Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning
Abstract Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic strategies. This study aims to elucidate...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-03625-0 |
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| author | Yongzheng Hu Qian An Xinxin Yu Wei Jiang |
| author_facet | Yongzheng Hu Qian An Xinxin Yu Wei Jiang |
| author_sort | Yongzheng Hu |
| collection | DOAJ |
| description | Abstract Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic strategies. This study aims to elucidate the roles of miR-223-3p and CRIM1 in HBV-MN using single-cell RNA sequencing (scRNA-seq) and machine learning. scRNA-seq analysis identified a distinct subcluster of podocytes linked to HBV-MN progression. miR-223-3p emerged as a critical regulatory molecule, with overexpression resulting in decreased CRIM1 expression. Dual-luciferase reporter assays confirmed miR-223-3p targeting CRIM1 at a conserved binding site. These findings were corroborated by machine learning models, which highlighted the significance of miR-223-3p and CRIM1 in disease pathology. miR-223-3p plays a pivotal role in modulating CRIM1 expression in HBV-MN, providing a potential therapeutic target. Integrating scRNA-seq with machine learning offers valuable insights into the molecular landscape of HBV-MN, paving the way for novel interventions. |
| format | Article |
| id | doaj-art-71e30eb9623347ce940fa6f36275304b |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-71e30eb9623347ce940fa6f36275304b2025-08-20T03:16:40ZengNature PortfolioScientific Reports2045-23222025-05-0115111710.1038/s41598-025-03625-0Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learningYongzheng Hu0Qian An1Xinxin Yu2Wei Jiang3Department of Nephrology, The Affiliated Hospital of Qingdao UniversityDepartment of Nephrology, Qingdao Central HospitalDepartment of Nephrology, Qingdao Eighth People’s HospitalDepartment of Nephrology, The Affiliated Hospital of Qingdao UniversityAbstract Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic strategies. This study aims to elucidate the roles of miR-223-3p and CRIM1 in HBV-MN using single-cell RNA sequencing (scRNA-seq) and machine learning. scRNA-seq analysis identified a distinct subcluster of podocytes linked to HBV-MN progression. miR-223-3p emerged as a critical regulatory molecule, with overexpression resulting in decreased CRIM1 expression. Dual-luciferase reporter assays confirmed miR-223-3p targeting CRIM1 at a conserved binding site. These findings were corroborated by machine learning models, which highlighted the significance of miR-223-3p and CRIM1 in disease pathology. miR-223-3p plays a pivotal role in modulating CRIM1 expression in HBV-MN, providing a potential therapeutic target. Integrating scRNA-seq with machine learning offers valuable insights into the molecular landscape of HBV-MN, paving the way for novel interventions.https://doi.org/10.1038/s41598-025-03625-0HBV-MNMiR-223-3pCRIM1ScRNA-seqMachine learning |
| spellingShingle | Yongzheng Hu Qian An Xinxin Yu Wei Jiang Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning Scientific Reports HBV-MN MiR-223-3p CRIM1 ScRNA-seq Machine learning |
| title | Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning |
| title_full | Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning |
| title_fullStr | Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning |
| title_full_unstemmed | Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning |
| title_short | Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning |
| title_sort | identification of novel therapeutic targets in hepatitis b virus associated membranous nephropathy using scrna seq and machine learning |
| topic | HBV-MN MiR-223-3p CRIM1 ScRNA-seq Machine learning |
| url | https://doi.org/10.1038/s41598-025-03625-0 |
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