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Leveraging Molecular and Clinical Data to Better Understand Alzheimer鈥檚 Disease

Marina Sirota, University of California, San Francisco
Tuesday April 18, 12-1pm
Zoom Link:聽

Abstract:聽Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder caused by interactions among multiple genetic and environmental factors. Apolipoprotein (APO) E4 has been identified as the major genetic risk factor for AD. It increases the risk and lowers the age of onset of AD in a gene dose鈥揹ependent manner. The genetic complexity and multifactorial nature of AD pose unique challenges for developing effective therapies and suggest the need of a precision medicine approach that takes into account individual variability. We aim to use an integrative approach leveraging publicly available human genomics and transcriptomics as well as electronic medical record data to elucidate sex-specific and apoE genotype-specific molecular pathways involved in AD with a focus towards neuroinflammation. We are further interested in seeing how these differences impact diagnostics and therapeutics. We leverage different techniques including supervised as well as unsupervised machine learning and computational drug repurposing in order to achieve these goals.