Integration of Bio-, Medical, and Imaging Informatics for Complex Diseases

描述(由申请人提供)：我是美国国家医学图书馆(NLM)生物医学信息学(BMI)研究员，在雷根斯特里夫研究所和印第安纳大学医学院(IUSM)神经成像中心(IUSM)工作。我的职业目标是成为一名成功的独立研究员，专注于整合生物、医学和成像信息学方法，包括下一代测序(NGS)和先进的神经成像，以增强对复杂疾病机制的理解，从而促进新疗法的开发。NLM BMI培训计划是一次无价的经历，使我能够成功地将我的职业生涯从计算物理过渡到生物医学信息学。在我三年的NLM BMI奖学金期间，我在高级医学成像分析、医学信息学、生物信息学、基因组学和统计学方面获得了丰富的经验，为实现我的职业目标做好了准备。为了巩固我的跨学科技能并完成向独立研究人员的过渡，我的直接职业目标是应用和扩展我的方法论技能，并对BMI中当前的生物学知识和未来的计算挑战有更广泛的理解。利用正在进行的阿尔茨海默病神经成像计划(ADNI)的全外显子组测序试点项目数据作为初始学习平台，我将综合使用生物、医学和成像信息学策略，以确定与从轻度认知障碍(MCI)到阿尔茨海默病(AD)进展相关的中间多模式表型相关的功能罕见变体。先前的研究已经确定了大量常见的遗传变异，但AD的遗传性中有相当大一部分仍未被已知的易感基因解释。NGS可以通过罕见的变异检测来帮助缩小差距。拟议的研究计划建立在我之前使用成像和医学信息学表型进行全基因组关联研究(GWAS)工作的基础上，并将把我的专业知识扩展到NGS。丰富的ADNI数据集提供了一个独特的机会来解决我的特定目标中提出的挑战，而IU神经成像中心作为ADNI遗传学核心，极大地促进了数据访问和专家协助。具体目标：(1)识别与MCI/AD诊断相关的中间表型生物标志物的子集，用于在全ADNI样本集中进行遗传关联分析；(2)在ADNI全外显子组测序试点项目中，对罕见的变异与与MCI/AD相关的中间表型生物标记物进行基于基因集的关联分析；以及(3)通过输入全ADNI样本集中被检测基因的靶区并对其进行基因分型，验证新的变异和风险基因。与公共健康相关：在美国，AD是一种越来越常见的神经退行性疾病，是第六大主要死亡原因。识别新的易感基因座 功能对MCI进展的影响将增强关于AD通路的机制知识，并可能使早期诊断和治疗成为可能。

DESCRIPTION (provided by applicant): I am a National Library of Medicine (NLM) Biomedical Informatics (BMI) fellow at both the Regenstrief Institute and the Center for Neuroimaging at Indiana University School of Medicine (IUSM). My career goal is to become a successful independent investigator with a focus on integrating bio-, medical, and imaging informatics approaches, including next generation sequencing (NGS) and advanced neuroimaging, to enhance the understanding of complex disease mechanisms and thereby facilitate development of novel treatments. The NLM BMI training program has been a priceless experience that enabled me to successfully transition my career from computational physics to biomedical informatics. During my three year NLM BMI fellowship, I gained extensive experience in advanced medical imaging analysis, medical informatics, bioinformatics, genomics, and statistics to prepare me to achieve my career goal. In order to consolidate my transdisciplinary skills and complete the transition to an independent researcher, my immediate career objective is to apply and expand my methodological skills and gain a broader understanding of current biological knowledge and future computational challenges in BMI. Using whole- exome sequencing pilot project data from the ongoing Alzheimer's Disease Neuroimaging Initiative (ADNI) as an initial learning platform, I will employ bio-, medical, and imaging informatics strategies in an integrated manner to identify functional rare variants associated with intermediate multi-modality phenotypes related to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Prior studies have identified a large number of common genetic variants but a substantial proportion of the heritability of AD remains unexplained by the known susceptibility genes. NGS can help close the gap by rare variant detection. The proposed research plan builds on my previous work in genome-wide association studies (GWAS) using imaging and medical informatics phenotypes and will expand my expertise to NGS. The rich ADNI data set provides a unique opportunity to address the challenges proposed in my specific aims and the IU Center for Neuroimaging serves as the ADNI Genetics Core which greatly facilitates data access and expert assistance. Specific aims: (1) identify a subset of intermediate phenotypic biomarkers associated with a diagnosis of MCI/AD for genetic association analysis in the full ADNI sample set; (2) perform gene set- based association analysis of rare variants with MCI/AD-related intermediate phenotypic biomarkers in the ADNI whole-exome sequencing pilot project; and (3) validate novel variants and risk genes by imputing and genotyping target regions of detected genes in the full ADNI sample set. RELEVANCE TO PUBLIC HEALTH: AD is an increasingly common neurodegenerative disease and the sixth leading cause of death in the United States. Identifying new susceptibility loci with functional impact on MCI progression will enhance mechanistic knowledge regarding AD pathways and may enable earlier diagnosis and treatment.