Network analysis reveals functional cross-links between disease and inflammation genes

Exploring potential ion channel targets for rheumatoid arthritis: combination of network analysis and gene expression analysis

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane that leads to the destruction of cartilage and bone. Currently, pharmacological targeting of ion channels is being increasingly recognized as an attractive and feasible strategy for the treatment of RA. The present work employs a network analysis approach to predict the most promising ion channel target for potential RA-treating drugs. A protein-protein interaction map was generated for 343 genes associated with inflammation in RA and ion channel genes using Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. Based on the betweenness centrality and traffic values as key topological parameters, 17 hub nodes were identified, including FOS (9800.85), tumor necrosis factor (3654.60), TGFB1 (3305.75), and VEGFA (3052.88). The backbone network constructed with these 17 hub genes was intensely analyzed to identify the most promising ion channel target using network analyzer. Calcium permeating ion channels, especially store-operated calcium entry channels, and their associated regulatory proteins were found to highly interact with RA inflammatory hub genes. This significant ion channel target for RA identified by theoretical and statistical studies was further validated by a pilot case-control gene expression study. Experimental verification of the above findings in 75 RA cases and 25 controls showed increased ORAI1 expression. Thus, with a combination of network analysis approach and gene expression studies, we have explored potential targets for RA treatment.

A plasma proteomic approach in patients with heart failure after acute myocardial infarction: insights into the pathogenesis and progression of the disease

Aims

The pathogenesis of disease progression targets for patients with heart failure after acute myocardial infarction was investigated by using plasma proteomics.

Methods

The plasma proteomes of acute myocardial infarction patients with (MI-HF) and without (MI-WHF) heart failure were compared. Each group consisted of 10 patients who were matched for age and sex. The peptides were analyzed by 2-dimensional liquid chromatography coupled to tandem mass spectrometry in a high definition mode. Parallel reaction monitoring (PRM) verified the selected target proteins.

Results

We identified and quantified 2,589 and 2,222 proteins, respectively, and found 117 differentially expressed proteins (DEPs) (≥1.5-fold), when the MI-HF and MI-WHF groups were compared. Of these 51 and 66 were significantly up-regulated and down-regulated, respectively. The significant DEPs was subjected to protein-protein interaction network analysis which revealed a central role of the NF-κB signaling pathway in the MI-HF patients. PRM verified that MB, DIAPH1, VNN1, GOT2, SLC4A1, CRP, CKM, SOD3, F7, DLD, PGAM2, GOT1, UBA7 and HYOU1 were 14 proteins which were highly expressed in MI-HF patients.

Conclusions

These findings showed a group of proteins related to the NF-κB signaling pathway in the pathogenesis of patients with poor outcomes after experiencing MI-HF. These proteins may be useful candidate markers for the diagnosis of MI-HF as well as help to elucidate the pathophysiology of this major cause of mortality in older patients.

Anti-Septic Potential of 7-α-Obacunyl Acetate Isolated from the Toona sinensis on Cecal Ligation/Puncture Mice via Suppression of JAK-STAT/NF-κB Signal Pathway

Purpose

Sepsis is a life-threatening clinical syndrome and characterized by an inflammatory and innate immune response to infections. The current study was aimed to evaluate the anti-sepsis effect of 7-α-Obacunyl acetate (7-OBA), the abundant constituent isolated from Toona sinensis (Meliaceae), in cecal ligation and puncture (CLP)-induced mice and to investigate the related molecular mechanisms.

Methods

The CLP operation was performed to establish the sepsis mice model, and the survival rate and temperature were measured after 7-OBA treatment (7.5, 15, and 30 mg/kg; i.p.). Inflammatory cytokines levels of TNF-α, IL-1β, IL-6, and IL-10 were detected by ELISA kits, and the kidney, liver, and heart function were measured using an automatic biochemistry analyzer. Effects of 7-OBA on NF-κB and JAK2-STAT3 signaling pathways were determined by Western blot analysis in a lipopolysaccharide (LPS) stimulated RAW264.7 cells model.

