Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate
Abstract Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims t...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-85900-8 |
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| author | Minyue Jia Liya Lin Hanxiao Yu Zhichao Dong Xin Pan Xiaoxiao Song |
| author_facet | Minyue Jia Liya Lin Hanxiao Yu Zhichao Dong Xin Pan Xiaoxiao Song |
| author_sort | Minyue Jia |
| collection | DOAJ |
| description | Abstract Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims to discover novel therapeutic targets for PA using integrated bioinformatics and experimental validation approaches. We employed a systematic approach combining: gene identification through transcriptome-wide association studies (TWAS); causal inference using summary data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) analyses; additional analyses included phenome-wide association analysis, enrichment analysis, protein-protein interaction (PPI) networks, drug repurposing, molecular docking and clinical validation through aldosterone-producing adenomas (APAs) tissue. Through systematic screening and prioritization, we identified 163 PA-associated genes, of which seven emerged as potential drug targets: CEP104, HIP1, TONSL, ZNF100, SHMT1, and two long non-coding RNAs (AC006369.2 and MRPL23-AS1). SHMT1 was identified as the most promising target, showing significantly elevated expression in APAs compared to adjacent non-tumorous tissues. Drug repurposing analysis identified four potential SHMT1-targeting compounds (Mimosine, Pemetrexed, Leucovorin, and Irinotecan), supported by molecular docking studies. The integration of multiple bioinformatics methods and experimental validation successfully identified novel drug targets for hyperaldosteronism. SHMT1, in particular, represents a promising candidate for future therapeutic development. These findings provide new opportunities for developing causative treatments for PA, though further clinical validation is warranted. |
| format | Article |
| id | doaj-art-42f51087205e48448f5b906ffc7103d4 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-42f51087205e48448f5b906ffc7103d42025-01-12T12:15:25ZengNature PortfolioScientific Reports2045-23222025-01-0115112110.1038/s41598-025-85900-8Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidateMinyue Jia0Liya Lin1Hanxiao Yu2Zhichao Dong3Xin Pan4Xiaoxiao Song5Department of Ultrasonography, The Second Affiliated Hospital, Zhejiang University School of MedicineClinical Research Center, The Second Affiliated Hospital, Zhejiang University School of MedicineClinical Research Center, The Second Affiliated Hospital, Zhejiang University School of MedicineDepartment of Urology, The Second Affiliated Hospital, Zhejiang University School of MedicineDepartment of Endocrinology, The First People’s Hospital of Xiaoshan DistrictDepartment of Endocrinology, The Second Affiliated Hospital, Zhejiang University School of MedicineAbstract Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims to discover novel therapeutic targets for PA using integrated bioinformatics and experimental validation approaches. We employed a systematic approach combining: gene identification through transcriptome-wide association studies (TWAS); causal inference using summary data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) analyses; additional analyses included phenome-wide association analysis, enrichment analysis, protein-protein interaction (PPI) networks, drug repurposing, molecular docking and clinical validation through aldosterone-producing adenomas (APAs) tissue. Through systematic screening and prioritization, we identified 163 PA-associated genes, of which seven emerged as potential drug targets: CEP104, HIP1, TONSL, ZNF100, SHMT1, and two long non-coding RNAs (AC006369.2 and MRPL23-AS1). SHMT1 was identified as the most promising target, showing significantly elevated expression in APAs compared to adjacent non-tumorous tissues. Drug repurposing analysis identified four potential SHMT1-targeting compounds (Mimosine, Pemetrexed, Leucovorin, and Irinotecan), supported by molecular docking studies. The integration of multiple bioinformatics methods and experimental validation successfully identified novel drug targets for hyperaldosteronism. SHMT1, in particular, represents a promising candidate for future therapeutic development. These findings provide new opportunities for developing causative treatments for PA, though further clinical validation is warranted.https://doi.org/10.1038/s41598-025-85900-8HyperaldosteronismTWASGWASQTLMendelian randomizationSHMT1 |
| spellingShingle | Minyue Jia Liya Lin Hanxiao Yu Zhichao Dong Xin Pan Xiaoxiao Song Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate Scientific Reports Hyperaldosteronism TWAS GWAS QTL Mendelian randomization SHMT1 |
| title | Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate |
| title_full | Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate |
| title_fullStr | Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate |
| title_full_unstemmed | Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate |
| title_short | Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate |
| title_sort | integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism with a focus on shmt1 as a promising therapeutic candidate |
| topic | Hyperaldosteronism TWAS GWAS QTL Mendelian randomization SHMT1 |
| url | https://doi.org/10.1038/s41598-025-85900-8 |
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