Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach

Kawasaki Disease: An update on Genetics and Pathophysiology

Kawasaki disease (KD), a systemic vasculitic condition predominantly affecting children, remains a significant challenge in pediatric health care. First identified in 1967, KD is now recognized as the primary cause of pediatric ischemic heart disease in developed countries. This review provides a comprehensive update of KD, focusing on biomarkers, pathophysiology, and genetic associations. KD's clinical manifestation, including symptoms such as persistent fever and mucocutaneous changes, often overlaps with other pediatric conditions, complicating its diagnosis. This ambiguity, especially in cases of incomplete KD, highlights the critical need for specific biomarkers and more precise diagnostic methods. Recent studies have made promising advancements in identifying serum biomarkers and microRNAs, contributing to the development of rapid diagnostic tools. However, these are yet to be fully integrated into clinical practice. The article focuses on the pathophysiological aspects of KD, highlighting the potential for targeted therapies and personalized medicine approaches based on genetic predispositions. Collaborative efforts in global research and raising public awareness about KD are emphasized as key strategies for improving its management. This review presents the current understanding of KD while pointing out the gaps and future directions in research and clinical care. The ultimate goal is to enhance diagnostic accuracy, optimize treatment strategies, and improve patient outcomes, thereby addressing the complexities of this enigmatic and potentially life-threatening condition in pediatric medicine.

Efficacy Evaluation of Human Skin Treatment with Photodynamic Therapy in Actinic Keratoses Patients

Introduction: Photodynamic therapy (PDT) is a combined method of light and light-activated chemicals that are called photosensitizers (PSs). PDT is recommended as a high cure rate method with fewer side effects and a noninvasive tool to treat cancer. This study aimed to evaluate PDT efficacy as a therapeutic method against actinic keratoses in patients via protein-protein interaction (PPI) network analysis by using the gene expression profiles of Gene Expression Omnibus (GEO). Methods: Twenty-one gene expression profiles were extracted from GEO and analyzed by GEO2R to determine the significant differentially expressed genes (DEGs). The significant DEGs were included in PPI networks via Cytoscape software. The networks were analyzed by the "Network Analyzer", and the elements of the main connected components were assessed. Results: There were three main connected components for the compared sets of the gene expression profiles including the lesional region of skin before (Before set) and after (After set) PDT versus healthy (healthy set) skin and before versus after. The before-health comparison showed a partial similarity with the After-Healthy assessment. The before-after evaluation indicated that there were not considerable differences between the gene expression profile of the lesional region before and after PDT. Conclusion: In conclusion, PDT was unable to return the gene expression pattern of the actinic keratoses skin to a healthy condition completely.

Bridging a diagnostic Kawasaki disease classifier from a microarray platform to a qRT-PCR assay

BACKGROUND

Kawasaki disease (KD) is a systemic vasculitis that mainly affects children under 5 years of age. Up to 30% of patients develop coronary artery abnormalities, which are reduced with early treatment. Timely diagnosis of KD is challenging but may become more straightforward with the recent discovery of a whole-blood host response classifier that discriminates KD patients from patients with other febrile conditions. Here, we bridged this microarray-based classifier to a clinically applicable quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay: the Kawasaki Disease Gene Expression Profiling (KiDs-GEP) classifier.

METHODS

We designed and optimized a qRT-PCR assay and applied it to a subset of samples previously used for the classifier discovery to reweight the original classifier.

RESULTS

The performance of the KiDs-GEP classifier was comparable to the original classifier with a cross-validated area under the ROC curve of 0.964 [95% CI: 0.924-1.00] vs 0.992 [95% CI: 0.978-1.00], respectively. Both classifiers demonstrated similar trends over various disease conditions, with the clearest distinction between individuals diagnosed with KD vs viral infections.

CONCLUSION

We successfully bridged the microarray-based classifier into the KiDs-GEP classifier, a more rapid and more cost-efficient qRT-PCR assay, bringing a diagnostic test for KD closer to the hospital clinical laboratory.

