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.

摘要 眼透镜混浊是眼内白内障的主要病因。白内障也是 与伤害性福尔斯和增加的死亡率相关，并且在美国是一个重要的公共卫生问题， 约占与视力相关的医疗保险费用的60%。鉴于美国人口老龄化，白内障 手术需求预计在未来25年内将翻一番。因此，重要的是要了解的病因， 白内障，以识别高危患者，并制定有效的预防策略。最近，我们进行了一次大型的- 一项大规模的多种族全基因组关联研究（GWAS）对白内障进行了荟萃分析， 遗传基因座，包括38个新的基因座，是白内障风险的基础。这些基因座中的大多数基因是 iSyTE（集成系统工具）数据库独立支持其作为白内障的有希望候选者 for Eye gene discovery），基于它们在透镜中的显著表达。虽然这些数据揭示了潜在的 新的致病基因在已确定的基因座中，它们在透镜中的功能尚未确定，它们在白内障中的作用 风险在很大程度上仍然未知。此外，白内障基因座是否调节基因以及调节如何在不同的基因中不同。 组织尚未被探索。我们的研究还确定了白内障和白内障之间的强烈遗传相关性。 几种疾病/特征，包括青光眼、近视、吸烟和BMI，支持既往 观察性研究然而，尚不清楚这些关联是否是因果关系。最后，不存在预测工具 用于评估白内障风险个体。本提案的总体目标是了解 遗传和非遗传因素以及白内障病因学的因果机制，并制定一项 预测工具，以促进白内障的风险分层筛查。通过利用丰富的多民族群体， 通过电子健康记录收集的全基因组基因型数据和广泛的临床数据， 英国生物库参与者的全外显子组测序（WES）数据，我们将完成以下具体工作 目的：1.a）使用高质量WES数据和全转录组识别白内障风险的新遗传预测因子 关联研究（TWAS）方法; 1.b）评估青光眼、近视屈光不正、糖尿病、高 血压、高BMI、吸烟或饮酒以及其他临床和行为因素 使用孟德尔随机化方法，是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沿着与其他风险因素来评估白内障风险;以及3）确定功能- 在透镜中使用动物模型-在白内障相关基因座中优先考虑的新候选基因。这一拟议 这项研究意义重大，因为它将填补白内障遗传学的一个重要空白， 对白内障发病机理的深入了解。该项目是创新的发展， 基于遗传和非遗传风险因素的白内障风险预测模型以及 新型白内障动物模型。这项研究的长期目标是提高白内障病因学知识 有效的干预措施和非手术疗法，以预防、延迟或治疗。