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Background <p>Diabetic retinopathy (DR), a serious microvascular complication of diabetes, has a complex pathogenic mechanism that is intricately linked to programmed cell death (PCD) and also to N6-methyladenosine (m<sup>6</sup>A) modification. The objective of this research was to pinpoint crucial genes related to m<sup>6</sup>A-related PCD in DR using transcriptomic data, offering novel targets and a theoretical basis for the pathogenesis of DR.</p> Methods <p>In this study, transcriptomic data of DR samples and control samples were obtained from a public database. Meanwhile, m<sup>6</sup>A-and PCD-related genes were retrieved from the literature. Candidate genes were identified via differential expression and correlation analyses. Using constructed protein-protein interaction (PPI) networks, a machine learning algorithms screened for feature genes, which underwent expression validation to determine key genes. A predictive nomogram was subsequently developed and its performance evaluated. Enrichment analysis, along with immune infiltration analysis were carried out. Finally, molecular regulatory networks and molecular docking was performed.</p> Results <p>Initially, 3,716 differentially expressed genes between DR and control samples (DRDEGs) were identified. By intersecting DRDEGs with PCD-related genes and m⁶A-related differentially expressed genes, followed by Spearman correlation analysis, 58 candidate genes were identified. Subsequently, Forkhead box K1 (FOXK1) and Semaphorin 7&#xa0;A (SEMA7A) were identified as key genes through PPI, machine learning, and expression analyses. Furthermore, the two key genes constructed a well accurate nomogram for DR diagnosis. GSEA revealed their critical roles in DR pathogenesis. Moreover, immune infiltration analysis highlighted the involvement of immune dysregulation in DR. The constructed TF-mRNA-miRNA regulatory network contained 2 key genes, 14 transcription factors, and 12 miRNAs (e.g. BRCA1-FOXK1-mmu-miR-7234-3p). Molecular docking showed that decitabine and other drugs bound well to FOXK1,warranting further experimental investigation into their therapeutic efficacy.</p> Conclusion <p>This study identified FOXK1 and SEMA7A as key genes in DR related to m<sup>6</sup>A-associated programmed cell death, which may provide a new direction for subsequent research on diagnosis and treatment.</p>

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Identification of FOXK1 and SEMA7A as key genes associated with m6A-related programmed cell death in diabetic retinopathy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月10日

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  • Jie Yang,
  • Zhenyu Wu,
  • Ningning Dong

摘要

Background

Diabetic retinopathy (DR), a serious microvascular complication of diabetes, has a complex pathogenic mechanism that is intricately linked to programmed cell death (PCD) and also to N6-methyladenosine (m6A) modification. The objective of this research was to pinpoint crucial genes related to m6A-related PCD in DR using transcriptomic data, offering novel targets and a theoretical basis for the pathogenesis of DR.

Methods

In this study, transcriptomic data of DR samples and control samples were obtained from a public database. Meanwhile, m6A-and PCD-related genes were retrieved from the literature. Candidate genes were identified via differential expression and correlation analyses. Using constructed protein-protein interaction (PPI) networks, a machine learning algorithms screened for feature genes, which underwent expression validation to determine key genes. A predictive nomogram was subsequently developed and its performance evaluated. Enrichment analysis, along with immune infiltration analysis were carried out. Finally, molecular regulatory networks and molecular docking was performed.

Results

Initially, 3,716 differentially expressed genes between DR and control samples (DRDEGs) were identified. By intersecting DRDEGs with PCD-related genes and m⁶A-related differentially expressed genes, followed by Spearman correlation analysis, 58 candidate genes were identified. Subsequently, Forkhead box K1 (FOXK1) and Semaphorin 7 A (SEMA7A) were identified as key genes through PPI, machine learning, and expression analyses. Furthermore, the two key genes constructed a well accurate nomogram for DR diagnosis. GSEA revealed their critical roles in DR pathogenesis. Moreover, immune infiltration analysis highlighted the involvement of immune dysregulation in DR. The constructed TF-mRNA-miRNA regulatory network contained 2 key genes, 14 transcription factors, and 12 miRNAs (e.g. BRCA1-FOXK1-mmu-miR-7234-3p). Molecular docking showed that decitabine and other drugs bound well to FOXK1,warranting further experimental investigation into their therapeutic efficacy.

Conclusion

This study identified FOXK1 and SEMA7A as key genes in DR related to m6A-associated programmed cell death, which may provide a new direction for subsequent research on diagnosis and treatment.