Genetic Architecture of Parkinson's Disease in African-American and Latino Veterans

非裔美国人和拉丁裔退伍军人帕金森病的遗传结构

• 批准号: 10703737
• 负责人: CYRUS P ZABETIAN
• 金额: --
• 依托单位: VA PUGET SOUND HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10703737
• 关键词: Address; Affect; African; African American; African American population; African ancestry; American; Area; Bioinformatics; Caregivers; Chromatin; Chromosome Mapping; Clinical; Collaborations; Custom; Data; Data Set; Diagnosis; Disease; Disparity; Distress; Equilibrium; Equity; European; European ancestry; Event; Exclusion; Exhibits; Family; Functional disorder; Future; Gene Frequency; Genes; Genetic; Genetic Diseases; Genetic Research; Genetic study; Genome; Genomics; Genotype; Goals; Human Genetics; Human Genome Diversity Project; Individual; Inherited; Intervention; Knowledge; Label; Latin American; Latino; Latino Population; Learning; Maps; Methods; Minor; Minority Groups; Modeling; Molecular; Molecular Genetics; Movement Disorders; Neurodegenerative Disorders; Neuronal Injury; Nursing Homes; Parkinson Disease; Participant; Pattern; Performance; Persons; Phase; Phenotype; Population; Population Genetics; Positioning Attribute; Prevalence; Process; Publishing; Quality of life; Quantitative Trait Loci; Research; Research Personnel; Resolution; Resources; Risk; Role; Sampling; Signal Transduction; Subgroup; Susceptibility Gene; Techniques; Testing; Therapeutic Intervention; Trans-Omics for Precision Medicine; Variant; Veterans; Work; admixture mapping; analysis pipeline; case control; causal variant; clinical care; clinical decision-making; clinical movement disorder; cohort; design; detection method; disorder risk; experience; gene discovery; genetic architecture; genetic information; genetic risk factor; genome sequencing; genome wide association study; genome-wide; genome-wide analysis; human data; improved; minority health disparity; mortality; nervous system disorder; novel; pandemic disease; polygenic risk score; precision medicine; programs; rare variant; risk stratification; skills; symptom treatment; targeted treatment; trait; trend; whole genome

Parkinson’s disease (PD) is the fastest growing neurological disorder and its worldwide prevalence is expected to double by the year 2040, a trend that some have labeled the “PD pandemic.” Disease disease-modifying therapies and better methods of detection in early or pre-symptomatic phases are desperately needed and data from human genetic studies have moved us much closer to those goals. Unfortunately, such studies have largely excluded individuals of non-European origin which risks further worsening existing health disparities for minority populations. The project seeks to address this gap in knowledge by studying the genetic architecture of PD in African American and Latino participants in the Million Veteran Program (MVP) and other cohorts. The research team assembled for this project has extensive expertise in clinical movement disorders, bioinformatics, molecular genetics, and statistical genetics with specialized knowledge in mapping disease genes in “admixed” (mixed ancestry) populations. This same group of investigators recently published the first and only admixture mapping analysis and genome-wide association study (GWAS) of PD ever conducted in a Latino population (based on a cohort from the Latin American Research Consortium on the Genetics of Parkinson’s Disease [LARGE-PD]). The fundamental approach will be to perform two complementary techniques (1) admixture mapping, a technique that leverages local ancestry to identify regions of the genome where ancestry from a particular ancestral population is inherited more frequently in cases vs controls, and (2) Tractor GWAS, a new analytical approach that unlike traditional GWAS methods is designed to accommodate admixed individuals. A Discovery sample will be created using cohorts from MVP and the Veterans Parkinson’s Disease Genetics Initiative (Vet- PD) and a Replication sample will be assembled from LARGE-PD and several publicly available datasets. Admixture mapping and Tractor GWAS will first be performed on the Discovery Sample, analyzing each ancestry group separately and all groups combined. We will also perform the “variant-set test for association using annotation information” (STAAR) to perform gene-centric association tests of rare variants that are not suitable for single-marker analyses (such as GWAS). These processes will be repeated in the Replication sample to validate results. Prioritization of candidate regions discovered will be performed using a combination of (1) physical position on the genome (positional mapping), (2) expression quantitative trait locus (eQTL) mapping, and (3) chromatin interaction mapping. In addition, polygenic risk scores (PRS) will be calculated. A PRS is an estimate of an individual’s genetic liability to a trait or disease, calculated according to their genotype profile and relevant GWAS data. These scores have been applied to an increasing number of diseases with the eventual goal of risk stratification followed by clinical interventions. But PRS models based on GWAS results from individuals of European origin are often less accurate when applied to non-European populations. Therefore, PRS models will be constructed from the European, African, and Latino components of the Discovery sample and their performance will be compared across all three subgroups (e.g., Latino to African American and Latino to European American). Finally, findings from this project will be cross-validated with results from any other suitable studies that become available in future years. Results from this project will provide a better understanding of the genetic architecture of PD in African Americans and Latinos which is important for two reasons. First it moves the field closer to a more equitable balance in the application of genetic information to clinical decisions in future years (e.g., PRS models). Second, it begins to unlock the potential for new PD gene discovery in non-European populations which will further our understanding of PD pathophysiology.