Results

7-OBA treatment significantly increased the survival rate (p<0.05 and p<0.01) and normalized temperature (p<0.05 and p<0.01) of sepsis mice. The levels of pro-inflammatory cytokines like TNF-α, IL-1β, and IL-6 in serum were obviously decreased, whereas the anti-inflammatory cytokines of IL-10 were increased. CLP-induced increases of the main markers of kidney, liver, and heart function in mice (p<0.01) were also obviously reversed by 7-OBA. The anti-sepsis effect of 7-OBA might be associated with regulation of nuclear factor kappa-B (NF-κB) and Janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) signal pathways.

Conclusion

Our investigation indicated that 7-OBA can be developed as an effective agent for treating/curing sepsis in the future.

TRIM Proteins in Inflammation: from Expression to Emerging Regulatory Mechanisms

Inflammation is an immune response to exogenous or endogenous insults that helps to maintain the tissue homeostasis under stressful conditions. Depending on the differential types of insults, inflammation is classified into microbial, autoimmune, metabolic, allergic, and physical inflammation. With regard to its involvement in the pathogenesis of most of human diseases, dissecting the key molecules in the regulation of inflammatory process is vital for the prevention and therapeutics of human diseases. Tripartite motif (TRIM) proteins are a versatile family of E3 ligases, which are composed of > 80 distinct members in humans recognized for their roles in antiviral responses. Recently, a large number of studies have shown the regulatory roles of TRIM proteins in mediating the inflammation. Herein in this review, we discuss the aberrations of TRIM proteins in autoimmune and autoinflammatory diseases, with a focus on the regulation of different components of inflammatory process, including inflammasome, NF-κB signaling, type I IFN (interferon) production, and Th1/Th17 cell differentiation. Importantly, elucidation of the mechanism underlying the regulation of inflammation by TRIMs provides insights into the use of TRIMs as therapeutic targets for disease treatment.

Contributions of Gene Modules Regulated by Essential Noncoding RNA in Colon Adenocarcinoma Progression

Noncoding RNAs (ncRNAs), especially microRNA (miRNA) and long noncoding RNA (lncRNA), have an impact on a variety of important biological processes during colon adenocarcinoma (COAD) progression. This includes chromatin organization, transcriptional and posttranscriptional regulation, and cell-cell signaling. The aim of this study is to identify the ncRNA-regulated modules that accompany the progression of COAD and to analyze their mechanisms, in order to screen the potential prognostic biomarkers for COAD. An integrative molecular analysis was carried out to identify the crosstalks of gene modules between different COAD stages, as well as the essential ncRNAs in the posttranscriptional regulation of these modules. 31 ncRNA regulatory modules were found to be significantly associated with overall survival in COAD patients. 17 out of the 31 modules (in which ncRNAs played essential roles) had improved the predictive ability for COAD patient survival compared to only the mRNAs of those modules, which were enriched in the core cancer hallmark pathways with closer interactions. These suggest that the ncRNAs' regulatory modules not only exhibit close relation to COAD progression but also reflect the dynamic significant crosstalk of genes in the modules to the different malignant extent of COAD.

CXCL8(3-72) K11R/G31P protects against sepsis-induced acute kidney injury via NF-κB and JAK2/STAT3 pathway

Background

Acute kidney injury (AKI), which is mainly caused by sepsis, has high morbidity and mortality rates. CXCL8_(3–72) K11R/G31P (G31P) can exert therapeutic effect on inflammatory diseases and malignancies. We aimed to investigate the effect and mechanism of G31P on septic AKI.

Methods

An AKI mouse model was established, and kidney injury was assessed by histological analysis. The contents of serum creatinine (SCr) and blood urea nitrogen (BUN) were measured by commercial kits, whereas neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) were detected by enzyme-linked immunosorbent assay (ELISA) kits. The expressions of CXCL8 in serum and kidney tissues were determined using ELISA and immunohistochemical analysis, respectively. Apoptosis rate of renal tissue was detected by terminal deoxynucleotidyl transfer-mediated dUTP nick end labeling (TUNEL) analysis. The expressions of inflammatory cytokines were measured by quantitative real-time PCR and Western blot, respectively. The apoptosis-related proteins, JAK2, STAT3, NF-κB and IκB were determined by Western blot.

