An association study of clock genes with major depressive disorder

To study the relationship between clock genes and Major Depressive Disorder (MDD). GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expres...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of affective disorders 2023-11, Vol.341, p.147-153
Hauptverfasser: Li, Ying, Miao, Peidong, Li, Fang, Huang, Jinsong, Fan, Lijun, Chen, Qiaoling, Zhang, Yunan, Yan, Feng, Gao, Yan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 153
container_issue
container_start_page 147
container_title Journal of affective disorders
container_volume 341
creator Li, Ying
Miao, Peidong
Li, Fang
Huang, Jinsong
Fan, Lijun
Chen, Qiaoling
Zhang, Yunan
Yan, Feng
Gao, Yan
description To study the relationship between clock genes and Major Depressive Disorder (MDD). GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD. Six genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF − beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathway
doi_str_mv 10.1016/j.jad.2023.08.113
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2857849370</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0165032723010935</els_id><sourcerecordid>2857849370</sourcerecordid><originalsourceid>FETCH-LOGICAL-c330t-9e3a4b652431e1eac1a49d168b714b8f46e461333a2617a62eb6f229ce322c763</originalsourceid><addsrcrecordid>eNp9kL1OwzAURi0EEqXwAGweWRJ87cROxFQq_qRKLDBbjn0DDmlc7LSob0-qMjPd5ZxPuoeQa2A5MJC3Xd4Zl3PGRc6qHECckBmUSmS8BHVKZhNTZkxwdU4uUuoYY7JWbEbuFwM1KQXrzejDQNO4dXsaWmr7YL_oBw6Y6I8fP-nadCFSh5uIKfkdUudTiA7jJTlrTZ_w6u_Oyfvjw9vyOVu9Pr0sF6vMCsHGrEZhikaWvBCAgMaCKWoHsmoUFE3VFhILCUIIwyUoIzk2suW8tig4t0qKObk57m5i-N5iGvXaJ4t9bwYM26R5VaqqqIViEwpH1MaQUsRWb6Jfm7jXwPShl-701EsfemlW6anX5NwdHZx-2HmMOlmPg0XnI9pRu-D_sX8B0ixyFA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2857849370</pqid></control><display><type>article</type><title>An association study of clock genes with major depressive disorder</title><source>Elsevier ScienceDirect Journals</source><creator>Li, Ying ; Miao, Peidong ; Li, Fang ; Huang, Jinsong ; Fan, Lijun ; Chen, Qiaoling ; Zhang, Yunan ; Yan, Feng ; Gao, Yan</creator><creatorcontrib>Li, Ying ; Miao, Peidong ; Li, Fang ; Huang, Jinsong ; Fan, Lijun ; Chen, Qiaoling ; Zhang, Yunan ; Yan, Feng ; Gao, Yan</creatorcontrib><description>To study the relationship between clock genes and Major Depressive Disorder (MDD). GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD. Six genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF − beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathways were Toll like receptor signaling pathway, glucolipid metabolism, amino acid metabolism, neuroactive ligand receptor interaction, and so on. The results of immune infiltration analysis showed that NK cells resting and Macrophages M2 were different between MDD and control groups. In MDD, the gene closely related to NK cells resting was HDAC1, and the genes closely related to Macrophages M2 were HDAC1 and NFIL3. The RNA interactions network of clock genes shows that the regulation process is complex, which can provide a reference for subsequent related research. Potential therapeutic drugs predict display, among the 5 clock genes, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. Among all CLOCK genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD. Among them, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. •It is of great clinical significance and social value to study the pathogenesis of depression and search for accurate and effective biomarkers to improve the diagnostic accuracy and reduce the medical burden.•The bioinformatics analysis was used to carry out data mining of clock genes in patients with Major Depressive Disorder (MDD).•Bioinformatics analysis showed that among all clock genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD.</description><identifier>ISSN: 0165-0327</identifier><identifier>EISSN: 1573-2517</identifier><identifier>DOI: 10.1016/j.jad.2023.08.113</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Clock genes ; HDAC1 ; Major depressive disorder (MDD) ; PRKAA1 ; TNF</subject><ispartof>Journal of affective disorders, 2023-11, Vol.341, p.147-153</ispartof><rights>2023 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c330t-9e3a4b652431e1eac1a49d168b714b8f46e461333a2617a62eb6f229ce322c763</citedby><cites>FETCH-LOGICAL-c330t-9e3a4b652431e1eac1a49d168b714b8f46e461333a2617a62eb6f229ce322c763</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0165032723010935$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,65309</link.rule.ids></links><search><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Miao, Peidong</creatorcontrib><creatorcontrib>Li, Fang</creatorcontrib><creatorcontrib>Huang, Jinsong</creatorcontrib><creatorcontrib>Fan, Lijun</creatorcontrib><creatorcontrib>Chen, Qiaoling</creatorcontrib><creatorcontrib>Zhang, Yunan</creatorcontrib><creatorcontrib>Yan, Feng</creatorcontrib><creatorcontrib>Gao, Yan</creatorcontrib><title>An association study of clock genes with major depressive disorder</title><title>Journal of affective disorders</title><description>To study the relationship between clock genes and Major Depressive Disorder (MDD). GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD. Six genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF − beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathways were Toll like receptor signaling pathway, glucolipid metabolism, amino acid metabolism, neuroactive ligand receptor interaction, and so on. The results of immune infiltration analysis showed that NK cells resting and Macrophages M2 were different between MDD and control groups. In MDD, the gene closely related to NK cells resting was HDAC1, and the genes closely related to Macrophages M2 were HDAC1 and NFIL3. The RNA interactions network of clock genes shows that the regulation process is complex, which can provide a reference for subsequent related research. Potential therapeutic drugs predict display, among the 5 clock genes, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. Among all CLOCK genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD. Among them, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. •It is of great clinical significance and social value to study the pathogenesis of depression and search for accurate and effective biomarkers to improve the diagnostic accuracy and reduce the medical burden.