Project 2: The Isoform repertoire and epigenome of Pediatric SLE

项目 2：儿科 SLE 的异构体库和表观基因组

基本信息

批准号：
10155423
负责人：
Jacques F Banchereau
金额：
$ 64.46万
依托单位：
WEILL MEDICAL COLL OF CORNELL UNIV
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-21 至 2022-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10155423
关键词：
ATAC-seq Address Affect Age Alternative Splicing Autoimmune Autoimmune Diseases Autoimmunity B-Lymphocytes Biological Assay Blood Blood Cells Cell physiology Cells Characteristics Child Childhood Chromatin Chronic Childhood Arthritis Clinical Clinical assessments Communicable Diseases Complement Complex Computational Biology Coupled DNA DNA methylation profiling Data Data Analyses Dermatomyositis Development Diagnostic Disease Epigenetic Process Etiology Gene Expression Gene Expression Profile Gene Expression Profiling Genes Genetic Transcription Genome Genomics Goals Health Heterogeneity Human Human Genome Hybrids Immune Immunology Interferon-alpha Interferons Lupus Messenger RNA Methods Modification Molecular Molecular Profiling Molecular Target Monoclonal Antibodies Mononuclear Monozygotic twins Morbidity - disease rate Myeloid Cells Patients Pattern Penetrance Peripheral Blood Mononuclear Cell Plasmablast Population Protein Isoforms Public Health Research Sampling Seminal Serum Site Subgroup Symptoms Systemic Lupus Erythematosus Systems Biology Technology Therapeutic Intervention Transposase Whole Blood analysis pipeline autoinflammatory base clinical heterogeneity cohort comparative data management design differential expression disease heterogeneity disorder subtype epigenome epigenomics exon skipping experimental study genomic data high throughput screening immune function in vitro Assay insight knowledge base link protein mRNA Precursor monocyte nano-string neutrophil new therapeutic target novel novel marker novel therapeutics patient stratification patient subsets promoter screening single molecule real time sequencing statistics targeted treatment tool transcriptome transcriptome sequencing transcriptomics

项目摘要

PROJECT SUMMARY SLE is a disease of high morbidity for which treatment options are poor. Identifying relevant targets for therapeutic intervention is difficult owing to the molecular and clinical heterogeneity of the disease. Through a large body of work, we have demonstrated that blood-based transcriptomic profiling can be used to parse out distinct transcriptional differences in immune function in health and disease. Relevant to the current application are our studies showing that SLE can be divided into seven disease subgroups based on distinct blood transcriptional signatures. More recently, we developed a sophisticated for integrated Profiling and Analysis Pipeline (iPAP) that we used to identify meaningful epigenetic and transcriptomic differences in human populations, including SLE cohorts. Building upon this knowledgebase will help us identify potential drivers of the disease, and ultimately novel biomarkers and novel therapeutic targets for SLE. We hypothesize that SLE is comprised of a spectrum of disease subtypes that can be categorized according to mutually distinct epigenomic, isoformic and transcriptomic features. The goal of this project is to characterize the repertoire of immune cell isoforms and the epigenome profiles associated with three of the seven most frequent pediatric SLE subgroups: SLE-Plasmablast (SLE-P), characterized by a plasmablast transcriptional signature and the presence of increased circulating plasmablasts; SLE-Interferon/Myeloid cells (SLE-IM), which shows an IFN and a neutrophil signature; and SLE-Plasmablast/ Interferon/Myeloid cells (SLE-PIM) displaying the three main signatures. We will use novel experimental paradigms that incorporate cutting-edge genomic technologies and build upon our established expertise in molecular immune profiling. Our project contains two Specific Aims: 1) To analyze the alternatively spliced transcriptome of blood cells from the three SLE patient subgroups, in which we will apply both short-read (Illumina HiSeq2500) and long-read (PacBio RSII) sequencing technologies to interrogate the isoform repertoire of PBMCs and select immune cell subsets; and 2) To determine the epigenome of blood cells from the three SLE subgroups, through studies capitalizing on a robust and sensitive new epigenomic assay called ATAC-seq coupled to Methyl-seq. Healthy age- matched samples will be used as controls in all experiments and, we will also examine samples from children with active juvenile dermatomyositis and systemic juvenile arthritis (n=5 per group), to identify those isoforms and signatures unique to SLE from those more generally associated with autoimmunity. Our team includes experts in immunology, genomics, epigenetics, systems biology of disease, computational biology, data management and statistics, who bring the collective expertise necessary for generating top quality genomics data and for robust data analysis using state-of-the-art methods. We will also create new tools, i.e., Nanostring probes and monoclonal antibodies, for high throughout screening assays suited to large patient cohorts. Successful completion of our project will reveal novel biomarkers of SLE and/or novel therapeutic targets.

项目概要 SLE 是一种发病率很高的疾病，治疗选择很差。确定相关目标由于该疾病的分子和临床异质性，治疗干预很困难。通过一个经过大量工作，我们已经证明基于血液的转录组分析可用于解析健康和疾病中免疫功能的明显转录差异。与当前应用相关我们的研究是否表明，SLE 可根据不同的血液分为七个疾病亚组转录签名。最近，我们开发了一个复杂的集成分析和分析工具我们用于识别人类有意义的表观遗传和转录组差异的流程 (iPAP) 人群，包括 SLE 人群。建立在这个知识库的基础上将帮助我们识别潜在的驱动因素疾病，并最终为 SLE 提供新的生物标志物和新的治疗靶点。我们假设 SLE 由一系列疾病亚型组成，这些亚型可以根据相互不同的特征进行分类表观基因组、同种型和转录组特征。该项目的目标是表征曲目免疫细胞亚型和与七个最常见的三个相关的表观基因组图谱儿科 SLE 亚组：SLE-浆母细胞 (SLE-P)，其特征为浆母细胞转录特征以及循环浆母细胞增加； SLE-干扰素/骨髓细胞 (SLE-IM)，显示干扰素和中性粒细胞特征；和 SLE-浆母细胞/干扰素/骨髓细胞 (SLE-PIM) 显示三个主要签名。我们将使用融合尖端基因组学的新颖实验范例技术并以我们在分子免疫分析方面的既定专业知识为基础。我们的项目包含两个具体目标： 1) 分析三种 SLE 血细胞的选择性剪接转录组患者亚组，我们将在其中应用短读长 (Illumina HiSeq2500) 和长读长 (PacBio RSII) 用于询问 PBMC 亚型库并选择免疫细胞亚群的测序技术；和 2) 通过研究确定三个 SLE 亚组的血细胞表观基因组一种稳健且灵敏的新表观基因组检测方法，称为 ATAC-seq 与 Mmethyl-seq 耦合。健康年龄- 匹配的样本将用作所有实验的对照，我们还将检查儿童样本患有活动性幼年皮肌炎和系统性幼年关节炎（每组 n=5），以识别这些亚型以及 SLE 特有的特征，这些特征通常与自身免疫相关。我们的团队包括免疫学、基因组学、表观遗传学、疾病系统生物学、计算生物学、数据专家管理和统计，他们带来了生成高质量基因组学所需的集体专业知识数据并使用最先进的方法进行可靠的数据分析。我们还将创建新工具，即 Nanostring 探针和单克隆抗体，用于适合大型患者群体的高通量筛选测定。我们项目的成功完成将揭示 SLE 的新生物标志物和/或新的治疗靶点。