Paneth cell phenotype as a predictive biomarker for ulcerative colitis

潘氏细胞表型作为溃疡性结肠炎的预测生物标志物

• 批准号: 10119843
• 负责人: Ta-Chiang Liu
• 金额: $ 38.65万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-24 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10119843
• 关键词: Affect; Anastomosis - action; Anus; Biological; Biological Markers; Caring; Cell physiology; Cellular Morphology; Chronic; Classification; Clinical; Clinical Trials; Colectomy; Complex; Cost Measures; Crohn' s disease; Data; Development; Disease; Disease Management; Disease remission; Economic Burden; Epithelial Cells; Excision; Genetic Markers; Genetic Predisposition to Disease; Goals; Grant; Homeostasis; Ileal Reservoirs; Image; Inflammatory; Inflammatory Bowel Diseases; Interobserver Variability; Longterm Follow-up; Manuals; Medical Genetics; Medical center; Methods; Molecular; Molecular Target; Monitor; Morphology; Mucous Membrane; Natural History; Natural Immunity; Observer Variation; Operative Surgical Procedures; Paneth Cells; Pathologist; Pathology; Pathway interactions; Patients; Phenotype; Positioning Attribute; Postoperative Period; Pouchitis; Prevalence; Process; Prognostic Marker; Public Health; Reproducibility; Research; Research Personnel; Role; Sampling; Serum; Serum Markers; Small Intestines; Specimen; Standardization; Subgroup; Surgical Pathology; Testing; Therapeutic; Time; Tissues; Translating; Ulcerative Colitis; Universities; Washington; Work; aggressive therapy; analysis pipeline; base; cell type; clinical practice; clinically relevant; cohort; combinatorial; deep learning; deep learning algorithm; dysbiosis; experience; experimental study; gastrointestinal; gene environment interaction; genetic association; improved; innate immune function; innovation; insight; intestinal epithelium; novel; novel strategies; outcome forecast; outcome prediction; patient stratification; personalized medicine; phenotypic biomarker; predictive marker; prognostic; treatment strategy

ABSTRACT One of the challenges for the management of ulcerative colitis (UC; a subtype of inflammatory bowel disease) is the lacking of a predictive biomarker that can help stratify patients for personalized treatment strategies. We have previously shown that in Crohn’s disease (CD; another subtype of inflammatory bowel disease), the morphologic phenotype of small intestinal Paneth cells readily predicts outcome in post-surgical CD patients. Given the shared genetic etiology and clinical features between CD and UC, we hypothesize that Paneth cell phenotype will also predict outcome in UC. Our long-term goal is to define the clinical indications of inflammatory bowel disease of which Paneth cell phenotype can predict outcome. The objective of this grant is to determine to the extent of which Paneth cell phenotype predicts development of ileal complications in UC. The central hypothesis is that in UC patients undergoing total colectomy and ileal pouch anal anastomosis (IPAA), the Paneth cell phenotype obtained at time of colectomy will predict development of pouchitis and de novo CD in the ileal pouch. Our rationale is that Paneth cell phenotype will offer better outcome prediction over current practice. Our specific aims will test the following hypotheses: (Aim1) Paneth cell phenotype correlates with ileal complications in UC patients with IPAA; (Aim 2) Deep learning will reduce observer variation and enhance rigor and reproducibility of Paneth cell phenotype analysis in surgical pathology specimens, and also identify novel clinical factors that correlate with Paneth cell function; (Aim 3) Serum markers that correlate with Paneth cell phenotype could be used to predict outcome in UC. Upon conclusion, we will understand the role for Paneth cell function in modulating disease course in IBD. This contribution is significant since it will establish Paneth cell phenotype as a critical predictive biomarker for IBD. The proposed research is innovative because we use state-of-the-art deep learning approach to build an imaging analysis pipeline, and to identify novel clinical factors that affect Paneth cell functions. Identifying how epithelial cells with innate immune function affect disease course will provide insight into other inflammatory disorders.

抽象的 溃疡性结肠炎治疗的挑战之一（UC；炎症性肠病的亚型） 是缺乏预测性生物标志物，可以帮助将患者分层以制定个性化治疗策略。我们 以前表明，在克罗恩病（CD；炎症性肠病的另一种亚型）中， 小肠道细胞的形态表型很容易预测术后CD患者的结局。 鉴于CD和UC之间的共享遗传病因和临床特征，我们假设Paneth Cell 表型还将预测UC的结果。我们的长期目标是定义 Paneth细胞表型的炎症性肠病可以预测结果。这笔赠款的目的是 确定在哪种泛池表型预测UC中回肠并发症的发展的程度。 中心假设是，在接受总收集术和回肠袋肛门吻合的UC患者中 （ipaa），在收集术时获得的泛池细胞表型将预测Pouchitis和de的发展 Novo CD中的伊利尔小袋。我们的理由是，Paneth Cell表型将提供更好的结果预测 当前的练习。我们的具体目的将检验以下假设：（ AIM1）Paneth细胞表型相关 IPAA患者的回肠并发症； （目标2）深度学习将减少观察者的变化和 增强Paneth细胞表型分析在手术病理标本中的严格性和可重复性，也可以 确定与Paneth细胞功能相关的新型临床因素； （目标3）与 Paneth细胞表型可用于预测UC的结果。总结一下，我们将了解角色 对于Paneth细胞功能，在调节IBD的疾病过程中。这种贡献很重要，因为它将 建立Paneth细胞表型作为IBD的关键预测生物标志物。拟议的研究是创新的 因为我们使用最先进的深度学习方法来构建成像分析管道，并确定 影响Paneth细胞功能的新型临床因素。确定具有先天免疫的上皮细胞 功能影响疾病课程将为其他炎症性疾病提供洞察力。