Evidence map›Paper›PMID 40297850›Full record

ArticleFrontiers in molecular biosciences2025

Identification of mitochondrial function and programmed cell death associated key biomarkers and the circRNA-miRNA-mRNA regulatory network in systemic lupus erythematosus.

Junjie Cao, Aifang Li, Hui Zhou, Yujie Yan, Gaiying Luo

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Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Junjie CaoDepartment of Laboratory Medicine, Xi'an Fifth Hospital, Xi'an, Shaanxi, China.
Aifang LiDepartment of Laboratory Medicine, Xi'an Chest Hospital, Xi'an, Shaanxi, China.
Hui ZhouDepartment of Cardiovascular, Xi'an Fifth Hospital, Xi'an, Shaanxi, China.
Yujie YanMedical Collage, Xi'an Peihua University, Xi'an, Shaanxi, China.
Gaiying LuoDepartment of Laboratory Medicine, Xi'an Fifth Hospital, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Systemic Lupus Erythematosus (SLE) is a highly heterogeneous autoimmune disease with complex pathogenic mechanisms. Mitochondrial function and programmed cell death (PCD) play important roles in SLE. This study aims to screen biomarkers related to mitochondrial function and programmed cell death in SLE and analyze their underlying mechanisms. Methods: SLE-related databases were derived from the GEO database, where three SLE databases were merged into one database as the training set. Genes related to mitochondrial function and PCD were sourced from the MitoCarta 3.0 database. Key genes were identified through bioinformatics and machine learning, and their expression levels and diagnostic efficacy were validated using two SLE-related datasets as the validation set. The relationship between diagnostic genes and immune cells was analyzed through CIBERSORT immune infiltration analysis. Diagnostic genes-related miRNAs were predicted using online databases. Differential circRNAs were screened in SLE circRNA datasets, and the relationship between circRNAs and miRNAs is predicted through circbank, finally constructing a circRNA-miRNA-mRNA ceRNA regulatory network. Results: From the 448 differential genes in the SLE training set, two key genes, IFI27 and LAMP3, were identified through machine learning and WGCNA. Enrichment analysis revealed that they were mainly enriched in pathways such as cell cycle, systemic lupus erythematosus, cytosolic DNA sensing pathway, toll-like receptor (TLR) signaling pathway and nod-like receptor (NLR) signaling pathway. Immune infiltration analysis found that compared with normal group, 11 immune cells were differentially expressed, with IFI27 related 9 types of immune cells and LAMP3 related 10 types of immune cells. The final constructed circRNA-miRNA-mRNA ceRNA regulatory network consists of 2 mRNAs, 5 miRNAs, and 4 circRNAs. Conclusion: Our study ultimately identified two biomarkers (IFI27 and LAMP3) related to mitochondrial function and programmed cell death that play an important role in SLE. In the future, IFI27 and LAMP3 have the potential to become important biomarkers in the diagnosis and treatment of SLE. Their role in the immune response may provide new strategies for the treatment of SLE.

Indexed as

bioinformaticsmachine learningmitochondrial functionprogrammed cell deathsystemic lupus erythematosus

Identifiers

PMID40297850
PMCPMC12034568

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