The gut microbiome, host genetics, and risk for inflammatory bowel disease

 描述(申请人提供)：炎症性肠病(IBD)是一种严重的、不可治愈的胃肠道疾病，以慢性炎症为特征，严重影响患者的生活质量。症状可能包括腹痛或不适、发烧、腹泻和便血。多达25%的患者经历了涉及心脏、肺、眼睛、胰腺、骨骼或关节的其他症状。美国和加拿大约有150万人患有IBD，这两个国家的IBD发病率在全球名列前茅，每年估计有17,000-93,000例新诊断病例。重要的是，发病的高峰年龄是青壮年，7%-20%的诊断是儿科的。由于个人需要血液测试来监测疾病、监测结肠镜检查、药物治疗症状，通常还需要手术，因此IBD对医疗保健系统有很大影响。最近对遗传数据的荟萃分析显示，163个与IBD显著相关的基因座解释了不到15%的疾病风险变异。有趣的是，与宿主对肠道微生物的反应有关的基因的相关基因也变得丰富起来。先前的研究表明，与对照组相比，IBD患者的肠道细菌群或微生物群的配置发生了变化，包括多样性总体减少以及特定细菌的丰度发生变化。此时此刻，尽管有消息称 IBD的遗传和微生物危险因素都存在，没有研究同时考虑这两个因素。输入细菌基因组来观察肠道微生物活动的有效性 也没有在IBD中进行研究。我们建议使用风险队列中的基因和微生物组数据来研究这些问题，风险队列是最大的早发性、治疗天真的克罗恩病例和非IBD对照病例的集合。我们的第一个目标是检验这样一个假设，即联合使用遗传和微生物组数据比单独使用遗传或微生物组数据更准确地估计IBD风险。正如Gevers等人所描述的，肠道微生物群失调评分将根据末端回肠活检和粪便样本的16S rRNA基因图谱来计算。多基因风险分数将使用最近Jostins等人的显著基因座和效应大小来计算。IBD的Meta分析。然后，我们将使用Logistic回归来检验病例/控制状态与多基因风险分数、生物失调指数以及多基因风险分数和生物失调指数的相关性。我们的第二个目标是检验这样一个假设，即与分类学信息相比，从粪便样本中推测的元基因组更准确地估计IBD风险。我们将使用已建立的工具PICRUST来计算目标1中讨论的同一队列的元基因组。然后，我们可以将这些基因家族的丰度包括在我们的模型中，以测试与失调指数、多基因风险评分或两者结合起来，元基因组中的差异是否显示出与病例/控制状态更好的相关性。这项拟议的研究将首次结合使用遗传和微生物组数据来评估IBD风险。我们的长期目标是促进对IBD发病机制的了解，并帮助改进诊断和治疗。更广泛地说，这项研究将有助于对宿主基因组和微生物组如何相互作用的重要初步见解。

 DESCRIPTION (provided by applicant): Inflammatory bowel disease (IBD) is a serious, incurable gastrointestinal illness characterized by chronic inflammation which profoundly impacts quality of life for patients. Symptoms can include abdominal pain or discomfort, fever, diarrhea, and bloody stools. Up to 25% of patients experience other symptoms involving the heart, lungs, eyes, pancreas, bones, or joints. Around 1.5 million people have IBD in the U.S. and Canada, where rates are among the highest worldwide, and an estimated 17,000-93,000 new diagnoses are made each year. Importantly, peak age of onset is young adulthood, and 7-20% of diagnoses are pediatric. Because individuals require blood tests to monitor disease, surveillance colonoscopy, pharmaceutical management of symptoms, and often surgery, IBD has a large impact on the healthcare system. Recent meta-analysis of genetic data revealed 163 loci significantly associated with IBD that explain less than 15% of variance in disease risk. Intriguingly, associated loci are enriched for genes involved in host response to intestinal microbes. Previous studies have shown IBD patients' gut bacterial populations, or microbiomes, have altered configurations compared to control individuals, including overall reduction in diversity as well as altered abundance of specific bacteria. At this time, despite information that both genetic and microbiome risk factors exist for IBD, no study has taken both into account simultaneously. The validity of imputing bacterial genomes to look at microbial activity in the gut has also not been studied in IBD. We propose to investigate these issues using genotype and microbiome data from the RISK cohort, the largest collection of early-onset, treatment-naïve Crohn's cases and non-IBD controls. Our first aim is to test the hypothesis that using genetic and microbiome data in combination is a more precise estimator of IBD risk than either genetic or microbiome profile alone. Gut microbiome dysbiosis scores will be calculated from 16S rRNA gene profiling of terminal ileum biopsy and fecal samples as described by Gevers et al. Polygenic risk scores will be calculated using significant loci and effect sizes from the recent Jostins et al. meta-analysis of IBD. We will then use logistic regression to test for association o case/control status with polygenic risk score, dysbiosis index, and both polygenic risk score and dysbiosis index. Our second aim is to test the hypothesis that metagenomes imputed from fecal samples more precisely estimate IBD risk compared to taxonomic information. We will impute the metagenomes of the same cohort discussed in Aim 1 using established tool PICRUSt. We can then include these gene family abundances in our model to test whether differences in the imputed metagenome demonstrate better association with case/control status compared to dysbiosis index, polygenic risk score, or the two in combination. The proposed study will be the first to evaluate IBD risk using both genetic and microbiome data in combination. Our long-term goal is to advance understanding of the mechanisms of IBD pathogenesis and help improve diagnosis and treatment. More broadly, this study will contribute important preliminary insights into how the host genome and microbiome interact.