Results

G31P could reduce the levels of SCr, BUN, HGAL and KIM-1 and inhibit the renal tissue injury in AKI mice. G31P was also found to suppress the serum and nephric CXCL8 expressions and attenuated the apoptosis rate. The levels of inflammatory cytokines, pro-apoptotic proteins were decreased, while the anti-apoptotic proteins were increased by G31P in AKI mice. G31P also inhibited the activation of JAK2, STAT3 and NF-κB in AKI mice.

Conclusion

These results suggest that G31P could protect renal function and attenuate the septic AKI. Our findings provide a potential target for the treatment of AKI.

Disease association of human tumor suppressor genes

The multifactorial disease, cancer, frequently emerges due to perturbations in tumor suppressor genes (TSGs). However, a growing number of noncanonical target genes of TSGs and the highly interconnected nature of the human interactome reveal that the functions of TSGs are not limited to cancer-specific events. The various functions of TSGs lead to the assumption that cancer is linked with other human disorders. Therefore, a disease-gene association network of TSGs (TSDN) was constructed by integrating protein-protein interaction networks of TSGs (TSN) with Morbid Map in Online Mendelian Inheritance in Man. The TSDN revealed links between TSGs and 22 different human disorders including cancer and indicated disease-disease associations. In addition, high-density functional protein clusters in the TSN showed cohesive and overlapping disease-TSG associations, which proved the prevalent role of TSGs in various human diseases beyond cancer. The presence of overlapping disease-gene modules and disease-disease associations via the TSN demonstrated that other diseases can serve as possible roots of the life-threatening disease cancer. Therefore, a disease association map of TSGs could be a promising tool for exploring intricate relationships between cancer and other diseases for the early prediction of cancer and the understanding of disease etiology.

Dysfunctional Mechanism of Liver Cancer Mediated by Transcription Factor and Non-coding RNA

Background:

There have been numerous experiments and studies on liver cancer by biomedical scientists, while no comprehensive and systematic exploration has yet been conducted. Therefore, this study aimed to systematically dissect the transcriptional and non-coding RNAmediated mechanisms of liver cancer dysfunction.

Method:

At first, we collected 974 liver cancer associated genes from the Online Mendelian Inheritance in Man (OMIM). Afterwards, their interactors were recruited from STRING database so as to identify 18 co-expression modules in liver cancer patient expression profile. Crosstalk analysis showed the interactive relationship between these modules. In addition, core drivers for modules were identified, including 111 transcription factors (STAT3, JUN and NFKB1, etc.) and 1492 ncRNAs (FENDRR and miR-340-5p, etc.).

Results:

In view of the results of enrichment, we found that these core drivers were significantly involved in Notch signaling, Wnt / β-catenin pathways, cell proliferation, apoptosis-related functions and pathways, suggesting they can affect the development of liver cancer. Furthermore, a global effect on bio-network associated with liver cancer has been integrated from the ncRNA and TF pivot network, module crosstalk network, module-function/pathways network. It involves various development and progression of cancer.

Conclusion:

Overall, our analysis further suggests that comprehensive network analysis will help us to not only understand in depth the molecular mechanisms, but also reveal the influence of related gene dysfunctional modules on the occurrence and progression of liver cancer. It provides a valuable reference for the design of liver cancer diagnosis and treatment.

Tissue-specific Network Analysis of Genetic Variants Associated with Coronary Artery Disease

Coronary artery disease (CAD) is a leading cause of death worldwide. Recent genome-wide association studies have identified more than one hundred susceptibility loci associated with CAD. However, the underlying mechanism of these genetic loci to CAD susceptibility is still largely unknown. We performed a tissue-specific network analysis of CAD using the summary statistics from one of the largest genome-wide association studies. Variant-level associations were summarized into gene-level associations, and a CAD-related interaction network was built using experimentally validated gene interactions and gene coexpression in coronary artery. The network contained 102 genes, of which 53 were significantly associated with CAD. Pathway enrichment analysis revealed that many genes in the network were involved in the regulation of peripheral arteries. In summary, we performed a tissue-specific network analysis and found abnormalities in the peripheral arteries might be an important pathway underlying the pathogenesis of CAD. Future functional characterization might further validate our findings and identify potential therapeutic targets for CAD.

