Integrative Analysis of Transcriptome-Wide Association Study and mRNA Expression Profiles Identifies Candidate Genes Associated With Idiopathic Pulmonary Fibrosis

Tertiary lymphoid structures and B-cell infiltration are IPF features with functional consequences

Background

Recent literature has shown the presence of B cells and autoantibodies in idiopathic pulmonary fibrosis (IPF) which would imply the presence of tertiary lymphoid structures (TLS, sites where the immune response is triggered), yet TLS are not considered features of the histological characteristics of IPF.

Aim

This study aims to quantify the presence, size, and degree of activation of TLS in biopsied and explanted lungs from patients with early- and late-IPF, never treated with antifibrotics, and relate their presence and activity to the clinical course, disease progression, and lung inflammation.

Methods

Immunohistochestry for B cells and CD4, CD8, and CD45 cells was performed in lung tissue from IPF patients: 18 at diagnosis (early), 39 explanted (end-stage), and 12 smoking controls. TLS activation was assessed by CD40 expression. Spirometry along 31 (12-72) months of follow-up was used to characterize end-stage IPF as slow progressors or rapid progressors.

Results

B cells, along with other inflammatory cells, were higher in early- and end-stage IPF than in controls (p < 0.001). In rapid progressors, all inflammatory cells were higher than in slow progressors (p < 0.05). TLS were present in 100% of early- and end-stage IPF and in 50% of controls. In end-stage IPF, the TLS area and activation score were higher than in early IPF (p < 0.0001; p = 0.005) and controls (p < 0.04; p < 0.002). TLS activation score correlated with FVC decline during follow-up in rapid progressors (r = 0.73; p = 0.007) but not in slow progressors.

Conclusions

A prominent B-cell infiltration, along with the presence of TLS, the activity of which correlates with FVC decline, is an important component of IPF from the beginning of the disease, likely playing an important role on its mechanism and progression.

Connecting intermediate phenotypes to disease using multi-omics in heart failure

Heart failure (HF) is one of the most common, complex, heterogeneous diseases in the world, with over 1-3% of the global population living with the condition. Progression of HF can be tracked via MRI measures of structural and functional changes to the heart, namely left ventricle (LV), including ejection fraction, mass, end-diastolic volume, and LV end-systolic volume. Moreover, while genome-wide association studies (GWAS) have been a useful tool to identify candidate variants involved in HF risk, they lack crucial tissue-specific and mechanistic information which can be gained from incorporating additional data modalities. This study addresses this gap by incorporating transcriptome-wide and proteome-wide association studies (TWAS and PWAS) to gain insights into genetically-regulated changes in gene expression and protein abundance in precursors to HF measured using MRI-derived cardiac measures as well as full-stage all-cause HF. We identified several gene and protein overlaps between LV ejection fraction and end-systolic volume measures. Many of the overlaps identified in MRI-derived measurements through TWAS and PWAS appear to be shared with all-cause HF. We implicate many putative pathways relevant in HF associated with these genes and proteins via gene-set enrichment and protein-protein interaction network approaches. The results of this study (1) highlight the benefit of using multi-omics to better understand genetics and (2) provide novel insights as to how changes in heart structure and function may relate to HF.

Mendelian randomization study on the causal effect of herpes simplex virus infection on idiopathic pulmonary fibrosis

BACKGROUND

Previous observational studies have shown that past infection of herpes simplex virus (HSV) is associated with idiopathic pulmonary fibrosis (IPF). The present study aims to identify the causal link between HSV infection (exposure factor) and IPF (outcome factor).

RESEARCH DESIGN AND METHODS

To date, the largest publicly available genome-wide association study (GWAS) for HSV infection (1,595 cases and 211,856 controls from Finnish ancestry) and for IPF (1,028 cases and 196,986 controls from Finnish ancestry) were used to perform this two-sample Mendelian randomization (MR) study.

RESULTS

We found no significant pleiotropy or heterogeneity of all selected nine HSV infection-associated genetic instrumental variants (IVs) in IPF GWAS dataset. Interestingly, we found that as HSV infection genetically increased, IPF risk increased based on an inverse-variance weighted (IVW) analysis (odds ratio [OR] = 1.280, 95% confidence interval [CI]: 1.048-1.563; p = 0.015) and weighted median (OR = 1.321, 95% CI: 1.032-1.692; p = 0.027).

CONCLUSIONS

Our analysis suggests a causal effect of genetically increased HSV infection on IPF risk. Thus, HSV infection may be a potential risk factor for IPF.

