Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke

Screening of Hub Genes Associated with Pulmonary Arterial Hypertension by Integrated Bioinformatic Analysis

Background

Pulmonary arterial hypertension (PAH) is a disease or pathophysiological syndrome which has a low survival rate with abnormally elevated pulmonary artery pressure caused by known or unknown reasons. In addition, the pathogenesis of PAH is not fully understood. Therefore, it has become an urgent matter to search for clinical molecular markers of PAH, study the pathogenesis of PAH, and contribute to the development of new science-based PAH diagnosis and targeted treatment methods.

Methods

In this study, the Gene Expression Omnibus (GEO) database was used to downloaded a microarray dataset about PAH, and the differentially expressed genes (DEGs) between PAH and normal control were screened out. Moreover, we performed the functional enrichment analyses and protein-protein interaction (PPI) network analyses of the DEGs. In addition, the prediction of miRNA and transcriptional factor (TF) of hub genes and construction miRNA-TF-hub gene network were performed. Besides, the ROC curve was used to evaluate the diagnostic value of hub genes. Finally, the potential drug targets for the 5 identified hub genes were screened out.

Results

69 DEGs were identified between PAH samples and normal samples. GO and KEGG pathway analyses revealed that these DEGs were mostly enriched in the inflammatory response and cytokine-cytokine receptor interaction, respectively. The miRNA-hub genes network was conducted subsequently with 131 miRNAs, 7 TFs, and 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) which screened out via constructing the PPI network. 17 drugs interacted with 5 hub genes were identified.

Conclusions

Through bioinformatic analysis of microarray data sets, 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) were identified from DEGs between control samples and PAH samples. Studies showed that the five hub genes might play an important role in the development of PAH. These 5 hub genes might be potential biomarkers for diagnosis or targets for the treatment of PAH. In addition, our work also indicated that paying more attention on studies based on these 5 hub genes might help to understand the molecular mechanism of the development of PAH.

Comprehensive analysis of autophagy-related genes and patterns of immune cell infiltration in valvular atrial fibrillation

Background

The development of atrial fibrillation (AF) following valvular heart disease (VHD) remains a common disease and is associated with substantial adverse complications. However, valid molecular diagnostic and therapeutic tools for post-VHD AF have not been fully established. This study was conducted to discover the molecular mechanisms and immune microenvironment underlying AF following VHD.

Methods

Gene expression profiles of the GSE41177 dataset were assessed to construct a protein–protein interaction network, and then, autophagy-related hub genes were identified. In addition, to determine the functions of immune cell infiltration in valvular AF, we used the CIBERSORT algorithm to estimate the composition of 22 immune cell types in valvular heart disease. Finally, correlation analysis was carried out to identify the relationship between differentially expressed autophagy-related genes (DEARGs) and significant immune cell subpopulations to reveal potential regulatory pathways.

Results

A total of 153 DEARGs were identified in AF-VHD patients compared with controlled donors. Moreover, we screened the top ten hub nodes with the highest degrees through a network analysis. The ten hub nodes were considered hub genes related to AF genesis and progression. Then, we revealed six significant immune cell subpopulations through the CIBERSORT algorithm. Finally, correlation analysis was performed, and six DEARGs (BECN1, GAPDH, ATG7, MAPK3, BCL2L1, and MYC) and three immune cell subpopulations (T cells CD4 memory resting, T cells follicular helper, and neutrophils) were identified as the most significant potential regulators.

Conclusion

The DEARGs and immune cells identified in our study may be critical in AF development following VHD and provide potential predictive markers and therapeutic targets for determining a treatment strategy for AF patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-01939-1.

Identified GNGT1 and NMU as Combined Diagnosis Biomarker of Non-Small-Cell Lung Cancer Utilizing Bioinformatics and Logistic Regression

