peter s. gargalovic, minori imura, bin zhang, nima m. gharavi, michael j. clark, joanne pagnon,...
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Peter S. Gargalovic, Peter S. Gargalovic,
Minori Imura, Bin Zhang, Nima M. Gharavi, Michael J. Clark, Minori Imura, Bin Zhang, Nima M. Gharavi, Michael J. Clark, Joanne Pagnon, Wen-Pin Yang, Aiqing He, Amy Truong, Shilpa Joanne Pagnon, Wen-Pin Yang, Aiqing He, Amy Truong, Shilpa
Patel , Stanley F. Nelson , Steve Horvath, Judith A. Berliner, Patel , Stanley F. Nelson , Steve Horvath, Judith A. Berliner, Todd G. Kirchgessner, and Aldons J. LusisTodd G. Kirchgessner, and Aldons J. Lusis
Identification of inflammatory gene modules based
on variations of human endothelial cell responses
to oxidized lipids
GOAL: GOAL: Understand the complex biological Understand the complex biological system/diseasesystem/disease
Evolution of approaches:Evolution of approaches:
1.1. gene cloning and single gene regulationgene cloning and single gene regulation
2.2. identification of gene-gene relationships identification of gene-gene relationships
(pathways)(pathways)
3.3. regulation of a pathway in the given systemregulation of a pathway in the given system
4.4. integration of a given pathway/genome into integration of a given pathway/genome into
complex and dynamic biological system (current complex and dynamic biological system (current
challenge)challenge)
Identify all genes regulated by Inflammatory Stimuli (Oxidized Lipids)
NEW TECHNOLOGIES (Expression arrays):NEW TECHNOLOGIES (Expression arrays):
Initial use in gene expression mapping:Initial use in gene expression mapping:
Classical approachClassical approach to exploratory expression to exploratory expression array experimentsarray experiments
oxPAPC (4hrs)
10 μg/ml
HAEC Data Data analysisanalysis
30 μg/ml
50 μg/ml
Data Data analysisanalysis
Multiple time points 0 - 4hrs (50 μg/ml)
HAEC
Dose response
Time course
LPS (2ng/ml)
87 genes
70
17
Bacterial LPS (2 ng/ml)oxPAPC (50 ug/ml)
742 genes
459
283
Major Differences in Gene Regulation Between LPS and OxPAPC
vs.
Many Genes and Pathways are Regulated by Oxidized Many Genes and Pathways are Regulated by Oxidized Lipids (complex system!!!)Lipids (complex system!!!)
LDL
OxidizedPhospholipids
Oxidation Endothelial Cells
Src/Jak/STAT
ERK/EGR-1CREB/HO-1
GPCR,cAMP
Inflammatory response
UnfoldedProtein
ResponseSREBPNitric Oxide
~ 800 genes
Approach: Weighted Gene Co-expression NETWORK Analysis (WGCNA)• Identifies network modules that can be used to explain gene Identifies network modules that can be used to explain gene regulation and function (pathway analysis)regulation and function (pathway analysis)
•Hierarchical clustering with the topological overlap matrixHierarchical clustering with the topological overlap matrix• Uses intramodular connectivity to identify important genes•References
•Bin Zhang and Steve Horvath (2005) "A General Framework for Weighted Gene Co-Expression Network Analysis", Statistical Applications in Genetics and Molecular Biology: Vol. 4: No. 1, Article 17. • Horvath S, Zhang B, Carlson M, Lu KV, Zhu S, Felciano RM, Laurance MF, Zhao W, Shu, Q, Lee Y, Scheck AC, Liau LM, Wu H, Geschwind DH, Febbo PG, Kornblum HI, Cloughesy TF, Nelson SF, Mischel PS (2006) "Analysis of Oncogenic Signaling Networks in Glioblastoma Identifies ASPM as a Novel Molecular Target", PNAS
Can we take advantage of the large amount of data collected from differentially perturbed states to learn more about the biological system?
Genetic variation modulates inflammatory responses to oxidized phospholipids in human population
Hypothesis:
Interleukin 8:
Pro-inflammatory cytokine implicated in atherogenesis
Mediates adhesion of monocytes to EC
Highly induced by oxPAPC
IL8 levels are higher in patients with unstable CAD then in healthy individuals
Elevated plasma IL8 levels are associated with increased risk for future CAD
DONOR HAEC #
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
IL8
(pg
/ml)
0
200
400
600
800
1000
1200
1400
oxPAPCPAPC
Genetic background influences inflammatory Genetic background influences inflammatory responses to oxidized lipids in human ECresponses to oxidized lipids in human EC
IL8 ELISA
1st (pg/ml)
0 200 400 600 800 1000 1200 1400
2nd
(p
g/m
l)
0
200
400
600
800
1000
1200
1400
1600
correlation=0.825 p<0.001
Inflammatory Responses are Preserved Inflammatory Responses are Preserved Between Cell Passages Between Cell Passages
Co-Expression Network of Endothelial Responses to Oxidized Phospholipids
ENDOTHELIAL CELL DONORS
1 2 3 4 5 6 7 8 9 10 11 12
Oxidized Phospholipids
EXPRESSION PATTERNSIL8
Gene X
Gene Y
