Identification of Key Genes and Underlying Mechanisms in Acute Kawasaki Disease Based on Bioinformatics Analysis

Identifying signature genes and their associations with immune cell infiltration in spinal cord injury

Background

Early detection of spinal cord injury (SCI) is conducive to improving patient outcomes. In addition, many studies have revealed the role of immune cells in the progression or treatment of SCI. The objective of this study was to identify the early signature genes and clarify how they are related to immune cell infiltration in SCI.

Methods

We analysed and identified early signature genes associated with SCI via bioinformatics analysis of the GSE151371 dataset from the GEO database. These genes were subsequently verified in the GSE33886 dataset and qRT-PCR. Finally, the CIBERSORT algorithm was used to examine the immune cell infiltration in SCI and its relationship with signature genes.

Results

Seven SCI-related signature genes, including ARG1, RETN, BPI, GGH, CCNB1, HIST1H2AC, and HIST1H2BJ, were identified, and their expression was verified via an external validation cohort and qRT-PCR. Moreover, the ROC curves revealed the diagnostic value of these genes. In addition, on the basis of immune cell infiltration analysis, plasma cells, M0 macrophages, activated CD4+ memory T cells, γδ T cells, naive CD4+ T cells, and resting CD4+ memory T cells may participate in the progression of SCI.

Conclusion

This study identified seven early signature genes of SCI that may serve as biomarkers for the early diagnosis of SCI and contribute to our understanding of immune changes during the pathology of SCI.

Transcriptome meta-analysis of Kawasaki disease in humans and mice

Kawasaki Disease (KD) affects young children less than five years old with severe blood vessel inflammation. Despite being treatable, the causes and mechanisms remain elusive. This study conducted a meta-analysis of RNA sequencing (RNA-seq) data from human and animal models to explore KD's transcriptomic profile and evaluate animal models. We retrieved bulk and single-cell RNA-seq data from Gene Expression Omnibus, with blood and coronary artery samples from KD patients, aorta samples from KD mouse models (Lactobacillus casei cell wall extract-injected mice), and their controls. Upon consistent quality control, we applied Fisher's exact test to assess differential gene expression, followed by an enrichment analysis of overlapping genes. These studies identified 400 differentially expressed genes in blood samples of KD patients compared to controls and 413 genes in coronary artery samples. The data from KD blood and KD coronary artery samples shared only 16 differentially expressed genes. Eighty-one genes overlapped between KD human coronary arteries and KD mouse aortas, and 67 of these 81 genes were regulated in parallel in both humans and mice: 30 genes were up-regulated, and 37 were down-regulated. These included previously identified KD-upregulated genes: CD74, SFRP4, ITGA4, and IKZF1. Gene enrichment analysis revealed significant alterations in the cardiomyopathy pathway. Single-cell RNAseq showed a few significant markers, with known KD markers like S100A9, S100A8, CD74, CD14, IFITM2, and IFITM3, being overexpressed in KD cohorts. Gene profiles obtained from KD human coronary artery are more compatible with data from aorta samples of KD mice than blood samples of KD humans, validating KD animal models for identifying therapeutic targets. Although blood samples can be utilized to discover novel biomarkers, more comprehensive single-cell sequencing is required to detail gene expression in different blood cell populations. This study identifies critical genes from human and mouse tissues to help develop new treatment strategies for KD.

Identification of hub genes and pathogenesis in Kawasaki disease based on bioinformatics analysis

BACKGROUND

The aim of this study was to explore new biomarkers of Kawasaki disease (KD) and provide evidence for clinical diagnosis and treatment.

MATERIALS AND METHODS

Gene Expression Omnibus (GEO) datasets GSE68004 and GSE73461 were downloaded, and the differentially expressed genes (DGEs) were taken, along with DEGs enrichment analysis and protein interaction network. Finally, five algorithms in CytoHubba plug-in were applied to obtain hub genes.

RESULTS

In this study, 32 Co-DEGs were identified, and these genes mainly participated in neutrophil degranulation, neutrophil activation involved in immune response, and negative regulation of cytokine production involved in immune response; meanwhile, they were primarily enriched in starch and sucrose metabolism, fatty acid metabolism, autophagy and apoptosis, ferroptosis, and other pathways. Combined with the results of PPI and CytoHubba, 13 key genes were selected as follows: S100A12, HK3, HP, MMP9, MCEMP1, PYGL, ARG1, HIST2H2AA, ANXA3, HIST2H2AC, HIST2H2AA3, GYG1, DYSF.

CONCLUSIONS

These 13 key genes may mediate the occurrence and development of KD through various processes such as immune regulation, inflammatory response, glucose metabolism, autophagy, and apoptosis, which provide valuable references for the diagnosis and treatment of KD.

Intravenous Immunoglobulin: Mechanism of Action in Autoimmune and Inflammatory Conditions

Intravenous immunoglobulin (IVIG) is the mainstay of therapy for humoral immune deficiencies and numerous inflammatory disorders. Although the use of IVIG may be supplanted by several targeted therapies to cytokines, the ability of polyclonal normal IgG to act as an effector molecule as well as a regulatory molecule is a clear example of the polyfunctionality of IVIG. This article will address the mechanism of action of IVIG in a number of important conditions that are otherwise resistant to treatment. In this commentary, we will highlight mechanistic studies that shed light on the action of IVIG. This will be approached by identifying effects that are both common and disease-specific, targeting actions that have been demonstrated on cells and processes that represent both innate and adaptive immune responses.

