Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes | Zendy

Rui Chen | Zendy; George I. Mias | Zendy; Jennifer LiPookThan | Zendy; Lihua Jiang | Zendy; Hugo Y. K. Lam | Zendy; Rong Chen | Zendy; Elana Miriami | Zendy; Konrad J. Karczewski | Zendy; Manoj Hariharan | Zendy; Frederick E. Dewey | Zendy; Yong Cheng | Zendy; Michael J. Clark | Zendy; Hogune Im | Zendy; Lukas Habegger | Zendy; Suganthi Balasubramanian | Zendy; Maeve O’Huallachain | Zendy; Joel T. Dudley | Zendy; Sara Hillenmeyer | Zendy; Rajini Haraksingh | Zendy; Donald Sharon | Zendy; Ghia Euskirchen | Zendy; Phil Lacroute | Zendy; Keith Bettinger | Zendy; Alan P. Boyle | Zendy; Maya Kasowski | Zendy; Fabian Grubert | Zendy; Scott Seki | Zendy; Marco Garcia | Zendy; Michelle WhirlCarrillo | Zendy; Mercedes Gallardo | Zendy; Marı́a A. Blasco | Zendy; Peter L. Greenberg | Zendy; Phyllis J. Snyder | Zendy; Teri E. Klein | Zendy; Russ B. Altman | Zendy; Atul J. Butte | Zendy; Euan A. Ashley | Zendy; Mark Gerstein | Zendy; Kari C. Nadeau | Zendy; Hua Tang | Zendy; M Snyder | Zendy

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Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Author(s) -

Rui Chen,

George I. Mias,

Jennifer LiPookThan,

Lihua Jiang,

Hugo Y. K. Lam,

Rong Chen,

Elana Miriami,

Konrad J. Karczewski,

Manoj Hariharan,

Frederick E. Dewey,

Yong Cheng,

Michael J. Clark,

Hogune Im,

Lukas Habegger,

Suganthi Balasubramanian,

Maeve O’Huallachain,

Joel T. Dudley,

Sara Hillenmeyer,

Rajini Haraksingh,

Donald Sharon,

Ghia Euskirchen,

Phil Lacroute,

Keith Bettinger,

Alan P. Boyle,

Maya Kasowski,

Fabian Grubert,

Scott Seki,

Marco Garcia,

Michelle WhirlCarrillo,

Mercedes Gallardo,

Marı́a A. Blasco,

Peter L. Greenberg,

Phyllis J. Snyder,

Teri E. Klein,

Russ B. Altman,

Atul J. Butte,

Euan A. Ashley,

Mark Gerstein,

Kari C. Nadeau,

Hua Tang,

M Snyder

Publication year - 2012

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2012.02.009

Subject(s) - biology , profiling (computer programming) , phenotype , omics , computational biology , gene expression profiling , bioinformatics , genetics , gene , gene expression , computer science , operating system

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.

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