Transcriptome-wide association studies: recent advances in methods, applications and available databases

Genome-wide association study has identified fruitful variants impacting heritable traits. Nevertheless, identifying critical genes underlying those significant variants has been a great task. Transcriptome-wide association study (TWAS) is an instrumental post-analysis to detect significant gene-trait associations focusing on modeling transcription-level regulations, which has made numerous progresses in recent years. Leveraging from expression quantitative loci (eQTL) regulation information, TWAS has advantages in detecting functioning genes regulated by disease-associated variants, thus providing insight into mechanisms of diseases and other phenotypes. Considering its vast potential, this review article comprehensively summarizes TWAS, including the methodology, applications and available resources.

Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease

The pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) is implicated in airway inflammation, oxidative stress, protease/anti-protease and emphysema. Abnormally expressed non-coding RNAs (ncRNAs) play a vital role in regulation of COPD occurrence and progression. The regulatory mechanisms of the circRNA/lncRNA-miRNA-mRNA (competing endogenous RNA, ceRNA) networks might facilitate our cognition of RNA interactions in COPD. This study aimed to identified novel RNA transcripts and constructed the potential ceRNA networks of COPD patients. Total transcriptome sequencing of the tissues from patients with COPD (COPD) (n = 7) and non-COPD control subjects (Normal) (n = 6) was performed, and the expression profiles of differentially expressed genes (DEGs), including mRNAs, lncRNAs, circRNAs, and miRNAs, were analyzed. The ceRNA network was established based on the miRcode and miRanda databases. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), Gene Set Enrichment Analysis (GSEA), and Gene set variation analysis (GSVA) were implemented for functional enrichment analysis of DEGs. Finally, CIBERSORTx was extracted to analyze the relevance between hub genes and various immune cells.The Starbase and JASPAR databases were used to construct hub-RNA binding proteins (RBPs) and lncRNA-transcription factor (TF) interaction networks. A total of 1,796 mRNAs, 2,207 lncRNAs, and 11 miRNAs showed differentially expression between the lung tissue samples from the normal and COPD groups. Based on these DEGs, lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed respectively. In addition, ten hub genes were identified. Among them, RPS11, RPL32, RPL5, and RPL27A were associated with the proliferation, differentiation, and apoptosis of the lung tissue. The biological function revealed that TNF-α via NF-kB and IL6/JAK/STAT3 signaling pathways were involved in COPD. Our research constructed the lncRNA/circRNA-miRNA-mRNA ceRNA networks, filtrated ten hub genes may regulate the TNF-α/NF-κB, IL6/JAK/STAT3 signally pathways, which indirectly elucidated the post-transcriptional regulation mechanism of COPD and lay the foundation for excavating the novel targets of diagnosis and treatment in COPD.

Centromeric protein K (CENPK) promotes gastric cancer proliferation and migration via interacting with XRCC5

BACKGROUND

CENPK is a novel oncogene which is aberrantly expression in some malignant tumors. However, the role and mechanisms of CENPK in gastric cancer have not been explored.

METHODS

In this study, we use RT-PCR and IHC to study CENPK expression in gastric cancer cells and tissues. In addition, we constructed the two kinds of CENPK siRNA lentivirus to knock down CENPK. Then, we use High content living cell imaging System, Cell Counting Kit-8, colony formation, wound healing and Transwell assays to demonstrate the function of CENPK on gastric cancer cells AGS and MKN45. Meanwhile, we use flow cytometry assay to study CENPK function on gastric cancer cell apoptosis and cell cycle arrest. Subcutaneous tumorigenesis in nude mice was also performed to confirm CENPK function on gastric cancer. Finally, we use Co-IP, LC-MS and function rescue assay to study the downstream interaction molecular of CENPK.

RESULTS

We demonstrated that CENPK expression were up-regulated in GC cell lines. Poor differentiation and III-IV stage had more percentages of high CENPK expression. Knocking down CENPK could significantly suppress GC cells proliferation, migration and invasion, and induce GC cells apoptosis and G1/S phase transition arrest. Subcutaneous tumorigenesis confirmed the tumor-promoting effects of CENPK in vivo. Remarkably, we found for the first time that XRCC5 might be interacted with CENPK through Co-IP, LC-MS and rescue study.

CONCLUSION

CENPK promotes GC cell proliferation and migration via interacting with XRCC5 and may be a novel prognostic factor or therapeutic target for CENPK.

