GXI Interactions

GXI 交互

• 批准号: 10628511
• 负责人: John Blangero
• 金额: $ 60.95万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10628511
• 关键词: 2019-nCoV; Acute; Acute Respiratory Distress Syndrome; Adult; African; African American population; Age; Age Years; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Amerindian; Anosmia; Argentina; Biological; COVID-19; COVID-19 impact; COVID-19 morbidity; COVID-19 mortality; COVID-19 patient; Caucasians; Cause of Death; Child; China; Cities; Complex; Data; Dementia; Disease; Elderly; Encephalopathies; Environmental Risk Factor; Ethnic Origin; Etiology; Fostering; Future; Gene Expression; Gene Frequency; Genes; Genetic; Genetic Variation; Genotype; Heritability; Hypoxic-Ischemic Brain Injury; Impaired cognition; Individual; Infection; Joints; Measures; Methods; Mexican Americans; Modeling; Morbidity - disease rate; Native Americans; Nerve Degeneration; Nervous System Physiology; Neurobiology; Neurocognitive; Neurologic; Neurons; Neuropathy; Parkinson Disease; Pathologic; Pathology; Pathway interactions; Patients; Persons; Phenotype; Pneumonia; Population; Population Heterogeneity; Predisposition; Prevalence; Proteins; Public Health; Puerto Rican; Recording of previous events; Risk; SARS-CoV-2 infection; South American; Stroke; Symptoms; Testing; Time; Variant; acute hypoxemic respiratory failure; aging brain; blood-based biomarker; brain based; cohort; dementia risk; design; endophenotype; experience; genetic architecture; genetic epidemiology; genome-wide; health care service utilization; high risk; human old age (65+); identity by descent; improved; insight; inter-individual variation; mortality; nervous system disorder; neuroimaging; neuropsychiatry; pandemic disease; response; whole genome

PROJECT SUMMARY/ABSTRACT By 2050, more than 2 billion people worldwide will be over the age of 65, with older adults outnumbering children for the first time in recorded history. This predicted major demographic shift highlights the importance of improving our understanding of factors that contribute to healthy brain aging. Currently, the biological bases of brain aging are poorly understood. Brain aging (often focused on cognitive decline) is characterized by numerous phenotypes that undoubtedly involve multiple environmental and genetic factors. Overtly pathological brain aging is seen in major neurological diseases such as Alzheimer’s disease and related dementias (ADRD); the prevalence of ADRD is expected to double every 20 years. On top of this existing public health crisis, we are now experiencing a global pandemic that appears to negatively influence neurological function. Growing evidence indicates that SARS-CoV-2 infection causes neurological complications of short-term consequence including acute neuropathy, encephalopathy, anosmia, and hypoxic/ischemic brain injury, and longer-term consequences including cognitive impairment and neuropsychiatric disturbances. The interindividual variation in the neurobiological responses to SARS-CoV-2 is marked. As with most complex phenotypes, causal determinants likely include both genetic and environmental factors. However, no genetic epidemiological study has yet considered differential neurophenotypic response to infection. Thus, delineating the genetic architecture of ADRD-relevant neurophenotypic responses to SARS-CoV-2 will offer important biological insights, which in turn could provide strategies for fostering healthy brain aging in the presence of future infectious challenges. Our project will assess the genetic basis of ADRD-relevant endophenotypic response (across a two year period with three examinations) to SARS-CoV-2 infection in a set of older (>60 years of age) adults from diverse populations (Amerindians from Argentina [ n=3000], US Native Americans [n=250], Mexican Americans [n=500], Puerto Ricans [n=125], African Americans [n=125], and Africans [n=300]) using whole genome sequence (WGS) data in a case/control design (75% post-infection cases, 25% never infected controls). The data generated will enable estimating the importance of genetics in disease response and the identification of key genes involved in the response. Our specific aims are to: 1) detect genetic influences on endophenotypic responses to SARS-CoV-2 infection using WGS data through testing for genotype×infection interaction in neurocognitive measures (neurocognitive measures, neuroimaging measures, and blood-based biomarkers); 2) search for sequence variation in genes and gene pathways influencing response to SARS-CoV-2 infection; and 3) test whether between-population variation in mean responses to infection has a genetic component. This project represents the genetic component of a large, integrated U19 application to examine the effect of COVID-19 on risk for ADRD in understudied ethnicities. Through the proposed project, we will identify causal genetic factors that underly differential response in ADRD risk to COVID-19.

项目摘要/摘要 到2050年，全球65岁以上的人口将超过20亿，老年人的数量将超过 这在有记录的历史上是第一次。这一预测的重大人口结构转变突显了 提高我们对有助于大脑健康老化的因素的理解。目前，生物基础 人们对大脑老化的原因知之甚少。大脑老化(通常集中在认知能力下降)的特点是 大量的表型无疑涉及多种环境和遗传因素。公开地 病理性脑老化见于阿尔茨海默病等主要神经系统疾病及相关疾病 痴呆症(ADRD)；ADRD的患病率预计每20年翻一番。在现有的基础上 公共卫生危机，我们现在正在经历一场全球大流行，似乎对 神经功能。越来越多的证据表明，SARS-CoV-2感染会导致神经系统 短期后果的并发症包括急性神经病、脑病、嗅觉障碍和 缺氧/缺血性脑损伤，以及包括认知障碍和 神经精神障碍。 SARS-CoV-2对SARS-CoV-2的神经生物学反应个体间差异显著。和大多数人一样 表型复杂，因果决定因素可能包括遗传和环境因素。然而，没有 遗传流行病学研究尚未考虑对感染的不同神经表型反应。因此， 描绘对SARS-CoV-2的ADRD相关神经表型反应的遗传结构将提供 重要的生物学见解，这反过来又可以为促进健康的大脑衰老提供策略 未来传染性挑战的存在。我们的项目将评估ADRD相关的遗传基础 一组SARS-CoV-2感染的内表型反应(跨越两年的三次检查) 来自不同人群的老年人(60岁)(来自阿根廷的美洲印第安人[n=3000]，美国原住民 美国人[n=250]，墨西哥裔美国人[n=500]，波多黎各人[n=125]，非裔美国人[n=125]，以及 非洲人[n=300])在病例/对照设计中使用全基因组序列(WGS)数据(75%感染后 病例中，25%从未感染对照组)。所产生的数据将使我们能够估计遗传学在 疾病反应以及参与反应的关键基因的识别。我们的具体目标是：1) 通过WGS数据检测遗传对SARS-CoV-2感染内表型反应的影响 神经认知测量(神经认知测量、神经成像)中的基因×感染交互作用测试 方法和基于血液的生物标记物)；2)搜索基因和基因途径的序列变异 影响对SARS-CoV-2感染的反应；以及3)检验种群间的平均值是否存在差异 对感染的反应有遗传成分。这个项目代表了一个大型的， 整合U19应用程序，以检查新冠肺炎对研究不足的种族中ADRD风险的影响。 通过拟议的项目，我们将确定导致ADRD反应不完全的原因遗传因素 新冠肺炎面临的风险。