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Mechanisms of action of SNPs associated with common disease

Mechanisms of action of SNPs associated with common disease
SNP与常见疾病相关的作用机制
批准号:
8116228
负责人:
OSNAT HERZBERG
金额:
$27.6万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2011-08-31

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中文摘要
翻译
描述(由申请人提供):最近的全基因组关联研究已经导致了与许多常见人类疾病发病率增加相关的多个常见snp的可靠鉴定。这些结果提供了对复杂性状疾病本质的重大新见解的诱人前景,以及对主要常见人类疾病潜在机制的具体理解。获得最大的洞察力不是微不足道的,需要开发和应用一系列计算和实验技术。这个项目的目标是发展和应用这些方法到目前可获得的关联研究和不久将获得的新结果。该项目侧重于基因和基因产物水平对人类常见疾病的贡献。这些过程构成了snp影响疾病风险的多层次机制的关键部分,充分了解它们的贡献对于有效研究更高水平的途径和子系统的影响至关重要。我们采取双管齐下的方法。首先,计算方法将用于确定一组可能的候选snp,这些snp位于常见疾病的易感性位点。对于每一个snp,一组可能的作用机制被检查。具体来说,对基因表达水平的影响;信使RNA结构;加工;稳定性和拼接;以及蛋白质在体内的折叠、结构、稳定性和功能。其次,对于其中一个已经明确起重要作用的机制,蛋白质中的错义snp,我们将实验研究由此产生的氨基酸取代对体外功能的影响。为此,我们将克隆、表达和纯化一些受影响的蛋白质和SNP变体,并研究它们的性质,特别是结构稳定性和与适当结合伙伴的相互作用。最初的研究是关于WTCCC基因组与常见疾病的大范围关联数据,以及克罗恩病的额外关联数据。随着更多的数据可用,计算分析将扩展到包括额外的关联研究以及重新测序数据。结果将是对SNPs在基因和蛋白质水平上影响疾病易感性的机制进行全面的计算分析,并在高度优先的情况下,对相关错义SNPs对蛋白质功能的影响进行广泛的实验表征。所有数据将以可下载的形式提供,也可通过交互式网络界面提供。此外,我们将开发一个注释和讨论工具,以便最大限度地利用结果。
英文摘要
DESCRIPTION (provided by applicant): Recent genome wide association studies have led to the reliable identification of multiple common SNPs associated with increased incidence of a number of common human diseases. These results offer the tantalizing prospect of major new insights into the nature of complex trait disease in general and specific understanding of the mechanisms underlying major common human diseases. Deriving maximum insight is not trivial, and requires the development and application of a range of computational and experimental techniques. The goal of this project is to develop and apply such methods to the currently available association studies and new results that will be available shortly. The project focuses on the gene and gene product level contributions to common human disease. These processes constitute a key part of the multiple level mechanisms by which SNPs influence disease risk, and a full understanding of their contributions is essential to effective investigation of higher level pathway and subsystems impact. We take a two pronged approach. First, computational methods will be used to identify a set of possible candidate SNPs in established susceptibility loci for common diseases. For each of these SNPs, a set of possible mechanisms of action is examined. Specifically, effects on gene expression level; messenger RNA structure; processing; stability and splicing; and on protein folding, structure, stability and function in vivo. Secondly, for one of the mechanisms that it is already clear plays a significant role, missense SNPs in proteins, we will experimentally investigate the impact of the resulting amino acid substitutions on in vitro function. To this end, we will clone, express and purify a number of affected proteins and the SNP variants, and investigate their properties, particularly structural stability and interaction with appropriate binding partners. Initial studies are on the large scale WTCCC genome wide association data for common diseases, and on additional association data for Crohn's disease. As more data become available, the computational analysis will be extended to include additional association studies as well as re-sequencing data. The outcome will be a comprehensive computational analysis of the mechanisms by which SNPs influence disease susceptibility at the gene and protein level, and in high priority cases, extensive experimental characterization of the impact of relevant missense SNPs on protein function. All data will be made available in downloadable form, as well as through an interactive web interface. In addition, we will develop an annotation and discussion facility, so that the results can be maximally exploited. PUBLIC HEALTH RELEVANCE: New data are for the first time reliably establishing many associations between genetic variation among individuals and susceptibility to a number of common human diseases. These data open the way for investigation of the mechanisms underlying disease and hence the development of new therapies. We will use computational and experimental methods to determine the genome and protein level mechanisms, making use of these new data.
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