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CASP5 and CR1 as potential biomarkers for Kawasaki disease: an Integrated Bioinformatics-Experimental Study
Yazdan Rahmati1, Hasan Mollanoori1, Sajad Najafi2
1Department of Medical Genetics and Molecular Biology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Insights
Two novel biomarkers, CASP5 and CR1, were identified to accurately diagnose Kawasaki disease (KD) and differentiate it from similar pediatric inflammatory conditions and healthy controls.
Area of Science:
- Pediatric Inflammatory Disorders
- Genomics
- Biomarker Discovery
Background:
- Kawasaki disease (KD) is a pediatric inflammatory condition leading to coronary artery complications.
- Overlapping symptoms with other diseases like infections and juvenile idiopathic arthritis can cause misdiagnosis.
Purpose of the Study:
- To identify novel diagnostic biomarkers for Kawasaki disease.
- To differentiate KD from other symptomatically similar conditions and healthy individuals.
Main Methods:
- Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis (limma) were employed.
- Hub genes were identified by merging WGCNA and limma results.
- Real-Time Polymerase Chain Reaction (RT-PCR) validated findings in patient and control samples.
Main Results:
- Two genes, CASP5 (Caspase 5) and CR1 (Complement C3b/C4b Receptor 1), were identified as potential diagnostic biomarkers.
- The diagnostic potency was assessed using Area Under the Curve (AUC) analysis.
- CASP5 and CR1 demonstrated the ability to discriminate KD from other diseases and healthy states.
Conclusions:
- RT-PCR and AUC analyses confirmed the diagnostic potential of CASP5 and CR1.
- These genes serve as promising biomarkers for accurate Kawasaki disease diagnosis.
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.
