Weighted Gene Coexpression Network Analysis Identifies Key Genes and Pathways Associated with Idiopathic Pulmonary Fibrosis

Dissecting the lung transcriptome of pulmonary fibrosis-associated pulmonary hypertension

Integrative multiomics can help elucidate the pathophysiology of pulmonary fibrosis (PF)-associated pulmonary hypertension (PH) (PF-PH). Weighted gene coexpression network analysis (WGCNA) was performed on a transcriptomic dataset of explanted lung tissue from 116 patients with PF. Patients were stratified by pulmonary vascular resistance (PVR), and differential gene expression analysis was conducted. Gene modules were correlated with hemodynamics at the time of transplantation and tested for enrichment in the lung transcriptomics signature of an independent pulmonary arterial hypertension (PAH) cohort. We found 1,250 differentially expressed genes between high and low PVR groups. WGCNA identified that black and yellowgreen modules negatively correlated with PVR, whereas the tan and darkgrey modules are positively correlated with PVR in PF-PH. In addition, the tan module showed the strongest enrichment for an independent PAH gene signature, suggesting shared gene expression patterns between PAH and PF-PH. Pharmacotranscriptomic analysis using the Connectivity Map implicated the tan and darkgrey modules as potentially pathogenic in PF-PH, given their combined module signature demonstrated a high negative connectivity score for treprostinil, a medication used in the treatment of PF-PH, and a high positive connectivity score for bone morphogenetic protein (BMP) loss of function. Pathway enrichment analysis revealed that inflammatory pathways and oxidative phosphorylation were downregulated, whereas epithelial-mesenchymal transition was upregulated in modules associated with increased PVR. Our integrative systems biology approach to the lung transcriptome of PF with and without PH identified several PH-associated coexpression modules and gene targets with shared molecular features with PAH warranting further investigation to uncover potential new therapies for PF-PH.NEW & NOTEWORTHY An integrative systems biology approach that included transcriptomic analysis of explanted lung tissue from patients with pulmonary fibrosis (PF) with and without pulmonary hypertension (PH) undergoing lung transplantation, combined with hemodynamic correlation and pharmacotranscriptomics, identified modules of genes associated with pulmonary vascular disease severity. Comparison with an independent pulmonary arterial hypertension (PAH) dataset identified shared gene expression patterns between PAH and PF-PH.

Identification of key pathways and genes in the progression of silicosis based on WGCNA

Silicosis, induced by inhaling silica particles in workplaces, is one of the most common occupational diseases. The prognosis of silicosis and its consequent fibrosis is extremely poor due to limited treatment modalities and lack of understanding of the disease mechanisms. In this study, a Wistar rat model for silicosis fibrosis was established by intratracheal instillation of silica (0, 50, 100 and 200 mg/mL, 1 mL) with the evidence of Hematoxylin and Eosin (HE) and Masson staining and the expressions of inflammatory and fibrotic proteins of rats' lung tissues. RNA of lung tissues of rats exposed to 200 mg/mL silica particles and normal saline for 14 d and 28 d was extracted and sequenced to detect differentially expressed genes (DEGs) and to identify silicosis fibrosis-associated modules and hub genes by Weighted gene co-expression network analysis (WGCNA). Predictions of gene functions and signaling pathways were conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. In this study, it has been demonstrated the promising role of the Hippo signaling pathway in silicosis fibrosis, which will be conducive to elucidating the specific mechanism of pulmonary fibrosis induced by silica and to determining molecular initiating event (MIE) and adverse outcome pathway (AOP) of silicosis fibrosis.

Consensus Gene Co-Expression Network Analysis Identifies Novel Genes Associated with Severity of Fibrotic Lung Disease

Idiopathic pulmonary fibrosis (IPF) is a severe fibrotic lung disease characterized by irreversible scarring of the lung parenchyma leading to dyspnea, progressive decline in lung function, and respiratory failure. We analyzed lung transcriptomic data from independent IPF cohorts using weighted gene co-expression network analysis (WGCNA) to identify gene modules based on their preservation status in these cohorts. The consensus gene modules were characterized by leveraging existing clinical and molecular data such as lung function, biological processes, pathways, and lung cell types. From a total of 32 consensus gene modules identified, two modules were found to be significantly correlated with the disease, lung function, and preserved in other IPF datasets. The upregulated gene module was enriched for extracellular matrix, collagen metabolic process, and BMP signaling while the downregulated module consisted of genes associated with tube morphogenesis, blood vessel development, and cell migration. Using a combination of connectivity-based and trait-based significance measures, we identified and prioritized 103 "hub" genes (including 25 secretory candidate biomarkers) by their similarity to known IPF genetic markers. Our validation studies demonstrate the dysregulated expression of CRABP2, a retinol-binding protein, in multiple lung cells of IPF, and its correlation with the decline in lung function.