Experimental Design:Experimental Design:
ENDOTHELIAL CELL DONORS
1 2 3 4 5 6 7 8 9 10 11 12
TREATMENT (4hrs)
1. PAPC (40 ug/ml)
2. oxPAPC (40ug/ml)
1043 Genes Regulated by OxPAPC
Data Analysis Using Gene Co-expression Network Approach
oxPAPC
Endothelial cell line (1) Endothelial cell line (2)
SREBP activity (+) LOW
oxPAPC
SREBP activity (+++) HIGH
Expression of SREBP- regulated genes (+) LOW
Expression of SREBP- regulated genes (+++) HIGH
Genetic Perturbation Approach to Genetic Perturbation Approach to Study Gene RegulationStudy Gene Regulation
1043 genes in the oxPAPC network are 1043 genes in the oxPAPC network are separated into 15 modulesseparated into 15 modules
12 cell lines
Topological Overlap Matrix Plot
Brown Module is enriched in SREBP Pathway Brown Module is enriched in SREBP Pathway Genes Genes
INSIG1 6.257772
INSIG1 6.194221
SLC2A3 6.061201
INSIG1 5.695922
SLC2A14 5.606994
SLC2A14 5.227064
SLC2A14 4.260267
NQO1 3.984579
SQLE 3.5742
SLC2A3 3.483622
LPIN2 3.087652
ADRB2 2.922237
SC4MOL 2.915552
CYP51A1 2.373458
CPNE8 2.241534
SQSTM1 1.861886
CYP51A1 1.784242
--- 1.722028
LOC285148 1.674725
--- 1.602659
--- 1.528179
SQLE 1.36481
LTB4DH 0.84509
LOC283219 0.790956
ID3 0.691711
--- 0.255479
gene
Ranking based on connectivity
Highest
Brown module has 26 genes
8 of 14 SREBP targets are in Brown
module
(p-value 1.26x10-10 ))
5.586476MLYCD
5.65993IMAP1
5.904039C14orf27
6.031962LOC148418
6.062034RALA
6.155599VEGF
6.288301KIAA0121
6.40407KIAA0582
6.475676EEF2K
6.682974DDIT4
6.824852SPTLC2
6.86908MTHFD2
7.019388KIAA0582
7.270555XBP1
7.446907MGC4504
7.563844CEBPG
8.612143SLC7A5
9.178292ATF4
9.623114GIT2
10.82586CEBPB
Blue and Red module are enriched in UPR Blue and Red module are enriched in UPR genesgenes
BLUE MODULE (256 genes)
22 out of top 100 genes are UPR genes
Ranking based on network connectivity
Ranking based on network connectivity
RED MODULE (52 genes)
5 out of top 10 genes are UPR genes
BLUE module UPR enrichment (p-value 1.3x10-13 ) )
RED module UPR enrichment (p-value 0.049 ) )
Gene network separates genes into modules Gene network separates genes into modules based on mechanism of regulation based on mechanism of regulation
SREBP genes (Brown module)
UPR genes (Blue and Red module)
(p-value 1.26x10-10 ) )
(p-value 1.3x10-13 and 0.049)
IL8 (Blue module)
IL8 expression in cell lines is highly correlated with UPR genes IL8 expression in cell lines is highly correlated with UPR genes
ATF4XBP1
UPR genes
Screen for UPR regulatory sites in 1043 network genes
UPRE 5’-TGACGTGG-3’)
ERSE-I 5’- CCAAT(N9)CCACG -3’
ERSE-II 5 –ATTGGNCCACG- 3’
C/EBP-ATF 5’-TTGCATCA -3’
XBP1 and ATF6
ATF4
CRE-like site found in IL8 promoter
ATF6PERKIRE1
Endoplasmic ReticulumEndoplasmic Reticulum
ATF4 siRNA inhibits IL8 expression in primary human aortic ECs
ATF4
CONT OX TUN
mR
NA
(%
of
co
ntr
ol)
0
100
200
300
400Scrambled siRNAATF4 siRNA
71%
p<0.0001
81%85%
p=0.003
p<0.0001
ATF4 CONT OX TUN
mR
NA
(%
of
co
ntr
ol)
0
100
200
300
400Scrambled siRNAATF4 siRNA
74%72%
68%
p=0.001
p=0.0002
p=0.0006
UPR UPR Blue Blue modulemodule
CONT OX TUN
mR
NA
(%
of
con
tro
l)
0
200
400
600
800
1000Scrambled siRNAATF4 siRNA SREBP SREBP
Brown Brown modulemodule
IL8
INSIG1
MGC4504
CONT OX TUN
mR
NA
(%
of
con
tro
l)
0
1000
2000
3000
4000
5000
6000
7000
8000Scrambled siRNAATF4 siRNA
96%
p=0.0007
97%
p=0.0008
89%
p=0.003
Co-expression network can be applied to new gene-function discovery
(MGC4504 in red module is regulated by ATF4)
ATF4
CONT OX TUN
mR
NA
(%
of
co
ntr
ol)
0
100
200
300
400Scrambled siRNAATF4 siRNA
71%
p<0.0001
81%85%
p=0.003
p<0.0001
MGC4504ATF4
Gene of unknown function present in UPR module
SUMMARY
Common genetic variations in human population have Common genetic variations in human population have significant impact on inflammatory responses to significant impact on inflammatory responses to oxidized lipidsoxidized lipids
Genetic variation-based gene co-expression network Genetic variation-based gene co-expression network approach was used to:approach was used to:
subdivide genes into pathways based on mechanism of subdivide genes into pathways based on mechanism of
regulation (UPR versus SREBP pathway) regulation (UPR versus SREBP pathway)
predict UPR involvement in regulation of IL8 and predict UPR involvement in regulation of IL8 and MGC4504 MGC4504
ER homeostasis and associated stress pathways may ER homeostasis and associated stress pathways may play a central role in mediating endothelial play a central role in mediating endothelial inflammatory responsiveness to oxidized inflammatory responsiveness to oxidized phospholipids and possibly other stimuliphospholipids and possibly other stimuli