Systems biology frameworks to unravel mechanisms driving complex disorders

系统生物学框架揭示复杂疾病的驱动机制

• 批准号: 9888378
• 负责人: Vinay Varadan
• 金额: $ 17.17万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9888378
• 关键词: 3-Dimensional; Ablation; Achievement; Address; Automobile Driving; Award; Barrett Esophagus; Biological; Biological Models; Biomedical Research; Candidate Disease Gene; Cell Culture Techniques; Clinical; Clinical Management; Columnar Epithelium; Communities; Competence; Complex; DNA Methylation; Data; Data Set; Development; Diagnostic; Disease; Disease model; Electrical Engineering; Ephrins; Epithelial; Epithelium; Esophageal Adenocarcinoma; Esophageal Tissue; Esophagitis; Esophagus; Etiology; Event; Exhibits; Follow-Up Studies; Gastrointestinal Diseases; Gene Expression; Gland; Goals; Human; In Vitro; Individual; Inflammatory; Informatics; Injury; Interleukin-1 beta; Investigation; Knowledge; Lesion; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of esophagus; Maps; Measurement; Mentors; Modeling; Molecular; Molecular Abnormality; Molecular Analysis; Molecular Genetics; Molecular Profiling; Mucous Membrane; Pathogenesis; Pathogenicity; Pathway interactions; Patients; Phenotype; Populations at Risk; Pre-Clinical Model; Prevention strategy; Process; Prognostic Marker; Proliferating; Proteins; Public Health; Recurrence; Research; Research Activity; Risk; Risk Factors; Sampling; Scientist; Signal Pathway; Signal Transduction; Specificity; Squamous Epithelium; Stomach; System; Systems Analysis; Systems Biology; Techniques; Testing; Time; Tissue Sample; Tissues; Training; Training Programs; Transgenic Mice; Translational Research; Universities; Validation; base; candidate identification; candidate marker; career; cohort; complex biological systems; computer framework; design; diagnostic biomarker; evidence base; experience; genetic manipulation; genome-wide; high risk; human disease; in vivo Model; injury and repair; intelligent algorithm; interest; mouse model; multiple omics; network models; novel; novel diagnostics; patient population; prevent; resistance mechanism; standard of care; stem cells; success; therapeutic target; transcriptome; transcriptomics; translational scientist; translational study

Project Summary/Abstract This application proposes a training program to integrate the PI, Dr. Varadan's previous research efforts in informatics and machine learning into investigations pertaining to the etiology and progression of Barrett's Esophagus, a gastrointestinal disorder of significant public health interest. Much of Dr. Varadan's previous research has involved developing intelligent algorithms and informatics approaches to decode the interconnections within complex biological systems, with only a basic understanding of the clinical needs and complexities involved in translational research. The proposed project would provide a broad and in-depth mentored experience focused on clinical and biological aspects of Barrett's Esophagus, as well as added knowledge in the use of preclinical model systems to investigate biological mechanisms. The overall goal is to expand the PI's experience and training in the design and conduct of translational studies focused on gastrointestinal (GI) diseases. This objective will be achieved through a combination of didactic and research activities conducted under an exceptional mentoring team of translational researchers at Case Western Reserve University, spanning achievements across clinical management of GI disorders, molecular genetics and inflammatory processes associated with diseases of the gut. Accordingly, this proposal leverages Dr. Varadan's computational background to address an urgent and unmet need within the biomedical research community to develop reliable analytic approaches that can quantify signaling network activities in individual biological samples by integrating multi-omics measurements. We recently conceived a systems biology computational framework, InFlo, which integrates molecular profiling data to decode the functional states of cellular/molecular processes underpinning complex human diseases. Barrett's esophagus is one such complex disease gaining increasing importance to public health, as it is the known precursor to the deadly cancer, esophageal adenocarcinoma. Given that the mechanisms underlying the etiology and pathogenesis of Barrett's Esophagus remain elusive, a major objective of this proposal is to employ the InFlo framework combined molecular profiles derived from primary tissue cohorts, in vitro and in vivo model systems to establish the molecular roadmap of BE pathogenesis and disease recurrence, thus elucidating unifying mechanisms underlying this disease. This systems biology approach would enable the development of evidence-based, diagnostic/prognostic biomarkers for Barrett's esophagus and inform preventive strategies within at-risk populations.

项目摘要/摘要 该申请提出了一项培训计划，以整合PI，瓦拉丹博士先前的研究工作 信息学和机器学习与巴雷特的病因和进展有关的调查 食道，一种具有重大公共健康兴趣的胃肠道疾病。瓦拉丹博士以前的大部分 研究涉及开发智能算法和信息学方法来解码 复杂的生物系统中的互连，只有对临床需求的基本了解和 转化研究涉及的复杂性。拟议的项目将提供广泛而深入的项目 指导的经验着重于巴雷特食管的临床和生物学方面，并增加了 使用临床前模型系统来研究生物学机制的知识。总体目标是 扩大PI的经验和培训在翻译研究的设计和进行的培训。 胃肠道（GI）疾病。这一目标将通过教学和研究的结合来实现 在Case Western的转化研究人员的杰出指导团队下进行的活动 储备大学，跨越胃肠道疾病临床管理的成就，分子遗传学 和与肠道疾病有关的炎症过程。因此，该建议利用博士。 瓦拉丹的计算背景，以解决生物医学研究中的紧急和未满足的需求 社区开发可靠的分析方法，可以量化个人信号网络活动 通过整合多词的测量来进行生物样品。我们最近构思了系统生物学 计算框架，Inflo，它集成了分子分析数据以解码 基于复杂人类疾病的细胞/分子过程。巴雷特的食道是这样复杂的 疾病对公共卫生的重要性越来越重要，因为它是致命癌症的已知先驱， 食管腺癌。鉴于Barrett的病因学和发病机理的基础机制 食道仍然难以捉摸，该提案的主要目的是采用INFLO框架合并 源自原代组织同类群体，体外和体内模型系统的分子剖面，以建立 是发病机理和疾病复发的分子路线图，从而阐明了统一机制 潜在的这种疾病。该系统生物学方法将使循证基于证据的发展， Barrett食管的诊断/预后生物标志物，并为处于风险的预防策略提供信息 人群。