Epigenetic and transcriptomic determinants of Sjogren's Syndrome subtypes utilizing data from the Sjogren's International Collaborative Clinical Alliance (SICCA) cohort

利用干燥综合征国际合作临床联盟 (SICCA) 队列的数据，研究干燥综合征亚型的表观遗传学和转录组决定因素

• 批准号: 10259816
• 负责人: CAROLINE Helene SHIBOSKI
• 金额: $ 16.15万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-09 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10259816
• 关键词: Accounting; Affect; American; Arthralgia; Autoantibodies; Biological; Biological Specimen Banks; Biopsy; Blood Cells; Caring; Cells; Classification; Clinical; Clinical Data; Clinical Trials; Cohort Studies; Collaborations; DNA Methylation; DNA methylation profiling; Data; Development; Diagnosis; Disease; Disease Pathway; Epidemiology; Epigenetic Process; Etiology; European; Exanthema; Exhibits; Exocrine System; Fatigue; Functional disorder; Funding; Future; Gene Expression; Genes; Genetic; Genetic Heterogeneity; Genetic study; Genome; Genomics; Genotype; Hereditary Disease; Immunologics; Infrastructure; International; Knowledge; Labial Salivary Gland; Laboratories; Lacrimal gland structure; Lymphoma; Machine Learning; Measures; Mediating; Mendelian randomization; Methylation; Modeling; Modification; Molecular; Multiomic Data; National Institute of Dental and Craniofacial Research; Oral; Participant; Pathogenesis; Pathway interactions; Patients; Peripheral Blood Mononuclear Cell; Pharmaceutical Preparations; Phenotype; Positioning Attribute; Process; Quantitative Trait Loci; Registries; Research; Research Personnel; Resources; Rheumatism; Rheumatology; Risk; Risk Factors; Salivary Gland Tissue; Salivary Glands; Secure; Site; Sjogren' s Syndrome; Standardization; Symptoms; Systemic Lupus Erythematosus; Testing; United States National Institutes of Health; Validation; Variant; Work; Xerostomia; biobank; cell type; cohort; college; differential expression; disease heterogeneity; epigenome; eye dryness; genetic association; genetic epidemiology; genetic risk factor; genetic variant; genome wide association study; genomic data; improved; methylation testing; monocyte; multiple omics; novel therapeutics; repository; single-cell RNA sequencing; success; systemic autoimmune disease; transcriptome; transcriptome sequencing; transcriptomics; whole genome

ABSTRACT Sjögren's Syndrome (SS) is a systemic autoimmune disease affecting the exocrine system, with hallmark symptoms of dry mouth and/or dry eyes caused by the dysfunction of salivary and/or lacrimal glands, respectively. While Genome-Wide Association Studies (GWAS) and other studies have increased our knowledge of genetic risk factors for SS, the disease etiology remains not well understood, and such risk factors have not been translatable to any immunological treatment options for SS. The NIH-NIDCR-funded Sjögren's International Collaborative Clinical Alliance (SICCA) was established to improve the understanding, diagnosis and treatment of patients with SS by developing/validating standardized classification criteria for SS; and developing a rich biospecimen repository with clinical data to be used for future epidemiologic, pathogenesis, and genetic studies of SS.[1, 2] For this project, we will focus on genomic data and measures of the 2016 ACR-EULAR classification criteria, involving ocular, oral, and autoantibody manifestations. As shown in our previous work, the genetics of SS varies with ancestry; thus, we will cluster patients by both the criteria subphenotypes and genetic ancestry. We believe that accounting for disease heterogeneity in this way will enable us to more precisely identify disease pathways and mechanisms. Using previously secured funding, we are completing DNA methylation typing on LSGs in 373 SICCA patients and single-cell RNA sequencing (scRNAseq) on PBMCs of 86 SICCA patients who also have DNA methylation profiling. This data provides a unique opportunity for multi-omics analysis to determine correlates between LSG tissue epigenetics, peripheral blood cell-type distributions and cell-specific gene expression by SS subsets. First, using GWAS data and DNA methylation data from LSG biopsies, we will identify genetic and epigenetic modifications associated with subtypes of SS in SICCA patients. We will then examine the relationships between them by testing for genotype-specific methylation and expression, and utilizing mendelian randomization and causal inference testing to investigate causality between these measures. Second, we will analyze scRNAseq data to identify how cell types, states and cell- specific gene expression correlate with SS subtypes. Finally, we will integrate genetics, epigenetics, and transcriptomics to determine multi-omics profiles associated with SS subtypes. We will jointly model associated features from the genomic data to investigate causal pathways via correlation networks, conditional analysis, and machine learning. We anticipate that SS subtypes will exhibit specific relationships within the multi- omics data and that this will advance our understanding of SS disease processes, leading to better treatment targets.

摘要 干燥综合征（SS）是一种影响外分泌系统的全身性自身免疫性疾病，其特征是 由唾液腺和/或泪腺功能障碍引起的口干和/或眼干症状， 分别虽然全基因组关联研究（GWAS）和其他研究增加了我们的知识， SS的遗传危险因素，疾病的病因仍然没有很好的理解，这些危险因素没有 可以转化为任何SS的免疫治疗方案。美国国立卫生研究院-NIDCR资助的舍格伦国际 建立了临床协作联盟（SICCA），以提高认识、诊断和治疗 通过开发/验证SS的标准化分类标准， 生物标本库，包含临床数据，用于未来的流行病学、发病机制和遗传学研究 的SS。[1，2]对于本项目，我们将专注于2016年ACR-EULAR分类的基因组数据和措施 标准，包括眼部，口腔和自身抗体表现。正如我们以前的工作所示， SS随祖先而变化;因此，我们将通过亚表型和遗传祖先标准对患者进行聚类。 我们相信，以这种方式解释疾病的异质性将使我们能够更精确地识别疾病 途径和机制。利用先前获得的资金，我们正在完成DNA甲基化分型。 373名SICCA患者的LSG和86名SICCA患者PBMC的单细胞RNA测序（scRNAseq）， 也有DNA甲基化图谱。这些数据为多组学分析提供了独特的机会， 确定LSG组织表观遗传学、外周血细胞类型分布和细胞特异性 SS亚群的基因表达。首先，使用来自LSG活检的GWAS数据和DNA甲基化数据， 我们将鉴定与SICCA患者SS亚型相关的遗传和表观遗传修饰。 然后，我们将通过检测基因型特异性甲基化来检查它们之间的关系， 表达，并利用孟德尔随机化和因果推理测试，以调查因果关系之间 这些措施。其次，我们将分析scRNAseq数据，以确定细胞类型，状态和细胞- 特异性基因表达与SS亚型相关。最后，我们将整合遗传学，表观遗传学， 转录组学以确定与SS亚型相关的多组学谱。我们将共同塑造 从基因组数据的相关特征，通过相关网络，条件 分析和机器学习。我们预计，SS亚型将在多个组织中表现出特定的关系。 组学数据，这将促进我们对SS疾病过程的理解，从而更好地治疗 目标的