Non-small-cell lung cancer (NSCLC) is one of the most devastating diseases worldwide. The study is aimed at identifying reliable prognostic biomarkers and to improve understanding of cancer initiation and progression mechanisms. RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA) database. Subsequently, comprehensive bioinformatics analysis incorporating gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the protein-protein interaction (PPI) network was conducted to identify differentially expressed genes (DEGs) closely associated with NSCLC. Eight hub genes were screened out using Molecular Complex Detection (MCODE) and cytoHubba. The prognostic and diagnostic values of the hub genes were further confirmed by survival analysis and receiver operating characteristic (ROC) curve analysis. Hub genes were validated by other datasets, such as the Oncomine, Human Protein Atlas, and cBioPortal databases. Ultimately, logistic regression analysis was conducted to evaluate the diagnostic potential of the two identified biomarkers. Screening removed 1,411 DEGs, including 1,362 upregulated and 49 downregulated genes. Pathway enrichment analysis of the DEGs examined the Ras signaling pathway, alcoholism, and other factors. Ultimately, eight prioritized genes (GNGT1, GNG4, NMU, GCG, TAC1, GAST, GCGR1, and NPSR1) were identified as hub genes. High hub gene expression was significantly associated with worse overall survival in patients with NSCLC. The ROC curves showed that these hub genes had diagnostic value. The mRNA expressions of GNGT1 and NMU were low in the Oncomine database. Their protein expressions and genetic alterations were also revealed. Finally, logistic regression analysis indicated that combining the two biomarkers substantially improved the ability to discriminate NSCLC. GNGT1 and NMU identified in the current study may empower further discovery of the molecular mechanisms underlying NSCLC's initiation and progression.

Bioinformatic gene analysis for potential therapeutic targets of Huntington's disease in pre-symptomatic and symptomatic stage

Background

Huntington’s disease (HD) is a neurodegenerative disorder characterized by psychiatric symptoms, serious motor and cognitive deficits. Certain pathological changes can already be observed in pre-symptomatic HD (pre-HD) patients; however, the underlying molecular pathogenesis is still uncertain and no effective treatments are available until now. Here, we reanalyzed HD-related differentially expressed genes from the GEO database between symptomatic HD patients, pre-HD individuals, and healthy controls using bioinformatics analysis, hoping to get more insight in the pathogenesis of both pre-HD and HD, and shed a light in the potential therapeutic targets of the disease.

Methods

Pre-HD and symptomatic HD differentially expressed genes (DEGs) were screened by bioinformatics analysis Gene Expression Omnibus (GEO) dataset GSE1751. A protein–protein interaction (PPI) network was used to select hub genes. Subsequently, Gene Ontology (GO) enrichment analysis of DEGs and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of hub genes were applied. Dataset GSE24250 was downloaded to verify our hub genes by the Kaplan–Meier method using Graphpad Prism 5.0. Finally, target miRNAs of intersected hub genes involved in pre-HD and symptomatic HD were predicted.

Results

A total of 37 and 985 DEGs were identified in pre-HD and symptomatic HD, respectively. The hub genes, SIRT1, SUZ12, and PSMC6, may be implicated in pre-HD, and the hub genes, FIS1, SIRT1, CCNH, SUZ12, and 10 others, may be implicated in symptomatic HD. The intersected hub genes, SIRT1 and SUZ12, and their predicted target miRNAs, in particular miR-22-3p and miR-19b, may be significantly associated with pre-HD.

Conclusion

The PSMC6, SIRT1, and SUZ12 genes and their related ubiquitin-mediated proteolysis, transcriptional dysregulation, and histone metabolism are significantly associated with pre-HD. FIS1, CCNH, and their related mitochondrial disruption and transcriptional dysregulation processes are related to symptomatic HD, which might shed a light on the elucidation of potential therapeutic targets in HD.

Can miRNAs Be Considered as Diagnostic and Therapeutic Molecules in Ischemic Stroke Pathogenesis?-Current Status

Ischemic stroke is one of the leading causes of death worldwide. Clinical manifestations of stroke are long-lasting and causing economic burden on the patients and society. Current therapeutic modalities to treat ischemic stroke (IS) are unsatisfactory due to the intricate pathophysiology and poor functional recovery of brain cellular compartment. MicroRNAs (miRNA) are endogenously expressed small non-coding RNA molecules, which can act as translation inhibitors and play a pivotal role in the pathophysiology associated with IS. Moreover, miRNAs may be used as potential diagnostic and therapeutic tools in clinical practice; yet, the complete role of miRNAs is enigmatic during IS. In this review, we explored the role of miRNAs in the regulation of stroke risk factors viz., arterial hypertension, metabolic disorders, and atherosclerosis. Furthermore, the role of miRNAs were reviewed during IS pathogenesis accompanied by excitotoxicity, oxidative stress, inflammation, apoptosis, angiogenesis, neurogenesis, and Alzheimer's disease. The functional role of miRNAs is a double-edged sword effect in cerebral ischemia as they could modulate pathological mechanisms associated with risk factors of IS. miRNAs pertaining to IS pathogenesis could be potential biomarkers for stroke; they could help researchers to identify a particular stroke type and enable medical professionals to evaluate the severity of brain injury. Thus, ascertaining the role of miRNAs may be useful in deciphering their diagnostic role consequently it is plausible to envisage a suitable therapeutic modality against IS.

