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.
Intermediate neuropathology-based endophenotypes?which are biologically-relevant, quantitative and heritable phenotypes?are valuable in addressing limitations of conventional case-control analyses of Alzheimer's disease (AD) and are underutilized in AD genetic research. Integrative approaches such as network analyses, which incorporate prior biological knowledge in statistical models, are a powerful technique to refine genetic association studies. The overarching goal of this proposal is to use sophisticated statistical and biological approaches at SNP-, gene-, and network-levels to improve and refine genetic analyses of AD and AD neuropathological endophenotypes and utilize model organism to functionally validate and explore molecular mechanisms of these candidate loci.
