Computational Characterization of Environmental Enteropathy

项目摘要/摘要 在低收入和中等收入国家(LMIC)，营养不良困扰着20%的5岁以下儿童，是一种 死亡的主要危险因素。儿童的线性发育障碍(或发育迟缓)与不可逆转密切相关 身体和认知缺陷，对发展具有深远影响。儿童发育迟缓的常见原因 LMICs是一种环境肠病(EE)，也与口服疫苗减少有关 免疫原性。到目前为止，还没有普遍接受的、清晰的诊断算法或非侵入性的 EE的生物标志物使这成为一个关键的优先事项。在这份K23导师职业发展奖的申请中， Sana Syed博士是一位在弗吉尼亚大学接受高级营养学培训的儿科胃肠病专家， 建议1)开发和验证深度学习网络来识别EE和 2)关联深度学习网络识别的区分EE的深度学习网络 肠道组织的临床表型、肠道屏障和吸收的测量以及胆汁酸 去共轭，以及3)使用深度学习网络计算方法来识别区分多词 EE与乳糜泻的类型。这项工作将在正在进行的出生队列范围内进行 巴基斯坦环境肠病研究(SEAM)。赛义德博士提出了一项职业发展计划 包括指导、实地调查、课程、出版物和临床时间，这些都将使她成为 独立的内科医生-科学家，在使用计算经济学和 用图像方法阐明发育迟缓途径的生物学机制并在鉴定新的和 治疗EE的有效方法。

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.