Pathway analysis of coronary atherosclerosis.
Large-scale gene expression studies provide significant insight into genes differentially regulated in disease processes such as cancer. However, these investigations offer limited understanding of multisystem, multicellular diseases such as atherosclerosis. A systems biology approach that accounts for gene interactions, incorporates nontranscriptionally regulated genes, and integrates prior knowledge offers many advantages. We performed a comprehensive gene level assessment of coronary atherosclerosis using 51 coronary artery segments isolated from the explanted hearts of 22 cardiac transplant patients. After histological grading of vascular segments according to American Heart Association guidelines, isolated RNA was hybridized onto a customized 22-K oligonucleotide microarray, and significance analysis of microarrays and gene ontology analyses were performed to identify significant gene expression profiles. Our studies revealed that loss of differentiated smooth muscle cell gene expression is the primary expression signature of disease progression in atherosclerosis. Furthermore, we provide insight into the severe form of coronary artery disease associated with diabetes, reporting an overabundance of immune and inflammatory signals in diabetics. We present a novel approach to pathway development based on connectivity, determined by language parsing of the published literature, and ranking, determined by the significance of differentially regulated genes in the network. In doing this, we identify highly connected "nexus" genes that are attractive candidates for therapeutic targeting and followup studies. Our use of pathway techniques to study atherosclerosis as an integrated network of gene interactions expands on traditional microarray analysis methods and emphasizes the significant advantages of a systems-based approach to analyzing complex disease.
King
Jennifer Y
JY
Donald W. Reynolds Cardiovascular Research Center, Division of Cardiovascular Medicine, Falk Cardiovascular Research Center, Stanford University, Stanford, California 94305, USA.
Ferrara
Rossella
R
Tabibiazar
Raymond
R
Spin
Joshua M
JM
Chen
Mary M
MM
Kuchinsky
Allan
A
Vailaya
Aditya
A
Kincaid
Robert
R
Tsalenko
Anya
A
Deng
David Xing-Fei
DX
Connolly
Andrew
A
Zhang
Peng
P
Yang
Eugene
E
Watt
Clifton
C
Yakhini
Zohar
Z
Ben-Dor
Amir
A
Adler
Annette
A
Bruhn
Laurakay
L
Tsao
Philip
P
Quertermous
Thomas
T
Ashley
Euan A
EA
D000328:Adult; D000368:Aged; D000818:Animals; D002478:Cells, Cultured; D019295:Computational Biology; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000473:pathology*; D018076:DNA, Complementary / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D016678:Genome; D006801:Humans; D007107:Immune System; D007150:Immunohistochemistry; D007249:Inflammation; D008297:Male; D051379:Mice; D008822:Mice, Transgenic; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D017202:Myocardial Ischemia / Q000473:pathology; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis; D012313:RNA / Q000737:chemistry / Q000378:metabolism; D049490:Systems Biology
D018076:DNA, Complementary; D012313:RNA