Computational Characterization of Environmental Enteropathy

环境性肠病的计算表征

• 批准号: 10627838
• 负责人: Sana Syed
• 金额: $ 19.26万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10627838
• 关键词: 5 year old; Address; Age; Antigens; Asia; Bangladeshi; Bile Acids; Biochemical; Biological; Biological Markers; Biopsy; Birth; Caring; Celiac Disease; Cessation of life; Child; Childhood; Chronic; Classification; Clinical; Clinical Markers; Clinical Research; Cognitive deficits; Cohort Studies; Collaborations; Computing Methodologies; Data Science; Detection; Development; Development Plans; Diagnosis; Diagnostic; Duodenum; Environmental Risk Factor; Etiology; Exhibits; Exposure to; Failure; Foundations; Funding; Gastroenterologist; Genetic Transcription; Gluten; Goals; Growth; Health; Histologic; Histology; Histopathology; Human Pathology; Image; Impairment; Inflammation; Injury; Intestinal permeability; Intestines; K-Series Research Career Programs; Knowledge; Lactulose; Lamina Propria; Lead; Length; Link; Lymphocytosis; MS4A1 gene; Malnutrition; Measurement; Measures; Mediating; Mentors; Mentorship; Metabolic; Milieu Therapy; Morphology; Mucositis; Multiomic Data; Neurocognitive; Pakistan; Pathogenesis; Pathologic; Pathway interactions; Pattern; Physicians; Population; Populations at Risk; Prevalence; Publications; Research; Resource-limited setting; Rhamnose; Risk Factors; Role; Scientist; Severities; Small Intestines; Standardization; Structure; System; Time; Tissues; Training; Translational Research; Universities; Validation; Villous; Villous Atrophy; Virginia; Visual; Work; absorption; career; career development; circulating biomarkers; clinical phenotype; cohort; deep learning; diagnostic algorithm; dietary; disorder control; effective intervention; effective therapy; enteric pathogen; epithelium regeneration; genetic risk factor; imaging approach; improved; intraepithelial; low and middle-income countries; microbiome; mortality; multiple omics; novel; novel marker; novel therapeutics; nutrient absorption; nutrition; oral vaccine; patient oriented; socioeconomics; systemic inflammatory response; tissue injury; transcriptome; urinary; vaccine immunogenicity; 5 year old; Address; Age; Antigens; Asia; Bangladeshi; Bile Acids; Biochemical; Biological; Biological Markers; Biopsy; Birth; Caring; Celiac Disease; Cessation of life; Child; Childhood; Chronic; Classification; Clinical; Clinical Markers; Clinical Research; Cognitive deficits; Cohort Studies; Collaborations; Computing Methodologies; Data Science; Detection; Development; Development Plans; Diagnosis; Diagnostic; Duodenum; Environmental Risk Factor; Etiology; Exhibits; Exposure to; Failure; Foundations; Funding; Gastroenterologist; Genetic Transcription; Gluten; Goals; Growth; Health; Histologic; Histology; Histopathology; Human Pathology; Image; Impairment; Inflammation; Injury; Intestinal permeability; Intestines; K-Series Research Career Programs; Knowledge; Lactulose; Lamina Propria; Lead; Length; Link; Lymphocytosis; MS4A1 gene; Malnutrition; Measurement; Measures; Mediating; Mentors; Mentorship; Metabolic; Milieu Therapy; Morphology; Mucositis; Multiomic Data; Neurocognitive; Pakistan; Pathogenesis; Pathologic; Pathway interactions; Pattern; Physicians; Population; Populations at Risk; Prevalence; Publications; Research; Resource-limited setting; Rhamnose; Risk Factors; Role; Scientist; Severities; Small Intestines; Standardization; Structure; System; Time; Tissues; Training; Translational Research; Universities; Validation; Villous; Villous Atrophy; Virginia; Visual; Work; absorption; career; career development; circulating biomarkers; clinical phenotype; cohort; deep learning; diagnostic algorithm; dietary; disorder control; effective intervention; effective therapy; enteric pathogen; epithelium regeneration; genetic risk factor; imaging approach; improved; intraepithelial; low and middle-income countries; microbiome; mortality; multiple omics; novel; novel marker; novel therapeutics; nutrient absorption; nutrition; oral vaccine; patient oriented; socioeconomics; systemic inflammatory response; tissue injury; transcriptome; urinary; vaccine immunogenicity

PROJECT SUMMARY/ABSTRACT Undernutrition afflicts 20% of children < 5 years of age in low- and middle-income countries (LMICs) and is a major risk factor for mortality. Linear growth failure (or stunting) in children is tightly linked to irreversible physical and cognitive deficits, with profound implications for development. A common cause of stunting in LMICs is Environmental Enteropathy (EE) which has also been linked to decreased oral vaccine immunogenicity. To date, there are no universally accepted, clear diagnostic algorithms or non-invasive biomarkers for EE making this a critical priority. In this K23 Mentored Career Development Award application, Dr. Sana Syed, a Pediatric Gastroenterologist with advanced training in Nutrition at the University of Virginia, proposes to 1) Develop and validate a Deep Learning Net to identify morphological features of EE versus celiac and healthy small intestinal tissue, 2) correlate the Deep Learning Net identified distinguishing EE intestinal tissue findings with clinical phenotype, measures of gut barrier and absorption, and bile acid deconjugation, and 3) Use a Deep Learning Net computational approach to identify distinguishing multiomic patterns of EE versus celiac disease. This work will be carried out in the context of an ongoing birth cohort study of environmental enteropathy in Pakistan (SEEM). Dr. Syed proposes a career development plan which includes mentorship, fieldwork, coursework, publications, and clinical time that will situate her as an independent physician-scientist with expertise in translational research employing computational `omics and image approaches to elucidate biologic mechanisms of stunting pathways and in identification of novel and effective therapies for EE.

项目摘要/摘要 在低收入和中等收入国家（LMIC）的儿童中，营养不良遭受了20％的儿童 死亡率的主要风险因素。儿童的线性生长失败（或发育迟缓）与不可逆 身体和认知缺陷，对发展具有深远的影响。发育迟缓的常见原因 LMIC是环境肠病（EE），它也与口服疫苗减少有关 免疫原性。迄今为止，还没有普遍接受的，清晰的诊断算法或无创的 EE的生物标志物将其成为关键的优先事项。在这个K23指导的职业发展奖应用程序中， Sana Syed博士，儿科胃肠病学家，在弗吉尼亚大学接受营养高级培训， 提议1）开发和验证深度学习网络以识别EE与EE的形态特征 乳糜泻和健康的小肠组织，2）与鉴定EE的深度学习网络相关 具有临床表型的肠道组织发现，肠道屏障和吸收的度量以及胆汁酸 deconjugation和3）使用深度学习的净计算方法来识别区分多组分 EE与腹腔疾病的模式。这项工作将在正在进行的出生队列的背景下进行 巴基斯坦环境肠病的研究（See）。 Syed博士提出了一项职业发展计划 包括指导，实地调查，课程工作，出版物和临床时间，将她作为一个 独立医师科学家在翻译研究方面具有专业知识，采用计算`omics和omics和 图像方法阐明了发育途径的生物学机制以及新颖和新颖的鉴定 EE的有效疗法。