Integrative omics analysis identifies biomarkers of idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease characterized by chronic progressive pulmonary fibrosis and a poor prognosis. Genetic studies, including transcriptomic and proteomics, have provided new insight into revealing mechanisms of IPF. Herein we provided a novel strategy to identify biomarkers by integrative analysis of transcriptomic and proteomic profiles of IPF patients. We examined the landscape of IPF patients' gene expression in the transcription and translation phases and investigated the expression and functions of two new potential biomarkers. Differentially expressed (DE) mRNAs were mainly enriched in pathways associated with immune system activities and inflammatory responses, while DE proteins are related to extracellular matrix production and wound repair. The upregulated genes in both phases are associated with wound repair and cell differentiation, while the downregulated genes in both phases are associated with reduced immune activities and the damage of the alveolar tissues. On this basis, we identified thirteen potential marker genes. Among them, we validated the expression changes of butyrophilin-like 9 (BTNL9) and plasmolipin (PLLP) and investigated their functional pathways in the IPF mechanism. Both genes are downregulated in the tissues of IPF patients and Bleomycin-induced mice, and co-expression analysis indicates that they have a protective effect by inhibiting extracellular matrix production and promoting wound repair in alveolar epithelial cells.

Immune infiltration landscape and immune-marker molecular typing of pulmonary fibrosis with pulmonary hypertension

BACKGROUND

Pulmonary arterial hypertension (PH) secondary to pulmonary fibrosis (PF) is one of the most common complications in PF patients, it causes severe disease and usually have a poor prognosis. Whether the combination of PH and PF is a unique disease phenotype is unclear. We aimed to screen the key modules associated with PH-PF immune infiltration based on WGCNA and identify the hub genes for molecular typing.

METHOD

Using the gene expression profile GSE24988 of PF patients with or without PH from the Gene Expression Omnibus (GEO) database, we evaluated immune cell infiltration using Cibersortx and immune cell gene signature files. Different immune cell types were screened using the Wilcoxon test; differentially expressed genes were screened using samr. The molecular pathways implicated in these differential responses were identified using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses. A weighted co-expression network of the differential genes was constructed, relevant co-expression modules were identified, and relationships between modules and differential immune cell infiltration were calculated. The modules most relevant to this disease were identified using weighted correlation network analysis. From these, we constructed a co-expression network; using the STRING database, we integrated the values into the human protein-protein interaction network before constructing a co-expression interaction subnet, screening genes associated with immunity and unsupervised molecular typing, and analyzing the immune cell infiltration and expression of key genes in each disease type.

RESULTS

Of the 22 immune cell types from the PF GEO data, 20 different immune cell types were identified. There were 1622 differentially expressed genes (295 upregulated and 1327 downregulated). The resulting weighted co-expression network identified six co-expression modules. These were screened to identify the modules most relevant to the disease phenotype (the green module). By calculating the correlations between modules and the differentially infiltrated immune cells, extracting the green module co-expression network (46 genes), extracting 25 key genes using gene significance and module-membership thresholds, and combining these with the 10 key genes in the human protein-protein interaction network, we identified five immune cell-related marker genes that might be applied as biomarkers. Using these marker genes, we evaluated these disease samples using unsupervised clustering molecular typing.

CONCLUSION

Our results demonstrated that all PF combined with PH samples belonged to four categories. Studies on the five key genes are required to validate their diagnostic and prognostic value.

