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