World Journal of Emergency Medicine ›› 2025, Vol. 16 ›› Issue (3): 248-255.doi: 10.5847/wjem.j.1920-8642.2025.063
• Original Article • Previous Articles Next Articles
Zhongshu Kuang1, Runrong Li2, Su Lu1, Yusong Wang2, Yue Luo1, Yongqi Shen1, Li Yuan1, Yilin Yang1, Zhenju Song1,3,4(), Ning Jiang2(
), Chaoyang Tong1(
)
Received:
2024-10-16
Accepted:
2025-04-10
Online:
2025-05-19
Published:
2025-05-01
Contact:
Chaoyang Tong, Email: Zhongshu Kuang, Runrong Li, Su Lu, Yusong Wang, Yue Luo, Yongqi Shen, Li Yuan, Yilin Yang, Zhenju Song, Ning Jiang, Chaoyang Tong. Uncovering host response in adults with severe community-acquired pneumonia: a proteomics and metabolomics perspective study[J]. World Journal of Emergency Medicine, 2025, 16(3): 248-255.
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URL: http://wjem.com.cn/EN/10.5847/wjem.j.1920-8642.2025.063
Figure 1.
Study design and omic differences analysis between healthy control and CAP groups. A: overview of the plasma proteomic and metabolomic workflow, including samples collection (healthy control/HC: n=19, non-severe CAP/NS-CAP: n=19, severe CAP/S-CAP: n=27); B: GSEA analysis showed up- and down-regulated pathways in CAP group compared with healthy control group. C: a heatmap listed proteins linked to the pathways shown in B; D: metabolomic pathway enrichment results. E: representative metabolite levels of enriched pathways in D. CAP: community-acquired pneumonia; GSEA: gene set enrichment analysis.
Figure 2.
Proteomic and metabolomic differences between non-severe and severe CAP. A: clustering illustrating six protein variation patterns across three groups. The purple line is the center line of the trend for each cluster. B: KEGG pathway enrichment analysis result of cluster 3 and cluster 6 in A. C: the relative abundance of proteins in platelet activation, cholesterol metabolism and cadherin binding pathway between NS-CAP and S-CAP groups. D: lipid-related metabolite levels between NS-CAP and S-CAP groups. PC: phosphatidylcholine; SM: sphingomyelin.
Figure 3.
Identification of potential biomarkers and prediction model training for CAP classification. A: overview of the feature selection and model training workflow; B: confusion matrix of the random forest prediction model in the test set; C: receiver operating characteristic (ROC) curve of the prediction model; AUC: area under the curve; D: classification report of the prediction model; E: top 20 proteins and metabolites with the highest feature importance obtained by the prediction model.
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