Exploring Common Biological Pathways Underlying Insulin Resistance and Alzheimer Disease using Genetic and Omic Tools

使用遗传和组学工具探索胰岛素抵抗和阿尔茨海默病的常见生物途径

• 批准号: 10373944
• 负责人: Chloé Sarnowski
• 金额: $ 8.94万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2022-08-16
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10373944
• 关键词: Address; Aging; Alzheimer' s Disease; Alzheimer' s disease risk; Amyloid; Apoptosis; Bioinformatics; Biological; Biological Markers; Biology; Blood; Blood - brain barrier anatomy; Brain; Brain region; Bypass; Cognition; Collaborations; Complex; DNA Methylation; Data; Dementia; Doctor of Philosophy; Elderly; Environmental Risk Factor; Evaluation; Failure; Framingham Heart Study; Functional disorder; Gene Expression; Genes; Genetic; Genetic Annotation; Genetic Risk; Genetic study; Genomics; Glucose; Goals; Grant; Impaired cognition; Individual; Insulin; Insulin Resistance; Joints; Knowledge; Late Onset Alzheimer Disease; Lead; Learning; Machine Learning; Measures; Memory; Mendelian randomization; Mentorship; Methods; Mission; Molecular Profiling; Nerve Degeneration; Neurofibrillary Tangles; Obesity; Outcome; Pathogenesis; Pathway interactions; Patients; Phase; Plasma; Predisposition; Prevalence; Principal Investigator; Public Health; Research; Research Personnel; Research Project Grants; Risk Factors; Role; Scientist; Senile Plaques; Statistical Methods; Techniques; Testing; Therapeutic Intervention; Tissues; Training; Trans-Omics for Precision Medicine; United States National Institutes of Health; base; brain cell; brain health; brain tissue; career; career development; design; endophenotype; experience; genetic resistance; genetic risk factor; genetic variant; genomic locus; human disease; improved; innovation; insight; instrument; insulin sensitivity; mild cognitive impairment; multiple omics; neuroimaging; novel; peripheral blood; prevent; preventive intervention; programs; religious order study; tau Proteins; tissue resource; tool; trait; transcriptome sequencing; treatment response; vascular risk factor; whole genome

Project Summary / Abstract Insulin resistance (IR) is a major risk factor for Alzheimer’s disease (AD) but the mechanisms by which IR predisposes to AD is unknown, notably, if IR is causally related to AD and which regulatory mechanisms underlie IR and contribute to AD. The proposal is designed to address these critical gaps in scientific knowledge by using omics to evaluate the causal relationship of IR on AD and to reveal new regulatory mechanisms involved in IR and AD. The Principal Investigator (PI), Dr. Sarnowski, is a statistical geneticist and an early career investigator with a research focus on the identification of genetic and environmental risk factors of complex traits. The long-term goal of this project is to identify individuals who will benefit from treatments improving insulin sensitivity to better prevent, delay or stop the progression of AD. The overall objective is to better characterize mechanisms by which IR contributes to AD and evaluate how they may differ from known mechanisms involved in AD pathogenesis. The central hypothesis is that omics will help to better understand and characterize the relationships between IR and AD. The rationale is that omics will help to disentangle the mode of action of IR on AD and identify targets for preventive and therapeutic interventions. Guided by strong preliminary results in the Framingham Heart Study, the hypothesis will be tested through three specific aims: 1) Determine if IR is causally related to AD in a Mendelian Randomization (MR) framework with various genetic instrument variables (IVs); 2) Characterize molecular signatures of IR associated with AD using brain and blood omic data; and 3) Develop a joint test to evaluate the genetic contribution at IR signatures associated with AD. In Aim 1, genetic IVs, including standard and pathway-specific genetic risk scores and predictors identified by machine learning, will be constructed to evaluate the causal relationships between IR and AD using various MR methods. In Aim 2, association analyses will be performed to identify brain and blood omic signatures of IR related to AD. In Aim 3, new integrative statistical methods leveraging annotations will be developed to evaluate the genetic contribution on omics at loci involved in IR and AD. Career development activities will include training in AD pathophysiology, multi-omic analysis and machine learning techniques through coursework, seminars, mentorship, and collaborations with a team of leading expert scientists. The approach is innovative by shifting focus to omics to study the regulatory mechanisms involved in IR and AD. The proposed research is significant as the expected outcomes will contribute to a better understanding of how insulin sensitivity can be improved to better prevent, delay or stop the progression of AD, reduce cognitive decline and prevalence of dementia due to AD, and promote brain health in late life. The experience acquired in achieving the aims of this grant will advance the PI’s career to an independent statistical geneticist with bioinformatics expertise, to dissect how vascular risk factors interact with genomics to influence AD and dementia susceptibility using large-scale omics.

项目概要/摘要 胰岛素抵抗 (IR) 是阿尔茨海默病 (AD) 的主要危险因素，但 IR 的机制 易患 AD 尚不清楚，尤其是 IR 是否与 AD 存在因果关系以及哪些调节机制 是 IR 的基础并有助于 AD。该提案旨在解决科学方面的这些关键差距 通过使用组学来评估 IR 对 AD 的因果关系并揭示新的监管知识 IR 和 AD 涉及的机制。首席研究员 (PI) Sarnowski 博士是一位统计遗传学家， 早期职业调查员，研究重点是遗传和环境风险因素的识别 的复杂特征。该项目的长期目标是确定将从治疗中受益的个人 提高胰岛素敏感性，以更好地预防、延缓或阻止 AD 的进展。总体目标是 更好地描述 IR 促进 AD 的机制，并评估它们与已知的机制有何不同 AD 发病机制。中心假设是组学将有助于更好地理解 并描述 IR 和 AD 之间的关系。理由是组学将有助于理清 IR 对 AD 的作用方式并确定预防和治疗干预的目标。强者引导 根据弗雷明汉心脏研究的初步结果，该假设将通过三个具体目标进行检验：1) 在具有各种遗传因素的孟德尔随机化 (MR) 框架中确定 IR 是否与 AD 存在因果关系 工具变量（IV）； 2) 使用大脑和血液表征与 AD 相关的 IR 分子特征 组学数据； 3) 开发联合测试来评估与 AD 相关的 IR 特征的遗传贡献。 在目标 1 中，遗传 IV，包括标准和特定路径遗传风险评分以及由 机器学习，将使用各种 MR 来评估 IR 和 AD 之间的因果关系 方法。在目标 2 中，将进行关联分析来识别 IR 的大脑和血液组学特征 与AD有关。在目标 3 中，将开发利用注释的新综合统计方法来评估 IR 和 AD 相关位点对组学的遗传贡献。职业发展活动将包括培训 通过课程作业、研讨会，了解 AD 病理生理学、多组学分析和机器学习技术 指导以及与领先专家科学家团队的合作。该方法的创新在于转变 重点关注组学研究 IR 和 AD 的调控机制。拟议的研究意义重大 因为预期结果将有助于更好地了解如何提高胰岛素敏感性 更好地预防、延缓或阻止 AD 的进展，减少认知能力下降和痴呆症的患病率 AD，并促进晚年大脑健康。在实现这笔赠款的目标中获得的经验将促进 PI 的职业生涯为具有生物信息学专业知识的独立统计遗传学家，剖析血管风险如何 使用大规模组学，因素与基因组学相互作用，影响 AD 和痴呆症的易感性。