{"title":"FLVCR1作为他汀类药物相关性糖尿病铁代谢相关基因的鉴定","authors":"YiJia Huang, Kai Chen, Xiao Xiao, Shilong Zhong","doi":"10.1007/s00592-025-02491-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Long-term statin use has been linked to increased diabetes risk. Iron metabolism disruption may explain this association. The objective of this study was to identify the co-expression gene modules and the iron metabolism-related gene (IMG) linking statin administration and diabetes, making the hunt for novel therapeutic targets necessary.</p><p><strong>Methods: </strong>Weighted gene co-expression network analysis (WGCNA) was applied to the GSE130991 dataset to detect co-expressed gene modules. Enrichment analysis and single sample gene set enrichment analysis (ssGSEA) were conducted to characterize the biological processes and iron metabolism differences, respectively. Candidate IMGs were identified by intersecting WGCNA hub genes, differentially expressed genes (DEGs) from the statin-using and non-using obese individuals within the GSE130991 liver tissue dataset, and IMGs from Molecular Signatures Database Molecular Signatures Database (MisgDB). Mediation analysis was utilized to identify the definitive IMG. Expression validation was conducted through reverse transcription quantitative PCR (RT-qPCR) experiments and cross-referencing with additional datasets.</p><p><strong>Results: </strong>A shared gene module was identified between statin-users and diabetes patients, with functional enrichment analysis indicating involvement in iron ion binding. ssGSEA revealed differentially expressed iron metabolism in both statin-users and diabetes patients. Five IMG genes (CYP51A1, SC5D, MSMO1, SCD, and FLVCR1) were shortlisted, with FLVCR1 emerging as the key intermediary biomarker. FLVCR1 was positively correlated with insulin resistance and demonstrated robust predictive capabilities for diabetes. An increase in FLVCR1 mRNA levels was observed following statin treatment, as confirmed by RT-qPCR experiments and the GSE24188 dataset. Elevated FLVCR1 mRNA was also noted in diabetes patients across datasets GSE130991, GSE23343, and GSE95849.</p><p><strong>Conclusion: </strong>In this study, bioinformatics evidence supporting the association between statin use and diabetes was presented. FLVCR1 was identified as the iron metabolism-related mediator gene implicated in this relationship. Overall, our findings provide a theoretical foundation for new directions for future research exploring the complex interplay between statin treatment, iron metabolism regulation, and diabetes pathogenesis.</p>","PeriodicalId":6921,"journal":{"name":"Acta Diabetologica","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of FLVCR1 as the iron metabolism-related gene of statin-associated diabetes.\",\"authors\":\"YiJia Huang, Kai Chen, Xiao Xiao, Shilong Zhong\",\"doi\":\"10.1007/s00592-025-02491-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>Long-term statin use has been linked to increased diabetes risk. Iron metabolism disruption may explain this association. The objective of this study was to identify the co-expression gene modules and the iron metabolism-related gene (IMG) linking statin administration and diabetes, making the hunt for novel therapeutic targets necessary.</p><p><strong>Methods: </strong>Weighted gene co-expression network analysis (WGCNA) was applied to the GSE130991 dataset to detect co-expressed gene modules. Enrichment analysis and single sample gene set enrichment analysis (ssGSEA) were conducted to characterize the biological processes and iron metabolism differences, respectively. Candidate IMGs were identified by intersecting WGCNA hub genes, differentially expressed genes (DEGs) from the statin-using and non-using obese individuals within the GSE130991 liver tissue dataset, and IMGs from Molecular Signatures Database Molecular Signatures Database (MisgDB). Mediation analysis was utilized to identify the definitive IMG. Expression validation was conducted through reverse transcription quantitative PCR (RT-qPCR) experiments and cross-referencing with additional datasets.</p><p><strong>Results: </strong>A shared gene module was identified between statin-users and diabetes patients, with functional enrichment analysis indicating involvement in iron ion binding. ssGSEA revealed differentially expressed iron metabolism in both statin-users and diabetes patients. Five IMG genes (CYP51A1, SC5D, MSMO1, SCD, and FLVCR1) were shortlisted, with FLVCR1 emerging as the key intermediary biomarker. FLVCR1 was positively correlated with insulin resistance and demonstrated robust predictive capabilities for diabetes. An increase in FLVCR1 mRNA levels was observed following statin treatment, as confirmed by RT-qPCR experiments and the GSE24188 dataset. Elevated FLVCR1 mRNA was also noted in diabetes patients across datasets GSE130991, GSE23343, and GSE95849.