Scutellarin attenuated tubule cell apoptosis by modulating HIF-1α for the treatment of DKD: the insight integrating network analysis, machine learning and single-cell transcriptome
Year: 2025
Type: article
Abstract: Aim To explore the possible mechanism and target of scutellarin (Scu) on diabetic kidney disease (DKD). Method The Network analysis was used to explore and enrich the possible pathway. RNA transcriptome were employed to deepen the understanding of candidate targets in key signaling pathways. Core targets were optimized through 8 machine learning algorithms. Single-cell transcriptome were utilized to clarify the expression locations and temporal trajectories of core targets, identifying high-expression cell types. Finally, molecular docking and cell experiments were conducted to validate the regulatory effects of Scutellarin on the molecular targets. Result The Network analysis showed the roles of hypoxic response and apoptosis pathways. RNA transcriptome and machine learning identified HIF-1α and CASP3 as the hub genes related to DKD outcomes and hypoxic apoptosis. Single-cell transcriptome analysis confirmed the expression patterns and locations of hub genes, identifying the CD-PC cells as the high-expression cell type. In-vitro experiments demonstrated 20 μM scutellarin was most beneficial for mIMCD-3 cell proliferation. The hypoxia significantly enhanced HIF-1α gene transcription driven by HRE conserved genes (P < 0.0001), whereas high glucose inhibited hypoxia-induced HIF-1α transcription (P < 0.05). Scutellarin significantly upregulated HIF-1α transcriptional activity (P < 0.05) and HIF-1α total protein expression under high glucose-hypoxia (P < 0.05), reduced mitochondrial ROS release (P < 0.05) and renal tubular cell apoptosis (P < 0.01). Conclusion Scutellarin attenuated renal collecting duct cell apoptosis by modulating HIF-1α for the treatment of DKD.
Source: Frontiers in Pharmacology
Authors: Li Jiang, Jie Jian, Haojun Zhang, Xiai Wu
Institution: China-Japan Friendship Hospital
Language: English
Subfield: Nephrology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
Award: G100268075
OpenAlex ID: W4414600227