Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis
Abstract Background No objective diagnostic indicators have been identified for schizophrenia (SCZ) because of the complexity of its pathogenesis. Whole-transcriptome analysis may help identify early diagnostic markers. While circular RNAs (circRNAs) have been reported to be involved in the onset an...
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BMC
2025-07-01
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| Series: | European Journal of Medical Research |
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| Online Access: | https://doi.org/10.1186/s40001-025-02899-4 |
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| author | Jianxiong Long Bing Shen Fangping Liao Hong Cai Jiale Li Rumei Lu Zhicheng Zhong Zukang Gong Jianfeng Xu |
| author_facet | Jianxiong Long Bing Shen Fangping Liao Hong Cai Jiale Li Rumei Lu Zhicheng Zhong Zukang Gong Jianfeng Xu |
| author_sort | Jianxiong Long |
| collection | DOAJ |
| description | Abstract Background No objective diagnostic indicators have been identified for schizophrenia (SCZ) because of the complexity of its pathogenesis. Whole-transcriptome analysis may help identify early diagnostic markers. While circular RNAs (circRNAs) have been reported to be involved in the onset and development of many diseases, their association with SCZ remains unclear. Methods This case‒control study analysed 5 pairs of peripheral blood samples from SCZ patients and controls. The samples were subjected to whole transcriptome analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed to identify the biological functions and pathways of the circRNAs. The competing endogenous RNA (ceRNA) network was predicted via miRanda, TargetScan, and miRTarBase. Protein–protein interactions were predicted with STRING. In addition, the interaction network between circRNAs and RNA binding proteins (RBPs) was predicted via the catRAPID and starBase databases. The expression of circRNAs was detected via qRT-PCR. Results The expression of 38699 circRNAs in the peripheral blood of 5 SCZ patients and 5 paired controls was profiled, and 589 differentially expressed circRNAs (DEcircRNAs) were identified. GO and KEGG analyses revealed that the host genes of these DEcircRNAs' are involved in molecular modifications and pathways such as the TNF and Wnt signalling pathways. A ceRNA network of 252 DEcircRNAs, 297 miRNAs, and 1075 mRNAs was constructed, highlighting potential regulatory molecules in SCZ. Three DEcircRNAs (hsa_circ_0006157, hsa_circ_0071422, and hsa_circ_0071095) were found to be significantly upregulated in patients. In addition, 27 RBPs were identified to bind to these DEcircRNAs, with DDX54 and RBM15B being significantly expressed. Conclusion Our study provides new insights into circRNAs that could act as potential diagnostic markers for SCZ, namely upregulated hsa_circ_0006157, hsa_circ_0071422, and hsa_circ_0071095. However, further functional validation is warranted to elucidate the precise contributions of these three circRNAs in SCZ. |
| format | Article |
| id | doaj-art-e1ca3d9d423d4dca9ee988ac22bdebb1 |
| institution | Kabale University |
| issn | 2047-783X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj-art-e1ca3d9d423d4dca9ee988ac22bdebb12025-08-20T04:01:53ZengBMCEuropean Journal of Medical Research2047-783X2025-07-0130111910.1186/s40001-025-02899-4Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesisJianxiong Long0Bing Shen1Fangping Liao2Hong Cai3Jiale Li4Rumei Lu5Zhicheng Zhong6Zukang Gong7Jianfeng Xu8Epidemiology and Biostatistics, School of Public Health, Guangxi Medical UniversityEpidemiology and Biostatistics, School of Public Health, Guangxi Medical UniversityKey Laboratory of Basic Research on Regional Diseases (Guangxi Medical University), School of Basic Medical Sciences, Guangxi Medical UniversityUnit of Medical Psychology and Behavior Medicine, School of Public Health, Guangxi Medical UniversityEpidemiology and Biostatistics, School of Public Health, Guangxi Medical UniversityEpidemiology and Biostatistics, School of Public Health, Guangxi Medical UniversityEpidemiology and Biostatistics, School of Public Health, Guangxi Medical UniversityNanning Fifth People’s HospitalEpidemiology and Biostatistics, School of Public Health, Guangxi Medical UniversityAbstract Background No objective diagnostic indicators have been identified for schizophrenia (SCZ) because of the complexity of its pathogenesis. Whole-transcriptome analysis may help identify early diagnostic markers. While circular RNAs (circRNAs) have been reported to be involved in the onset and development of many diseases, their association with SCZ remains unclear. Methods This case‒control study analysed 5 pairs of peripheral blood samples from SCZ patients and controls. The samples were subjected to whole transcriptome analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed to identify the biological functions and pathways of the circRNAs. The competing endogenous RNA (ceRNA) network was predicted via miRanda, TargetScan, and miRTarBase. Protein–protein interactions were predicted with STRING. In addition, the interaction network between circRNAs and RNA binding proteins (RBPs) was predicted via the catRAPID and starBase databases. The expression of circRNAs was detected via qRT-PCR. Results The expression of 38699 circRNAs in the peripheral blood of 5 SCZ patients and 5 paired controls was profiled, and 589 differentially expressed circRNAs (DEcircRNAs) were identified. GO and KEGG analyses revealed that the host genes of these DEcircRNAs' are involved in molecular modifications and pathways such as the TNF and Wnt signalling pathways. A ceRNA network of 252 DEcircRNAs, 297 miRNAs, and 1075 mRNAs was constructed, highlighting potential regulatory molecules in SCZ. Three DEcircRNAs (hsa_circ_0006157, hsa_circ_0071422, and hsa_circ_0071095) were found to be significantly upregulated in patients. In addition, 27 RBPs were identified to bind to these DEcircRNAs, with DDX54 and RBM15B being significantly expressed. Conclusion Our study provides new insights into circRNAs that could act as potential diagnostic markers for SCZ, namely upregulated hsa_circ_0006157, hsa_circ_0071422, and hsa_circ_0071095. However, further functional validation is warranted to elucidate the precise contributions of these three circRNAs in SCZ.https://doi.org/10.1186/s40001-025-02899-4SchizophreniaCircRNACeRNA networkRBP networkCase‒control study |
| spellingShingle | Jianxiong Long Bing Shen Fangping Liao Hong Cai Jiale Li Rumei Lu Zhicheng Zhong Zukang Gong Jianfeng Xu Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis European Journal of Medical Research Schizophrenia CircRNA CeRNA network RBP network Case‒control study |
| title | Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis |
| title_full | Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis |
| title_fullStr | Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis |
| title_full_unstemmed | Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis |
| title_short | Whole transcriptome sequencing to uncover CircRNA expression patterns linked to schizophrenia pathogenesis |
| title_sort | whole transcriptome sequencing to uncover circrna expression patterns linked to schizophrenia pathogenesis |
| topic | Schizophrenia CircRNA CeRNA network RBP network Case‒control study |
| url | https://doi.org/10.1186/s40001-025-02899-4 |
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