I dentification of inflammatory gene modules based on variations of - - PowerPoint PPT Presentation

Peter S. Gargalovic, Peter S. Gargalovic, Minori Minori Imura Imura, Bin Zhang, , Bin Zhang, Nima Nima M.

• M. Gharavi

Gharavi, Michael J. Clark, , Michael J. Clark, Joanne Joanne Pagnon Pagnon, Wen , Wen-

• Pin Yang,

Pin Yang, Aiqing Aiqing He, Amy Truong, He, Amy Truong, Shilpa Shilpa Patel , Stanley F. Nelson , Steve Horvath, Judith A. Berliner, Patel , Stanley F. Nelson , Steve Horvath, Judith A. Berliner, Todd G. Todd G. Kirchgessner Kirchgessner, and , and Aldons Aldons J. Lusis

• J. Lusis

I dentification of inflammatory gene modules based

• n variations of human endothelial cell responses

to oxidized lipids

GOAL: GOAL: Understand the complex biological system/ disease Understand the complex biological system/ disease Evolution of approaches: Evolution of approaches: 1. 1.

gene cloning and single gene regulation gene cloning and single gene regulation 2. 2. identification of gene identification of gene-

• gene relationships (pathways)

gene relationships (pathways) 3. 3. regulation of a pathway in the given system regulation of a pathway in the given system 4. 4. integration of a given pathway/ genome into complex integration of a given pathway/ genome into complex and dynamic biological system (current challenge) and dynamic biological system (current challenge)

I dentify all genes regulated by I nflammatory Stimuli (Oxidized Lipids)

NEW TECHNOLOGI ES (Expression arrays): NEW TECHNOLOGI ES (Expression arrays):

I nitial use in gene expression mapping: I nitial use in gene expression mapping:

Classical approach Classical approach to exploratory expression array to exploratory expression array experiments experiments

• xPAPC (4hrs)

10 μg/ml

HAEC

Data Data analysis analysis 30 μg/ml 50 μg/ml Data Data analysis analysis

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)

• xPAPC (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 Lipids Many Genes and Pathways are Regulated by Oxidized Lipids (complex system!!!) (complex system!!!)

LDL

Oxidized

Phospholipids Oxidation

Endothelial Cells

Src/Jak/STAT ERK/EGR-1 CREB/HO-1 GPCR, cAMP

Inflammatory response

Unfolded Protein Response SREBP Nitric 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 matrix

Hierarchical 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)

200 400 600 800 1000 1200 1400

• xPAPC

PAPC

Genetic background influences inflammatory Genetic background influences inflammatory responses to oxidized lipids in human EC responses to oxidized lipids in human EC

IL8 ELISA 1st (pg/ml)

200 400 600 800 1000 1200 1400

2nd (pg/ml)

200 400 600 800 1000 1200 1400 1600

correlation=0.825 p<0.001

I nflammatory Responses are Preserved Between I nflammatory Responses are Preserved Between Cell Passages 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 PATTERNS

IL8 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.

• xPAPC (40ug/ml)

1043 Genes Regulated by OxPAPC Data Analysis Using Gene Co-expression Network Approach

• xPAPC

Endothelial cell line (1) Endothelial cell line (2)

SREBP activity (+) LOW

• xPAPC

SREBP activity (+++) HIGH

Expression of SREBP- regulated genes (+) LOW Expression of SREBP- regulated genes (+++) HIGH

Genetic Perturbation Approach to Study Genetic Perturbation Approach to Study Gene Regulation Gene Regulation

1043 genes in the oxPAPC network are separated 1043 genes in the oxPAPC network are separated into 15 modules into 15 modules

12 cell lines

Topological Overlap Matrix Plot

Brown Module is enriched in SREBP Pathway Genes Brown Module is enriched in SREBP Pathway 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 )

)

5.586476 MLYCD 5.65993 IMAP1 5.904039 C14orf27 6.031962 LOC148418 6.062034 RALA 6.155599 VEGF 6.288301 KIAA0121 6.40407 KIAA0582 6.475676 EEF2K 6.682974 DDIT4 6.824852 SPTLC2 6.86908 MTHFD2 7.019388 KIAA0582 7.270555 XBP1 7.446907 MGC4504 7.563844 CEBPG 8.612143 SLC7A5 9.178292 ATF4 9.623114 GIT2 10.82586 CEBPB

Blue and Red module are enriched in UPR genes Blue and Red module are enriched in UPR genes

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 based on Gene network separates genes into modules based on mechanism of regulation 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

ATF4 XBP1

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

ATF6

PERK IRE1

Endoplasmic Reticulum Endoplasmic Reticulum

ATF4 siRNA inhibits I L8 expression in primary human aortic ECs

ATF4

CONT OX TUN mRNA (% of control) 100 200 300 400

Scrambled siRNA ATF4 siRNA

71%

p<0.0001

81% 85%

p=0.003 p<0.0001

ATF4

CONT OX TUN mRNA (% of control) 100 200 300 400

Scrambled siRNA ATF4 siRNA

74% 72% 68%

p=0.001 p=0.0002 p=0.0006

UPR UPR Blue Blue module module

CONT OX TUN mRNA (% of control) 200 400 600 800 1000

Scrambled siRNA ATF4 siRNA

SREBP SREBP Brown Brown module module

IL8 INSIG1

MGC4504

CONT OX TUN mRNA (% of control) 1000 2000 3000 4000 5000 6000 7000 8000

Scrambled siRNA ATF4 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 mRNA (% of control) 100 200 300 400

Scrambled siRNA ATF4 siRNA

71%

p<0.0001

81% 85%

p=0.003 p<0.0001

MGC4504 ATF4

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 oxidized significant impact on inflammatory responses to oxidized lipids lipids

• Genetic variation

Genetic variation-

• based gene co

based gene co-

• expression network

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 I L8 and MGC4504

predict UPR involvement in regulation of I L8 and MGC4504

• ER homeostasis and associated stress pathways may play a

ER homeostasis and associated stress pathways may play a central role in mediating endothelial inflammatory central role in mediating endothelial inflammatory responsiveness to oxidized phospholipids and possibly other responsiveness to oxidized phospholipids and possibly other stimuli stimuli