Combinatory Effects of Genetic Variants in Eosinophilic Esophagitis

项目摘要/摘要 嗜酸性食管炎(EoE)是一种慢性变态反应性炎症性食管炎，临床特征为 食道功能障碍(呕吐、疼痛、吞咽困难和食物嵌塞)； 与屏障功能受损相关的嗜酸性粒细胞增多、上皮细胞增生和细胞间隙扩张； 以及高度的遗传性。大多数遗传学研究都集中在分析常见的遗传变异上。 通过全基因组关联研究(GWAS)，有证据表明Calain 14(CAPN14)和胸腺 基质淋巴生成素(TSLP)，两者均由同一相关细胞类型食道显著表达 上皮细胞。最近，我们对EoE多基因家族进行了全外显子组测序(WES)和 确定了一组与EoE有关的罕见遗传变异。尽管最近的研究进展提供了证据 对于EoE遗传病因学与遗传变异有关，单独测试单个遗传变异不会 考虑一下基因之间复杂的相互作用格局。我们的中心假设是EoE结果的一个子集 来自同一生物路径中的多个变种的组合。这项研究将从统计和 通过实验评估组合效应以及遗传变异对EoE和Will的影响 利用最新开发的创新技术，根据生物途径开发风险评分，以预测EoE (例如，WES、GWAS、RNA-SEQ、CHIP-SEQ和体外疾病建模[食道器官和器官类型 文化]))。在随附的建议书中，我们概述了一套综合的多学科研究，以及 为评估EoE之间的组合效应的影响提供必要的统计和实验支持 基因变异。在目标1中，我们将检验这样的假设，即EoE的风险将通过组合 稀有-稀有变种、稀有-常见变种/单核苷酸多态性和生物途径。确定对风险的影响 对于EoE，我们将在变量、基因和途径水平上联合分析组合效应。在目标2中，我们将测试 假设DSP和PPL罕见变异对食道屏障功能和食道屏障功能具有联合作用 基因/蛋白质表达。为了探索运行机制，我们将检查这些变体是否具有 使用体外、三维培养模型的组合效应(例如，食道器官、器官类型 文化)。最后，在目标3中，我们将检验这样一个假设，即遗传和基因组数据的合成 导致能够预测谁有患EoE的风险、其疾病特征和/或对治疗的反应。 目标3将作为未来R01应用程序的基础，以进行机制研究，以表征 融合基因/通路的影响及进一步验证和探索其临床应用的病例对照研究 风险分值。这项拟议的研究将解决NIH最近一次研讨会概述的未得到满足的医疗需求， 提供对疾病遗传机制的洞察，从而潜在地有助于个性化医疗， 特别是加强筛查或预防性治疗的应用。

PROJECT SUMMARY/ABSTRACT Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory esophageal disorder characterized clinically by esophageal dysfunction (vomiting, pain, dysphagia, and food impaction); histologically by esophageal eosinophilia, epithelial hyperplasia, and dilated intercellular spaces associated with impaired barrier function; and by a high degree of heritability. Most genetic studies have focused on analyzing common genetic variants by genome-wide association studies (GWAS), with evidence implicating the calpain 14 (CAPN14) and thymic stromal lymphopoietin (TSLP), which are notably both expressed by the same relevant cell type, esophageal epithelial cells. Recently, we have performed whole-exome sequencing (WES) on EoE multiplex families and identified a set of rare genetic variants involved in EoE. Though recent research progress provides the evidence for EoE genetic etiology being linked to genetic variants, testing single genetic variants separately does not consider the complex interaction landscape of genes. Our central hypothesis is that a subset of EoE results from the combination of multiple variants in the same biological pathways. This study will statistically and experimentally evaluate combinatory effects and how the genetic variants are contributing to EoE and will develop risk scores based on the biological pathways to predict EoE by using recently developed innovations (e.g., WES, GWAS, RNA-seq, ChIP-seq, and ex vivo disease modeling [esophageal organoids and organotypic culture]). In the attached proposal, we have outlined an integrated set of multidisciplinary studies with the necessary statistical and experimental support to evaluate the impact of the combinatory effects among EoE genetic variants. In Aim 1, we will test the hypothesis that the risk for EoE will be increased by the combinatory rare-rare variants, rare-common variants/SNPs, and biological pathways. To determine the impact on the risk for EoE, we will jointly analyze combinatory effects at variant, gene, and pathway levels. In Aim 2, we will test the hypothesis that DSP and PPL rare variants have combinatory effects on esophageal barrier functions and gene/protein expression. To explore the operational mechanisms, we will examine whether these variants have combinatory effects using ex vivo, 3-dimensional culture models (e.g., esophageal organoids, organotypic culture) of EoE. Finally, in Aim 3, we will test the hypothesis that the synthesis of genetic and genomic data will lead to the ability to predict who is at risk of developing EoE, its disease features, and/or response to therapy. Aim 3 will serve as the foundation for a future R01 application to conduct a mechanistic study to characterize the impact of convergent genes/pathways and a case-control study to further validate and explore the clinical utility of risk scores. The proposed study will address an unmet medical need as outlined by a recent NIH workshop, providing insight into disease genetic mechanisms and thereby potentially contributing to personalized medicine, especially the application of enhanced screening or preventive therapies.