Evidence map›Paper›PMID 40146399›Full record

ArticleActa diabetologica2025

Identification of FLVCR1 as the iron metabolism-related gene of statin-associated diabetes.

YiJia Huang, Kai Chen, Xiao Xiao, Shilong Zhong

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Article in Acta diabetologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

YiJia Huang *South China University of Technology School of Medicine, Guangzhou, 510006, China.
Kai Chen *South China University of Technology School of Medicine, Guangzhou, 510006, China.
Xiao XiaoDepartment of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, 510080, China. xiaoxiao@gdph.org.cn.
Shilong ZhongSouth China University of Technology School of Medicine, Guangzhou, 510006, China. shz2020@qq.com.ORCID http://orcid.org/0000-0002-2696-7696

Funding

Guangzhou Municipal Science and Technology Program key projects 2023B03J1251National Natural Science Foundation of China 81872934National Natural Science Foundation of China 82274016
6 · The paper itself

Abstract

aimsLong-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.

methodsWeighted 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.

resultsA 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.

conclusionIn 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.

Indexed as

Diabetes MellitusHydroxymethylglutaryl-CoA Reductase InhibitorsIronMembrane Transport ProteinsReceptors, VirusFemaleGene Regulatory NetworksHumansMaleFLVCR1 protein, humanHydroxymethylglutaryl-CoA Reductase InhibitorsIronMembrane Transport ProteinsReceptors, VirusDiabetesFLVCR1Iron metabolismStatin

Identifiers

PMID40146399

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.