IMPACT

A diagnostic test is needed for Kawasaki disease and is currently not available. We describe the development of a One-Step multiplex qRT-PCR assay and the subsequent modification (i.e., bridging) of the microarray-based host response classifier previously described by Wright et al. The bridged KiDs-GEP classifier performs well in discriminating Kawasaki disease patients from febrile controls. This host response clinical test for Kawasaki disease can be adapted to the hospital clinical laboratory.

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.

CASP5 and CR1 as potential biomarkers for Kawasaki disease: an Integrated Bioinformatics-Experimental Study

BACKGROUND

Kawasaki disease (KD) is a pediatric inflammatory disorder causes coronary artery complications. The disease overlapping manifestations with a set of symptomatically like diseases such as bacterial and viral infections, juvenile idiopathic arthritis, Henoch-Schönlein purpura, infection of unknown etiology, group-A streptococcal and adenoviral infections, and incomplete KD could lead to misdiagnosis of the disease.

METHODS

In the present study, we applied weighted gene co-expression network analysis (WGCNA) to identify network modules of co-expressed genes in GSE73464 and also, limma package was used to identify the differentially expressed genes (DEGs) in KD expression arrays composed of GSE73464, GSE18606, GSE109351, and GSE68004. By merging the results of WGCNA and limma, we detected hub genes. Then, analyzed the peripheral blood mononuclear cells (PBMCs) of 16 patients and 8 control subjects using Real-Time Polymerase Chain Reaction (RT-PCR) to evaluate the previous results.

RESULTS

We assessed the diagnostic potency of the screened genes by plotting the area under curve (AUC). We finally identified 2 genes CASP5(Caspase 5) and CR1(Complement C3b/C4b Receptor 1) which were shown to potentially discriminate KD from other similar diseases and also from healthy people.

CONCLUSIONS

The results of RT-PCR and AUC confirmed the diagnostic potentials of two suggested biomarkers for KD.

In silico Identification of 10 Hub Genes and an miRNA-mRNA Regulatory Network in Acute Kawasaki Disease

Kawasaki disease (KD) causes acute systemic vasculitis and has unknown etiology. Since the acute stage of KD is the most relevant, the aim of the present study was to identify hub genes in acute KD by bioinformatics analysis. We also aimed at constructing microRNA (miRNA)–messenger RNA (mRNA) regulatory networks associated with acute KD based on previously identified differentially expressed miRNAs (DE-miRNAs). DE-mRNAs in acute KD patients were screened using the mRNA expression profile data of GSE18606 from the Gene Expression Omnibus. The functional and pathway enrichment analysis of DE-mRNAs were performed with the DAVID database. Target genes of DE-miRNAs were predicted using the miRWalk database and their intersection with DE-mRNAs was obtained. From a protein–protein interaction (PPI) network established by the STRING database, Cytoscape software identified hub genes with the two topological analysis methods maximal clique centrality and Degree algorithm to construct a miRNA-hub gene network. A total of 1,063 DE-mRNAs were identified between acute KD and healthy individuals, 472 upregulated and 591 downregulated. The constructed PPI network with these DE-mRNAs identified 38 hub genes mostly enriched in pathways related to systemic lupus erythematosus, alcoholism, viral carcinogenesis, osteoclast differentiation, adipocytokine signaling pathway and tumor necrosis factor signaling pathway. Target genes were predicted for the up-regulated and down-regulated DE-miRNAs, 10,203, and 5,310, respectively. Subsequently, 355, and 130 overlapping target DE-mRNAs were obtained for upregulated and downregulated DE-miRNAs, respectively. PPI networks with these target DE-mRNAs produced 15 hub genes, six down-regulated and nine upregulated hub genes. Among these, ten genes (ATM, MDC1, CD59, CD177, TRPM2, FCAR, TSPAN14, LILRB2, SIRPA, and STAT3) were identified as hub genes in the PPI network of DE-mRNAs. Finally, we constructed the regulatory network of DE-miRNAs and hub genes, which suggested potential modulation of most hub genes by hsa-miR-4443 and hsa-miR-6510-5p. SP1 was predicted to potentially regulate most of DE-miRNAs. In conclusion, several hub genes are associated with acute KD. An miRNA–mRNA regulatory network potentially relevant for acute KD pathogenesis provides new insights into the underlying molecular mechanisms of acute KD. The latter may contribute to the diagnosis and treatment of acute KD.