Analysis of Peripheral Blood Cells' Transcriptome in Patients With Subarachnoid Hemorrhage From Ruptured Aneurysm Reveals Potential Biomarkers

Identification of differentially expressed autophagy-related genes in cases of intracranial aneurysm: Bioinformatics analysis

OBJECTIVE

Recent research indicates that autophagy is essential for the rupture of intracranial aneurysm (IA). This study aimed to examine and validate potential autophagy-related genes (ARGs) in cases of IA using bioinformatics analysis.

METHODS

Two expression profiles (GSE54083 and GSE75436) were obtained from the Gene Expression Omnibus database. Differentially expressed ARGs (DEARGs) in cases of IA were screened using GSE75436, and enrichment analysis and Protein-Protein Interaction (PPI) networks were used to identify the hub genes and related pathways. Furthermore, a novel predictive diagnostic signature for IA based on the hub genes was constructed. The area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the signature performance in GSE75436.

RESULTS

In total, 75 co-expressed DEARGs were identified in the GSE75436 and GSE54083 dataset (28 upregulated and 47 downregulated genes). Enrichment analysis of DEARGs revealed several enriched terms associated with proteoglycans in cancer and human immunodeficiency virus 1 infection. PPI analysis revealed interactions between these genes. Hub DEARGs included insulin-like growth factor 1, clusters of differentiation 4, cysteine-aspartic acid protease 8, Bcl-2-like protein 11, mouse double mutant 2 homolog, toll-like receptor 4, growth factor receptor-bound protein 2, Jun proto-oncogene, AP-1 transcription factor subunit, hypoxia inducible factor 1 alpha, and erythroblastic oncogene B-2. Notably, the signature showed good performance in distinguishing IA (AUC = 0.87). The sig calibration curves showed good calibration.

CONCLUSION

Bioinformatic analysis identified 75 potential DEARGs in cases of IA. This study revealed that IA is affected by autophagy, which could explain the pathogenesis of IA and aid in its diagnosis and treatment. However, future research with experimental validation is necessary to identify potential DEARGs in cases of IA.

Comprehensive analysis of mitochondrial dysfunction and necroptosis in intracranial aneurysms from the perspective of predictive, preventative, and personalized medicine

Mitochondrial dysfunction and necroptosis are closely associated, and play vital roles in the medical strategy of multiple cardiovascular diseases. However, their implications in intracranial aneurysms (IAs) remain unclear. In this study, we aimed to explore whether mitochondrial dysfunction and necroptosis could be identified as valuable starting points for predictive, preventive, and personalized medicine for IAs. The transcriptional profiles of 75 IAs and 37 control samples were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), weighted gene co-expression network analysis, and least absolute shrinkage and selection operator (LASSO) regression were used to screen key genes. The ssGSEA algorithm was performed to establish phenotype scores. The correlation between mitochondrial dysfunction and necroptosis was evaluated using functional enrichment crossover, phenotype score correlation, immune infiltration, and interaction network construction. The IA diagnostic values of key genes were identified using machine learning. Finally, we performed the single-cell sequencing (scRNA-seq) analysis to explore mitochondrial dysfunction and necroptosis at the cellular level. In total, 42 IA-mitochondrial DEGs and 15 IA-necroptosis DEGs were identified. Screening revealed seven  key genes invovled in mitochondrial dysfunction (KMO, HADH, BAX, AADAT, SDSL, PYCR1, and MAOA) and five genes involved in necroptosis (IL1B, CAMK2G, STAT1, NLRP3, and BAX). Machine learning confirmed the high diagnostic value of these key genes for IA. The IA samples showed  higher expression of mitochondrial dysfunction and necroptosis. Mitochondrial dysfunction and necroptosis exhibited a close association. Furthermore, scRNA-seq indicated that mitochondrial dysfunction and necroptosis were preferentially up-regulated in monocytes/macrophages and vascular smooth muscle cells (VSMCs) within IA lesions. In conclusion, mitochondria-induced necroptosis was involved in IA formation, and was mainly up-regulated in monocytes/macrophages and VSMCs within IA lesions. Mitochondria-induced necroptosis may be a novel potential target for diagnosis, prevention, and treatment of IA.

Transcriptomic Studies on Intracranial Aneurysms

Intracranial aneurysm (IA) is a relatively common vascular malformation of an intracranial artery. In most cases, its presence is asymptomatic, but IA rupture causing subarachnoid hemorrhage is a life-threating condition with very high mortality and disability rates. Despite intensive studies, molecular mechanisms underlying the pathophysiology of IA formation, growth, and rupture remain poorly understood. There are no specific biomarkers of IA presence or rupture. Analysis of expression of mRNA and other RNA types offers a deeper insight into IA pathobiology. Here, we present results of published human studies on IA-focused transcriptomics.

