Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy
ObjectiveInflammation plays an important role in the pathophysiology of ischemic cardiomyopathy (ICM). We aimed to identify potential biomarkers of inflammation-related genes for ICM and build a model based on the potential biomarkers for the diagnosis of ICM.Materials and methodsThe microarray data...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2022.972274/full |
| _version_ | 1798037117085941760 |
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| author | Jianru Wang Jianru Wang Shiyang Xie Shiyang Xie Yanling Cheng Xiaohui Li Jian Chen Jian Chen Mingjun Zhu |
| author_facet | Jianru Wang Jianru Wang Shiyang Xie Shiyang Xie Yanling Cheng Xiaohui Li Jian Chen Jian Chen Mingjun Zhu |
| author_sort | Jianru Wang |
| collection | DOAJ |
| description | ObjectiveInflammation plays an important role in the pathophysiology of ischemic cardiomyopathy (ICM). We aimed to identify potential biomarkers of inflammation-related genes for ICM and build a model based on the potential biomarkers for the diagnosis of ICM.Materials and methodsThe microarray datasets and RNA-Sequencing datasets of human ICM were downloaded from the Gene Expression Omnibus database. We integrated 8 microarray datasets via the SVA package to screen the differentially expressed genes (DEGs) between ICM and non-failing control samples, then the differentially expressed inflammation-related genes (DEIRGs) were identified. The least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest were utilized to screen the potential diagnostic biomarkers from the DEIRGs. The potential biomarkers were validated in the RNA-Sequencing datasets and the functional experiment of the ICM rat, respectively. A nomogram was established based on the potential biomarkers and evaluated via the area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and Clinical impact curve (CIC).Results64 DEGs and 19 DEIRGs were identified, respectively. 5 potential biomarkers (SERPINA3, FCN3, PTN, CD163, and SCUBE2) were ultimately selected. The validation results showed that each of these five potential biomarkers showed good discriminant power for ICM, and their expression trends were consistent with the bioinformatics results. The results of AUC, calibration curve, DCA, and CIC showed that the nomogram demonstrated good performance, calibration, and clinical utility.ConclusionSERPINA3, FCN3, PTN, CD163, and SCUBE2 were identified as potential biomarkers associated with the inflammatory response to ICM. The proposed nomogram could potentially provide clinicians with a helpful tool to the diagnosis and treatment of ICM from an inflammatory perspective. |
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| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2297-055X |
| language | English |
| last_indexed | 2024-04-11T21:22:13Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj.art-675d4af7b39548a09f683d3aaa53cb5b2022-12-22T04:02:34ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2022-08-01910.3389/fcvm.2022.972274972274Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathyJianru Wang0Jianru Wang1Shiyang Xie2Shiyang Xie3Yanling Cheng4Xiaohui Li5Jian Chen6Jian Chen7Mingjun Zhu8Department of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaCentral Laboratory, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaDepartment of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaCentral Laboratory, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaDepartment of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaDepartment of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaDepartment of Vascular Disease, Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaInstitute of Vascular Anomalies, Shanghai Academy of Traditional Chinese Medicine, Shanghai, ChinaDepartment of Cardiovascular, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, ChinaObjectiveInflammation plays an important role in the pathophysiology of ischemic cardiomyopathy (ICM). We aimed to identify potential biomarkers of inflammation-related genes for ICM and build a model based on the potential biomarkers for the diagnosis of ICM.Materials and methodsThe microarray datasets and RNA-Sequencing datasets of human ICM were downloaded from the Gene Expression Omnibus database. We integrated 8 microarray datasets via the SVA package to screen the differentially expressed genes (DEGs) between ICM and non-failing control samples, then the differentially expressed inflammation-related genes (DEIRGs) were identified. The least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest were utilized to screen the potential diagnostic biomarkers from the DEIRGs. The potential biomarkers were validated in the RNA-Sequencing datasets and the functional experiment of the ICM rat, respectively. A nomogram was established based on the potential biomarkers and evaluated via the area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and Clinical impact curve (CIC).Results64 DEGs and 19 DEIRGs were identified, respectively. 5 potential biomarkers (SERPINA3, FCN3, PTN, CD163, and SCUBE2) were ultimately selected. The validation results showed that each of these five potential biomarkers showed good discriminant power for ICM, and their expression trends were consistent with the bioinformatics results. The results of AUC, calibration curve, DCA, and CIC showed that the nomogram demonstrated good performance, calibration, and clinical utility.ConclusionSERPINA3, FCN3, PTN, CD163, and SCUBE2 were identified as potential biomarkers associated with the inflammatory response to ICM. The proposed nomogram could potentially provide clinicians with a helpful tool to the diagnosis and treatment of ICM from an inflammatory perspective.https://www.frontiersin.org/articles/10.3389/fcvm.2022.972274/fullischemic cardiomyopathyinflammation-related genesbiomarkernomogrambioinformatics analysesheart failure |
| spellingShingle | Jianru Wang Jianru Wang Shiyang Xie Shiyang Xie Yanling Cheng Xiaohui Li Jian Chen Jian Chen Mingjun Zhu Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy Frontiers in Cardiovascular Medicine ischemic cardiomyopathy inflammation-related genes biomarker nomogram bioinformatics analyses heart failure |
| title | Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy |
| title_full | Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy |
| title_fullStr | Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy |
| title_full_unstemmed | Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy |
| title_short | Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy |
| title_sort | identification of potential biomarkers of inflammation related genes for ischemic cardiomyopathy |
| topic | ischemic cardiomyopathy inflammation-related genes biomarker nomogram bioinformatics analyses heart failure |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2022.972274/full |
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