A Naive Bayes model on lung adenocarcinoma projection based on tumor microenvironment and weighted gene co-expression network analysis

Based on the lung adenocarcinoma (LUAD) gene expression data from the cancer genome atlas (TCGA) database, the Stromal score, Immune score and Estimate score in tumor microenvironment (TME) were computed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm. And gene modules significantly related to the three scores were identified by weighted gene co-expression network analysis (WGCNA). Based on the correlation coefficients and P values, 899 key genes affecting tumor microenvironment were obtained by selecting the two most correlated modules. It was suggested through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis that these key genes were significantly involved in immune-related or cancer-related terms. Through univariate cox regression and elastic network analysis, genes associated with prognosis of the LUAD patients were screened out and their prognostic values were further verified by the survival analysis and the University of ALabama at Birmingham CANcer (UALCAN) database. The results indicated that eight genes were significantly related to the overall survival of LUAD. Among them, six genes were found differentially expressed between tumor and control samples. And immune infiltration analysis further verified that all the six genes were significantly related to tumor purity and immune cells. Therefore, these genes were used eventually for constructing a Naive Bayes projection model of LUAD. The model was verified by the receiver operating characteristic (ROC) curve where the area under curve (AUC) reached 92.03%, which suggested that the model could discriminate the tumor samples from the normal accurately. Our study provided an effective model for LUAD projection which improved the clinical diagnosis and cure of LUAD. The result also confirmed that the six genes in the model construction could be the potential prognostic biomarkers of LUAD.

Identifying and Exploring the Candidate Susceptibility Genes of Cirrhosis Using the Multi-Tissue Transcriptome-Wide Association Study

Objective: We identify and explore the candidate susceptibility genes for cirrhosis and their underlying biological mechanism.

Methods: We downloaded the genome-wide association studies summary data of 901 cirrhosis cases and 451,363 controls and integrated them with reference models of five potential tissues from the Genotype-Tissue Expression (GTEx) Project, including whole blood, liver, pancreas, spleen, and thyroid, to identify genes whose expression is predicted to be associated with cirrhosis. Then, we downloaded gene expression data of individuals with hepatocellular carcinoma from TCGA database to conduct differential expression analysis to validate these identified genes and explored their possible role in driving cirrhosis via functional enrichment and gene set enrichment analysis (GSEA).

Results: We identified 10 significant genes (SKIV2L, JPH4, UQCC2, RP11-91I8.3, MAU2, ERAP1, PUS3, ZNF677, ARHGAP40, and SHANK3) associated with cirrhosis at a Bonferroni-corrected threshold of p < 0.01, among which two (SKIV2L and JPH4) were identified in the liver and five (SKIV2L, JPH4, MAU2, SHANK3, and UQCC2) were validated by differential expression analysis at an FDR-corrected threshold of p < 0.01. The enrichment analysis showed that the degradation process of RNA, which is enriched by 58 genes, is significantly under-enriched in liver cancer tissues (p = 0.0268).

Conclusion: We have identified several candidate genes for cirrhosis in multiple tissues and performed differential genetic analysis using the liver cancer database to verify the significant genes. We found that the genes SKIV2L and JPH4 identified in the liver are of particular concern. Finally, through enrichment analysis, we speculate that the process of mRNA transcription and RNA degradation may play a role in cirrhosis.

Identification and Validation of Potential Biomarkers and Pathways for Idiopathic Pulmonary Fibrosis by Comprehensive Bioinformatics Analysis

Objective

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, irreversible, high-mortality lung disease, but its pathogenesis is still unclear. Our purpose was to explore potential genes and molecular mechanisms underlying IPF.

Methods

IPF-related data were obtained from the GSE99621 dataset. Differentially expressed genes (DEGs) were identified between IPF and controls. Their biological functions were analyzed. The relationships between DEGs and microRNAs (miRNAs) were predicted. DEGs and pathways were validated in a microarray dataset. A protein-protein interaction (PPI) network was constructed based on these common DEGs. Western blot was used to validate hub genes in IPF cell models by western blot.

Results

DEGs were identified for IPF than controls in the RNA-seq dataset. Functional enrichment analysis showed that these DEGs were mainly enriched in immune and inflammatory response, chemokine-mediated signaling pathway, cell adhesion, and other biological processes. In the miRNA-target network based on RNA-seq dataset, we found several miRNA targets among all DEGs, like RAB11FIP1, TGFBR3, and SPP1. We identified 304 upregulated genes and 282 downregulated genes in IPF compared to controls both in the microarray and RNA-seq datasets. These common DEGs were mainly involved in cell adhesion, extracellular matrix organization, oxidation-reduction process, and lung vasculature development. In the PPI network, 3 upregulated and 4 downregulated genes could be considered hub genes, which were confirmed in the IPF cell models.

Conclusion

Our study identified several IPF-related DEGs that could become potential biomarkers for IPF. Large-scale multicentric studies are eagerly needed to confirm the utility of these biomarkers.