Page 7 - 北京京煤集团总医院第十一届·2023学术年会论文集

北京京煤集团总医院 第十一届·2023 学术年会论文集

hub genes were identified by applying the MCC algorithm of the cytoHubba plugin of Cytoscape.
2.4 Immune function analysis

The ssGSEA, GSEABase, and GSVA algorithms were used to evaluate the infiltration of 16
different immune cell types and 13 immune functions in samples from patients with severe asthma.
The correlation between immune-infiltrating cells and immune functions was analyzed using the
corrplot package in R.

In addition, the psych and ggcorrplot packages in R were used to analyze the correlations
between the hub genes in the PPI network and immune-infiltrating cells and immune functions in
severe asthma cases.
2.5 Constructing a prognostic prediction model

CRs with a high correlation in immune analyses were used to construct a prognostic model of
severe asthma. A receiver operating characteristic (ROC) curve was used to verify the accuracy of
the model.
2.6 Identifying potential drugs for the treatment of severe asthma

The CRs used to construct the model were entered into the Enrichr online tool [19] and the
DSigDB database was used to predict the 10 most probable effective therapeutic drugs for severe
asthma [20].

2.7 Prediction of miRNAs targeting model genes
The TargetScan database (https://www.targetscan.org/vert_80/) at the Enrichr online website
was used to predict the miRNAs that target those genes used for the construction of the prognostic
prediction model, and a regulatory network was constructed.

3 Results
3.1 Differentially expressed CRs
When comparing the transcriptome data of patients with severe asthma with those of healthy
individuals, we identified 80 differentially expressed CRs, including 32 upregulated and 48

downregulated genes (Figure 1).

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