Statistical Genetics Methods for Mixed Pathologies

混合病理学的统计遗传学方法

• 批准号: 8719903
• 负责人: David William Fardo
• 金额: $ 14.85万
• 依托单位: UNIVERSITY OF KENTUCKY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8719903
• 关键词: Achievement; Age; Aging; Alzheimer' s Disease; Alzheimer' 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; 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 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

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）：这个指导的职业发展资助申请提出了一个培训计划，将Fardo博士以前在生物统计学和统计遗传学方面的研究整合到包括高度流行的神经退行性疾病在内的衰老疾病的调查中。他的长期职业目标是开发一个独立的研究项目，专注于统计方法的进步，以了解复杂疾病的遗传学基础，重点是大脑老化疾病。这将通过以下方式实现：通过正式课程和辅导经验获得老龄化脑疾病领域的知识;在相关研究数据的管理、分析和解释方面进行培训;全面审查老龄化研究中使用的大规模遗传数据以及新的、尖端的生物统计方法可以改进分析的领域;应用、改进和发展遗传统计方法来分析这种大规模的遗传数据;继续进行负责任地进行研究的培训。法尔多博士的研究培训将涉及一个充满热情的跨学科研究人员团队，他们拥有强大的研究记录。该K25应用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，以鉴定与特定神经病理学内表型相关的单核苷酸多态性（SNP）。大多数调查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有或没有疾病的模型来概念化的，例如，有或没有阿尔茨海默病（AD）。然而，这种疾病/非疾病的方法是低效的，不适合调查所谓的混合病理的遗传风险因素，这是在高龄的常态。拟议的研究计划将询问遗传协会与神经病理学特征的一个大队列的尸检大脑。这将通过利用数据来实现。 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，混合病理学痴呆和神经病理学特征的遗传关联将得到全面测试。这项工作将导致新的方法来分析混合病理性痴呆和神经病理学特征，以及探索相关的遗传风险因素和基因-环境相互作用。