Peter S. Gargalovic, Minori Imura, Bin Zhang, Nima M. Gharavi, Michael J. Clark, Joanne Pagnon, Wen-Pin Yang, Aiqing He, Amy Truong, Shilpa Patel, Stanley F. Nelson, Steve Horvath, Judith A. Berliner, Todd G. Kirchgessner, and Aldons J. Lusis Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids

GOAL: Understand the complex biological system/disease Evolution of approaches: 1. gene cloning and single gene regulation 2. identification of gene-gene relationships (pathways) 3. regulation of a pathway in the given system 4.integration of a given pathway/genome into complex and dynamic biological system (current challenge)

Identify all genes regulated by Inflammatory Stimuli (Oxidized Lipids) NEW TECHNOLOGIES (Expression arrays): Initial use in gene expression mapping:

Classical approach to exploratory expression array experiments oxPAPC (4hrs) 10 μg/ml HAEC Data analysis 30 μg/ml 50 μg/ml Data analysis Multiple time points 0 - 4hrs (50 μg/ml) HAEC Dose response Time course LPS (2ng/ml)

87 genes Bacterial LPS (2 ng/ml)oxPAPC (50 ug/ml) 742 genes Major Differences in Gene Regulation Between LPS and OxPAPC vs.

Many Genes and Pathways are Regulated by Oxidized Lipids (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 regulation and function (pathway analysis) Identifies network modules that can be used to explain gene 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

Genetic background influences inflammatory responses to oxidized lipids in human EC

Inflammatory Responses are Preserved Between Cell Passages

Co-Expression Network of Endothelial Responses to Oxidized Phospholipids ENDOTHELIAL CELL DONORS Oxidized Phospholipids EXPRESSION PATTERNS IL8 Gene X Gene Y

Experimental Design: ENDOTHELIAL CELL DONORS 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 Study Gene Regulation

1043 genes in the oxPAPC network are separated into 15 modules 12 cell lines Topological Overlap Matrix Plot

Brown Module is enriched in SREBP Pathway Genes INSIG INSIG SLC2A INSIG SLC2A SLC2A SLC2A NQO SQLE SLC2A LPIN ADRB SC4MOL CYP51A CPNE SQSTM CYP51A LOC SQLE LTB4DH LOC ID gene Ranking based on connectivity Highest Brown module has 26 genes 8 of 14 SREBP targets are in Brown module ) (p-value 1.26x )

MLYCD IMAP C14orf LOC RALA VEGF KIAA KIAA EEF2K DDIT SPTLC MTHFD KIAA XBP MGC CEBPG SLC7A ATF GIT CEBPB 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 RED MODULE (52 genes) 5 out of top 10 genes are UPR genes ) BLUE module UPR enrichment (p-value 1.3x ) ) RED module UPR enrichment (p-value )

Gene network separates genes into modules based on mechanism of regulation SREBP genes (Brown module) UPR genes (Blue and Red module) ) (p-value 1.26x ) (p-value 1.3x and 0.049) IL8 (Blue module) 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 ATF6 PERKIRE1 Endoplasmic Reticulum

ATF4 siRNA inhibits IL8 expression in primary human aortic ECs ATF4 UPR Blue module SREBP Brown module IL8 INSIG1

Co-expression network can be applied to new gene-function discovery (MGC4504 in red module is regulated by ATF4) MGC4504ATF4 Gene of unknown function present in UPR module

SUMMARY  Common genetic variations in human population have significant impact on inflammatory responses to oxidized lipids  Genetic variation-based gene co-expression network approach was used to:  subdivide genes into pathways based on mechanism of regulation (UPR versus SREBP pathway)  predict UPR involvement in regulation of IL8 and MGC4504  ER homeostasis and associated stress pathways may play a central role in mediating endothelial inflammatory responsiveness to oxidized phospholipids and possibly other stimuli