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

基本信息

批准号：
10269023
负责人：
Ta-Chiang Liu
金额：
$ 36.23万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
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/10269023
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&apos s disease Data Development Disease Disease Management Disease remission Economic Burden Epithelial Cells Excision Genetic Markers Genetic Predisposition to Disease Goals Grant 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 Prognosis 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 gut homeostasis improved innate immune function innovation insight intestinal epithelium novel novel strategies outcome prediction patient stratification personalized medicine phenotypic biomarker predictive marker prognostic treatment strategy

项目摘要

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（UC；炎症性肠病的一种亚型）治疗面临的挑战之一缺乏可以帮助对患者进行个性化治疗策略分层的预测生物标志物。之前已经表明，在克罗恩病（CD；炎症性肠病的另一种亚型）中，小肠潘氏细胞的形态表型很容易预测 CD 患者术后的结果。鉴于 CD 和 UC 之间共有的遗传病因和临床特征，我们勇敢地认为潘氏细胞表型还将预测 UC 的结果。我们的长期目标是确定 UC 的临床适应症。潘氏细胞表型可以预测炎症性肠病的结果。这项资助的目的是。确定潘氏细胞表型在多大程度上预测 UC 回肠并发症的发生。中心假设是，在接受全结肠切除术和回肠贮袋肛门吻合术的 UC 患者中（IPAA），结肠切除术时获得的潘氏细胞表型将预测储袋炎的发展和去我们的理由是潘氏细胞表型将提供更好的结果预测。我们的具体目标将检验以下假设：（目标1）潘氏细胞表型相关。（目标 2）深度学习将减少观察者的变化并提高手术病理标本中潘氏细胞表型分析的严谨性和重现性，并且确定与潘氏细胞功能相关的新临床因素；（目标 3）与相关的血清标记物潘氏细胞表型可用于预测 UC 的结果。根据结论，我们将了解其作用。潘氏细胞在调节 IBD 疾病过程中的功能这一贡献非常重要，因为它将建立潘氏细胞表型作为 IBD 的关键预测生物标志物这项研究具有创新性。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，并识别影响潘氏细胞功能的新临床因素确定上皮细胞如何具有先天免疫。功能影响疾病进程将提供对其他炎症性疾病的深入了解。