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被定义为晶状体混浊，是全世界失明的主要原因。白内障也是 与跌倒伤害和死亡率增加有关，是美国的一个重大公共卫生问题， 约占与视力相关的 Medicare 费用的 60%。鉴于美国人口老龄化，白内障 预计未来 25 年手术需求将翻一番。因此，了解该病的病因非常重要 白内障识别高危患者并制定有效的预防策略。近期，我们进行了一次大型的—— 对白内障进行的大规模多种族全基因组关联研究 (GWAS) 荟萃分析已确定了 55 遗传位点，包括 38 个新位点，是白内障风险的基础。这些基因座中的大多数基因是 数据库 iSyTE（集成系统工具）独立支持作为白内障的有希望的候选者 眼基因发现），基于它们在晶状体中的显着表达。虽然这些数据揭示了潜力 已识别位点中的新因果基因，它们在晶状体中的功能尚未确定，并且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在不同人群中有何不同 组织尚未被探索。我们的研究还发现白内障和白内障之间存在很强的遗传相关性 多种疾病/特征，包括青光眼、近视、吸烟和体重指数，支持以前的 观察性研究。然而，尚不清楚这些关联是否存在因果关系。最后，不存在预测工具 用于评估有白内障风险的个人。该提案的总体目标是了解角色 研究白内障病因的遗传和非遗传因素以及因果机制，并制定 促进白内障风险分层筛查的预测工具。通过利用丰富的多种族群体， 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，并使用 英国生物银行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 目标：1.a) 使用高质量的 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) 评估是否患有青光眼、近视屈光不正、糖尿病、高血压 血压、高体重指数、吸烟或饮酒以及其他临床和行为因素 是使用孟德尔随机化方法的白内障的因果危险因素； 2）开发风险预测模型 通过将多基因风险评分与其他风险因素相结合来评估白内障风险； 3) 确定函数 – 在使用动物模型的晶状体中——优先考虑白内障相关基因座的新候选基因。这个提议 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，并将提供重要的信息 对白内障发病机制的机制见解。该项目的开发具有创新性 基于遗传和非遗传风险因素的白内障风险预测模型以及开发 新的白内障动物模型。这项研究的长期目标是推进白内障病因学知识 寻求有效的干预措施和非手术疗法来预防、延迟或治疗。