Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment
BackgroundMild cognitive impairment (MCI), a syndrome defined as decline of cognitive function greater than expected for an individual’s age and education level, occurs in up to 22.7% of elderly patients in United States, causing the heavy psychological and economic burdens to families and society....
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2023.1139789/full |
| _version_ | 1797837615268888576 |
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| author | Songmei Ma Songmei Ma Tong Xia Xinyi Wang Xinyi Wang Xinyi Wang Xinyi Wang Haiyun Wang Haiyun Wang Haiyun Wang Haiyun Wang |
| author_facet | Songmei Ma Songmei Ma Tong Xia Xinyi Wang Xinyi Wang Xinyi Wang Xinyi Wang Haiyun Wang Haiyun Wang Haiyun Wang Haiyun Wang |
| author_sort | Songmei Ma |
| collection | DOAJ |
| description | BackgroundMild cognitive impairment (MCI), a syndrome defined as decline of cognitive function greater than expected for an individual’s age and education level, occurs in up to 22.7% of elderly patients in United States, causing the heavy psychological and economic burdens to families and society. Cellular senescence (CS) is a stress response that accompanies permanent cell-cycle arrest, which has been reported to be a fundamental pathological mechanism of many age-related diseases. This study aims to explore biomarkers and potential therapeutic targets in MCI based on CS.MethodsThe mRNA expression profiles of peripheral blood samples from patients in MCI and non-MCI group were download from gene expression omnibus (GEO) database (GSE63060 for training and GSE18309 for external validation), CS-related genes were obtained from CellAge database. Weighted gene co-expression network analysis (WGCNA) was conducted to discover the key relationships behind the co-expression modules. The differentially expressed CS-related genes would be obtained through overlapping among the above datasets. Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MCI. The protein–protein interaction network was used to extract hub genes and the logistic regression was performed to distinguish the MCI patients from controls. The hub gene-drug network, hub gene-miRNA network as well as transcription factor-gene regulatory network were used to analyze potential therapeutic targets for MCI.ResultsEight CS-related genes were identified as key gene signatures in MCI group, which were mainly enriched in the regulation of response to DNA damage stimulus, Sin3 complex and transcription corepressor activity. The receiver operating characteristic curves of logistic regression diagnostic model were constructed and presented great diagnostic value in both training and validation set.ConclusionEight CS-related hub genes – SMARCA4, GAPDH, SMARCB1, RUNX1, SRC, TRIM28, TXN, and PRPF19 – serve as candidate biomarkers for MCI and display the excellent diagnostic value. Furthermore, we also provide a theoretical basis for targeted therapy against MCI through the above hub genes. |
| first_indexed | 2024-04-09T15:28:40Z |
| format | Article |
| id | doaj.art-0cab940107ee4289897437799288b4c8 |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-04-09T15:28:40Z |
| publishDate | 2023-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-0cab940107ee4289897437799288b4c82023-04-28T10:31:21ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652023-04-011510.3389/fnagi.2023.11397891139789Identification and validation of biomarkers based on cellular senescence in mild cognitive impairmentSongmei Ma0Songmei Ma1Tong Xia2Xinyi Wang3Xinyi Wang4Xinyi Wang5Xinyi Wang6Haiyun Wang7Haiyun Wang8Haiyun Wang9Haiyun Wang10Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin, ChinaDepartment of Anesthesiology, The First People’s Hospital of Shangqiu, Shangqiu, Henan, ChinaDepartment of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin, ChinaDepartment of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin, ChinaTianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, ChinaArtificial Cell Engineering Technology Research Center, Tianjin, ChinaTianjin Institute of Hepatobiliary Disease, Tianjin, ChinaDepartment of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin, ChinaTianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, ChinaArtificial Cell Engineering Technology Research Center, Tianjin, ChinaTianjin Institute of Hepatobiliary Disease, Tianjin, ChinaBackgroundMild cognitive impairment (MCI), a syndrome defined as decline of cognitive function greater than expected for an individual’s age and education level, occurs in up to 22.7% of elderly patients in United States, causing the heavy psychological and economic burdens to families and society. Cellular senescence (CS) is a stress response that accompanies permanent cell-cycle arrest, which has been reported to be a fundamental pathological mechanism of many age-related diseases. This study aims to explore biomarkers and potential therapeutic targets in MCI based on CS.MethodsThe mRNA expression profiles of peripheral blood samples from patients in MCI and non-MCI group were download from gene expression omnibus (GEO) database (GSE63060 for training and GSE18309 for external validation), CS-related genes were obtained from CellAge database. Weighted gene co-expression network analysis (WGCNA) was conducted to discover the key relationships behind the co-expression modules. The differentially expressed CS-related genes would be obtained through overlapping among the above datasets. Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MCI. The protein–protein interaction network was used to extract hub genes and the logistic regression was performed to distinguish the MCI patients from controls. The hub gene-drug network, hub gene-miRNA network as well as transcription factor-gene regulatory network were used to analyze potential therapeutic targets for MCI.ResultsEight CS-related genes were identified as key gene signatures in MCI group, which were mainly enriched in the regulation of response to DNA damage stimulus, Sin3 complex and transcription corepressor activity. The receiver operating characteristic curves of logistic regression diagnostic model were constructed and presented great diagnostic value in both training and validation set.ConclusionEight CS-related hub genes – SMARCA4, GAPDH, SMARCB1, RUNX1, SRC, TRIM28, TXN, and PRPF19 – serve as candidate biomarkers for MCI and display the excellent diagnostic value. Furthermore, we also provide a theoretical basis for targeted therapy against MCI through the above hub genes.https://www.frontiersin.org/articles/10.3389/fnagi.2023.1139789/fullmild cognitive impairmentcellular senescencediagnostic modelbiomarkerelderly patients |
| spellingShingle | Songmei Ma Songmei Ma Tong Xia Xinyi Wang Xinyi Wang Xinyi Wang Xinyi Wang Haiyun Wang Haiyun Wang Haiyun Wang Haiyun Wang Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment Frontiers in Aging Neuroscience mild cognitive impairment cellular senescence diagnostic model biomarker elderly patients |
| title | Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment |
| title_full | Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment |
| title_fullStr | Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment |
| title_full_unstemmed | Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment |
| title_short | Identification and validation of biomarkers based on cellular senescence in mild cognitive impairment |
| title_sort | identification and validation of biomarkers based on cellular senescence in mild cognitive impairment |
| topic | mild cognitive impairment cellular senescence diagnostic model biomarker elderly patients |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2023.1139789/full |
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