Dataset Information


Autoantibody profile timecourse of UNK

ABSTRACT: We have determined the whole genome sequence of an individual at high accuracy and performed an integrated analysis of omics profiles over a 1.5 year period that included healthy and two virally infected states. Omics profiling of transcriptomes, proteomes, cytokines, metabolomes and autoantibodyomes from blood components have revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways that occurred during healthy and disease states. Many changes were associated with allele- and edit-specific expression at the RNA and protein levels, which may contribute to personalized responses. Importantly, genomic information was also used to predict medical risks, including Type II Diabetes (T2D), whose onset was observed during the course of our study using standard clinical tests and molecular profiles, and whose disease progression was monitored and subsequently partially managed. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states. Plasma and serum from a virus infected timepoint (in triplicate) and 34 healthy contorl samples were collected and used to probe Invitrogen human protoarray v5.0.

ORGANISM(S): Homo sapiens  

SUBMITTER: Rui Chen   Jennifer Li-Pook-Than  Mark Gerstein  Sara Hillemenyer  Sugnthi Balasubramanian  Elana Miriami  Konrad Karczewski  Maria A Blasco  Phyllis Snyder  Peter L Greenberg  Scott Seki  Kari Nadeau  Manoj Hariharan  George I Mias  Lukas Habegger  Hugo Lam  Euan Ashley  Frederick Dewey  Russ B Altman  Phil Lacroute  Keith Bettinger  Rajini Haraksingh  Rong Chen  Teri E Klein  Yong Cheng  Donald Sharon  Joel Dudley  Lihua Jiang  Marco Garcia  Ghia Euskirchen  Hua Tang  Michelle Whirl-Carrillo  Mercedes Gallardo  Maeve O'Huallachain  Atul Butte  Michael J Clark  Michael Snyder  Hogune Im  Shin Lin 

PROVIDER: E-GEOD-32691 | ArrayExpress | 2012-03-16



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Personal omics profiling reveals dynamic molecular and medical phenotypes.

Chen Rui R   Mias George I GI   Li-Pook-Than Jennifer J   Jiang Lihua L   Lam Hugo Y K HY   Chen Rong R   Miriami Elana E   Karczewski Konrad J KJ   Karczewski Konrad J KJ   Hariharan Manoj M   Dewey Frederick E FE   Cheng Yong Y   Clark Michael J MJ   Im Hogune H   Habegger Lukas L   Balasubramanian Suganthi S   O'Huallachain Maeve M   Dudley Joel T JT   Hillenmeyer Sara S   Haraksingh Rajini R   Sharon Donald D   Euskirchen Ghia G   Lacroute Phil P   Bettinger Keith K   Boyle Alan P AP   Kasowski Maya M   Grubert Fabian F   Seki Scott S   Garcia Marco M   Whirl-Carrillo Michelle M   Gallardo Mercedes M   Blasco Maria A MA   Greenberg Peter L PL   Snyder Phyllis P   Klein Teri E TE   Altman Russ B RB   Butte Atul J AJ   Ashley Euan A EA   Gerstein Mark M   Nadeau Kari C KC   Tang Hua H   Snyder Michael M  

Cell 20120301 6

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  ...[more]

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