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.

帕金森病 (PD) 是增长最快的神经系统疾病，预计其在全球范围内患病率 到 2040 年，这一数字将翻一番，一些人将这一趋势称为“PD 流行病”。疾病缓解 迫切需要早期或症状前阶段的治疗方法和更好的检测方法 人类遗传学研究的数据使我们更接近这些目标。不幸的是，此类研究 很大程度上排除了非欧洲血统的个人，这有可能进一步恶化现有的健康差距 少数民族人口。该项目旨在通过研究遗传结构来解决这一知识差距 百万退伍军人计划 (MVP) 和其他群体的非裔美国人和拉丁裔参与者的 PD。 为该项目组建的研究团队在临床运动障碍方面拥有丰富的专业知识， 生物信息学、分子遗传学和统计遗传学，具有绘制疾病图谱的专业知识 “混合”（混合血统）群体中的基因。同一组研究人员最近发表了第一篇 也是迄今为止唯一在PD中进行的混合图分析和全基因组关联研究（GWAS） 拉丁裔人口（基于拉丁美洲遗传学研究联盟的一项队列研究） 帕金森病 [LARGE-PD]）。 基本方法是执行两种互补的技术（1）混合映射， 利用当地血统来识别基因组区域的技术，其中血统来自特定 与对照相比，在病例中祖先群体的遗传更为频繁，以及（2）拖拉机 GWAS，一种新的分析方法 与传统的 GWAS 方法不同，该方法旨在适应混合个体。一个发现 样本将使用 MVP 和退伍军人帕金森病遗传学计划 (Vet- PD）和复制样本将由 LARGE-PD 和几个公开可用的数据集组装而成。 首先将在发现样本上执行混合物映射和拖拉机 GWAS，分析每个样本 祖先群体分开，所有群体合并。我们还将执行“关联的变体集测试” 使用注释信息”（STAAR）对罕见变异进行以基因为中心的关联测试 适用于单标记分析（例如 GWAS）。这些过程将在 Replication 中重复 样品来验证结果。将使用组合对发现的候选区域进行优先级排序 (1) 基因组上的物理位置（位置作图），(2) 表达数量性状基因座 (eQTL) 作图，以及（3）染色质相互作用作图。 此外，还将计算多基因风险评分（PRS）。 PRS 是对个体遗传基因的估计 根据其基因型谱和相关 GWAS 数据计算对某种性状或疾病的责任。这些 评分已应用于越来越多的疾病，最终目标是风险分层 其次是临床干预。但基于 GWAS 的 PRS 模型来自欧洲血统的个体 当应用于非欧洲人群时通常不太准确。因此，PRS 模型将 由发现样本的欧洲、非洲和拉丁美洲成分及其 将比较所有三个亚组的表现（例如，拉丁裔与非裔美国人、拉丁裔与非裔美国人） 欧洲美国人）。最后，该项目的结果将与任何其他项目的结果进行交叉验证 未来几年可用的合适研究。 该项目的结果将有助于更好地了解非洲帕金森病的遗传结构 美国人和拉丁美洲人这很重要，原因有两个。首先，它使这个领域更接近于更加公平 未来几年遗传信息在临床决策中应用的平衡（例如 PRS 模型）。 其次，它开始释放在非欧洲人群中发现新的 PD 基因的潜力，这将 进一步加深我们对 PD 病理生理学的理解。