Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis
Abstract Obesity (OB) and atherosclerosis (AS) represent two highly prevalent and detrimental chronic diseases that are intricately linked. However, the shared genetic signatures and molecular pathways underlying these two conditions remain elusive. This study aimed to identify the shared diagnostic...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-85825-2 |
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| author | Wenrong An Kegong Tang Juan Liu Wenfei Zheng Guoxia Li Yunsheng Xu |
| author_facet | Wenrong An Kegong Tang Juan Liu Wenfei Zheng Guoxia Li Yunsheng Xu |
| author_sort | Wenrong An |
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| description | Abstract Obesity (OB) and atherosclerosis (AS) represent two highly prevalent and detrimental chronic diseases that are intricately linked. However, the shared genetic signatures and molecular pathways underlying these two conditions remain elusive. This study aimed to identify the shared diagnostic genes and the associated molecular mechanism between OB and AS. The microarray datasets of OB and AS were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis and the weighted gene co-expression network analysis (WGCNA) were conducted to identify the shared genes. Then least absolute shrinkage selection (LASSO) algorithm was used for diagnostic genes discovery. The diagnostic genes were validated using expression analysis and receiver operating characteristic (ROC) curves. Furthermore, Gene set enrichment analysis (GSEA) was used to investigate molecular pathways and immune infiltration related to the diagnostic genes. TF-gene and miRNA-gene networks were also constructed by utilizing the NetworkAnalyst tool. By intersecting the key module genes of WGCNA with DEGs in OB and AS, 56 shared genes with the same expression trend were identified. Using LASSO algorithm, we obtained two shared diagnostic genes, namely SAMSN1 and PHGDH. Validation confirmed their expression patterns and robust predictive abilities. GSEA revealed the crucial roles of SAMSN1 and PHGDH in disease-associated pathways. Additionally, higher immune cell infiltration expression was found in both diseases and strongly linked to the diagnostic genes. Finally, we constructed the TF-gene and miRNA-gene networks. We identified SAMSN1 and PHGDH as potential diagnostic genes for OB and AS. Our findings provide novel insights into the molecular underpinnings of the OB-AS link. |
| format | Article |
| id | doaj-art-0a5ac602b56a4a108ccb939d51641033 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-0a5ac602b56a4a108ccb939d516410332025-01-19T12:18:17ZengNature PortfolioScientific Reports2045-23222025-01-0115111310.1038/s41598-025-85825-2Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysisWenrong An0Kegong Tang1Juan Liu2Wenfei Zheng3Guoxia Li4Yunsheng Xu5Second Clinical Medical College, Shandong University of Traditional Chinese MedicineDepartment of Pathology, Shandong Provincial Qianfoshan Hospital, The First Affiliated Hospital of Shandong First Medical University, Shandong Lung Cancer Institute, Shandong Institute of NephrologyDepartment of Traditional Chinese Medicine, Rehabilitation Hospital of Shandong UniversityDepartment of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese MedicineDepartment of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese MedicineDepartment of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese MedicineAbstract Obesity (OB) and atherosclerosis (AS) represent two highly prevalent and detrimental chronic diseases that are intricately linked. However, the shared genetic signatures and molecular pathways underlying these two conditions remain elusive. This study aimed to identify the shared diagnostic genes and the associated molecular mechanism between OB and AS. The microarray datasets of OB and AS were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis and the weighted gene co-expression network analysis (WGCNA) were conducted to identify the shared genes. Then least absolute shrinkage selection (LASSO) algorithm was used for diagnostic genes discovery. The diagnostic genes were validated using expression analysis and receiver operating characteristic (ROC) curves. Furthermore, Gene set enrichment analysis (GSEA) was used to investigate molecular pathways and immune infiltration related to the diagnostic genes. TF-gene and miRNA-gene networks were also constructed by utilizing the NetworkAnalyst tool. By intersecting the key module genes of WGCNA with DEGs in OB and AS, 56 shared genes with the same expression trend were identified. Using LASSO algorithm, we obtained two shared diagnostic genes, namely SAMSN1 and PHGDH. Validation confirmed their expression patterns and robust predictive abilities. GSEA revealed the crucial roles of SAMSN1 and PHGDH in disease-associated pathways. Additionally, higher immune cell infiltration expression was found in both diseases and strongly linked to the diagnostic genes. Finally, we constructed the TF-gene and miRNA-gene networks. We identified SAMSN1 and PHGDH as potential diagnostic genes for OB and AS. Our findings provide novel insights into the molecular underpinnings of the OB-AS link.https://doi.org/10.1038/s41598-025-85825-2SAMSN1PHGDHObesityAtherosclerosisDiagnostic geneImmune infiltration |
| spellingShingle | Wenrong An Kegong Tang Juan Liu Wenfei Zheng Guoxia Li Yunsheng Xu Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis Scientific Reports SAMSN1 PHGDH Obesity Atherosclerosis Diagnostic gene Immune infiltration |
| title | Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis |
| title_full | Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis |
| title_fullStr | Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis |
| title_full_unstemmed | Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis |
| title_short | Exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis |
| title_sort | exploration of the shared diagnostic genes and molecular mechanism between obesity and atherosclerosis via bioinformatic analysis |
| topic | SAMSN1 PHGDH Obesity Atherosclerosis Diagnostic gene Immune infiltration |
| url | https://doi.org/10.1038/s41598-025-85825-2 |
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