Non-coding Variants Predisposing to Age-related Macular Degeneration

易患年龄相关性黄斑变性的非编码变异

基本信息

批准号：
8792806
负责人：
Bing Ren
金额：
$ 78.68万
依托单位：
LUDWIG INSTITUTE FOR CANCER RES LTD
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-08-24 至 2018-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8792806
关键词：
Address Affect Age related macular degeneration Alleles Binding Blindness Cell Culture Techniques Cell Line Cell model Cells Clinical Collaborations Collection Complex Computational algorithm Computer Simulation Country DNA Sequence Data Set Diabetes Mellitus Disease Elderly Event Exhibits Gene Expression Genetic Genetic Engineering Genome Genomic Segment Genomics Goals Height Hereditary Disease Human Human Genome Individual Link Linkage Disequilibrium Macular degeneration Mental disorders Methods Modeling Molecular Mutation Nucleotides Other Genetics Patients Persons Phenotype Photoreceptors Physiological Population Probability Recording of previous events Regulation Research Personnel Risk Rodent Model Solutions Structure of retinal pigment epithelium Technology Testing Untranslated RNA Variant disease phenotype genome editing genome sequencing genome wide association study genome-wide analysis improved induced pluripotent stem cell personalized medicine predictive modeling public health relevance trait transcription factor

项目摘要

DESCRIPTION (provided by applicant): The genome of each individual harbors millions of nucleotide variants, and a major challenge is to understand how these variants contribute to phenotypic variations in the population. We propose a combined computational and experimental framework for identifying non-coding variants that affect cellular and physiological traits, with the goal to establish computational models that can predict the probability of exhibiting a physiological trait from the sequences of non-coding genomic regions. This framework involves iterative refinement of model assumptions and parameters with experimentation. To develop the framework and validate the predictive models, we will focus on the disease Age-related Macular Degeneration (AMD), the leading cause of blindness among the elderly in the country. Previous studies have identified a number of sequence variants strongly associated with AMD. We will develop computational models to predict (or narrow down) the set of non-coding sequence variants that contribute to the disease phenotype. As experimental assessment, we will perform genome editing in patient-derived induced pluripotent stem cells (iPSC) to test the consequence of removing or introducing such sequence variants on molecular and cellular phenotypes in cell culture and in rodent models. While the proposed method is developed for AMD, the general approach is expected to apply to other genetic diseases.

描述（由申请人提供）：每个个体的基因组都包含数百万个核苷酸变异，主要的挑战是了解这些变异如何导致群体的表型变异。我们提出了一个用于识别非编码变异的组合计算和实验框架。该框架涉及通过实验对模型假设和参数进行迭代细化，以建立能够预测非编码基因组区域序列表现出生理特征的概率的计算模型。框架并验证预测模型，我们将重点关注年龄相关性黄斑变性（AMD），这是该国老年人失明的主要原因。之前的研究已经确定了许多与 AMD 密切相关的序列变异。开发计算模型来预测（或缩小）导致疾病表型的非编码序列变异集作为实验评估，我们将在患者来源的诱导多能干细胞（iPSC）中进行基因组编辑以测试其结果。去除或引入此类序列变体细胞培养和啮齿动物模型中的分子和细胞表型虽然所提出的方法是针对 AMD 开发的，但该通用方法预计也适用于其他遗传疾病。