Insight into atrial fibrillation through analysis of the coding transcriptome in humans

Atrial fibrillation is the most common sustained cardiac arrhythmia in humans, and its prevalence continues to increase because of the aging of the world population. Much still needs to be learned about the molecular pathways involved in the development and the persistence of the disease. Analysis of the transcriptome of cardiac tissue has provided valuable insight into diverse aspects of atrial remodeling, in particular concerning electrical remodeling-related to ion channels-and structural remodeling identified by dysregulation of processes linked to inflammation, fibrosis, oxidative stress, and thrombogenesis. The huge amount of data produced by these studies now represents a valuable source for the identification of novel potential therapeutic targets. In addition, the shift from cardiac tissue to peripheral blood as a substrate for transcriptome analysis revealed this strategy as a promising tool for improved diagnosis and therefore better patient care.

Vascular smooth muscle cell phenotypic transition regulates gap junctions of cardiomyocyte

Atrial fibrillation (AF) is one of the most prevalent arrhythmias. Myocardial sleeves of the pulmonary vein are critical in the occurrence of AF. Our study aims to investigate the effect of synthetic vascular smooth muscle cells (SMCs) on gap junction proteins in cardiomyocytes. (1) Extraction of vascular SMCs from the pulmonary veins of Norway rats. TGF-β1 was used to induce the vascular SMCs switching to the synthetic phenotype and 18-α-GA was used to inhibit gap junctions of SMCs. The contractile and synthetic phenotype vascular SMCs were cocultured with HL-1 cells; (2) Western blotting was used to detect the expression of Cx43, Cx40 and Cx45 in HL-1 cells, and RT-PCR to test microRNA 27b in vascular SMCs or in HL-1 cells; (3) Lucifer yellow dye transfer experiment was used to detect the function of gap junctions. (1) TGF- β1 induced the vascular SMCs switching to synthetic phenotype; (2) Cx43 was significantly increased, and Cx40 and Cx45 were decreased in HL-1 cocultured with synthetic SMCs; (3) The fluorescence intensity of Lucifer yellow was higher in HL-1 cocultured with synthetic SMCs than that in the cells cocultured with contractile SMCs, which was inhibited by18-α-GA; (4) the expression of microRNA 27b was increased in HL-1 cocultured with synthetic SMCs, which was attenuated markedly by 18-α-GA. (5) the expression of ZFHX3 was decreased in HL-1 cocultured with synthetic SMCs, which was reversed by 18-α-GA. The gap junction proteins of HL-1 were regulated by pulmonary venous SMCs undergoing phenotypic transition in this study, accompanied with the up-regulation of microRNA 27b and the down-regulation of ZFHX3 in HL-1 cells, which was associated with heterocellular gap junctions between HL-1 and pulmonary venous SMCs.

Upregulated C-C Motif Chemokine Ligand 2 Promotes Ischemic Stroke via Chemokine Signaling Pathway

BACKGROUND

This study aims to evaluate the potential effect and the underlying mechanism of C-C motif chemokine ligand 2 (CCL2) in ischemic stroke.

METHODS

An integrated bioinformatics analysis was performed to identify the differentially expressed (DE) genes and their related pathways in ischemic stroke. In vivo study of a rat model of middle cerebral artery occlusion (MCAO) was further established to assess the effect of CCL2 on severity of neurologic impairments. The expression levels of proinflammatory cytokines were also evaluated using the ELISA assay, and Western blot was also used to determine the expression of CCL2 and other DE proteins in the related pathways.

