ArticleIranian journal of biotechnology2026
Screening of Biomarkers Related to Mitophagy in Severe Pancreatitis Based on Bioinformatics Methods.
Article in Iranian journal of biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: This study aimed to identify mitophagy-related biomarkers in severe acute pancreatitis through integrated bioinformatics and machine-learning approaches, and to elucidate their potential regulatory mechanisms and diagnostic value. Materials and Methods: Differentially expressed genes (DEGs) related to SAP were screened based on the GSE194331 dataset (human whole blood samples), and candidate genes were obtained by taking the intersection with the mitophagy gene set. Key genes were screened by combining the least absolute shrinkage and selection operator (LASSO) regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms; the diagnostic efficacy was evaluated using the ROC curve, and a nomogram model was constructed. Furthermore, gene functions and regulatory mechanisms were revealed through Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), immune infiltration analysis, and ceRNA network, and potential targeted drugs were predicted using molecular docking. Results: A total of 16 DEGs related to mitophagy were identified. Functional enrichment analysis showed that they were significantly associated with metabolic and immune regulation pathways. Machine learning and expression level validation jointly screened PGD and LMNB1 genes as two key genes. The key genes showed significant expression differences in the training set and external validation set (upregulated in the SAP group), and had excellent diagnostic efficacy (area under the curve (AUC) > 0.85). Immune infiltration analysis showed that the infiltration of 13 types of immune cells increased in the SAP group, and PGD was highly positively correlated with immune cells such as activated dendritic cells (r = 0.82). Molecular docking indicated that estradiol and progesterone might target and regulate PGD and LMNB1. Conclusion: PGD and LMNB1 are key genes related to mitophagy in SAP and have excellent diagnostic value. This study provides a theoretical basis for the analysis of the molecular mechanism of SAP and the development of precise diagnosis and treatment strategies.
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