Molecular mechanisms of Alzheimer's disease neuropathological endophenotypes

摘要 Shubhabrata Mukherjee是牛津大学医学系的研究助理教授， 华盛顿。他寻求一个指导职业发展奖，以获得阿尔茨海默氏症的关键知识技能， 疾病（AD）相关的衰老生物学，特别关注复杂的遗传模型来分析 神经病理学结果和必要的研究经验，作为一个独立的职业生涯， 多学科研究者。 该培训计划详细介绍了分子和生理学方面的正式和非正式教学的五年计划 AD的方面。该计划包括由一个既定的专家小组指导研究，课程，研讨会， 并指导研究生物学和神经病理学的老化和统计遗传学。该计划还包括 具有在动物模型中验证基因功能和探索基因分子机制的经验 作为富有教育意义的工作组的合作。慕克吉博士将有机会与 在全国会议上的同事。慕克吉博士的短期职业目标包括：1）获得一个强大的 应用于神经退行性疾病的实验老化领域的知识基础，2） 接受实验老化研究数据分析和解释的培训，3）学习和应用新的 整合遗传数据的方法，然后在模式生物中验证技术，4）改进手稿 并授予写作技能，和5）继续培训，在负责任的研究行为。他的长期职业生涯 目标是成为一个独立的多学科研究人员与多样化的工具箱，包括复杂的 统计方法和实验方法，以了解和揭示年龄的病理生理学- 相关的神经退行性疾病。 在过去的几年中，AD的遗传学研究已经确定了大约20个易感基因座。的翻译 可行疗法和生物标志物发现的成功取决于以下因素的鉴定和表征： 这些易感基因座上的实际疾病基因和功能变体。为了克服这些主要障碍 在后全基因组关联研究时代， 使用神经病理学内表型，其是生物学相关的和可遗传的表型。 提出的研究的具体目标是实现复杂的基因网络分析集成 适当评估AD相关神经病理学内表型数据的既往生物学知识， 获得新的见解。最有前途的神经病理学相关位点将与动物模型进行验证。 最后，这些验证基因的分子机制将在C。elegans长寿模型 拟议目标的完成将为随后的独立资金使用网络奠定基础。 分析方法，以进一步科学地了解AD的遗传和内表型数据， 为新一代AD疗法奠定了基础。

ABSTRACT Shubhabrata Mukherjee is a Research Assistant Professor in the Department of Medicine at the University of Washington. He seeks a mentored career development award to obtain critical knowledge skills in Alzheimer's disease (AD) related biology of aging focusing particularly on sophisticated genetic models to analyze neuropathological outcomes and necessary research experience for an independent career as a multidisciplinary researcher. The training proposal details a five-year plan of formal and informal instruction in molecular and physiological aspect of AD. The plan includes mentored research by an established team of experts, coursework, seminars, and guided study in biology and neuropathology of aging and statistical genetics. The plan also includes experience in functional validation and exploration of molecular mechanisms of genes in animal models as well as collaborations in richly educational working groups. Dr. Mukherjee will have the opportunity to interact with colleagues at national meetings. Dr. Mukherjee's short-term career goals include 1) acquire a strong foundation of knowledge in the area of experimental aging as applied to neurodegenerative disorders, 2) receive training in the analysis and interpretation of experimental aging research data, 3) learn and apply novel ways of integrating genetic data followed by validation techniques in model organisms, 4) improve manuscript and grant writing skills, and 5) continue training in the responsible conduct of research. His long-term career goals are to be an independent multidisciplinary researcher with a diverse toolbox including sophisticated statistical methodologies and experimental approaches to understand and uncover pathophysiology of age- related neurodegenerative diseases. Genetic studies of AD have identified around 20 susceptibility loci in the past several years. The translation of this success to viable therapies and biomarker discovery depends on the identification and characterization of the actual disease genes and functional variants at these susceptibility loci. To overcome these major hurdles in the post-genome wide association studies era requires a multitude of alternative approaches including the use of neuropathological endophenotypes, which are biologically-relevant, and heritable phenotypes. The specific aims of the research proposed are to implement sophisticated gene-network analysis integrating prior biological knowledge properly to evaluate data from AD-related neuropathological endophenotypes and gain new insights. The most promising neuropathology-associated loci will be validated with animal models. Lastly, molecular mechanisms of these validated genes will be explored in C. elegans longevity models. Completion of the proposed aims will set the stage for subsequent independent funding to use network analysis approaches to further the scientific understanding of genetic and endophenotype data of AD, laying the groundwork for a new generation of AD therapeutics.