CDI 重新分类为定植连续体 (CDI/cc)。哈维尔·维拉富尔特 Gálvez [JVG] 医学博士是哈佛医学院 (HMS) 的讲师，也是一位胃肠病学家，专攻以下领域 贝斯以色列女执事医疗中心 (BIDMC) 的免疫介导消化系统疾病。他已经获得了 在博士后和 T32 奖学金期间，他在临床和转化研究方面积累了丰富的经验 证明对以患者为中心的研究事业的承诺。 该奖项将为申请人提供发展定量分析技能的机会，同时充分利用 利用指导研究机会来解决预测、分类和预测方面的知识差距 CDI 的病理学。 CDI 和肠道炎症专家 Ciarán P. Kelly 博士将担任导师 与研究人类肠道微生物群动态的生物信息学专家 Yang-Yu Liu 博士一起 成为共同导师。咨询委员会由 CDI 和方法学专家（Garey 博士、Pollock 博士、 Gerszten 和 Dubberke）将定期与申请人协商以评估进展情况。 K23 奖将帮助 JVG 建立一个独立的研究项目，应用生物信息学工具来解决未满足的问题 免疫消化疾病的需求，以 CDI 作为第一个模型。课程的支柱将是 HMS 生物医学信息学硕士。通过哈佛催化剂 (Harvard Catalyst) 提供的资助写作培训和支持将 批判的。该项目的首要目标是确定 CDI 时粪便 IMM/d 生物标志物和途径 与严重后果、复发和疾病轨迹相关的诊断。受此通知，我们将招募 一个新的 CDI 队列在收集生物样本时测量 PCO（症状、生活质量），以便识别 IMM/d 生物标志物和预测 PCO 的途径。最后，以IMM/d为底物 机器学习算法对标准诊断视而不见，我们将在新的 CDI/cc 中对患者进行重新分类 功能性疾病分组。这项研究将回答 CDI 诊断、预测和 病理生物学，同时将 PCO 置于最前沿，为 R 级提案生成基础数据。

项目成果

Editorial: Peering through the fog-New tools to assess neurocognitive symptoms in coeliac disease.

社论：透过迷雾窥视——评估乳糜泻神经认知症状的新工具。

• DOI: 10.1111/apt.17979
• 发表时间: 2024
• 期刊: Alimentary pharmacology & therapeutics
• 影响因子: 7.6
• 作者: VillafuerteGálvez,JavierA;Leffler,DanielA
• 通讯作者: Leffler,DanielA