Identification of Shared Molecular Signatures Indicate the Susceptibility of Endometriosis to Multiple Sclerosis

Women with endometriosis (EMS) appear to be at a higher risk of developing other autoimmune diseases predominantly multiple sclerosis (MS). Though EMS and MS are evidently diverse in their phenotype, they are linked by a common autoimmune condition or immunodeficiency which could play a role in the expansion of endometriosis and possibly increase the risk of developing MS in women with EMS. However, the common molecular links connecting EMS with MS are still unclear. We conducted a meta-analysis of microarray experiments focused on EMS and MS with their respective controls. The GEO2R web application discovered a total of 711 and 1516 genes that are differentially expressed across the experimental conditions in EMS and MS, respectively with 129 shared DEGs between them. The functional enrichment analysis of DEGs predicts the shared gene expression signatures as well as the overlapping biological processes likely to infer the co-occurrence of EMS with MS. Network based meta-analysis unveiled six interaction networks/crosstalks through overlapping edges between commonly dysregulated pathways of EMS and MS. The PTPN1, ERBB3, and CDH1 were observed to be the highly ranked hub genes connected with disease-related genes of both EMS and MS. Androgen receptor (AR) and nuclear factor-kB p65 (RelA) were observed to be the most enriched transcription factor in the upstream of shared down-regulated and up-regulated genes, respectively. The two disease sample sets compared through crosstalk interactions between shared pathways revealed commonly up- and down-regulated expressions of 10 immunomodulatory proteins as probable linkers between EMS and MS. This study pinpoints the number of shared genes, pathways, protein kinases, and upstream regulators that may help in the development of biomarkers for diagnosis of MS and endometriosis at the same time through improved understanding of shared molecular signatures and crosstalk.

CXCL8 Antagonist Improves Diabetic Nephropathy in Male Mice With Diabetes and Attenuates High Glucose-Induced Mesangial Injury

Inflammation is recognized as a crucial contribution to diabetic nephropathy (DN). CXCL8 binds to its CXC chemokine receptors (CXCR1 and CXCR2) for recruiting neutrophil infiltration and initiates tissue inflammation. Therefore, we explored the effect of CXCR1 and CXCR2 inhibition on DN. This was achieved by CXCL8(3-72)K11R/G31P (G31P), an antagonist of CXCL8 that has exhibited therapeutic efficacy in inflammatory diseases and malignancies. In this study, we found that renal leukocyte accumulation and rapid increases of CXCL8 occurred in high-fat diet/streptozocin-induced diabetic mice. G31P effectively reduced urine volume, urine albumin/creatinine ratio, blood urea nitrogen, and creatinine clearance rate in mice with diabetes. In addition, renal histopathologic changes including mesangial expansion, glomerulosclerosis, and extracellular matrix deposition were partially moderated in G31P-treated diabetic mice. Furthermore, G31P attenuated renal inflammation and renal fibrosis of diabetic mice by inhibiting proinflammatory and profibrotic elements. G31P also inhibited high glucose-induced inflammatory and fibrotic factor upregulation in human renal mesangial cells. At the molecular level, G31P inhibited activation of CXCR1/2 downstream signaling JAK2/STAT3 and ERK1/2 pathways in in vitro and in vivo experiments. Our results suggest blockade of CXCR1/2 by G31P could confer renoprotective effects that offer potential therapeutic opportunities in DN.

