Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia
AimThis study aimed to identify autophagy-related genes (ARGs) associated with non-obstructive azoospermia and explore the underlying molecular mechanisms.MethodsTwo datasets associated with azoospermia were downloaded from the Gene Expression Omnibus database, and ARGs were obtained from the Human...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-03-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1088261/full |
| _version_ | 1811158373402411008 |
|---|---|
| author | Yucheng Zhong Jun Zhao Hao Deng Yaqin Wu Li Zhu Meiqiong Yang Qianru Liu Guoqun Luo Wenmin Ma Wenmin Ma Huan Li |
| author_facet | Yucheng Zhong Jun Zhao Hao Deng Yaqin Wu Li Zhu Meiqiong Yang Qianru Liu Guoqun Luo Wenmin Ma Wenmin Ma Huan Li |
| author_sort | Yucheng Zhong |
| collection | DOAJ |
| description | AimThis study aimed to identify autophagy-related genes (ARGs) associated with non-obstructive azoospermia and explore the underlying molecular mechanisms.MethodsTwo datasets associated with azoospermia were downloaded from the Gene Expression Omnibus database, and ARGs were obtained from the Human Autophagy-dedicated Database. Autophagy-related differentially expressed genes were identified in the azoospermia and control groups. These genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, protein–protein interaction (PPI) network, and functional similarity analyses. After identifying the hub genes, immune infiltration and hub gene–RNA-binding protein (RBP)–transcription factor (TF)–miRNA–drug interactions were analyzed.ResultsA total 46 differentially expressed ARGs were identified between the azoospermia and control groups. These genes were enriched in autophagy-associated functions and pathways. Eight hub genes were selected from the PPI network. Functional similarity analysis revealed that HSPA5 may play a key role in azoospermia. Immune cell infiltration analysis revealed that activated dendritic cells were significantly decreased in the azoospermia group compared to those in the control groups. Hub genes, especially ATG3, KIAA0652, MAPK1, and EGFR were strongly correlated with immune cell infiltration. Finally, a hub gene–miRNA–TF–RBP–drug network was constructed.ConclusionThe eight hub genes, including EGFR, HSPA5, ATG3, KIAA0652, and MAPK1, may serve as biomarkers for the diagnosis and treatment of azoospermia. The study findings suggest potential targets and mechanisms for the occurrence and development of this disease. |
| first_indexed | 2024-04-10T05:22:22Z |
| format | Article |
| id | doaj.art-59d11754ccd74623a2b6b9665b5d9703 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-10T05:22:22Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-59d11754ccd74623a2b6b9665b5d97032023-03-08T06:01:39ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-03-011410.3389/fimmu.2023.10882611088261Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermiaYucheng Zhong0Jun Zhao1Hao Deng2Yaqin Wu3Li Zhu4Meiqiong Yang5Qianru Liu6Guoqun Luo7Wenmin Ma8Wenmin Ma9Huan Li10Assisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAssist Reproductive Medical Center, Zhaoqing West River Hospital, Zhaoqing, Guangdong, ChinaAssisted Reproductive Technology Center, Southern Medical University Affiliated Maternal and Child Health Hospital of Foshan, Foshan, Guangdong, ChinaAimThis study aimed to identify autophagy-related genes (ARGs) associated with non-obstructive azoospermia and explore the underlying molecular mechanisms.MethodsTwo datasets associated with azoospermia were downloaded from the Gene Expression Omnibus database, and ARGs were obtained from the Human Autophagy-dedicated Database. Autophagy-related differentially expressed genes were identified in the azoospermia and control groups. These genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, protein–protein interaction (PPI) network, and functional similarity analyses. After identifying the hub genes, immune infiltration and hub gene–RNA-binding protein (RBP)–transcription factor (TF)–miRNA–drug interactions were analyzed.ResultsA total 46 differentially expressed ARGs were identified between the azoospermia and control groups. These genes were enriched in autophagy-associated functions and pathways. Eight hub genes were selected from the PPI network. Functional similarity analysis revealed that HSPA5 may play a key role in azoospermia. Immune cell infiltration analysis revealed that activated dendritic cells were significantly decreased in the azoospermia group compared to those in the control groups. Hub genes, especially ATG3, KIAA0652, MAPK1, and EGFR were strongly correlated with immune cell infiltration. Finally, a hub gene–miRNA–TF–RBP–drug network was constructed.ConclusionThe eight hub genes, including EGFR, HSPA5, ATG3, KIAA0652, and MAPK1, may serve as biomarkers for the diagnosis and treatment of azoospermia. The study findings suggest potential targets and mechanisms for the occurrence and development of this disease.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1088261/fullazoospermiaautophagyhub geneimmunebiomarkers |
| spellingShingle | Yucheng Zhong Jun Zhao Hao Deng Yaqin Wu Li Zhu Meiqiong Yang Qianru Liu Guoqun Luo Wenmin Ma Wenmin Ma Huan Li Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia Frontiers in Immunology azoospermia autophagy hub gene immune biomarkers |
| title | Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia |
| title_full | Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia |
| title_fullStr | Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia |
| title_full_unstemmed | Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia |
| title_short | Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia |
| title_sort | integrative bioinformatics analysis to identify novel biomarkers associated with non obstructive azoospermia |
| topic | azoospermia autophagy hub gene immune biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1088261/full |
| work_keys_str_mv | AT yuchengzhong integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT junzhao integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT haodeng integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT yaqinwu integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT lizhu integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT meiqiongyang integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT qianruliu integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT guoqunluo integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT wenminma integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT wenminma integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia AT huanli integrativebioinformaticsanalysistoidentifynovelbiomarkersassociatedwithnonobstructiveazoospermia |