Fibromine is a multi-omics database and mining tool for target discovery in pulmonary fibrosis

Idiopathic pulmonary fibrosis is a lethal lung fibroproliferative disease with limited therapeutic options. Differential expression profiling of affected sites has been instrumental for involved pathogenetic mechanisms dissection and therapeutic targets discovery. However, there have been limited efforts to comparatively analyse/mine the numerous related publicly available datasets, to fully exploit their potential on the validation/creation of novel research hypotheses. In this context and towards that goal, we present Fibromine, an integrated database and exploration environment comprising of consistently re-analysed, manually curated transcriptomic and proteomic pulmonary fibrosis datasets covering a wide range of experimental designs in both patients and animal models. Fibromine can be accessed via an R Shiny application (http://www.fibromine.com/Fibromine) which offers dynamic data exploration and real-time integration functionalities. Moreover, we introduce a novel benchmarking system based on transcriptomic datasets underlying characteristics, resulting to dataset accreditation aiming to aid the user on dataset selection. Cell specificity of gene expression can be visualised and/or explored in several scRNA-seq datasets, in an effort to link legacy data with this cutting-edge methodology and paving the way to their integration. Several use case examples are presented, that, importantly, can be reproduced on-the-fly by a non-specialist user, the primary target and potential user of this endeavour.

The derepression of transposable elements in lung cells is associated with the inflammatory response and gene activation in idiopathic pulmonary fibrosis

BACKGROUND

Transposable elements (TEs) are repetitive sequences of viral origin that compose almost half of the human genome. These elements are tightly controlled within cells, and if activated, they can cause changes in both gene regulation and immune viral responses that have been associated with several chronic inflammatory diseases in humans. As oxidants are potent activators of TEs, and because oxidative injury is a major risk factor in relation to idiopathic pulmonary fibrosis (IPF), we hypothesized that TEs might be involved in the regulation of gene expression and so contribute to inflammation in cases of IPF. IPF is a fatal lung disease that involves the gradual replacement of the alveolar tissue with fibrotic scars as well as the accumulation of inflammatory cells in the lower respiratory tract. Although IPF is known to occur as a result of the complex interaction between age, environmental risk factors (i.e., oxidative stress) and genetics, the relative contributions of these factors to the disease remain unclear. To determine whether TEs are associated with IPF, we compared the transcriptional profiles of the genes and TEs of lung cells obtained from both healthy donors and IPF patients.

RESULTS

We quantified TE and gene expression levels using a published bulk RNA-seq dataset containing 24 subjects (16 donors and eight IPF patients), including three lung-cell types per subject, as well as an scRNA-seq dataset concerning 16 subjects (eight donors and eight IPF patients). We found evidence of TE dysregulation in the alveolar type II lung cells and alveolar macrophages of the IPF patients. In addition, the activation of the LINE1 family of elements in IPF is associated with the increased expression of TE cellular regulators (MOV10, IFI16, SAMHD1, and APOBECG3), interferon-stimulating genes (ISG15, IFI6, IFI27, IFI44, and OAS1), chemokines (CX3CL1 and CXCL9), and interleukins (IL15RA). We also propose that TE derepression might be involved in the regulation of previously reported IPF candidate genes (MUC5B, CHL1, SPP1, and MMP7).

CONCLUSION

Based on our findings, we propose that TE derepression plays an important role in the regulation of gene expression and can also prompt both the recruitment of inflammatory processes and the disruption of the immunological balance, which can lead to chronic inflammation in IPF.

Genome-Wide Epigenetic Signatures of Adaptive Developmental Plasticity in the Andes

High-altitude adaptation is a classic example of natural selection operating on the human genome. Physiological and genetic adaptations have been documented in populations with a history of living at high altitude. However, the role of epigenetic gene regulation, including DNA methylation, in high-altitude adaptation is not well understood. We performed an epigenome-wide DNA methylation association study based on whole blood from 113 Peruvian Quechua with differential lifetime exposures to high altitude (>2,500) and recruited based on a migrant study design. We identified two significant differentially methylated positions (DMPs) and 62 differentially methylated regions (DMRs) associated with high-altitude developmental and lifelong exposure statuses. DMPs and DMRs were found in genes associated with hypoxia-inducible factor pathway, red blood cell production, blood pressure, and others. DMPs and DMRs associated with fractional exhaled nitric oxide also were identified. We found a significant association between EPAS1 methylation and EPAS1 SNP genotypes, suggesting that local genetic variation influences patterns of methylation. Our findings demonstrate that DNA methylation is associated with early developmental and lifelong high-altitude exposures among Peruvian Quechua as well as altitude-adaptive phenotypes. Together these findings suggest that epigenetic mechanisms might be involved in adaptive developmental plasticity to high altitude. Moreover, we show that local genetic variation is associated with DNA methylation levels, suggesting that methylation associated SNPs could be a potential avenue for research on genetic adaptation to hypoxia in Andeans.

