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

基本信息

批准号：
10687255
负责人：
Chloé Sarnowski
金额：
$ 24.19万
依托单位：
UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2025-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10687255
关键词：
Address Aging Alzheimer&apos s Disease Alzheimer&apos 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 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 apolipoprotein E-4 brain cell brain health brain tissue career career development design endophenotype experience feature selection 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

项目摘要

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.

项目摘要 /摘要胰岛素抵抗（IR）是阿尔茨海默氏病（AD）的主要危险因素，但IR的机制如果IR有时与AD相关以及哪些调节机制，则易于AD是未知的，尤其是未知的 IR的基础并为广告做出了贡献。该提案旨在解决科学的这些关键差距通过使用OMIC来评估IR在AD上的因果关系并揭示新调节的知识 IR和AD涉及的机制。首席研究员（PI）Sarnowski博士是统计遗传学家，研究人员的早期职业调查员侧重于识别遗传和环境风险因素复杂的特征。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，延迟或停止AD的发展。总体目标是更好地表征IR有助于AD的机制，并评估它们与已知的不同与AD发病机理有关的机制。中心假设是OMICS将有助于更好地理解并表征IR和AD之间的关系。理由是，OMICS将有助于解散 IR在AD上的作用方式并识别预防和治疗干预措施的目标。在强者的指导下在Framingham心脏研究中，初步结果将通过三个特定目的进行检验：1）确定IR有时与具有各种遗传的Mendelian随机化（MR）框架中的AD有关仪器变量（IVS）； 2）表征使用大脑和血液与AD相关的IR的分子特征 OMIC数据； 3）制定联合测试，以评估与AD相关的IR特征的遗传贡献。在AIM 1中，遗传IV，包括标准和途径特异性遗传风险评分和预测因素将构建机器学习，以使用各种MR来评估IR和AD之间的因果关系方法。在AIM 2中，将进行关联分析以识别IR的大脑和血液质量特征与AD有关。在AIM 3中，将开发新的综合统计方法来评估注释 IR和AD中本地化的OMICS的遗传贡献。职业发展活动将包括培训在AD病理生理学中，多词分析和机器学习技术通过课程，半手，指导和与领先的专家科学家团队合作。这种方法是通过转移而创新的专注于OMICS研究IR和AD涉及的调节机制。拟议的研究很重要由于预期的结果将有助于更好地理解如何提高胰岛素敏感性更好地预防，延迟或停止AD的发展，减少认知能力下降和痴呆症的患病率广告，并在后期促进大脑健康。实现这笔赠款目标的经验将促进 Pi的职业生涯是具有生物信息学专业知识的独立统计遗传学家，以剖析血管风险因素与基因组学相互作用，以影响AD和痴呆症的易感性使用大型OMICS。