Integrating Genetics of Gene Expression into Pathway Analysis for Melanoma GWAS

将基因表达遗传学整合到黑色素瘤 GWAS 的通路分析中

基本信息

批准号：
8458512
负责人：
JIALI HAN
金额：
$ 1.28万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-01 至 2013-09-02
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8458512
关键词：
Accounting Adipose tissue Affect Biological Burn injury Cancer Center Case-Control Studies Classification Complex Cutaneous Melanoma Data Development Disease Disease Association Disease Pathway Disease susceptibility Etiology Gene Expression Gene Expression Profiling Genes Genetic Genomics Genotype Goals Hair Color Health Professional Individual Joints Lead Liver Location Mediation Melanocytic nevus Methods Molecular Non-Insulin-Dependent Diabetes Mellitus Nurses&apos Health Study Pathway Analysis Pathway interactions Phenotype Positioning Attribute Prevention Quantitative Trait Loci Recording of previous events Reporting Research Research Design Research Personnel Risk Risk Estimate Signal Transduction Single Nucleotide Polymorphism Skin Staging Structural Genes Sunburn Testing Transcript Variant Work base case control cohort cost effective follow-up genetic association genetic variant genome wide association study genotyping technology innovation insight melanoma novel novel strategies

项目摘要

DESCRIPTION (provided by applicant): The genome-wide association studies (GWAS) have successfully identified a number of single nucleotide polymorphisms (SNPs) associated with melanoma risk. However, the traditional GWASs focus only on marginal effects of individual markers and have incorporated external functional information only after identifying robust statistical associations, which often miss relatively small effects conferred by most genetic variants. The pathway-based approaches, which evaluate the cumulative contribution of genes within biological pathways, may help collect the modest signals embedded in GWASs and identify the disease-related pathways on a pathway level. Though, the traditional pathway analyses simply assign the SNPs into nearby genes based on physical location, which may introduce numerous false positive associations due to multiple testing on non- functional SNPs and mis-annotate the SNPs regulating gene expression in distance. GWASs on gene expression that study the genetic variants regulating gene expression at a genomic scale have identified thousands of expression quantitative trait loci (eQTLs) that affect gene expression. Defining the eQTLs and assigning them into the genes that they regulate may help functionally annotate SNPs and increase the enrichment of functional variants in the biological pathways. The selection of the eQTLs in the pathways identified by pathway analysis for replication may increase the likelihood of targeting true signals than by chance. The integration of eQTLs of liver and adipose tissues into the pathway analysis for the GWAS of type 2 diabetes has successfully identified several disease-related pathways. More recently, a GWAS on global gene expression of the skin has systematically generated skin eQTLs. The goal of the current application is to assess the associations of biological pathways with melanoma risk by integrating the skin eQTLs into the pathway analysis for melanoma GWAS in the discovery stage and to validate the associations of specific loci within the identified pathways in the replication stage. Mediatio analysis on potential intermediate phenotypes will be conducted to investigate the etiological contribution of the identified pathways/SNPs. We plan to use a nested melanoma case-control study of 420 melanoma cases and 2,284 controls in two large, well- characterized cohorts, the Nurses' Health Study and the Health Professionals Follow-up Study in the discovery stage, and use a melanoma case-control study of 1,804 melanoma cases and 1,026 controls from the MD Anderson Cancer Center in the replication stage. All the cases and controls have been previously genotyped on Illumina SNP chips. The existing GWAS genotype data give us a cost-effective opportunity to apply the new approach to melanoma research. Our proposed study would be the first to combine the genetics of gene expression and functional classification of genes as prior information to apply in melanoma GWAS. This innovative work will utilize the GWAS data to a greater extent. Findings from this study will identify the genetic variants with modest effects from the GWAS data and provide new insights into the etiology of melanoma.

描述（由申请人提供）：全基因组关联研究（GWAS）已成功鉴定出许多与黑色素瘤风险相关的单核苷酸多态性（SNP）。然而，传统的 GWAS 仅关注单个标记的边际效应，并且仅在识别出强大的统计关联后才纳入外部功能信息，这往往会错过大多数遗传变异所赋予的相对较小的影响。基于通路的方法评估生物通路中基因的累积贡献，可能有助于收集 GWAS 中嵌入的适度信号，并在通路水平上识别与疾病相关的通路。然而，传统的通路分析只是根据物理位置将SNP分配到附近的基因中，这可能会由于对非功能性SNP的多次测试而引入大量假阳性关联，并错误注释调节远处基因表达的SNP。基因表达全基因组关联分析（GWAS）在基因组规模上研究调节基因表达的遗传变异，已鉴定出数千个影响基因表达的表达数量性状位点（eQTL）。定义 eQTL 并将它们分配到它们调节的基因中可能有助于对 SNP 进行功能注释并增加生物途径中功能变异的富集。在通过复制途径分析确定的途径中选择 eQTL 可能会比偶然增加靶向真实信号的可能性。肝脏 eQTL 的整合将脂肪组织和脂肪组织纳入 2 型糖尿病 GWAS 的通路分析已成功确定了多个疾病相关通路。最近，关于皮肤全局基因表达的 GWAS 系统地生成了皮肤 eQTL。当前应用的目标是通过在发现阶段将皮肤 eQTL 整合到黑色素瘤 GWAS 的路径分析中来评估生物路径与黑色素瘤风险的关联，并在复制阶段验证已识别路径内特定位点的关联。将进行潜在中间表型的中介分析，以研究已确定的途径/SNP 的病因学贡献。我们计划在发现阶段使用一项巢式黑色素瘤病例对照研究，该研究涉及两个大型、特征明确的队列（即护士健康研究和健康专业人员随访研究）中的 420 例黑色素瘤病例和 2,284 例对照，并使用黑色素瘤病例-来自 MD 安德森癌症中心的 1,804 例黑色素瘤病例和 1,026 例对照的对照研究，处于复制阶段。所有病例和对照均已在 Illumina SNP 芯片上进行了基因分型。现有的 GWAS 基因型数据为我们提供了一个具有成本效益的机会，将新方法应用于黑色素瘤研究。我们提出的研究将是第一个将基因表达遗传学和基因功能分类结合起来作为先验信息应用于黑色素瘤 GWAS 的研究。这项创新工作将更大程度地利用 GWAS 数据。这项研究的结果将从 GWAS 数据中识别出影响不大的遗传变异，并为黑色素瘤的病因学提供新的见解。