Identification of co-expressed central genes and transcription factors in atherosclerosis-related intracranial aneurysm

Background

Numerous clinical studies have shown that atherosclerosis is one of the risk factors for intracranial aneurysms. Calcifications in the intracranial aneurysm walls are frequently correlated with atherosclerosis. However, the pathogenesis of atherosclerosis-related intracranial aneurysms remains unclear. This study aims to investigate this mechanism.

Methods

The Gene Expression Omnibus (GEO) database was used to download the gene expression profiles for atherosclerosis (GSE100927) and intracranial aneurysms (GSE75436). Following the identification of the common differentially expressed genes (DEGs) of atherosclerosis and intracranial aneurysm, the network creation of protein interactions, functional annotation, the identification of hub genes, and co-expression analysis were conducted. Thereafter, we predicted the transcription factors (TF) of hub genes and verified their expressions.

Results

A total of 270 common (62 downregulated and 208 upregulated) DEGs were identified for subsequent analysis. Functional analyses highlighted the significant role of phagocytosis, cytotoxicity, and T-cell receptor signaling pathways in this disease progression. Eight hub genes were identified and verified, namely, CCR5, FCGR3A, IL10RA, ITGAX, LCP2, PTPRC, TLR2, and TYROBP. Two TFs were also predicted and verified, which were IKZF1 and SPI1.

Conclusion

Intracranial aneurysms are correlated with atherosclerosis. We identified several hub genes for atherosclerosis-related intracranial aneurysms and explored the underlying pathogenesis. These discoveries may provide new insights for future experiments and clinical practice.

The clinical significance of peripheral blood cell ratios in patients with intracranial aneurysm

Background and objective

Inflammation is an important factor in the development of aneurysm, and has been identified as a key characteristic predictive of rupture of intracranial aneurysm (IA). However, the role of inflammatory peripheral blood cell ratios in patients with IA has not been well delineated.

Methods

A total of 1,209 patients, including 1,001 with unruptured IA and 208 with ruptured IA, were enrolled in this study. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), platelet-to-neutrophil ratio (PNR), and platelet-to-white-blood-cell ratio (PWR) were compared between ruptured and unruptured IA.

Results

Compared with the ruptured IA group, the unruptured IA group had higher PNR {median, 65.96 [interquartile range (IQR) 48.95-85.05] vs. 37.78 (IQR, 23.17-54.05); p < 0.001} and PWR [median, 36.89 (IQR 29.38-44.56) vs. 22.39 (IQR, 16.72-29.29); p < 0.001]. In multivariate analysis, PNR and PWR were independently associated with ruptured IA (p = 0.001 and p < 0.001, respectively). Unruptured IA subgroup analyses according to the PHASES scores showed that a higher PHASES score was associated with significantly higher NLR and erythrocyte sedimentation rate (p < 0.001 and p = 0.025) and lower PNR and PWR (p < 0.001 and p = 0.007).

Conclusions

We demonstrated that lower PNR and PWR levels are associated with ruptured IA and a higher PHASES score. Unlike many other inflammatory markers and bioassays, peripheral blood cell ratios are inexpensive and readily available biomarkers that may be useful for risk stratification in patients with cerebral aneurysm. However, a long-term prospective study is needed to clarify this matter.

Identification of Circulating Gene Expression Signatures of Intracranial Aneurysm in Peripheral Blood Mononuclear Cells

Peripheral blood mononuclear cells (PBMCs) play an important role in the inflammation that accompanies intracranial aneurysm (IA) pathophysiology. We hypothesized that PBMCs have different transcriptional profiles in patients harboring IAs as compared to IA-free controls, which could be the basis for potential blood-based biomarkers for the disease. To test this, we isolated PBMC RNA from whole blood of 52 subjects (24 with IA, 28 without) and performed next-generation RNA sequencing to obtain their transcriptomes. In a randomly assigned discovery cohort of n = 39 patients, we performed differential expression analysis to define an IA-associated signature of 54 genes (q < 0.05 and an absolute fold-change ≥ 1.3). In the withheld validation dataset, these genes could delineate patients with IAs from controls, as the majority of them still had the same direction of expression difference. Bioinformatics analyses by gene ontology enrichment analysis and Ingenuity Pathway Analysis (IPA) demonstrated enrichment of structural regulation processes, intracellular signaling function, regulation of ion transport, and cell adhesion. IPA analysis showed that these processes were likely coordinated through NF-kB, cytokine signaling, growth factors, and TNF activity. Correlation analysis with aneurysm size and risk assessment metrics showed that 4/54 genes were associated with rupture risk. These findings highlight the potential to develop predictive biomarkers from PBMCs to identify patients harboring IAs.

Identification of upregulated NF-κB inhibitor alpha and IRAK3 targeting lncRNA following intracranial aneurysm rupture-induced subarachnoid hemorrhage

Background

This study was performed to identify genes and lncRNAs involved in the pathogenesis of subarachnoid hemorrhage (SAH) from ruptured intracranial aneurysm (RIA).

