Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers

Wang, I‐Ming; Zhang, Bin; Yang, Xia; Zhu, Jun; Stepaniants, S.; Zhang, Chunsheng; Meng, Qingying; Peters, Mette A.; He, Yudong; Ni, Chester; Slipetz, Deborah; Crackower, Michael A.; Houshyar, Hani; Tan, Christopher M.; Asante‐Appiah, Ernest; O’Neill, Gary P.; Luo, Miyang; Thieringer, Rolf; Yuan, Jeffrey; Chiu, Chi-Sung; Lum, Pek Yee; Lamb, John; Boie, Yves; Wilkinson, Hilary A.; Schadt, Eric E.; Dai, Hongyue; Roberts, Christopher

doi:10.1038/msb.2012.24

Cited by 127 publications

(140 citation statements)

References 99 publications

(164 reference statements)

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“…The ‘Immunity’ superset may represent the same core inflammatory signature that we have observed across species, tissues, and multiple diseases [12]. Four of the top key drivers ( HCK , TYROBP , NCKAP1L and AIF1 ) identified from the previous multi-disease inflammatory signature were also detected as key drivers for the ‘Immunity’ superset in this study (Figure 2D).…”

Section: Discussionsupporting

confidence: 65%

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Mäkinen¹,

et al. 2014

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The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.

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Section: Discussionsupporting

confidence: 65%

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Mäkinen¹,

et al. 2014

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“…Importantly, the interconnected genes in the P450 subnetwork can sense perturbations from genetic loci (Wang et al, 2012) and identify the key intermediates that contribute to the perturbations. It was thus informative that the Fig.…”

Section: Discussionmentioning

confidence: 99%

Genetic Variation in Aldo-Keto Reductase 1D1 (AKR1D1) Affects the Expression and Activity of Multiple Cytochrome P450s

et al. 2013

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Human liver gene regulatory (Bayesian) network analysis was previously used to identify a cytochrome P450 (P450) gene subnetwork with Aldo-keto reductase 1D1 (AKR1D1) as a key regulatory driver of this subnetwork. This study assessed the biologic importance of AKR1D1 [a key enzyme in the synthesis of bile acids, ligand activators of farnesoid X receptor (FXR), pregnane X receptor (PXR), and constitutive androstane receptor (CAR), known transcriptional regulators of P450s] to hepatic P450 expression. Overexpression of AKR1D1 in primary human hepatocytes led to increased expression of CYP3A4, CYP2C8, CYP2C9, CYP2C19, and CYP2B6. Conversely, AKR1D1 knockdown decreased expression of these P450s. We resequenced AKR1D1 from 98 donor livers and identified a 39-untranslated region (UTR) (rs1872930) single nucleotide polymorphism (SNP) significantly associated with higher AKR1D1 mRNA expression. AKR1D1 39-UTR-luciferase reporter studies showed that the variant allele resulted in higher luciferase activity, suggesting that the SNP increases AKR1D1 mRNA stability and/or translation efficiency. Consistent with AKR1D1's putative role as a driver of the P450 subnetwork, the AKR1D1 39-UTR SNP was significantly associated with increased hepatic mRNA expression of multiple P450s (CYP3A4, CYP2C8, CYP2C9, CYP2C19, and CYP2B6) and CYP3A4, CYP2C8, CYP2C19, and CYP2B6 activities. After adjusting for multiple testing, the association remained significant for AKR1D1, CYP2C9, and CYP2C8 mRNA expression and CYP2C8 activity. These results provide new insights into the variation in expression and activity of P450s that can account for interindividual differences in drug metabolism/efficacy and adverse drug events. In conclusion, we provide the first experimental evidence supporting a role for AKR1D1 as a key genetic regulator of the P450 network.

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“…In GSE38037, there were eight samples (4 normal and 4 test samples) [22] . In GSE32529, there were 224 samples including 6 experimental conditions such as LPS treatment + ischemic challenge, and CpG treatment + ischemic challenge [23,24] .…”

Section: Ischemic Brainmentioning

confidence: 99%

Identification of autophagy signaling network that contributes to stroke in the ischemic rodent brain via gene expression

et al. 2015

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Autophagy plays a vital role in cerebral ischemia and may be a potential target for developing novel therapy for stroke. In this study, we constructed an autophagy-related pathway network by analyzing the genes related to autophagy and ischemic stroke, and the risk genes were screened. Two autophagy-related modules were signifi cantly up-regulated and clustered to influence cerebral ischemia. Besides, three key modular genes (NFKB1, RELA, and STAT3) were revealed. With 5-fold cross validation, the ROC curves of NFKB1, RELA, and STAT3 were 0.8256, 0.8462, and 0.8923. They formed a complex module and competitively mediated the activation of autophagy in cerebral ischemia. In conclusion, a module containing NFKB1, RELA, and STAT3 mediates autophagy, serving as a potential biomarker for the diagnosis and therapy of ischemic stroke.

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Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers

Abstract: A common inflammatome signature, as well as disease-specific expression patterns, was identified from 11 different rodent inflammatory disease models. Causal regulatory networks and the drivers of the inflammatome signature were uncovered and validated.

Cited by 127 publications

References 99 publications

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

Genetic Variation in Aldo-Keto Reductase 1D1 (AKR1D1) Affects the Expression and Activity of Multiple Cytochrome P450s

Identification of autophagy signaling network that contributes to stroke in the ischemic rodent brain via gene expression

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