Post GWAS approach to identify cell-specific genetic pathways underlying MS risk

GWAS 后方法可识别 MS 风险背后的细胞特异性遗传途径

• 批准号: 8925166
• 负责人: SERGIO E BARANZINI
• 金额: $ 51.13万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8925166
• 关键词: 6p21.3; Accounting; Address; Affect; Alleles; Anterior; B-Lymphocytes; Benign; Bioinformatics; Biological; Brain; CD8B1 gene; Candidate Disease Gene; Cells; Central Nervous System Diseases; Chromosome Mapping; Chronic; Clinical; Code; Communities; Complex; Computer Simulation; Custom; DNA; Data; Data Analyses; Data Set; Databases; Development; Disabled Persons; Disease; Disease susceptibility; Elements; Enrollment; Future; Gene Expression; Genes; Genetic; Genetic Epistasis; Genetic Heterogeneity; Genetic Polymorphism; Genetic Predisposition to Disease; Genetic Transcription; Genets; Genotype; Gliosis; Goals; HLA-DRB1; Health; Heritability; Image; Individual; Inflammation; Inflammatory; International; Interruption; Knowledge; Laboratories; Link; Linkage Disequilibrium; Magnetic Resonance Imaging; Major Histocompatibility Complex; Maps; Measures; Meta-Analysis; Multiple Sclerosis; Myelin; Nature; Neuraxis; Neurologic; Neurologic Dysfunctions; Oligodendroglia; Optical Coherence Tomography; Participant; Pathogenesis; Pathology; Pathway interactions; Patients; Phenotype; Play; Population; Predisposition; Proteins; Regulatory Element; Relapse; Reporting; Resolution; Retina; Risk; Scheme; Signal Transduction; Source; Stratification; Susceptibility Gene; Thick; Trauma; Update; Variant; Visual Pathways; Work; base; cohort; combinatorial; disability; disorder risk; disorder subtype; endophenotype; exhaust; exome; falls; genetic variant; genome wide association study; genome-wide; gray matter; handicapping condition; innovation; interest; macula; monocyte; neuron loss; novel therapeutics; personalized therapeutic; quantitative imaging; research clinical testing; retinal nerve fiber layer; risk variant; trait; transcriptome sequencing; young adult

DESCRIPTION (provided by applicant): Multiple sclerosis (MS) is a common and severe disorder of the central nervous system characterized by chronic inflammation, myelin loss, gliosis, varying degrees of axonal and oligodendrocyte pathology, and progressive neurological dysfunction. MS pathogenesis includes a complex genetic component. In spite of intensive long-standing efforts, the knowledge of MS genetics remains incomplete and significant genetic questions still remain unanswered. In particular, we plan to address how susceptibility variants influence disease susceptibility and whether variants also influence disease trajectory. This application is primarily hypothesis and data-driven, and will employ a combination of advanced bioinformatics and experimental approaches thus bridging efficiently the dry and wet laboratories to advance our knowledge on the pathways at play in MS. The unifying rationale of this proposal is to functionally link DNA polymorphisms (i.e. at the bottom of the hierarchical organization of biological complexity) with higher strata (e.g. protein networks, imaging endophenotypes) through the integration of information from intermediate levels. We propose these goals: Specific Aim 1. Cell specific eQTLs in multiple sclerosis. Building on the hypothesis that allele-specific RNA expression levels can act as surrogate of the functionality of the risk variants, we will integrate the most updated SNP-based MS dataset with information available on the encyclopedia of DNA (regulatory) elements (ENCODE) and additional databases in an effort to identify robust eQTLs and narrow the roster candidate causative variants. We will study their functional relevance for MS by RNAseq in 4 relevant cell populations (CD4, CD8, B cells and monocytes) isolated from MS patients with extreme disease trajectories. Specific Aim 2. In-silico functional analysis of gene x gene interactions. Here we propose to extend our earlier work and develop limited stratification schemes to identify gene networks enriched in well-defined extreme phenotypes (e.g. aggressive vs. benign disease). We will follow a computational strategy that takes into account whether risk alleles fall within functional elements and integrates them in a combinatorial fashion with available cell-specific gene expression datasets. The ultimate goal of this aim is to refine the MS genetics map and identify the source of genetic heterogeneity in MS. Specific Aim 3. Genotype-MRI phenotype associations in multiple sclerosis. We will examine an ongoing prospectively ascertained longitudinal cohort (n > 500) of deeply phenotyped patients for genotype-phenotype associations. This unique cohort will be studied to determine whether genetic variants genome-wide correlate with direct and indirect metrics of disease activity and progression as determined by brain MRI and optical coherence tomography (OCT). Specifically, relapse-related activity and brain neuronal loss will be estimated by global and regional measures of grey matter volume changes. We will also use OCT prospectively to measure thickness of the retinal nerve fiber layer and macular volume longitudinally as surrogates of disease activity.

描述（由申请人提供）：多发性硬化症（MS）是中枢神经系统的常见和严重疾病，其特征是慢性炎症，髓磷脂丧失，胶质病，轴突差异不同，轴突和少突胶质细胞病理学以及进行性神经功能障碍。 MS发病机理包括一个复杂的遗传成分。尽管长期努力，但MS遗传学的知识仍然不完整，而且重大的遗传问题仍然没有得到解决。特别是，我们计划解决易感性变异如何影响疾病的敏感性以及变体是否也影响疾病轨迹。该应用主要是假设和数据驱动的，它将采用先进的生物信息学和实验方法的组合，从而有效地桥接干燥和湿的实验室，以提高我们对MS中发挥作用的途径的了解。该建议的统一基本原理是通过在中等水平的信息中整合信息，在功能上将DNA多态性（即在生物复杂性的等级组织的底部联系起来）。我们提出这些目标：特定目标1。多发性硬化症中的细胞特异性EQTL。 Building on the hypothesis that allele-specific RNA expression levels can act as surrogate of the functionality of the risk variants, we will integrate the most updated SNP-based MS dataset with information available on the encyclopedia of DNA (regulatory) elements (ENCODE) and additional databases in an effort to identify robust eQTLs and narrow the roster candidate causative variants.我们将研究从具有极端疾病轨迹的MS患者中分离出的4个相关细胞群（CD4，CD8，B细胞和单核细胞）中RNASEQ对MS的功能相关性。特定目标2。基因X基因相互作用的硅内功能分析。在这里，我们建议扩展我们的早期工作并制定有限的分层方案，以鉴定富含定义明确的极端表型（例如侵略性与良性疾病）中的基因网络。我们将遵循一种计算策略，该策略考虑了风险等位基因是否属于功能元素 并以组合方式将它们与可用的细胞特异性基因表达数据集集成在一起。该目标的最终目标是完善MS遗传学图并确定MS中遗传异质性的来源。特定目标3。多发性硬化症中的基因型-MRI表型关联。我们将研究持续的基因型 - 表型关联的深层表型患者的前瞻性确定的纵向队列（n> 500）。将研究这种独特的队列，以确定全基因组的遗传变异是否与脑MRI和光学相干断层扫描（OCT）确定的疾病活性和进展的直接和间接指标相关。具体而言，将通过灰质体积变化的全球和区域度量来估计与复发相关的活性和大脑神经元丧失。我们还将前瞻性地使用OCT来测量视网膜神经纤维层的厚度和黄斑体积作为疾病活动的替代物。