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Personal omics profiling reveals dynamic molecular and medical phenotypes
Rui Chen1, George I Mias, Jennifer Li-Pook-Than
1Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
Cell
|March 20, 2012
Summary
This study introduces an integrative personal omics profile (iPOP), combining multiple data types over time. iPOP reveals dynamic molecular changes and medical risks, connecting genomics to overall health states.
Area of Science:
- Multi-omics
- Systems biology
- Personalized medicine
Background:
- Personalized medicine integrates genomic data with physiological monitoring.
- High-throughput methods enable comprehensive molecular profiling.
- Longitudinal analysis is crucial for understanding dynamic health changes.
Purpose of the Study:
- To present an integrative personal omics profile (iPOP) for a single individual.
- To analyze multi-omics data longitudinally over 14 months.
- To connect genomic information with dynamic molecular and physiological changes.
Main Methods:
- Collected genomic, transcriptomic, proteomic, metabolomic, and autoantibody data.
- Performed integrative analysis of diverse omics profiles.
- Analyzed data from a single individual over a 14-month period.
Main Results:
- iPOP revealed medical risks, including type 2 diabetes.
- Observed extensive, dynamic molecular and pathway changes in health and disease.
- High-coverage genomics identified heteroallelic changes and RNA editing.
Conclusions:
- Longitudinal iPOP provides a comprehensive view of individual health.
- iPOP connects static genomic information with dynamic biological activity.
- This approach aids in interpreting healthy and diseased states.
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