New York Center for Collaborative Research in Common Disease Genomics

纽约常见疾病基因组学合作研究中心

• 批准号: 9050000
• 负责人: ROBERT B DARNELL
• 金额: $ 1000万
• 依托单位: NEW YORK GENOME CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-14 至 2019-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9050000
• 关键词: Address; Admixture; Algorithms; Alleles; Alzheimer' s Disease; Architecture; Asthma; Autistic Disorder; Biological Assay; Clinical Data; Code; Collaborations; Collection; Communities; Comorbidity; Complex; Computing Methodologies; Data; Data Set; Databases; Disease; Ethnic Origin; Exhibits; Family; Foundations; Future; Gene Frequency; Genes; Genetic; Genetic Risk; Genetic Variation; Genome; Genomics; Genotype; Goals; Healthcare; Hereditary Disease; Heterogeneity; Human; Human Genome; Individual; Joints; Late-Onset Disorder; Link; Methods; Microfluidics; Mining; Modeling; Mutation; New York; Nucleotides; Outcomes Research; Pathway interactions; Patient-Focused Outcomes; Patients; Phenotype; Physicians; Population; Population Heterogeneity; Prevention; Public Health; RNA; Reading; Research; Research Design; Research Institute; Resources; Risk; Sampling; Sequence Analysis; Statistical Models; Technology; Time; United States; Variant; base; cohort; computerized data processing; cost; data access; deep sequencing; disorder prevention; drug development; early onset; epigenomics; ethnic diversity; falls; fitness; frontier; gene interaction; genetic variant; genome sequencing; improved; innovation; insight; next generation; novel; rare variant; reproductive; screening; sequencing platform; tool; whole genome

In this proposal, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease- associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort will be put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants. We will explore a wide spectrum of human variation using the WGS platform, including rare variants of modest to large effect, de novo variants of large effect, and common variants of small effect. We will combine available RNA and epigenomic datasets to predict modes of action of risk and identify protective alleles. These results, combined with the integration of environmental and clinical data, will enhance our understanding of genetic risk for common disease and lay the groundwork for utilization of personal genomics in disease prevention and treatment, including the delineation of pathways for drug development. Many of the population cohorts proposed for study are from New York, which harbors the most diverse population in the world. Analyzing diverse populations is a critical component of comprehensive common disease analysis, as effect sizes of individual alleles are believed to vary in different populations due to gene- gene interactions. Using the genetic admixture present in different populations from NY and throughout the United States, we will conduct the first systematic study of these interaction effects in many phenotypes. These aims will be accomplished through widespread collaborations, with genomicists, physicians, and patients, organized through a focused team at NYGC. They will be enriched by the collaboration and support from independent Foundations.

在这项提案中，我们解决了常见的复杂疾病对基因组造成的巨大挑战 分析以及超越这些分析为推进医疗保健提供了巨大的机会。常见的 此处建议研究的遗传性疾病被认为具有极端的位点异质性，需要 分析大量样本以全面识别其背后的基因组变异。我们 建议将深入的群体研究与 SNP、插入缺失和结构的联合分析相结合 编码区和非编码区的变异将提供对共同遗传的新水平的理解 失调。全基因组测序（WGS）对于下一代基因组学方法至关重要 的复杂疾病。 WGS 需要具备生成和处理非常多的信息的技术能力。 大数据集是 NYGC 的特别关注点和优势。 WGS 还需要伴随新的 统计工具和算法，将由致力于该提案的强大核心小组开发。 该提案的首要目标是利用全基因组测序的力量来识别疾病—— 个体核苷酸水平上的相关变异。在许多情况下，致病性突变落在非编码区域 基因组的区域，只有通过全基因组测序才能有效地探索这些区域。将大力投入建设 新的计算策略对非编码转录序列进行功能注释，并构建新的 数据集来实现此类策略，开辟了理解疾病相关监管的新领域 变种。我们将使用 WGS 平台探索广泛的人类变异，包括罕见变异 中度到大效应、大效应的从头变体以及小效应的常见变体。我们将 结合可用的 RNA 和表观基因组数据集来预测风险的作用模式并确定保护性 等位基因。这些结果与环境和临床数据的整合相结合，将增强我们的 了解常见疾病的遗传风险，并为个人基因组学的利用奠定基础 疾病预防和治疗，包括描绘药物开发途径。 提议进行研究的许多人群来自纽约，这里拥有最多样化的人群 世界人口。分析不同人群是全面共同认识的重要组成部分 疾病分析，因为个体等位基因的效应大小被认为在不同人群中由于基因原因而有所不同 基因相互作用。利用纽约和整个地区不同人群中存在的基因混合物 在美国，我们将首次对许多表型中的这些相互作用效应进行系统研究。 这些目标将通过与基因组学家、医生和科学家的广泛合作来实现。 患者，由 NYG​​C 的一个重点团队组织。他们将因合作和支持而变得更加丰富 来自独立基金会。