Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression
收藏NIAID Data Ecosystem2026-05-02 收录
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https://www.omicsdi.org/dataset/bioimages/S-BIAD1415
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资源简介:
Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, affects 10% of the population but lacks specific treatments. This study uses a multi-omics approach with human kidney PDGFRβ+ mesenchymal cells to analyze ECM changes. Through network modeling integrating various -omics data with ECM imaging, we tracked biomolecule changes across seven time points after TGF-β stimulation. The analysis revealed temporal patterns in ECM-related markers and modulators. Through validation experiments, we identified transcription factors like FLI1 and E2F1 as negative regulators of collagen deposition, providing insights into ECM regulation in kidney fibrosis progression.
创建时间:
2024-10-15



