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.

项目摘要 从不对称的马车到威胁生命的腹泻和结肠炎，缺乏人类通过A与人相互作用 表型范围。该频谱的基础机制尚不完全理解。尽管进展 在理解疾病和新疗法的冒险中，患者结果，例如无法 迅速对治疗（约20％），复发（约21％），死亡，收集术或重症监护需要（严重 结果，〜3％）仍然很普遍。随着以患者为中心的结果（PCOS）在临床研究中成为中心阶段， C.缺乏感染（CDI）将不是例外。该职业发展建议基于中央 假设是对新和现有的免疫，微生物和代谢数据（IMM/D）的综合分析 通过识别生物学标记和途径，CDI患者和载体的同类人群可以改变患者 结果（尤其是PCOS），并将CDI重新分类为定殖连续性（CDI/CC）。哈维尔·A·维拉弗特 Gálvez[JVG]，医学博士是哈佛医学院（HMS）的讲师，胃肠病学家在 贝丝以色列执事医疗中心（BIDMC）免疫介导的消化疾病。他有了 在他的博士后和T32奖学金期间，在临床和翻译研究方面有丰富的经验 证明对以患者为中心的研究职业的承诺。 该奖项将为申请人提供开发定量分析技能的机会 有指导的研究机会的优势来解决预测，分类和 CDI病理生物学。 CDI和排便专家CiaránP。Kelly博士将担任导师 与杨刘博士一起研究了人类肠道微生物组动力学的生物信息学专家 成为院。由CDI和方法论专家组成的咨询委员会（Garey博士，Pollock， Gerszten和Dubberke）将定期与适用以评估进度的适用。 K23奖将帮助JVG建立一项独立研究计划，该计划应用生物信息学工具以未满足 免疫消化疾病的需求，将CDI作为第一个模型。课程的骨干将是 HMS生物医学信息学硕士。通过哈佛催化剂的授予写作培训和支持将是 批判的。该项目的第一个目的是在CDI时识别粪便IMM/D生物学标记和途径 与严重结果，复发和疾病轨迹相关的诊断。因此，我们将招募 收集生物测量的新的CDI队列，用于测量PCOS（症状，生活质量），以识别 IMM/D生物标记和途径预测和潜在的PCOS。最后，以imm/d作为基板到 机器学习算法对标准诊断视而不见，我们将在新的CDI/CC中重新列为新的患者 功能性疾病分组。这项研究将回答CDI诊断，提示和 病理生物学将PCOS放在最前沿的同时，为R级建议生成基础数据。

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