What question did this study set out to answer?

To identify key ferroptosis-related genes, regulatory networks, and diagnostic biomarkers associated with diabetic retinopathy using bioinformatics methods.

January 23, 2023PLoS ONEOpen Access

Identification of key ferroptosis genes in diabetic retinopathy based on bioinformatics analysis

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Authors

YHYan Huang JPJun Peng QLQiu-Hua Liang

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Overview

Bioinformatics analysis uncovers key ferroptosis hub genes in diabetic retinopathy, highlighting novel regulatory pathways and diagnostic targets.

Key Points

To identify key ferroptosis-related genes, regulatory networks, and diagnostic biomarkers associated with diabetic retinopathy using bioinformatics methods.
Analyzed retinal RNA-sequencing data from the GEO database (N=15 diabetic retinopathy samples and N=3 healthy controls) using DESeq2 and WGCNA algorithms.
Intersected co-expression modules with the FerrDb database to identify differentially expressed ferroptosis-related genes, followed by functional enrichment and protein-protein interaction network analyses.
Predicted upstream transcription factors via TRRUST, identified miRNA regulators using multiple prediction databases, and validated hub genes in an independent external dataset.
Identified 52 ferroptosis-related differentially expressed genes (43 upregulated and 9 downregulated) significantly enriched in intrinsic apoptosis, autophagosomes, iron ion binding, and p53 signaling pathways.
Filtered 7 initial hub genes down to HMOX1 and PTGS2, which were successfully validated as differentially expressed in an external dataset.
Identified critical upstream regulators, linking HMOX1 to hsa-miR-873-5p and 13 transcription factors, and PTGS2 to hsa-miR-624-5p, hsa-miR-542-3p, and 20 transcription factors.

Cite This Study

Huang et al. (2023) studied this question.

synapsesocial.com/papers/6a6cb1ae35aa2c282cdfa421 https://doi.org/10.1371/journal.pone.0280548

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January 23, 2023PLoS ONEOpen Access

Identification of key ferroptosis genes in diabetic retinopathy based on bioinformatics analysis

View Full Paper

Ask AI

Bookmark

Authors

YHYan Huang JPJun Peng QLQiu-Hua Liang

Discussion

Member takes

Overview

Bioinformatics analysis uncovers key ferroptosis hub genes in diabetic retinopathy, highlighting novel regulatory pathways and diagnostic targets.

Key Points

To identify key ferroptosis-related genes, regulatory networks, and diagnostic biomarkers associated with diabetic retinopathy using bioinformatics methods.
Analyzed retinal RNA-sequencing data from the GEO database (N=15 diabetic retinopathy samples and N=3 healthy controls) using DESeq2 and WGCNA algorithms.
Intersected co-expression modules with the FerrDb database to identify differentially expressed ferroptosis-related genes, followed by functional enrichment and protein-protein interaction network analyses.
Predicted upstream transcription factors via TRRUST, identified miRNA regulators using multiple prediction databases, and validated hub genes in an independent external dataset.
Identified 52 ferroptosis-related differentially expressed genes (43 upregulated and 9 downregulated) significantly enriched in intrinsic apoptosis, autophagosomes, iron ion binding, and p53 signaling pathways.
Filtered 7 initial hub genes down to HMOX1 and PTGS2, which were successfully validated as differentially expressed in an external dataset.
Identified critical upstream regulators, linking HMOX1 to hsa-miR-873-5p and 13 transcription factors, and PTGS2 to hsa-miR-624-5p, hsa-miR-542-3p, and 20 transcription factors.

Cite This Study

Huang et al. (2023) studied this question.

synapsesocial.com/papers/6a6cb1ae35aa2c282cdfa421 https://doi.org/10.1371/journal.pone.0280548

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