RESULTS

A total of 88 DE genes were identified from the microarray dataset of ischemic stroke. The bioinformatics analysis revealed that CCL2 was highly expressed in ischemic stroke tissue and promoted the ischemic stroke progression via activation of the chemokine signaling pathway and cytokine-cytokine receptor interaction pathway. The in vivo study of the ischemic stroke rat model also showed that the CCL2 expression was elevated in the MCAO/R rats, with significant neurological impairments and ischemic infarct area in the brain tissue being observed. The administration of CCL2 inhibitors significantly inhibited the inflammatory response, attenuated the neurological impairments, and decreased the ischemic infarct area in the MCAO/R rats. Furthermore, the downregulation of CCL2 also inhibited the expression of the pathway-related proteins including CCL7, CCR2, CXCL16, and TNF-α.

CONCLUSIONS

These results indicate that the CCL2/chemokine signaling pathway is responsible for ischemic stroke progression and might represent a potential therapeutic target for ischemic stroke treatment.

Virtual Screening of the Multi-pathway and Multi-gene Regulatory Molecular Mechanism of Dachengqi Decoction in the Treatment of Stroke Based on Network Pharmacology

BACKGROUND

Stroke is ranked second among diseases that cause mortality worldwide. Owing to its complicated pathogenesis, no satisfactory treatment strategies for stroke are available. Dachengqi decoction (DCQD), a traditional Chinese herbal medicine, has been widely used in China for a long time, as it has a good effect on stroke. However, the molecular mechanism underlying this effect of DCQD is unclear.

OBJECTIVE

In the present study, we aimed to reveal and explore the multi-pathway and multi-gene regulatory molecular mechanism of Dachengqi decoction in the treatment of stroke.

METHODS

In this study, a network pharmacology method, in combination with oral bioavailability prediction and drug-likeness evaluation, was employed to predict the active ingredients of DCQD. The target genes of the active components and the traced pathways related to these target genes were predicted. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using clusterProfiler software package on the R platform and ClueGo+CluePedia plug-ins. Finally, the key DCQD targets were verified using the Gene Expression Omnibus (GEO) dataset.

RESULTS AND DISCUSSION

According to the ADME model, 52 active components were screened from 296 active components of DCQD. After prediction and screening, 215 stroke-related targets were obtained and analyzed via GO and KEGG analyses. GO analysis showed that DCQD targets were mainly involved in the regulation of oxidative stress, lipid metabolism, inflammation, and other biological processes. KEGG pathway analysis further revealed pathways involved in stroke, such as arachidonic acid metabolic, HIF-1 signaling pathway, estrogen signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, platelet activation pathway, VEGF signaling pathway, and cAMP signaling pathway. Network analysis revealed that DCQD might be involved in the regulation of lipid metabolism, blood pressure, inflammation, angiogenesis, neuroprotection, platelet aggregation, apoptosis, and oxidation in stroke treatment. GEO dataset analysis showed that DCQD's therapeutic effects might be exerted via the bidirectional regulation principle.

CONCLUSION

Based on the methods of network pharmacology and GEO analysis, it was found that, during stroke treatment, DCQD regulates and controls multiple genes and multiple pathways in a synergistic manner, providing a new strategy for stroke treatment.

Potential mechanisms and serum biomarkers involved in sex differences in pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a disease associated with high mortality, but notable sex differences have been observed between males and females. For this reason, further research on the mechanisms underlying sex differences in PAH is required to better understand and treat the disease. This study mainly focused on gene expression levels to investigate potential differences in the pathogenesis and progression of PAH between the male and female sexes.Sex-specific differentially expressed genes (DEGs) were analyzed using the Gene Expression Omnibus datasets GSE117261 and GSE38267. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted, and a protein-protein interaction (PPI) network was established based on the identified DEGs to predict potential mechanisms involved in the observed sex differences in the pathogenesis of PAH.We identified 26 female- and 53 male-specific DEGs from lung tissue and 498 female-specific DEGs in blood samples. No male-specific DEGs were identified from blood samples. GO and KEGG pathway analyses revealed that female-specific DEGs in lung tissue were enriched in inflammatory response and cytokine-cytokine receptor interaction, whereas male-specific DEGs were mainly enriched in cellular chemotaxis and the nuclear factor of kappa light polypeptide gene enhancer in B-cell (NF-kappa B) signaling pathway. Lipocalin 2 (LCN2) was the only gene that was differentially expressed in both the lung tissue and the blood of female patients.In conclusion, inflammation and immunity may play key roles in the pathogenesis of female PAH, and LCN2 may act as a serum biomarker of female PAH, whereas the pathogenesis in males is more complicated.

