Early Cognitive Impairment as a function of Alzheimer's Disease and Trauma

阿尔茨海默病和创伤导致的早期认知障碍

• 批准号: 10479319
• 负责人: MARK W LOGUE
• 金额: --
• 依托单位: VA BOSTON HEALTH CARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10479319
• 关键词: Address; African; African American; African ancestry; Age; Age-associated memory impairment; Aging; Algorithms; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Area; Benchmarking; Blood Vessels; Clinical; Cognitive; Cohort Studies; Complex; Computerized Medical Record; Craniocerebral Trauma; Data; Dementia; Development; Diabetes Mellitus; Diagnosis; Disparity; Early Diagnosis; Environment; Environmental Exposure; Environmental Risk Factor; Genes; Genetic; Genetic Diseases; Genetic Risk; Genome; Genomics; Genotype; Health; Hispanic; Hispanic Populations; Hispanic ancestry; Impaired cognition; Individual; International Classification of Disease Codes; Knowledge; Late Onset Alzheimer Disease; Link; Machine Learning; Medical Records; Methods; Military Personnel; Not Hispanic or Latino; Participant; Pathology; Patient Self-Report; Patients; Performance; Phenotype; Population; Post-Traumatic Stress Disorders; Prevalence; Proxy; Psychopathology; Reporting; Research Priority; Risk; Risk Factors; Sensitivity and Specificity; Source; Techniques; Toxin; Trauma; Traumatic Brain Injury; Variant; Vascular Dementia; Veterans; Work; agent orange; biobank; cognitive testing; cohort; combat; combat trauma; dementia risk; disorder risk; effective therapy; follow-up; gene environment interaction; genetic analysis; genetic architecture; genetic association; genetic risk factor; genetic variant; genome wide association study; genome-wide; health disparity; improved; machine learning method; mild cognitive impairment; phenotyping algorithm; polygenic risk score; programs; risk prediction; risk variant; symptomatology

Risk for dementia, including late-onset Alzheimer’s disease (AD) and vascular dementia, is determined by a complex mix of environmental, health, and genetic factors. Veterans have higher rates of vascular problems, PTSD, combat trauma, and traumatic brain injuries, which have all been linked to increased rates of age-related cognitive impairment and dementia. Further, studies have indicated that these Veteran-relevant exposures may interact with AD genetics to further increase the risk of cognitive decline. This application represents an outgrowth of a project examining dementia and combat related gene by environment (GxE) interactions in the Million Veteran Program (MVP), one of the world’s largest electronic-medical record (EMR) linked biobanks. The original 2-year MVP Gamma project (MVP015) generated working definitions of mild cognitive impairment (MCI), AD, and all-cause dementia from the VA EMR. These were examined for association with combat exposure, head injury, and PTSD in aging Veterans. We found evidence that head injury, combat, PTSD symptomatology, and AD genetic risk variants were all associated with self-reported cognitive difficulties and MCI in Veterans as young as 45-55, and with AD and related dementias in those age 65+. We additionally identified GxE interactions between candidate variants in several genes and combat/head injury on MCI and AD risk. In this application, we propose expanding on the initial study, by 1) performing a genome wide association study (GWAS) of Dementia cases and controls in multiple ancestry groups as well as examining the performance of GWAS-based genetic risk scores in African American and Hispanic MVP participants, 2) performing multivariate GxE analyses examining a range of Veteran relevant health exposures, 3) Further developing and validating dementia diagnoses in MVP for genetic analyses including a machine learning based method of identification of Dementia cases. This project will expand on our continuing work and increase our knowledge of the impact of Veteran specific environmental exposures and their interactions with AD genes on risk for AD and dementia.

痴呆症的风险，包括晚发性阿尔茨海默病(AD)和血管性痴呆症， 由环境、健康和遗传因素的复杂组合决定的。退伍军人有 血管问题、创伤后应激障碍、战斗创伤和创伤性脑损伤的发生率更高， 所有这些都与年龄相关的认知障碍和痴呆症的发生率增加有关。 此外，研究表明，这些与退伍军人相关的暴露可能与AD相互作用 遗传因素会进一步增加认知功能衰退的风险。此应用程序表示一个 按环境检查痴呆症和战斗相关基因的项目的结果(GxE) 百万退伍军人计划(MVP)中的互动，世界上最大的电子医疗之一 记录(EMR)链接的生物库。最初为期2年的MVP Gamma项目(MVP015)产生 来自退伍军人事务部的轻度认知障碍(MCI)、阿尔茨海默病和全因痴呆症的工作定义 电子病历。他们检查了这些疾病与战斗暴露、头部损伤和创伤后应激障碍的关系。 上了年纪的老兵。我们发现有证据表明，头部损伤、战斗、创伤后应激障碍症状和阿尔茨海默病 遗传风险变异都与自我报告的认知困难和MCI有关 退伍军人年龄在45-55岁之间，65岁以上的人患有阿尔茨海默病和相关痴呆。我们 另外还发现了几个基因和候选变异之间的GxE相互作用 战斗/头部损伤对MCI和AD风险的影响。在此应用程序中，我们建议在初始 研究，通过1)对痴呆症病例和 多个祖先组中的控制以及检查基于GWAS的性能 非洲裔美国人和西班牙裔MVP参与者的遗传风险评分，2)表演 检查一系列退伍军人相关健康暴露的多变量GxE分析，3)进一步 开发和验证用于包括机器在内的遗传分析的MVP中的痴呆诊断 基于学习的痴呆症病例识别方法。这个项目将扩大我们的 继续工作并增加对退伍军人特定环境的影响的知识 暴露及其与AD基因的相互作用对AD和痴呆风险的影响。