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 2 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, revealed 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 diseased states by connecting genomic information
with additional dynamic omics activity.
Copyright © 2012 Elsevier Inc. All rights reserved.