The Vanderbilt Urologic Infection Repository, a Resource for Personalized Clinical Discovery

范德比尔特泌尿感染存储库，个性化临床发现的资源

基本信息

批准号：
9913352
负责人：
Maria Hadjifrangiskou
金额：
$ 23.98万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/9913352
关键词：
Acinetobacter baumannii Age Anatomy Antibiotic susceptibility Bacteremia Bacteriuria Bioinformatics Biological CLIA certified Caring Catalogs Categories Catheters Clinical Clinical Data Clinical Microbiology Collection Communicable Diseases Communities Cystitis Data Databases Diagnostic Electronic Health Record Equilibrium Escherichia coli Ethics Foundations Genes Genetic Genetic Polymorphism Genitourinary system Genomics Genotype Genus staphylococcus Gestational Diabetes Health Heterogeneity Human Individual Infection Informatics Infrastructure Institution Knowledge Laboratories Light Link Logistics Machine Learning Medical Medical Informatics Medical Records Medical center Methods Microbial Genome Sequencing Microbiology Mining Modeling Molecular Organism Pathogenesis Pathology Patient Care Patients Phenotype Physicians Pilot Projects Precision Medicine Initiative Protocols documentation Public Domains Pyelonephritis Reporting Research Research Personnel Resource Informatics Resources Risk Factors Site Source Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Sterility Taxonomy Technology Therapeutic Uncertainty Urinary tract infection Urine Urology Uropathogen base biobank clinical practice clinical sequencing clinically actionable clinically relevant combat demographics evidence base genome sequencing genome wide association study genomic data high throughput technology interest microbial microbial genome pathogen pathogen genome phenome phenotypic data prognostic tool programs protein profiling repository sex symptomatology tool translational impact urologic whole genome young woman

项目摘要

SUMMARY - RESOURCE PROJECT Urinary tract infections (UTIs) represent not only one of the most prevalent urologic pathologies, but also one of the most diverse. With both traditional and emerging risk factors, commonly encountered clinical scenarios range from asymptomatic bacteriuria and uncomplicated cystitis to pyelonephritis, bacteremia, and outright urosepsis. The causative microbial agents likewise include a tremendous variety of opportunistic pathogens, with additional (and significant) genotypic/phenotypic diversity among individual strains of these species. On a molecular level, the host-pathogen factors that dictate the balance between urologic health and UTI remain incompletely defined. Generalized models of pathogenesis fail to account for commonly encountered nuances of real-world clinical practice, limiting the ability of physicians to provide care that is both evidence-based and personalized. To combat these challenges, we seek to create the Vanderbilt Urologic Infection Repository (VUIR): a massive (but de-identified) collection of patient-specific clinical information and paired microbial isolates, repurposed from our Medical Center's routine workflow of diagnostic urine cultures. As both an informatic and biologic resource, the VUIR will build on unique foundations that are already in place at Vanderbilt. These include our Synthetic Derivative, an anonymized mirror of our electronic health records, along with microVU, an initiative through which all sterile-site microbial isolates from our Diagnostic Laboratories are systematically retained for academic inquiry. We now propose to expand microVU activities to include Vanderbilt's formidable volume of urine cultures, linking the banked organisms (many thousand annually) to key searchable parameters from the source-patients (e.g. demographics, symptomatology, risk factors), as well as the broader body of data within the Synthetic Derivative. As a two-way bridge, the VUIR will create an opportunity to parse human phenomes in light of microbiologic results, while providing a tremendous quantity of wild-type microbial strains for downstream experimentation, all stratified by human UTI-phenotypes. One particularly exciting application of the VUIR involves genome-wide association studies (GWAS) that network genetic features of pathogens directly to clinical features of their hosts. In addition to building the VUIR, we will mine the repository to select underrepresented microbial targets for whole-genome sequencing. Through a machine-learning approach, the multi-partite genomic features of these strains will be correlated to their hosts' clinical parameters, with an emphasis on Escherichia coli and the global phenotypes of [1] symptomatic UTI and [2] asymptomatic bacteriuria (ASB). The microbial features that distinguish these phenomenological categories remain poorly defined—at least by the simplified metrics considered to date—although a rigorous molecular definition of UTI- vs-ASB would carry significant diagnostic value for physicians and pathogenetic value for investigators. In light of this complexity, we will utilize the VUIR to harmonize bioinformatic and medical informatic data across host and pathogen, as proof-of-concept for this program's broad utility in clinical/basic urology and allied fields.

摘要 - 资源项目尿路感染（UTI）不是最普遍的泌尿科病理之一最多样化的是传统和新兴风险因素，通常遇到临床场景从无症状的双肌尿和简单的细胞系统到肾盂肾炎，双骨气血症和蛋白酶彻底的尿。病因微生物剂同样包括各种各样的机会病原体，还有其他（和显着）在分子水平的单个菌株之间的基因型/表型多样性。决定泌尿科健康和UTI之间平衡的宿主病原因子仍然没有完全定义。广义的发病机理模型无法解释现实世界中通常遇到的细微差别练习，限制医生提供既是证据又基于个性化的护理的能力。应对挑战，我们试图创建范德比尔特泌尿外科感染存储库（Vuir）：（但被取消识别）收集患者特异性临床信息和成对的微生物分离株，从我们医疗中心的诊断尿文化工作流程中重新使用。和生物学资源，Vuir将建立在范德比尔特（Vanderbilt）的独特基础上包括我们的合成衍生物，元素健康记录的无反射镜，以及microvu，从我们的诊断实验室中的所有无菌位点微生物分离株都是系统的主动性保留进行学术询问。尿文化的数量，将存储的生物（每年数千）连接到关键搜索参数从源患者（例如人口统计学，症状，风险因素）以及更广泛的数据体在合成衍生物中，Vuir将创造出人类的机会根据微生物学结果的现象，同时提供大量的野生型微生物菌株为了进行下游实验，全部由人的UTI-Phenotypes分层。 Vuir涉及全基因组关联研究（GWAS），即病原体的网络遗传特征直接除了建造Vuir之外，我们的宿主的临床特征通过机器学习方法，对全基因组测序的微生物靶标的不足。这些菌株的多目标基因组特征将与宿主的临床参数相关，强调大肠杆菌和[1]症状UTI和[2]无症状的全球表型细菌（ASB）。定义的 - 至少是由迄今为止被认为的简化指标 - 非常严格的分子定义 VS-ASB将对医生具有显着的诊断价值，并在光线下具有致病价值。在这种复杂性中，我们将利用Vuir来协调主机的生物信息和医学信息数据和病原体，作为该计划的临床/基本泌尿外科和盟军领域的Brogragon的概念证明。