•The bioinformatics analysis was used to carry out data mining of clock genes in patients with Major Depressive Disorder (MDD).•Bioinformatics analysis showed that among all clock genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD.</description><subject>Clock genes</subject><subject>HDAC1</subject><subject>Major depressive disorder (MDD)</subject><subject>PRKAA1</subject><subject>TNF</subject><issn>0165-0327</issn><issn>1573-2517</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kL1OwzAURi0EEqXwAGweWRJ87cROxFQq_qRKLDBbjn0DDmlc7LSob0-qMjPd5ZxPuoeQa2A5MJC3Xd4Zl3PGRc6qHECckBmUSmS8BHVKZhNTZkxwdU4uUuoYY7JWbEbuFwM1KQXrzejDQNO4dXsaWmr7YL_oBw6Y6I8fP-nadCFSh5uIKfkdUudTiA7jJTlrTZ_w6u_Oyfvjw9vyOVu9Pr0sF6vMCsHGrEZhikaWvBCAgMaCKWoHsmoUFE3VFhILCUIIwyUoIzk2suW8tig4t0qKObk57m5i-N5iGvXaJ4t9bwYM26R5VaqqqIViEwpH1MaQUsRWb6Jfm7jXwPShl-701EsfemlW6anX5NwdHZx-2HmMOlmPg0XnI9pRu-D_sX8B0ixyFA</recordid><startdate>20231115</startdate><enddate>20231115</enddate><creator>Li, Ying</creator><creator>Miao, Peidong</creator><creator>Li, Fang</creator><creator>Huang, Jinsong</creator><creator>Fan, Lijun</creator><creator>Chen, Qiaoling</creator><creator>Zhang, Yunan</creator><creator>Yan, Feng</creator><creator>Gao, Yan</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20231115</creationdate><title>An association study of clock genes with major depressive disorder</title><author>Li, Ying ; Miao, Peidong ; Li, Fang ; Huang, Jinsong ; Fan, Lijun ; Chen, Qiaoling ; Zhang, Yunan ; Yan, Feng ; Gao, Yan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c330t-9e3a4b652431e1eac1a49d168b714b8f46e461333a2617a62eb6f229ce322c763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Clock genes</topic><topic>HDAC1</topic><topic>Major depressive disorder (MDD)</topic><topic>PRKAA1</topic><topic>TNF</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Miao, Peidong</creatorcontrib><creatorcontrib>Li, Fang</creatorcontrib><creatorcontrib>Huang, Jinsong</creatorcontrib><creatorcontrib>Fan, Lijun</creatorcontrib><creatorcontrib>Chen, Qiaoling</creatorcontrib><creatorcontrib>Zhang, Yunan</creatorcontrib><creatorcontrib>Yan, Feng</creatorcontrib><creatorcontrib>Gao, Yan</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of affective disorders</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Ying</au><au>Miao, Peidong</au><au>Li, Fang</au><au>Huang, Jinsong</au><au>Fan, Lijun</au><au>Chen, Qiaoling</au><au>Zhang, Yunan</au><au>Yan, Feng</au><au>Gao, Yan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An association study of clock genes with major depressive disorder</atitle><jtitle>Journal of affective disorders</jtitle><date>2023-11-15</date><risdate>2023</risdate><volume>341</volume><spage>147</spage><epage>153</epage><pages>147-153</pages><issn>0165-0327</issn><eissn>1573-2517</eissn><abstract>To study the relationship between clock genes and Major Depressive Disorder (MDD). GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD. Six genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF − beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathways were Toll like receptor signaling pathway, glucolipid metabolism, amino acid metabolism, neuroactive ligand receptor interaction, and so on. The results of immune infiltration analysis showed that NK cells resting and Macrophages M2 were different between MDD and control groups. In MDD, the gene closely related to NK cells resting was HDAC1, and the genes closely related to Macrophages M2 were HDAC1 and NFIL3. The RNA interactions network of clock genes shows that the regulation process is complex, which can provide a reference for subsequent related research. Potential therapeutic drugs predict display, among the 5 clock genes, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. Among all CLOCK genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD. Among them, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs. •It is of great clinical significance and social value to study the pathogenesis of depression and search for accurate and effective biomarkers to improve the diagnostic accuracy and reduce the medical burden.•The bioinformatics analysis was used to carry out data mining of clock genes in patients with Major Depressive Disorder (MDD).•Bioinformatics analysis showed that among all clock genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jad.2023.08.113</doi><tpages>7</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0165-0327
ispartof Journal of affective disorders, 2023-11, Vol.341, p.147-153
issn 0165-0327
1573-2517
language eng
recordid cdi_proquest_miscellaneous_2857849370
source Elsevier ScienceDirect Journals
subjects Clock genes
HDAC1
Major depressive disorder (MDD)
PRKAA1
TNF
title An association study of clock genes with major depressive disorder
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T19%3A52%3A34IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20association%20study%20of%20clock%20genes%20with%20major%20depressive%20disorder&rft.jtitle=Journal%20of%20affective%20disorders&rft.au=Li,%20Ying&rft.date=2023-11-15&rft.volume=341&rft.spage=147&rft.epage=153&rft.pages=147-153&rft.issn=0165-0327&rft.eissn=1573-2517&rft_id=info:doi/10.1016/j.jad.2023.08.113&rft_dat=%3Cproquest_cross%3E2857849370%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2857849370&rft_id=info:pmid/&rft_els_id=S0165032723010935&rfr_iscdi=true