The Role of Genetic and Non-Genetic Factors and Causal Mechanisms Underlying Cataract Susceptibility For Risk Prediction

遗传和非遗传因素的作用以及白内障风险预测的因果机制

• 批准号: 10446770
• 负责人: Helene Choquet
• 金额: $ 40.49万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10446770
• 关键词: Accounting; Address; Affect; Aging; Alcohol consumption; Animal Model; Behavioral; Biological; Blindness; Body mass index; CD100 antigen; Candidate Disease Gene; Cataract; Cataract Extraction; Cellular Assay; Cigarette; Clinical; Clinical Data; Code; Crystalline Lens; Data; Databases; Defect; Development; Diabetes Mellitus; Disease; Electronic Health Record; Etiology; Eye; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Transcription; Genotype; Glaucoma; Goals; Histology; Homeostasis; Hypertension; Individual; Investigation; Knockout Mice; Knowledge; Lens Opacities; Link; Literature; Medicare; Mendelian randomization; Meta-Analysis; Molecular; Myopia; Observational Study; Operative Surgical Procedures; Participant; Pathogenesis; Pathology; Pathway interactions; Patients; Performance; Population; Predisposition; Prevention; Prevention strategy; Probability; Proteomics; Public Health; Refractive Errors; Research; Risk; Risk Factors; Role; Scanning Electron Microscopy; Smoking; System; Testing; Therapeutic; Therapeutic Intervention; Tissues; Variant; Vision; Visual Acuity; Visual impairment; age related; base; biobank; causal variant; cigarette smoking; cohort; conditional knockout; cost; disorder risk; effective intervention; exome sequencing; fall injury; gene discovery; genetic predictors; genome wide association study; genome-wide; genomic locus; high body mass index; improved; innovation; insight; knockout gene; lens; mortality; mouse model; multi-ethnic; multiple datasets; new therapeutic target; non-genetic; novel; novel strategies; personalized intervention; polygenic risk score; predictive modeling; predictive tools; prevent; programs; risk prediction; risk prediction model; risk stratification; risk variant; screening; tool; trait; transcriptome; transcriptome sequencing

Abstract Age-related cataract, defined as ocular lens opacity, is a leading cause of blindness worldwide. Cataract is also associated with injurious falls and increased mortality and is a significant public health problem in the U.S., accounting for approximately 60% of Medicare costs related to vision. Given the aging U.S. population, cataract surgery demand is expected to double over the next 25 years. Thus, it is important to understand the etiology of cataract to identify at-risk patients and develop effective prevention strategies. Recently, we conducted a large- scale multiethnic genome-wide association study (GWAS) meta-analysis of cataract that has identified 55 genetic loci, including 38 novel loci, that underlie the risk of cataract. Majority of the genes in these loci were independently supported as promising candidates for cataract by the database iSyTE (integrated Systems Tool for Eye gene discovery), based on their significant expression in the lens. While these data uncovered potential new causal genes in the identified loci, their function in the lens is not defined and their role underlying cataract risk remains largely unknown. Further, whether cataract-loci regulate genes and how regulation differs across tissues has not yet been explored. Our study also identified strong genetic correlations between cataract and several disorders/traits, including, glaucoma, myopia, cigarettes smoking, and BMI, supporting previous observational studies. However, it is not clear that these associations are causal. Finally, no predictive tool exists for evaluating individuals at-risk for cataract. The overall objective of this proposal is to understand the role of genetic and non-genetic factors and causal mechanisms underlying the etiology of cataract and develop a prediction tool to facilitate risk-stratified screening for cataract. By leveraging a rich multiethnic cohort, with both genome-wide genotype data and extensive clinical data collected through electronic health records, and using whole-exome sequencing (WES) data of UK Biobank participants, we will accomplish the following specific aims: 1.a) Identify novel genetic predictors of cataract risk using high quality WES data and transcriptome-wide association study (TWAS) approach; 1.b) Evaluate whether glaucoma, myopic refractive error, diabetes, high blood pressure, high BMI, cigarette smoking, or alcohol consumption and other clinical and behavioral factors are causal risk factors of cataract using a Mendelian randomization approach; 2) Develop risk prediction models of cataract risk by integrating polygenic risk scores along with other risk factors; and 3) Determine the function – in the lens using animal models – of novel candidate genes prioritized in cataract-associated loci. This proposed research is significant because it will fill an important gap in cataract genetics and will provide important mechanistic insights into the pathogenesis of cataract. The project is innovative in the development of prediction models of cataract risk based on genetic and non-genetic risk factors as well as the development of novel animal models of cataract. The long-term goal of this research is to advance cataract etiology knowledge for effective interventions and non-surgical therapeutics for its prevention, delay or treatment.

抽象的 与年龄相关的白内障，定义为眼镜透明度，是全球失明的主要原因 在美国，与伤害性跌倒和死亡率增加有关的重大公共卫生问题 约占与视力有关的医疗保险费用的60％。 手术需求预计将在未来25年中加倍。 白内障目的是确定危险患者并制定有效的预防策略。 鉴定全基因组关联研究（GWAS）的白内障荟萃分析已鉴定出55 遗传基因座，包括38个小说基因座，是白内障风险的基础。 数据库ISYTE（集成系统工具 对于眼基因发现），基于它们在镜头中的显着表达。 已确定的基因座中的新因果基因，它们在镜头中的功能不是当之无愧的白内障 风险仍然不明 尚未探索组织。 严重性障碍/特征，包括青光眼，近视，吸烟和BMI，支持以前 但是，观察性研究。 为了评估人白内障的人的整体目的。 遗传和非遗传因素以及因果机制的白内障病因学并发展 通过利用丰富的多种组合，可以促进白内障的风险分层筛查的预测工具。 全基因组基因型数据和通过电子健康记录收集的广泛临床数据收集器数据，并使用 英国生物库参与者的全外观测序（WES）数据，我们将完成以下特定的特定特定 目的：1.A）使用高质量的WES数据和整个转录组范围内确定白内障风险的新型遗传预测因子 协会研究（TWA）方法； 1.b）评估青光眼，近视误差，糖尿病是否 血压，高BMI，吸烟或饮酒以及其他临床和行为因素 是使用Mendelian随机方法的白内障的因果风险因素； 2）开发风险预测模型 通过整合多基因风险评分以及其他风险因素的风险； 3） 在晶状体中，使用动物模型的新型候选基因在白内障相关基因座中优先。 研究很重要，因为它将填补白内障遗传学的重要空白，并将提供重要 对白内障的发病机理的机械洞察力。 基于遗传和非遗传危险因素的白内障风险的预测模型以及发展 白内障的新型动物模型。 对于有效的干预措施和非手术治疗方法，是预防，延迟或治疗。