帕金森氏病（PD）是增长最快的神经系统疾病，其全球患病率有望 到2040年，有些人将“ PD大流行”标记为这一趋势。疾病改良 迫切需要早期或症状阶段的疗法和更好的检测方法 来自人类遗传研究的数据使我们更接近这些目标。不幸的是，这样的研究有 在很大程度上排除了非欧洲血统的人，这有可能进一步担心现有的健康分配 少数群体。该项目旨在通过研究遗传结构来解决知识的差距 在非洲裔美国人和拉丁裔参与者的PD中，百万退伍军人计划（MVP）和其他同伙。 为该项目组装的研究团队在临床运动障碍方面拥有广泛的专业知识， 生物信息学，分子遗传学和统计遗传学具有专业知识，用于映射疾病 “混合”（混合血统）种群中的基因。同一批调查人员最近发表了第一个 并且只有在A中进行的PD的混合映射分析和全基因组关联研究（GWAS） 拉丁裔人口（基于拉丁美洲研究联盟的同类人群 帕金森氏病[大PD]）。 基本方法是执行两种完整的技术（1）混合映射，一个 利用当地血统来识别基因组的区域的技术 祖先人口在vs控件中更频繁地继承，（2）拖拉机GWAS，一种新的分析 与传统GWAS方法不同的方法旨在容纳混合的个体。一个发现 样本将使用MVP和退伍军人帕金森氏病遗传学计划（VET- PD）和复制样本将从大型PD和几个公开可用的数据集中组装。 混合映射和拖拉机GWA将首先在发现样本上进行，分析每个 祖先组分别，所有组合并。我们还将执行“关联的变体测试 使用注释信息”（Staar）执行以基因为中心的稀有变体的测试 适用于单标记分析（例如GWAS）。这些过程将在复制中重复 样本以验证结果。发现的候选区域的优先级将使用组合进行 （1）基因组上的物理位置（位置映射），（2）表达定量性状基因座（EQTL） 映射和（3）染色质相互作用映射。 另外，将计算多基因风险评分（PR）。 PRS是对个人遗传的估计 根据特征或疾病的责任，根据其基因型概况和相关GWAS数据计算。这些 随着风险分层的事件目标，分数已应用于越来越多的疾病 其次是临床干预措施。但是基于GWAS的PRS模型来自欧洲血统的个人 当应用于非欧洲人口时，通常不准确。因此，PRS模型将是 由发现样本的欧洲，非洲和拉丁裔组成部分构建 将比较所有三个子组的性能（例如，拉丁裔到非裔美国人和拉丁裔的拉丁裔 欧美）。最后，该项目的发现将与其他任何结果进行交叉验证 适当的研究将在未来几年中使用。 该项目的结果将更好地了解非洲PD的遗传结构 美国人和拉丁美洲人，这很重要，原因有两个。首先，它使场地更靠近更公平 在未来几年（例如PRS模型）将遗传信息应用于临床决策的应用平衡。 其次，它开始解锁非欧洲人群中新的PD基因发现的潜力 进一步，我们对PD病理生理学的理解。