An Organic Anion Transporter 1 (OAT1)-centered Metabolic Network

There has been a recent interest in the broader physiological importance of multispecific "drug" transporters of the SLC and ABC transporter families. Here, a novel multi-tiered systems biology approach was used to predict metabolites and signaling molecules potentially affected by the in vivo deletion of organic anion transporter 1 (Oat1, Slc22a6, originally NKT), a major kidney-expressed drug transporter. Validation of some predictions in wet-lab assays, together with re-evaluation of existing transport and knock-out metabolomics data, generated an experimentally validated, confidence ranked set of OAT1-interacting endogenous compounds enabling construction of an "OAT1-centered metabolic interaction network." Pathway and enrichment analysis indicated an important role for OAT1 in metabolism involving: the TCA cycle, tryptophan and other amino acids, fatty acids, prostaglandins, cyclic nucleotides, odorants, polyamines, and vitamins. The partly validated reconstructed network is also consistent with a major role for OAT1 in modulating metabolic and signaling pathways involving uric acid, gut microbiome products, and so-called uremic toxins accumulating in chronic kidney disease. Together, the findings are compatible with the hypothesized role of drug transporters in remote inter-organ and inter-organismal communication: The Remote Sensing and Signaling Hypothesis (Nigam, S. K. (2015) Nat. Rev. Drug Disc. 14, 29). The fact that OAT1 can affect many systemic biological pathways suggests that drug-metabolite interactions need to be considered beyond simple competition for the drug transporter itself and may explain aspects of drug-induced metabolic syndrome. Our approach should provide novel mechanistic insights into the role of OAT1 and other drug transporters implicated in metabolic diseases like gout, diabetes, and chronic kidney disease.

Vitamin B-6 catabolism and long-term mortality risk in patients with coronary artery disease

BACKGROUND

Low vitamin B-6 status has been related to increased risk of coronary artery disease (CAD), which is a condition that is associated with inflammation. The most common status marker, plasma pyridoxal 5'-phosphate (PLP), decreases during inflammation; therefore, causal relations are uncertain.

OBJECTIVE

We evaluated the vitamin B-6 biomarkers PLP, pyridoxal, and pyridoxic acid (PA) and the pyridoxic acid:(pyridoxal + PLP) ratio (PAr), a proposed marker of vitamin B-6 catabolism during activated cellular immunity, as predictors of mortality.

DESIGN

Associations with risks of long-term all-cause mortality and cardiovascular mortality were evaluated with the use of Cox regression in patients who were undergoing elective coronary angiography for suspected stable angina pectoris (SAP) (n = 4131) and an independent cohort of patients who were hospitalized for acute myocardial infarction (AMI) (n = 3665).

RESULTS

Plasma PLP (AMI patients only) and PA predicted all-cause mortality in models that were adjusted for established risk predictors, but associations were attenuated or nonsignificant after additional adjustment for inflammatory markers. PAr was correlated with biomarkers of inflammation (Pearson's r ≥ 0.37) and predicted all-cause mortality and cardiovascular mortality after adjustment for established risk predictors. In SAP patients, PAr had greater predictive strength than did current smoking, diabetes, hypertension, apolipoproteins, or C-reactive protein. PAr provided multiadjusted HRs per SD of 1.45 (95% CI: 1.30, 1.63) and 1.31 (95% CI: 1.21, 1.41) in SAP and AMI patients, respectively. In both cohorts, PAr was a particularly strong predictor of all-cause mortality for patients with no previous CAD history (P-interaction ≤ 0.04).

CONCLUSION

PAr may capture unique aspects of inflammatory activation and thus provide new insights into disease mechanisms that may aid in identifying patients at increased risk of future fatal events.

A functional module-based exploration between inflammation and cancer in esophagus

Inflammation contributing to the underlying progression of diverse human cancers has been generally appreciated, however, explorations into the molecular links between inflammation and cancer in esophagus are still at its early stage. In our study, we presented a functional module-based approach, in combination with multiple data resource (gene expression, protein-protein interactions (PPI), transcriptional and post-transcriptional regulations) to decipher the underlying links. Via mapping differentially expressed disease genes, functional disease modules were identified. As indicated, those common genes and interactions tended to play important roles in linking inflammation and cancer. Based on crosstalk analysis, we demonstrated that, although most disease genes were not shared by both kinds of modules, they might act through participating in the same or similar functions to complete the molecular links. Additionally, we applied pivot analysis to extract significant regulators for per significant crosstalk module pair. As shown, pivot regulators might manipulate vital parts of the module subnetworks, and then work together to bridge inflammation and cancer in esophagus. Collectively, based on our functional module analysis, we demonstrated that shared genes or interactions, significant crosstalk modules, and those significant pivot regulators were served as different functional parts underlying the molecular links between inflammation and cancer in esophagus.