Methods

Microarray GSE36791 was downloaded from Gene Expression Omnibus (GEO) database followed by the identification of significantly different expressed RNAs (DERs, including lncRNA and mRNA) between patients with SAH and healthy individuals. Then, the functional analyses of DEmRNAs were conducted and weighted gene co-expression network analysis (WGCNA) was also performed to extract the modules associated with SAH. Following, the lncRNA-mRNA co-expression network was constructed and the gene set enrichment analysis (GSEA) was performed to screen key RNA biomarkers involved in the pathogenesis of SAH from RIA. We also verified the results in a bigger dataset GSE7337.

Results

Totally, 561 DERs, including 25 DElncRNAs and 536 DEmRNAs, were identified. Functional analysis revealed that the DEmRNAs were mainly associated with immune response-associated GO-BP terms and KEGG pathways. Moreover, there were 6 modules significantly positive-correlated with SAH. The lncRNA-mRNA co-expression network contained 2 lncRNAs (LINC00265 and LINC00937) and 169 mRNAs. The GSEA analysis showed that these two lncRNAs were associated with three pathways (cytokine-cytokine receptor interaction, neurotrophin signaling pathway, and apoptosis). Additionally, IRAK3 and NFKBIA involved in the neurotrophin signaling pathway and apoptosis while IL1R2, IL18RAP and IL18R1 was associated with cytokine-cytokine receptor interaction pathway. The expression levels of these genes have the same trend in GSE36791 and GSE7337.

Conclusion

LINC00265 and LINC00937 may be implicated with the pathogenesis of SAH from RIA. They were involved in three important regulatory pathways. 5 mRNAs played important roles in the three pathways.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02156-1.

Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome

Sepsis is defined as dysregulated host response caused by systemic infection, leading to organ failure. It is a life-threatening condition, often requiring admission to an intensive care unit (ICU). The causative agents and processes involved are multifactorial but are characterized by an overarching inflammatory response, sharing elements in common with severe inflammatory response syndrome (SIRS) of non-infectious origin. Sepsis presents with a range of pathophysiological and genetic features which make clinical differentiation from SIRS very challenging. This may reflect a poor understanding of the key gene inter-activities and/or pathway associations underlying these disease processes. Improved understanding is critical for early differential recognition of sepsis and SIRS and to improve patient management and clinical outcomes. Judicious selection of gene biomarkers suitable for development of diagnostic tests/testing could make differentiation of sepsis and SIRS feasible. Here we describe a methodologic framework for the identification and validation of biomarkers in SIRS, sepsis and septic shock patients, using a 2-tier gene screening, artificial neural network (ANN) data mining technique, using previously published gene expression datasets. Eight key hub markers have been identified which may delineate distinct, core disease processes and which show potential for informing underlying immunological and pathological processes and thus patient stratification and treatment. These do not show sufficient fold change differences between the different disease states to be useful as primary diagnostic biomarkers, but are instrumental in identifying candidate pathways and other associated biomarkers for further exploration.

A bioinformatics investigation into the pharmacological mechanisms of the effect of the Yinchenhao decoction on hepatitis C based on network pharmacology

Background

Globally, more than 170 million people are infected with hepatitis C virus, a major cause of cirrhosis and hepatocellular carcinoma. The Yinchenhao Decoction (YCHD) is a classic formula comprising three herbal medicines. This decoction have long been used in China for clinically treating acute and chronic infectious hepatitis and other liver and gallbladder damp heat-accumulation disorders.

Methods

In this study, we identified 32 active ingredients and 200 hepatitis C proteins and established a compound-predicted target network and a hepatitis C protein–protein interaction network by using Cytoscape 3.6.1. Then, we systematically analyzed the potential targets of the YCHD for the treatment of hepatitis C. Finally, molecular docking was applied to verify the key targets. In addition, we analyzed the mechanism of action of the predicted targets by the Kyoto Encyclopedia of Genes and Genomes and gene ontology analyses.

Results

This study adopted a network pharmacology approach, mainly comprising target prediction, network construction, module detection, functional enrichment analysis, and molecular docking to systematically investigate the mechanisms of action of the YCHD in hepatitis C. The targets of the YCHD in the treatment of hepatitis C mainly involved PIK3CG, CASP3, BCL2, CASP8, and MMP1. The module and pathway enrichment analyses showed that the YCHD had the potential to influence varieties of biological pathways, including the TNF signaling pathway, Ras signaling pathway, PI3K-Akt signaling pathway, FoxO signaling pathway, and pathways in cancer, that play an important role in the pathogenesis of hepatitis C.

Conclusion

The results of this study preliminarily verified the basic pharmacological effects and related mechanisms of the YCHD in the treatment of hepatitis C.