Network Approach to GWA Studies of Rheumatoid Arthritis (RA), Ankylosing Spondyli

描述（由申请人提供）： 尽管GWA研究在识别与复杂疾病相关的常见遗传变异方面取得了巨大成功，但我们仍然面临着巨大的挑战，不仅要确认显着SNP的关联发现，而且要最终确定从基因组信息到复杂表型的路径。目前的GWA研究主要集中在一次测试单个SNP的关联。由于常见疾病通常是由多个基因和环境组成的复杂网络引起的，仅检测单个SNP的关联性对复杂疾病的理解有限，不足以剖析疾病的复杂遗传结构。目前的GWA研究也很少关注全球的“系统水平”的方法，提供了一个功能的背景下，DNA变异发生。许多SNPs的功能可能没有得到很好的表征，但基因的功能，特别是通路，相反，得到了更好的研究。SNP和基因通过复杂的反应和相互作用途径发挥其功能。试图理解和解释一些重要的SNP，而没有任何统一的生物学主题可能是苛刻的。GWA研究面临的概念和统计挑战是：（1）如何全面了解常见疾病的复杂遗传结构，以深入了解生物学过程和疾病机制;（2）如何整合遗传学和其他功能数据，将基因组变异与最终临床结果联系起来。本申请的总体目标是使用WTCCC研究（病例：1860例，对照：2938，459，653个SNP）和NARAC研究（病例：866例，对照：1194，545，080个SNP）中RA、强直性脊柱炎（AS）（病例：1，000例，美国）、强直性脊柱炎（AS）（病例：1，000例，美国）和强直性脊柱炎（AS）（病例：1，000例，美国）的现有全基因组基因分型数据。美国，英国有1,000个，在美国有1,500个控制器。美国，3,000个对照组。K. 375，000个SNP）和GAIN中的银屑病（病例组：1421例，对照组：1425，451，725 SNPs）以及银屑病的表达数据（34例对照，37例受累和未受累皮肤，54例，675探针），以开发新的分析策略，基因和路径为基础的基因组-广泛关联分析，其中除了SNP之外，还将基因和途径作为关联分析的基本单元，以及遗传，基因表达和其他功能数据，以破译从基因组信息到复杂疾病临床终点的路径，以应对上述概念和统计挑战。 公共卫生相关性： 本申请中提出的工作使用现有的RA、AS和银屑病的全基因组基因型数据和银屑病的基因表达数据，这些数据通过数据访问协议从NIH、WTCCC获得，以及我们资助的项目P01 AR 052915 - 01 A1：遗传学和强直性脊柱炎（AS）发病机制，以进行RA、AS和银屑病的基于基因和途径的GWA研究。该应用程序还将使用结构方程来整合基因型和表达数据的分析，并建立网络模型，用于破译从基因组信息到RA，AS和银屑病疾病的路径。我们相信，拟议的研究是及时的，我们希望我们获得的方法学发展和见解将影响RA，AS，银屑病和其他复杂疾病的遗传研究，并继续超越本项目。

DESCRIPTION (provided by applicant): Despite great success of GWA studies in identification of common genetic variants associated with complex diseases, we are still faced with great challenges to not only confirm the association finding of significant SNPs, but to ultimately identify the path from genomic information to the complex phenotypes. The current GWA studies have primarily focused on testing association of a single SNP at a time. Since common disease are often caused by multiple genes and environments that are organized into a myriad of complex networks, to only test for association of single SNP offers limited understanding of complex diseases and is insufficient to dissect complex genetic structure of diseases. The current GWA studies have also paid less attention to global "systems-level" approach that provides a functional context within which DNA variation occurs. The function of many SNPs may not be well characterized, but function of genes and particularly pathways, on the contrary, are much better investigated. SNPs and genes carry out their functions through intricate pathways of reactions and interaction. Attempting to understand and interpret a number of significant SNPs without any unifying biological theme can be demanding. Pending conceptual and statistical challenges of the GWA studies are (1) how to take a comprehensive view of the complex genetic structure of common disease to gain insight into the biological processes and disease mechanism and (2) how to integrate genetics and other functional data to connect genomic variation to final clinical outcomes. Overall objective of this application is to use existing genome-wide genotyping data of RA in WTCCC studies (cases: 1860 and controls: 2938, 459,653 SNPs) and in NARAC studies (cases: 866 and controls: 1194, 545,080 SNPs), ankylosing spondylitis (AS) (cases: 1,000 in U. S., 1,000 in U.K., 1,500 controls in U. S., 3,000 controls in U. K. 375,000 SNPs), and psoriasis in GAIN(cases: 1421 and controls: 1425, 451,725 SNPs) as well as expression data of psoriasis ( 34 controls, 37 involved and uninvolved skins from cases, 54,675 probes) to develop novel analytic strategies for gene and pathway-based genome-wide association analysis in which genes and pathways are taken as basic units of association analysis in addition to SNPs, and integrations of genetic, gene expressions and other functional data to decipher path from genomic information to the clinical endpoints of complex diseases, to meet above conceptual and statistical challenges. PUBLIC HEALTH RELEVANCE: The work proposed in this application uses existing genome-wide genotype data of RA, AS and psoriasis and gene expression data of psoriasis that were obtained from NIH, WTCCC by data access agreement, and our funded project P01 AR052915-01A1: Genetics and Ankylosing Spondylitis (AS) Pathogenesis to perform gene and pathway-based GWA studies of RA, AS and psoriasis. This application will also use structural equations to integrate analysis of genotype and expression data and build network models for deciphering path from genomic information to diseases of RA, AS and psoriasis. We believe that the proposed study is timely and we expect that the methodological developments and insights we gain will influence genetic studies of RA, AS, psoriasis and other complex diseases and continue beyond this project.