Gene network and proteomic analyses of cardiac responses to pathological and physiological stress.
BACKGROUND
The molecular mechanisms underlying similarities and differences between physiological and pathological left ventricular hypertrophy (LVH) are of intense interest. Most previous work involved targeted analysis of individual signaling pathways or screening of transcriptomic profiles. We developed a network biology approach using genomic and proteomic data to study the molecular patterns that distinguish pathological and physiological LVH.


RESULTS
A network-based analysis using graph theory methods was undertaken on 127 genome-wide expression arrays of in vivo murine LVH. This revealed phenotype-specific pathological and physiological gene coexpression networks. Despite >1650 common genes in the 2 networks, network structure is significantly different. This is largely because of rewiring of genes that are differentially coexpressed in the 2 networks; this novel concept of differential wiring was further validated experimentally. Functional analysis of the rewired network revealed several distinct cellular pathways and gene sets. Deeper exploration was undertaken by targeted proteomic analysis of mitochondrial, myofilament, and extracellular subproteomes in pathological LVH. A notable finding was that mRNA-protein correlation was greater at the cellular pathway level than for individual loci.


CONCLUSIONS
This first combined gene network and proteomic analysis of LVH reveals novel insights into the integrated pathomechanisms that distinguish pathological versus physiological phenotypes. In particular, we identify differential gene wiring as a major distinguishing feature of these phenotypes. This approach provides a platform for the investigation of potentially novel pathways in LVH and offers a freely accessible protocol (http://sites.google.com/site/cardionetworks) for similar analyses in other cardiovascular diseases.
Cardiovascular Division, King's College London BHF Centre of Research Excellence, School of Medicine, James Black Centre, London, United Kingdom.
Ignat
I
Drozdov
Athanasios
A
Didangelos
Xiaoke
X
Yin
Anna
A
Zampetaki
Mélanie
M
Abonnenc
Colin
C
Murdoch
Min
M
Zhang
Christos A
CA
Ouzounis
Manuel
M
Mayr
Sophia
S
Tsoka
Ajay M
AM
Shah
D000818:Animals; D002853:Chromatography, Liquid; D016326:Extracellular Matrix Proteins / Q000235:genetics / Q000378:metabolism; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods; D017379:Hypertrophy, Left Ventricular / Q000235:genetics* / Q000378:metabolism* / Q000473:pathology; D051379:Mice; D009210:Myofibrils / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis; D020543:Proteome / Q000235:genetics / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D020133:Reverse Transcriptase Polymerase Chain Reaction; D013312:Stress, Physiological; D053719:Tandem Mass Spectrometry; D059467:Transcriptome / Q000235:genetics*
D016326:Extracellular Matrix Proteins; D020543:Proteome
computational biology; genetics; genomics; proteomics