Bioinformatic Analyses of Peripheral Blood Transcriptome Identify Altered Neutrophil-Related Pathway and Different Transcriptomic Profiles for Acute Pancreatitis in Patients with and without Chylomicronemia Syndrome

Figures

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  Figure 1. Characterization of gene expression profile in patients with non-chylomicronemia syndrome (CS)-associated acute pancreatitis (AP). (A) Uniform manifold approximation and projection (UMAP) plot of gene expression between AP samples and healthy controls in GSE194331. Patients with AP are divided into mild, moderately severe, and severe. Red: Healthy control. Blue: Mild. Green: Moderately severe. Purple: Severe. (B) Venn diagram of differentially expressed genes (DEGs) among three degrees of severity in GSE194331. There are 6513 common DEGs. (C) Volcano plot of the common DEGs in the Venn diagram. Red: Significantly up-regulated and down-regulated genes based on the |logFC| > 1.5 and the adj. p-value < 10 × 10−5. Blue: DEGs with |logFC| ≤ 1.5 and adj. p ≤ 10 × 10−5. Green: DEGs with |logFC| >1.5 and adj. p > 10 × 10−5. Gray: DEGs with |logFC| ≤ 1.5 and adj. p > 10 × 10−5. (D) Gene set enrichment analysis (GSEA) plot of gene ontology (GO): 0042581-specific granule. NES and adj. p are shown. (E) Gene-concept network of genes listed in GO: 0042581. Dot size of the GO term represents the number of DEGs that are annotated based on the term. Color bar indicates the fold change between AP…

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  Figure 2. Common pathway in CS- and non-CS-associated AP. (A) Venn diagram of DEGs between AP and control in GSE194331 and GSE149607. (B) Dot plots show clustered enrichment ontology categories from over-representation analysis (ORA) in GSE194331 and GSE149607. –Log10-transformed multiple testing-adj. p-value is shown for each enriched term. Black arrows indicate the name of the top enriched term. (C) Hub genes obtained using MCODE in Cytoscape. (D) Scatter plot of correlation between logFC of common DEGs in GSE194331 and GSE149607. Significance of correlation was obtained using Spearman’s test.

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  Figure 3. Regulation of hub genes in CS- and non-CS-associated AP. (A,B) Heatmaps show hierarchical clustering of hub gene expression in GSE194331 and GSE149607. Conditions of up-regulation and down-regulation are separated. Expression levels are normalized to the z-score. Columns of heatmaps are divided into AP and control. (C) Interaction graph of selected hub genes and miRNAs derived from miRTargetLink 2.0. A central component of hub genes with high node degrees is shown. (D) Box plots show expression of hsa-miR-21*, hsa-miR-146a, and hsa-miR-106a* between AP and control in GSE31568. Wilcoxon’s rank sum test P values are shown. * indicates the product is from the opposite arm of the miRNA precursor.

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  Figure 4. Regulatory activity of the hub genes in AP. (A) Box plots show differences in single-sample GSEA (ssGSEA) scores between AP and control in GSE194331 and GSE149607. Wilcoxon’s rank sum test P values are shown. (B) Scatter plots show Spearman’s correlation between ssGSEA scores and the estimated neutrophil infiltrations in GSE194331 and GSE149607. Gene signatures used for estimating the neutrophil infiltration are based on xCell, Bindea et al., Danaher et al., and MCP-counter. Correlation coefficients (r) are shown, and significance of correlation was obtained using Spearman’s test.

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  Figure 5. Correlation profiles of the hub genes. (A,B) Correlation coefficients calculated according to the four studies (xCell, Bindea et al., Danaher et al., and MCP-counter) between expression of the hub genes and their ssGSEA scores are plotted for GSE194331 and GSE149607. Due to higher variability between datasets, the top 10 genes with positive correlations are selected. Red boxes represent the top 10 genes with higher average correlation coefficients among the four studies in GSE194331. Blue boxes represent the top 10 genes with higher average correlation coefficients among the four studies GSE149607.

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  Figure 6. Protein–Protein networks of the hub genes. (A,B) The protein–protein interaction networks of the top 10 genes in the correlation profiles of GSE194331 and GSE149607 constructed using GeneMANIA. Interconnections between proteins are shown in terms of physical interaction, co-expression, predicted, co-localization, common pathway, genetic interaction, and shared protein domains. The top three enriched pathways are shown for the two networks.

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  Figure 7. Construction of diagnostic models for AP. (A,B) Binomial deviance plot with lambda as the tuning parameter for GSE194331 and GSE149607 (upper panels). The red dots are the values of binomial deviance. The gray lines indicate the standard error (SE). The vertical dashed lines indicate the optimal values by the minimum criteria and 1-SE criteria. The least absolute shrinkage and selection operator (LASSO) coefficient profile of the selected genes is shown in the lower panels. (C) Receiver operating characteristic (ROC) curves of the LASSO diagnostic models in the training, testing, and entire datasets for GSE194331 (upper) and GSE14960 (lower).