Developing a non-invasive diagnostic model for pediatric Crohn’s disease using RNA-seq analysis

Figures

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  FIGURE 1. Differential gene expression in Pediatric Crohn’s Disease and controls. (A) Enhanced volcano plot showing the log2 fold change and -log10 p-value for each gene in the dataset. Genes with a significant difference in expression (p < 0.05) are highlighted in red, with those showing an increased expression in Pediatric Crohn’s Disease in blue and decreased expression in green. (B) Principal component analysis (PCA) plot illustrating the separation of Pediatric Crohn’s Disease and control samples based on gene expression levels. Each point represents a sample, with Pediatric Crohn’s Disease samples shown in red and controls in blue. The first two principal components (PC1 and PC2) are plotted, representing the majority of the variation in the data.

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  FIGURE 2. Gene expression of FCGR3A, CBR3, CHST13, and FZD7 in three datasets. (A) Boxplot of FCGR3A gene expression in GSE101794, GSE57945 and GSE93624 datasets, representing the pediatric Crohn’s Disease (PD) and control samples. The center line of the box represents the median expression level, the top and bottom edges of the box represent the 75th and 25th percentiles, respectively, and the whiskers extend to the most extreme data points within 1.5 times the interquartile range. The red dots represent outliers. (B) Boxplot of CBR3 gene expression in GSE101794, GSE57945 and GSE93624 datasets. (C) Boxplot of CHST13 gene expression in GSE101794, GSE57945 and GSE93624 datasets. (D) Boxplot of FZD7 gene expression in GSE101794, GSE57945 and GSE93624 datasets.

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  FIGURE 3. Receiver Operating Characteristic (ROC) curves of gene expression-based classification of Pediatric Crohn’s Disease in three datasets. (A) ROC curve of GSE101794 dataset, showing the relationship between the true positive rate (sensitivity) and false positive rate (1-specificity) for different threshold values of gene expression levels for Pediatric Crohn’s Disease classification. The area under the curve (AUC) is indicated. (B) ROC curve of GSE57945 dataset, showing the relationship between the true positive rate (sensitivity) and false positive rate (1-specificity) for different threshold values of gene expression levels for Pediatric Crohn’s Disease classification. The area under the curve (AUC) is indicated. (C) ROC curve of GSE93624 dataset, showing the relationship between the true positive rate (sensitivity) and false positive rate (1-specificity) for different threshold values of gene expression levels for Pediatric Crohn’s Disease classification. The area under the curve (AUC) is indicated.

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  FIGURE 4. Gene expression and classier performance in an prospective independent validation dataset. (A) Boxplots of gene expression for FCGR3A, CBR3, CHST13, and FZD7 in the prospective independent validation set. The center line of the box represents the median expression level, the top and bottom edges of the box represent the 75th and 25th percentiles, respectively, and the whiskers extend to the most extreme data points within 1.5 times the interquartile range. The red dots represent outliers. The boxplots are split into pediatric Crohn’s Disease (PD) and control groups. (B) Receiver Operating Characteristic (ROC) curve of gene expression-based classification of Pediatric Crohn’s Disease in the prospective independent validation set. The curve shows the relationship between the true positive rate (sensitivity) and false positive rate (1-specificity) for different threshold values of gene expression levels for Pediatric Crohn’s Disease classification. The area under the curve (AUC) is indicated.