鉴定 DIO2 作为慢性鼻炎抑郁症的分子治疗靶点:一项全面的生物信息学和实验研究。

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Hao Lv, Peiqiang Liu, Yunfei Wang, Jingyu Huang, Yulie Xie, Mengting Guan, Jianchao Cong, Yang Jiang, Yu Xu
{"title":"鉴定 DIO2 作为慢性鼻炎抑郁症的分子治疗靶点:一项全面的生物信息学和实验研究。","authors":"Hao Lv, Peiqiang Liu, Yunfei Wang, Jingyu Huang, Yulie Xie, Mengting Guan, Jianchao Cong, Yang Jiang, Yu Xu","doi":"10.1007/s10528-025-11085-4","DOIUrl":null,"url":null,"abstract":"<p><p>Chronic rhinosinusitis (CRS) and depression are both common conditions with significant socioeconomic impact. The high co-occurrence of depression in CRS patients suggests a common pathophysiology, but the mechanisms are unclear. This study aimed to identify potential molecular links between the two conditions. We retrieved gene expression datasets for CRS and depression from the GEO database. Using differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA), we identified co-expression genes associated with CRS and depression. Enrichment analyses including GO, KEGG, and GSEA were performed to explore biological pathways. Machine learning algorithms including random forest and LASSO regression were engaged to screen for shared hub genes predictive of CRS and depression. Single-cell RNA sequencing (scRNA-seq) data were analyzed to delineate the expression profiles of the shared hub genes across different cell types. Animal experiments were employed to validate the role of core genes in CRS-related depression. We identified five shared hub genes: CHRDL1, DIO2, HSD17B6, PDE3A, and PLA2G5, with the TGF-β signaling, cytokine-cytokine interaction receptors, and cell adhesion as key biological pathways. DIO2, as identified by machine learning, is a promising diagnostic biomarker for CRS and depression. The scRNA-seq analysis showed that DIO2 is primarily expressed in neurons and astrocytes. Animal experiments showed that overexpression of DIO2 improved the depressive-like behaviors in CRS mice. This study sheds new light on the molecular basis of the comorbidity between CRS and depression. DIO2 is a potential diagnostic and therapeutic target for CRS patients with comorbid depression.</p>","PeriodicalId":482,"journal":{"name":"Biochemical Genetics","volume":" ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of DIO2 as a Molecular Therapeutic Target for Depression in Chronic Rhinosinusitis: A Comprehensive Bioinformatics and Experimental Study.\",\"authors\":\"Hao Lv, Peiqiang Liu, Yunfei Wang, Jingyu Huang, Yulie Xie, Mengting Guan, Jianchao Cong, Yang Jiang, Yu Xu\",\"doi\":\"10.1007/s10528-025-11085-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Chronic rhinosinusitis (CRS) and depression are both common conditions with significant socioeconomic impact. The high co-occurrence of depression in CRS patients suggests a common pathophysiology, but the mechanisms are unclear. This study aimed to identify potential molecular links between the two conditions. We retrieved gene expression datasets for CRS and depression from the GEO database. Using differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA), we identified co-expression genes associated with CRS and depression. Enrichment analyses including GO, KEGG, and GSEA were performed to explore biological pathways. Machine learning algorithms including random forest and LASSO regression were engaged to screen for shared hub genes predictive of CRS and depression. Single-cell RNA sequencing (scRNA-seq) data were analyzed to delineate the expression profiles of the shared hub genes across different cell types. Animal experiments were employed to validate the role of core genes in CRS-related depression. We identified five shared hub genes: CHRDL1, DIO2, HSD17B6, PDE3A, and PLA2G5, with the TGF-β signaling, cytokine-cytokine interaction receptors, and cell adhesion as key biological pathways. DIO2, as identified by machine learning, is a promising diagnostic biomarker for CRS and depression. The scRNA-seq analysis showed that DIO2 is primarily expressed in neurons and astrocytes. Animal experiments showed that overexpression of DIO2 improved the depressive-like behaviors in CRS mice. This study sheds new light on the molecular basis of the comorbidity between CRS and depression. DIO2 is a potential diagnostic and therapeutic target for CRS patients with comorbid depression.</p>\",\"PeriodicalId\":482,\"journal\":{\"name\":\"Biochemical Genetics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biochemical Genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1007/s10528-025-11085-4\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemical Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s10528-025-11085-4","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of DIO2 as a Molecular Therapeutic Target for Depression in Chronic Rhinosinusitis: A Comprehensive Bioinformatics and Experimental Study.

Chronic rhinosinusitis (CRS) and depression are both common conditions with significant socioeconomic impact. The high co-occurrence of depression in CRS patients suggests a common pathophysiology, but the mechanisms are unclear. This study aimed to identify potential molecular links between the two conditions. We retrieved gene expression datasets for CRS and depression from the GEO database. Using differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA), we identified co-expression genes associated with CRS and depression. Enrichment analyses including GO, KEGG, and GSEA were performed to explore biological pathways. Machine learning algorithms including random forest and LASSO regression were engaged to screen for shared hub genes predictive of CRS and depression. Single-cell RNA sequencing (scRNA-seq) data were analyzed to delineate the expression profiles of the shared hub genes across different cell types. Animal experiments were employed to validate the role of core genes in CRS-related depression. We identified five shared hub genes: CHRDL1, DIO2, HSD17B6, PDE3A, and PLA2G5, with the TGF-β signaling, cytokine-cytokine interaction receptors, and cell adhesion as key biological pathways. DIO2, as identified by machine learning, is a promising diagnostic biomarker for CRS and depression. The scRNA-seq analysis showed that DIO2 is primarily expressed in neurons and astrocytes. Animal experiments showed that overexpression of DIO2 improved the depressive-like behaviors in CRS mice. This study sheds new light on the molecular basis of the comorbidity between CRS and depression. DIO2 is a potential diagnostic and therapeutic target for CRS patients with comorbid depression.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信