</p><p><strong>Conclusion: </strong>In this study, bioinformatics evidence supporting the association between statin use and diabetes was presented. FLVCR1 was identified as the iron metabolism-related mediator gene implicated in this relationship. Overall, our findings provide a theoretical foundation for new directions for future research exploring the complex interplay between statin treatment, iron metabolism regulation, and diabetes pathogenesis.</p>\",\"PeriodicalId\":6921,\"journal\":{\"name\":\"Acta Diabetologica\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Diabetologica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00592-025-02491-6\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Diabetologica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00592-025-02491-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Identification of FLVCR1 as the iron metabolism-related gene of statin-associated diabetes.
Aims: Long-term statin use has been linked to increased diabetes risk. Iron metabolism disruption may explain this association. The objective of this study was to identify the co-expression gene modules and the iron metabolism-related gene (IMG) linking statin administration and diabetes, making the hunt for novel therapeutic targets necessary.
Methods: Weighted gene co-expression network analysis (WGCNA) was applied to the GSE130991 dataset to detect co-expressed gene modules. Enrichment analysis and single sample gene set enrichment analysis (ssGSEA) were conducted to characterize the biological processes and iron metabolism differences, respectively. Candidate IMGs were identified by intersecting WGCNA hub genes, differentially expressed genes (DEGs) from the statin-using and non-using obese individuals within the GSE130991 liver tissue dataset, and IMGs from Molecular Signatures Database Molecular Signatures Database (MisgDB). Mediation analysis was utilized to identify the definitive IMG. Expression validation was conducted through reverse transcription quantitative PCR (RT-qPCR) experiments and cross-referencing with additional datasets.
Results: A shared gene module was identified between statin-users and diabetes patients, with functional enrichment analysis indicating involvement in iron ion binding. ssGSEA revealed differentially expressed iron metabolism in both statin-users and diabetes patients. Five IMG genes (CYP51A1, SC5D, MSMO1, SCD, and FLVCR1) were shortlisted, with FLVCR1 emerging as the key intermediary biomarker. FLVCR1 was positively correlated with insulin resistance and demonstrated robust predictive capabilities for diabetes. An increase in FLVCR1 mRNA levels was observed following statin treatment, as confirmed by RT-qPCR experiments and the GSE24188 dataset. Elevated FLVCR1 mRNA was also noted in diabetes patients across datasets GSE130991, GSE23343, and GSE95849.
Conclusion: In this study, bioinformatics evidence supporting the association between statin use and diabetes was presented. FLVCR1 was identified as the iron metabolism-related mediator gene implicated in this relationship. Overall, our findings provide a theoretical foundation for new directions for future research exploring the complex interplay between statin treatment, iron metabolism regulation, and diabetes pathogenesis.
期刊介绍:
Acta Diabetologica is a journal that publishes reports of experimental and clinical research on diabetes mellitus and related metabolic diseases. Original contributions on biochemical, physiological, pathophysiological and clinical aspects of research on diabetes and metabolic diseases are welcome. Reports are published in the form of original articles, short communications and letters to the editor. Invited reviews and editorials are also published. A Methodology forum, which publishes contributions on methodological aspects of diabetes in vivo and in vitro, is also available. The Editor-in-chief will be pleased to consider articles describing new techniques (e.g., new transplantation methods, metabolic models), of innovative importance in the field of diabetes/metabolism. Finally, workshop reports are also welcome in Acta Diabetologica.