Multi-ethnic GWAS of diabetic retinopathy: enhanced power using new methods

糖尿病视网膜病变的多种族 GWAS：使用新方法增强功效

• 批准号: 8528611
• 负责人: Lucia Sobrin
• 金额: $ 26.93万
• 依托单位: MASSACHUSETTS EYE AND EAR INFIRMARY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8528611
• 关键词: Accounting; Admixture; Affect; African American; Age; American; Asians; Blindness; Blood Glucose; Candidate Disease Gene; Caucasians; Caucasoid Race; Counseling; Data; Data Set; Diabetes Mellitus; Diabetic Retinopathy; Diagnosis; Disease; Early treatment; Ethnic group; Eye; Eye diseases; Functional disorder; Genes; Genetic; Genetic Polymorphism; Genetic Risk; Genome; Genotype; Heritability; High Prevalence; Individual; Lead; Linkage Disequilibrium; Maps; Meta-Analysis; Methods; Metric; Modeling; Non-Insulin-Dependent Diabetes Mellitus; Participant; Pattern; Phenotype; Play; Population; Population Heterogeneity; Reporting; Risk; Risk Factors; Role; Sample Size; Sampling; Signal Transduction; Single Nucleotide Polymorphism; South Asian; Statistical Methods; Time; Variant; Work; cohort; diabetes control; diabetic; diabetic patient; genetic association; genetic risk factor; genetic variant; genome wide association study; genome-wide; glycemic control; improved; insight; non-genetic; novel; public health relevance; racial and ethnic; risk variant; sugar

DESCRIPTION (provided by applicant): Diabetic retinopathy (DR) is the leading cause of blindness in working-age Americans. There is evidence for a genetic contribution to DR~ the heritability of DR has been estimated to be as high as 27%. To date, only a few genes that might contribute to DR have been discovered. This is in part because genetic studies of DR have thus far contained limited numbers of participants. New methods of combining and analyzing samples from different racial/ethnic groups provide an opportunity to increase our ability to detect genes associated with DR. Hypotheses: Combining genetic samples from participants from multiple populations will increase the ability to discover DR genes. Use of novel admixture association, covariate modeling and fine-mapping methods will further maximize the power to detect associated genes. Specific Objectives: 1. To identify genetic variants associated to DR by performing a genome-wide association study (GWAS) using existing data from African American (AA) and Caucasian diabetic subjects and by incorporating admixture association into the GWAS. 2. To increase the power of genetic discovery by incorporating information about the participants' duration of diabetes and glycemic control into the GWAS using liability threshold modeling. 3. To replicate and fine-map the most promising associations using existing genetic data from DR participants from additional racial/ethnic groups. Methods: Existing genome-wide genotyping data from multiple AA and Caucasian cohorts of individuals with type 2 diabetes (T2D) and DR Phenotyping will be jointly analyzed using new statistical methods to combine single nucleotide polymorphism association and admixture association signals for increased power. Individuals with T2D and no DR with be compared to individuals with T2D and DR defined using the Early Treatment Diabetic Retinopathy Study scale. Subsequently, data on the two major non-genetic DR covariates, duration of diabetes and glycemic control, will be incorporated into the combined AA and Caucasian GWAS via liability threshold modeling. Finally, a set of genome-wide significant or suggestive variants (P-value < 10-5) from the GWAS analyses will be replicated in cohorts from additional populations, including South Asians and East Asians. All signals that attain genome-wide significance after replication analyses will be carried forward to fine-mapping. Fine-mapping will be performed without any additional genotyping using cross-population meta-analysis of genotyped and imputed HapMap 3 and 1000 Genomes variants, applying new metrics and methods developed for cross-population fine-mapping that optimally leverage the different patterns of linkage disequilibrium in different populations. Implications: If genes associated with DR are identified, they will provide insights into pathophysiology and may lead to new therapies for DR. In addition, results may provide information with which to counsel diabetic patients regarding their risk of DR.

描述（由申请人提供）：糖尿病视网膜病变（DR）是导致美国工作年龄人群失明的主要原因。有证据表明遗传对DR有贡献，DR的遗传率估计高达27%。到目前为止，只有少数可能导致DR的基因被发现。这在一定程度上是因为迄今为止，DR的基因研究的参与者数量有限。结合和分析来自不同种族/民族群体的样本的新方法为提高我们检测与DR假设相关的基因的能力提供了机会：结合来自多个人群参与者的遗传样本将提高发现DR基因的能力。使用新的混合关联、协变量建模和精细定位方法将进一步最大化检测相关基因的能力。具体目标：1；通过使用非裔美国人（AA）和高加索糖尿病受试者的现有数据进行全基因组关联研究（GWAS），并将混合关联纳入GWAS，确定与DR相关的遗传变异。2. 通过使用责任阈值模型将参与者的糖尿病持续时间和血糖控制信息纳入GWAS，增加基因发现的能力。3. 利用来自其他种族/民族群体的DR参与者的现有遗传数据复制和精细绘制最有希望的关联。方法：采用新的统计学方法，结合单核苷酸多态性关联和混合关联信号，对现有的AA和高加索2型糖尿病（T2D）患者全基因组基因分型数据和DR表型进行联合分析。将T2D和无DR的个体与使用早期治疗糖尿病视网膜病变研究量表定义的T2D和DR的个体进行比较。随后，通过责任阈值建模，将两个主要的非遗传DR协变量（糖尿病持续时间和血糖控制）的数据纳入AA和高加索人GWAS组合。最后，GWAS分析的一组全基因组显著或暗含性变异（p值< 10-5）将在其他人群（包括南亚人和东亚人）的队列中进行复制。所有在复制分析后获得全基因组意义的信号将进行精细定位。精细制图将在没有任何额外基因分型的情况下进行，使用基因分型和输入的HapMap 3和1000个基因组变异的跨种群荟萃分析，应用为跨种群精细制图开发的新指标和方法，最佳地利用不同种群中连锁不平衡的不同模式。如果与DR相关的基因被确定，它们将提供病理生理学的见解，并可能导致DR的新疗法。此外，研究结果可能为糖尿病患者提供关于DR风险的咨询信息。