Statistical Genetics Methods for Mixed Pathologies

混合病理学的统计遗传学方法

基本信息

批准号：
8848016
负责人：
David William Fardo
金额：
$ 14.84万
依托单位：
UNIVERSITY OF KENTUCKY
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-08-15 至 2017-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8848016
关键词：
Achievement Age Aging Alzheimer&apos s Disease Alzheimer&apos s disease model Applications Grants Area Autopsy Biological Biometry Brain Brain Diseases Brain Pathology Classification Clinical Complex Data Data Set Data Storage and Retrieval Databases Dementia Detection Development Diagnosis Disease Disease Progression Drug Targeting Elderly Funding Genes Genetic Genetic Predisposition to Disease Genetic Risk Genetic Variation Goals Health Hippocampus (Brain)Impaired cognition Impairment Intervention Investigation Knowledge Lewy Body Dementia Link Memory Mentors Methodology Methods Modeling Multicenter Studies National Institute on Aging Neurodegenerative Disorders Outcome Pathology Phenotype Postdoctoral Fellow Predisposition Prevention Process Quality Control Religion and Spirituality Research Research Personnel Research Training Resources Risk Factors Sclerosis Series Single Nucleotide Polymorphism Site Susceptibility Gene Testing Training Training Programs United States National Institutes of Health Vascular Dementia Work age related aging brain base career career development case control clinical Diagnosis cohort disease diagnosis endophenotype experience gene environment interaction genetic approach genetic association genetic risk factor genome wide association study genome-wide improved insight interest mixed dementia neuroimaging neuropathology novel programs responsible research conduct risk variant skills

项目摘要

DESCRIPTION (provided by applicant): This mentored career development grant application proposes a training program to integrate Dr. Fardo's previous research in biostatistics and statistical genetics into investigations of aging disorders including highly prevalent neurodegenerative diseases. His long-term career goal is to develop an independent research program focusing on the advancement of statistical methodologies to understand the genetics underlying complex diseases, with an emphasis on diseases of brain aging. This will be achieved through acquiring knowledge in the area of brain diseases of aging through formal coursework and mentored experiences; training in the management, analysis and interpretation of associated research data; comprehensive examination of the large-scale genetic data used in aging studies and the areas where novel, cutting-edge biostatistical methodologies could improve analyses; application, refinement and development of statistical genetic approaches to the analysis of this large-scale genetic data; and the continuation of training in the responsible conduct of research. Dr. Fardo's research training will involve an enthusiastic team of cross- disciplinary researchers with a strong research track record. An overall goal of this K25 application is to capitalize on the clinical and neuropathologic data available from large, multicenter-derived databases to identify single nucleotide polymorphisms (SNPs) associated with specific neuropathologic endophenotypes. Most research investigating the genetic predisposition of age-related complex diseases has been conceptualized with a model directly comparing those with or without a disease, for example, with or without Alzheimer's disease (AD). However, this disease/non-disease approach is inefficient and not appropriate for investigating the genetic risk factors for so-called mixed pathologies which are the norm in advanced age. The proposed research program will interrogate genetic associations with neuropathologic features of a large cohort of autopsied brains. This will be done by utilizing data collected from large, NIH-funded resources. Neuropathology data and genome-wide genetic data will be merged from these resources, and genetic associations for mixed-pathology dementias and neuropathologic features will be comprehensively tested. This work will result in new methods to analyze mixed-pathology dementias and neuropathologic features as well as the exploration of associated genetic risk factors and gene-environment interactions.

描述（由申请人提供）：这份指导性职业发展补助金申请提出了一项培训计划，将 Fardo 博士之前在生物统计学和统计遗传学方面的研究整合到衰老疾病（包括高度流行的神经退行性疾病）的研究中。他的长期职业目标是开发一个独立的研究项目，重点关注统计方法的进步，以了解复杂疾病的遗传学，重点是脑衰老疾病。这将通过正规课程和指导经验获取衰老脑部疾病领域的知识来实现；相关研究数据的管理、分析和解释培训；全面检查老龄化研究中使用的大规模遗传数据以及新颖、前沿的生物统计方法可以改进分析的领域；应用、完善和发展统计遗传学方法来分析这种大规模遗传数据；以及继续进行负责任的研究培训。 Fardo 博士的研究培训将由一支热情的、具有良好研究记录的跨学科研究人员团队参与。该 K25 应用程序的总体目标是利用来自大型多中心数据库的临床和神经病理学数据来识别与特定神经病理学内表型相关的单核苷酸多态性 (SNP)。大多数研究与年龄相关的复杂疾病的遗传易感性的研究都是通过直接比较患有或不患有疾病（例如患有或不患有阿尔茨海默病（AD））的模型来概念化的。然而，这种疾病/非疾病方法效率低下，不适合研究所谓的混合病理的遗传风险因素，而混合病理是老年的常态。拟议的研究计划将调查大量尸检大脑的遗传与神经病理学特征的关联。这将通过利用数据来完成从 NIH 资助的大型资源中收集。神经病理学数据和全基因组遗传数据将从这些资源中合并，并将全面测试混合病理性痴呆和神经病理学特征的遗传关联。这项工作将产生分析混合病理性痴呆和神经病理学特征的新方法，并探索相关的遗传风险因素和基因-环境相互作用。