Identification of significant gene biomarkers of low back pain caused by changes in the osmotic pressure of nucleus pulposus cells

The incidence of intervertebral disc (IVD) degeneration disease, caused by changes in the osmotic pressure of nucleus pulposus (NP) cells, increases with age. In general, low back pain is associated with IVD degeneration. However, the mechanism and molecular target of low back pain have not been elucidated, and there are no data suggesting specific biomarkers of low back pain. Therefore, the research aims to identify and verify the significant gene biomarkers of low back pain. The differentially expressed genes (DEGs) were screened in the Gene Expression Omnibus (GEO) database, and the identification and analysis of significant gene biomarkers were also performed with various bioinformatics programs. A total of 120 patients with low back pain were recruited. Before surgery, the degree of pain was measured by the numeric rating scale (NRS), which enables comparison of the pain scores from individuals. After surgery, IVD tissues were obtained, and NP cells were isolated. The NP cells were cultured in two various osmotic media, including iso-osmotic media (293 mOsm/kg H₂O) to account for the morbid environment of NP cells in IVD degeneration disease and hyper-osmotic media (450 mOsm/kg H₂O) to account for the normal condition of NP cells in healthy individuals. The relative mRNA expression levels of CCL5, OPRL1, CXCL13, and SST were measured by quantitative real-time PCR in the in vitro analysis of the osmotic pressure experiments. Finally, correlation analysis and a neural network module were employed to explore the linkage between significant gene biomarkers and pain. A total of 371 DEGs were identified, including 128 downregulated genes and 243 upregulated genes. Furthermore, the four genes (CCL5, OPRL1, SST, and CXCL13) were identified as significant gene biomarkers of low back pain (P < 0.001) based on univariate linear regression, and CCL5 (odds ratio, 34.667; P = 0.003) and OPRL1 (odds ratio, 19.875; P < 0.001) were significantly related to low back pain through multivariate logistic regression. The expression of CCL5 and OPRL1 might be correlated with low back pain in patients with IVD degeneration disease caused by changes in the osmotic pressure of NP cells.

Aberrant Expression Profiles of lncRNAs and Their Associated Nearby Coding Genes in the Hippocampus of the SAMP8 Mouse Model with AD

The senescence-accelerated mouse prone 8 (SAMP8) mouse model is a useful model for investigating the fundamental mechanisms involved in the age-related learning and memory deficits of Alzheimer’s disease (AD), while the SAM/resistant 1 (SAMR1) mouse model shows normal features. Recent evidence has shown that long non-coding RNAs (lncRNAs) may play an important role in AD pathogenesis. However, a comprehensive and systematic understanding of the function of AD-related lncRNAs and their associated nearby coding genes in AD is still lacking. In this study, we collected the hippocampus, the main area of AD pathological processes, of SAMP8 and SAMR1 animals and performed microarray analysis to identify aberrantly expressed lncRNAs and their associated nearby coding genes, which may contribute to AD pathogenesis. We identified 3,112 differentially expressed lncRNAs and 3,191 differentially expressed mRNAs in SAMP8 mice compared to SAMR1 mice. More than 70% of the deregulated lncRNAs were intergenic and exon sense-overlapping lncRNAs. Gene Ontology (GO) and pathway analyses of the AD-related transcripts were also performed and are described in detail, which imply that metabolic process reprograming was likely related to AD. Furthermore, six lncRNAs and six mRNAs were selected for further validation of the microarray results using quantitative PCR, and the results were consistent with the findings from the microarray. Moreover, we analyzed 780 lincRNAs (also called long “intergenic” non-coding RNAs) and their associated nearby coding genes. Among these lincRNAs, AK158400 had the most genes nearby (n = 13), all of which belonged to the histone cluster 1 family, suggesting regulation of the nucleosome structure of the chromosomal fiber by affecting nearby genes during AD progression. In addition, we also identified 97 aberrant antisense lncRNAs and their associated coding genes. It is likely that these dysregulated lncRNAs and their associated nearby coding genes play a role in the development and/or progression of AD.