Integrative analysis of human protein, function and disease networks

Protein-protein interaction (PPI) networks serve as a powerful tool for unraveling protein functions, disease-gene and disease-disease associations. However, a direct strategy for integrating protein interaction, protein function and diseases is still absent. Moreover, the interrelated relationships among these three levels are poorly understood. Here we present a novel systematic method to integrate protein interaction, function, and disease networks. We first identified topological modules in human protein interaction data using the network topological algorithm (NeTA) we previously developed. The resulting modules were then associated with functional terms using Gene Ontology to obtain functional modules. Finally, disease modules were constructed by associating the modules with OMIM and GWAS. We found that most topological modules have cohesive structure, significant pathway annotations and good modularity. Most functional modules (70.6%) fully cover corresponding topological modules, and most disease modules (88.5%) are fully covered by the corresponding functional modules. Furthermore, we identified several protein modules of interest that we describe in detail, which demonstrate the power of our integrative approach. This approach allows us to link genes, and pathways with their corresponding disorders, which may ultimately help us to improve the prevention, diagnosis and treatment of disease.

Neural effects of inflammation, cardiovascular disease, and HIV: Parallel, perpendicular, or progressive?

The pervasive reach of the inflammatory system is evidenced by its involvement in numerous disease states. Cardiovascular disease, marked by high levels of circulating inflammatory mediators, affects an estimated 83.6 million Americans. Similarly, human immunodeficiency virus (HIV) produces a paradoxical state of generalized immune activity despite widespread immunosuppression, and affects 35 million people worldwide. Patients living with HIV (PLWH) suffer from inflammatory conditions, including cardiovascular disease (CVD), at a rate exceeding the general population. In this combined disease state, immune mechanisms that are common to both CVD and HIV may interact to generate a progressive condition that contributes to the exacerbated pathogenesis of the other to the net effect of damage to the brain. In this review, we will outline inflammatory cell mediators that promote cardiovascular risk factors and disease initiation and detail how HIV-related proteins may accelerate this process. Finally, we examine the extent to which these comorbid conditions act as parallel, perpendicular, or progressive sequela of events to generate a neurodegenerative environment, and consider potential strategies that can be implemented to reduce the burden of CVD and inflammation in PLWH.

Network analysis of inflammatory genes and their transcriptional regulators in coronary artery disease

Network analysis is a novel method to understand the complex pathogenesis of inflammation-driven atherosclerosis. Using this approach, we attempted to identify key inflammatory genes and their core transcriptional regulators in coronary artery disease (CAD). Initially, we obtained 124 candidate genes associated with inflammation and CAD using Polysearch and CADgene database for which protein-protein interaction network was generated using STRING 9.0 (Search Tool for the Retrieval of Interacting Genes) and visualized using Cytoscape v 2.8.3. Based on betweenness centrality (BC) and node degree as key topological parameters, we identified interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA), interleukin-1 beta (IL-1B), tumor necrosis factor (TNF) and prostaglandin-endoperoxide synthase 2 (PTGS2) as hub nodes. The backbone network constructed with these five hub genes showed 111 nodes connected via 348 edges, with IL-6 having the largest degree and highest BC. Nuclear factor kappa B1 (NFKB1), signal transducer and activator of transcription 3 (STAT3) and JUN were identified as the three core transcription factors from the regulatory network derived using MatInspector. For the purpose of validation of the hub genes, 97 test networks were constructed, which revealed the accuracy of the backbone network to be 0.7763 while the frequency of the hub nodes remained largely unaltered. Pathway enrichment analysis with ClueGO, KEGG and REACTOME showed significant enrichment of six validated CAD pathways - smooth muscle cell proliferation, acute-phase response, calcidiol 1-monooxygenase activity, toll-like receptor signaling, NOD-like receptor signaling and adipocytokine signaling pathways. Experimental verification of the above findings in 64 cases and 64 controls showed increased expression of the five candidate genes and the three transcription factors in the cases relative to the controls (p<0.05). Thus, analysis of complex networks aid in the prioritization of genes and their transcriptional regulators in complex diseases.