Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here we present an integrative Personal Omics Profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14-month period. Our iPOP analysis revealed various medical risks, including Type II diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high coverage genomic and transcriptomic data, which provide the basis of our iPOP, discovered extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and disease states by connecting genomic information with additional dynamic omics activity.

 
snyder-abstract.txt · Last modified: 2012/02/15 18:09 by danyli
 
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