Personal omics profiling reveals dynamic molecular and medical phenotypes

2015-01-13

Personal omics profiling reveals dynamic molecular and medical phenotypes

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Abstract
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.

Some notes

Stanford Yale CNIO
Cell paper
lots of authors on this paper
dynamic

omics activity.

individual monitored was diagnosed with diabetes, has a mutation in TERT that increases risk for aplastic anemia, and obtained an influenza and a RSV infection during the monitoring time
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Personalized medicine is expected to bene?t from
combining genomic information with regular moni-
toring of physiological states by multiple high-
throughput methods

overview of personal omics profiling
this is pretty neat paper and a glimpse into the future. It looks at all types of omic data for one individual over 14 months
Whole-Genome Sequencing
WGS-Based Disease Risk Evaluation
Medical Phenotypes Monitoring
Dynamic Omics Analysis: Integrative Omics Pro?ling

of Molecular Responses

Dynamic Omics Analysis: Extensive Heteroallelic

Variation and RNA Editing

miRNA Variant Analysis
To our knowledge, our study is the ?rst to perform extensive

personal iPOP of an individual through healthy and diseased
states. It revealed extensive complex and dynamic changes in
the omics pro?les, especially in the transcriptomes, between
healthy states and viral infections, and between nondiabetic
and diabetic states.

WGS . . .sequencing
cytokine assay