Mitochondrial protein gene expression and the oxidative phosphorylation pathway associated with feed efficiency and energy balance in dairy cattle

Feed efficiency and energy balance are important traits underpinning profitability and environmental sustainability in animal production. They are complex traits, and our understanding of their underlying biology is currently limited. One measure of feed efficiency is residual feed intake (RFI), which is the difference between actual and predicted intake. Variation in RFI among individuals is attributable to the metabolic efficiency of energy utilization. High RFI (H_RFI) animals require more energy per unit of weight gain or milk produced compared with low RFI (L_RFI) animals. Energy balance (EB) is a closely related trait calculated very similarly to RFI. Cellular energy metabolism in mitochondria involves mitochondrial protein (MiP) encoded by both nuclear (NuMiP) and mitochondrial (MtMiP) genomes. We hypothesized that MiP genes are differentially expressed (DE) between H_RFI and L_RFI animal groups and similarly between negative and positive EB groups. Our study aimed to characterize MiP gene expression in white blood cells of H_RFI and L_RFI cows using RNA sequencing to identify genes and biological pathways associated with feed efficiency in dairy cattle. We used the top and bottom 14 cows ranked for RFI and EB out of 109 animals as H_RFI and L_RFI, and positive and negative EB groups, respectively. The gene expression counts across all nuclear and mitochondrial genes for animals in each group were used for differential gene expression analyses, weighted gene correlation network analysis, functional enrichment, and identification of hub genes. Out of 244 DE genes between RFI groups, 38 were MiP genes. The DE genes were enriched for the oxidative phosphorylation (OXPHOS) and ribosome pathways. The DE MiP genes were underexpressed in L_RFI (and negative EB) compared with the H_RFI (and positive EB) groups, suggestive of reduced mitochondrial activity in the L_RFI group. None of the MtMiP genes were among the DE MiP genes between the groups, which suggests a non-rate limiting role of MtMiP genes in feed efficiency and warrants further investigation. The role of MiP, particularly the NuMiP and OXPHOS pathways in RFI, was also supported by our gene correlation network analysis and the hub gene identification. We validated the findings in an independent data set. Overall, our study suggested that differences in feed efficiency in dairy cows may be linked to differences in cellular energy demand. This study broadens our knowledge of the biology of feed efficiency in dairy cattle.

Identification of transcriptomic markers for developing idiopathic pulmonary fibrosis: an integrative analysis of gene expression profiles

Idiopathic pulmonary fibrosis (IPF) remains a lethal disease with unknown etiology and unmet medical need. The aim of this study was to perform an integrative analysis of multiple public microarray datasets to investigate gene expression patterns between IPF patients and healthy controls. Moreover, functional interpretation of differentially expressed genes (DEGs) was performed to assess the molecular mechanisms underlying IPF progression. DEGs between IPF and normal lung tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. Protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). 5520 DEGs were identified in IPF based on six profile datasets, including 3714 up-regulated genes and 1806 down-regulated genes. Using Venn software, a total of 367 commonly altered DEGs were revealed, including 259 up-regulated genes mostly enriched in collagen catabolic process, heparin binding, and the extracellular region. For pathway analysis, up-regulated DEGs were mainly enriched in ECM-receptor interaction, protein digestion and absorption, and focal adhesion. Finally, 24 DEGs with degrees ≥10 were screened as hub genes from the PPI network, which were enriched in protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, amoebiasis, and platelet activation. The present integrative study identified DEGs and hub genes that may be diagnostic biomarkers or therapeutic targets, and provide novel insights into the pathogenesis of IPF.

Clinical Significance and Potential Regulatory Mechanisms of Serum Response Factor in 1118 Cases of Thyroid Cancer Based on Gene Chip and RNA-Sequencing Data

Background

Thyroid cancer (TC) is one of the most prevalent endocrine malignancies and there may be many unclarified molecular events and gene types involved in TC. The objective of this study was to assess the clinical implications and potential mechanisms of serum response factor (SRF) in TC.

Material/Methods

RNA-sequencing and gene chip data with TC expression were collected from The Cancer Genome Atlas/Genotype-Tissue Expression, Gene Expression Omnibus, ArrayExpress, Sequence Read Archive, and Oncomine. SRF expression of all TC and adjacent non-cancerous tissue were calculated using the t test, STATA, and Meta-DiSc. The related pathways of the potential SRF target genes and target miRNAs were explored. Dual-luciferase reporter assay was performed to validate the association between SRF and its putative miRNA.