Central and Peripheral Nervous System Complications of Vasculitis Syndromes from Pathology to Bedside: Part 2-Peripheral Nervous System

PURPOSE OF REVIEW

Peripheral nervous system vasculitides (PNSV) are a heterogeneous group of disorders with a clinical subset that may differ in prognosis and therapy. We provide a comprehensive update on the clinical assessment, diagnosis, complications, treatment, and follow-up of PNSV.

RECENT FINDINGS

Progress in neuroimaging, molecular testing, and peripheral nerve biopsy has improved clinical assessment and decision-making of PNSV, also providing novel insights on how to prevent misdiagnosis and increase diagnostic certainty. Advances in imaging techniques, allowing to clearly display the vessel walls, have also enhanced the possibility to differentiate inflammatory from non-inflammatory vascular lesions, while recent histopathology data have identified the main morphological criteria for more accurate diagnosis and differential diagnoses. Overall, the identification of peculiar morphological findings tends to improve diagnostic accuracy by defining a clearer boundary between systemic and non-systemic neuropathies. Therefore, the definition of epineurium vessel wall damage, type of vascular lesion, characterization of lymphocyte populations, antibodies, and inflammatory factors, as well as the identification of direct nerve damage or degeneration, are the common goals for pathologists and clinicians, who will both benefit for data integration and findings translation. Nevertheless, to date, treatment is still largely empiric and, in some cases, unsatisfactory, thus often precluding precise prognostic prediction. In this context, new diagnostic techniques and multidisciplinary management will be essential in the proper diagnosis and prompt management of PNSV, as highlighted in the present review. Thirty to fifty percent of all patients with vasculitis have signs of polyneuropathy. Neuropathies associated with systemic vasculitis are best managed according to the guidelines of the underlying disease because appropriate workup and initiation of treatment can reduce morbidity. Steroids, or in severe or progressive cases, cyclophosphamide pulse therapy is the standard therapy in non-systemic vasculitic neuropathies. Some patients need long-term immunosuppression. The use of novel technologies for high-throughput genotyping will permit to determine the genetic influence of related phenotypes in patients with PNSV.

Identifying differentially expressed genes and miRNAs in Kawasaki disease by bioinformatics analysis

Kawasaki disease (KD) is an acute systemic immune vasculitis caused by infection, and its etiology and underlying mechanisms are not completely clear. This study aimed to identify differentially expressed genes (DEGs) with diagnostic and treatment potential for KD using bioinformatics analysis. In this study, three KD datasets (GSE68004, GSE73461, GSE18606) were downloaded from the Gene Expression Omnibus (GEO) database. Identification of DEGs between normal and KD whole blood was performed using the GEO2R online tool. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of DEGs was undertaken with Metascape. Analysis and visualization of protein-protein interaction networks (PPI) were carried out with STRING and Cytoscape. Lastly, miRNA-genes regulatory networks were built by Cytoscape to predict the underlying microRNAs (miRNAs) associated with DEGs. Overall, 269 DEGs were identified, including 230 up-regulated and 39 down-regulated genes. The enrichment functions and pathways of DEGs involve regulation of defense response, inflammatory response, response to bacterium, and T cell differentiation. KEGG analysis indicates that the genes were significantly enriched in Neutrophil extracellular trap formation, TNF signaling pathway, Cytokine-cytokine receptor interaction, and Primary immunodeficiency. After combining the results of the protein-protein interaction (PPI) network and CytoHubba, 9 hub genes were selected, including TLR8, ITGAX, HCK, LILRB2, IL1B, FCGR2A, S100A12, SPI1, and CD8A. Based on the DEGs-miRNAs network construction, 3 miRNAs including mir-126-3p, mir-375 and mir-146a-5p were determined to be potential key miRNAs. To summarize, a total of 269 DEGs, 9 hub genes and 3 miRNAs were identified, which could be considered as KD biomarkers. However, further studies are needed to clarify the biological roles of these genes in KD.

Exploration of Potential Biomarker Genes and Pathways in Kawasaki Disease: An Integrated in-Silico Approach

Kawasaki disease (KD) is a common childhood systemic vasculitis with a special predilection for coronary arteries. Even after more than five decades of the initial description of the disease, the etiology of KD remains an enigma. This transcriptome data re-analysis study aimed to elucidate the underlying pathogenesis of KD using a bioinformatic approach to identify differentially expressed genes (DEGs) to delineate common pathways involved in KD. Array datasets from the Gene Expression Omnibus database were extracted and subjected to comparative meta-analysis for the identification of prominent DEGs. Fifteen hub genes with high connectivity were selected from these DEGs (IL1B, ITGAM, TLR2, CXCL8, SPI1, S100A12, MMP9, PRF1, TLR8, TREM1, CD44, UBB, FCER1G, IL7R, and FCGR1A). Of these 15 genes, five genes (CXCL8, FCGR1A, IL1B, TLR2, and TLR8) were found to be involved in neutrophil degranulation. To gain further insight into the molecular mechanism, a protein–protein network was established. Significantly enriched pathways based on the above-mentioned genes were mainly centered on biological regulation and signaling events. In addition, the pathway analysis also indicated that the majority of the DEGs in KD were enriched in systemic lupus erythematosus, suggesting a strong interplay between immunological and genetic factors in the pathogenesis of KD. These findings could significantly aid in identifying therapeutic targets and understanding KD biosignatures to design a biomarker panel for early diagnosis and severity of the disease.