Results

One RNA-sequencing and 15 gene chips were collected, and the pooled standardized mean difference of SRF was −1.00. Furthermore, the area under the curve of sROC of SRF in TC was 0.8251, indicating a dramatic decreased expression of SRF in TC tissues based on 1118 cases. The intersection of differentially expressed genes in TC, SRF co-expressed genes, and SRF potential target genes achieved from Cistrome Cancer led to 169 overlapped genes. miR-330-5p was predicted to target SRF, which was further confirmed by dual-luciferase reporter assay.

Conclusions

The reduction of SRF appears to play a crucial role in the origin of TC. These properties are accomplished by the target genes of SRF, as a transcription factor, or by the axes with the associated miRNAs.

MicroRNA-31/184 is involved in transforming growth factor-β-induced apoptosis in A549 human alveolar adenocarcinoma cells

AIMS

TGF-β-induced alveolar epithelial cells apoptosis were involved in idiopathic pulmonary fibrosis (IPF). This study aimed to explore potential targets and mechanisms of IPF.

MAIN METHODS

mRNA and microRNA arrays were used to analyze differentially expressed genes and miRNAs. Several essential targets of TGF-β-SMADs and TGF-β-PI3K-AKT pathways were detected.

KEY FINDINGS

miR-31 and miR-184 expression levels were positively correlated with smad6 and smad2/akt expression levels in IPF patients. TGF-β could induce miR-31 and suppress miR-184 levels in A549 cells. miR-31 was confirmed to bind to the smad6-3'UTR and functionally suppress its expression. Down-regulated SMAD6 enhanced SMAD2/SMAD4 dimer formation and translocation due to its failure to prevent SMAD2 phosphorylation. In contrast, anti-fibrotic functions of miR-184 were abolished due to TGF-β directly suppressing miR-184 levels in A549 cells. When A549 was stimulated by TGF-β combined with or without miR-31 inhibitor/miR-184 mimic, it was showed that depleted miR-31 and/or increased miR-184 significantly ameliorated TGF-β-induced viability of A549 cells, as well as inhibited the expression of profibrotic factors, MMP7 and RUNX2.

SIGNIFICANCE

Inhibiting miR-31 and/or promoting miR-184 protect against TGF-β-induced fibrogenesis by respectively repressing the TGF-β-SMAD2 and TGF-β-PI3K-AKT signaling pathways, implying that miR-31/184 are potential targets and suggesting a new management strategy for IPF.

Integrated assessment of CDK1 upregulation in thyroid cancer

Cyclin-dependent kinase 1 (CDK1) has a unique role in cell cycle regulation, as it is crucial for cell cycle progression and cell division. The aim of the present study was to use a combination of various detection methods to examine the expression and clinical significance of CDK1 in thyroid cancer (THCA). We used in-house tissue microarrays, immunohistochemistry, public RNA-sequencing, gene microarrays, and meta-analyses to conduct a comprehensive analysis of the role of CDK1 in the occurrence and development of THCA. CDK1 protein expression was notably higher in THCA tissues than in non-cancer tissues as evidenced by the in-house tissue microarrays. The expression of CDK1 protein was also significantly higher in pathologic T3-T4 than in T1-T2 samples. The pooled standardized mean difference (SMD) for CDK1 was 0.71 (95% CI, 0.46-0.95) including a total of 931 THCA and 585 non-cancerous thyroid tissue samples. An aggregation of the immunohistochemistry results and the RNA-sequencing/microarray findings gave a pooled SMD for CDK1 expression of 2.13 (95% CI, 1.30-2.96). The final area under curve (AUC) for the summarized receiver operating characteristic (sROC) was 0.7941 using all 1102 cases of THCA and 672 cases of controls. KEGG analysis with the co-expressed genes of CDK1 in THCA demonstrated the top enriched pathways to be the cell cycle, thyroid hormone synthesis, autoimmune thyroid disease, etc. In summary, we reveal the overexpression of CDK1 in THCA based on multiple detection methods that combine independent cohorts. However, further studies are required to elucidate the molecular mechanisms of CDK1 that promotes the biological aggressiveness of THCA cells.