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Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy

BACKGROUND: Diabetic retinopathy (DR) is deemed a microangiopathy and neurodegenerative disorder, which is a primary reason of visual impairment in the world. Ferritinophagy is a critical regulator of ferroptosis and has a vital part in the etiopathogenesis of DR. Nevertheless, its molecular mechani...

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Autores principales: Yu, Fenfen, Wang, Congyao, Su, Yihua, Chen, Tingting, Zhu, Wenhui, Dong, Xia, Ke, Wanyi, Cai, Leqi, Yang, Shasha, Wan, Pengxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377661/
https://www.ncbi.nlm.nih.gov/pubmed/37522124
http://dx.doi.org/10.3389/fendo.2023.1177488
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author Yu, Fenfen
Wang, Congyao
Su, Yihua
Chen, Tingting
Zhu, Wenhui
Dong, Xia
Ke, Wanyi
Cai, Leqi
Yang, Shasha
Wan, Pengxia
author_facet Yu, Fenfen
Wang, Congyao
Su, Yihua
Chen, Tingting
Zhu, Wenhui
Dong, Xia
Ke, Wanyi
Cai, Leqi
Yang, Shasha
Wan, Pengxia
author_sort Yu, Fenfen
collection PubMed
description BACKGROUND: Diabetic retinopathy (DR) is deemed a microangiopathy and neurodegenerative disorder, which is a primary reason of visual impairment in the world. Ferritinophagy is a critical regulator of ferroptosis and has a vital part in the etiopathogenesis of DR. Nevertheless, its molecular mechanism in DR remains to be expounded. METHODS: The GSE146615 dataset was adopted to identify ferritinophagy-related differentially expressed genes (FRDEGs). The interactions and biological functions of the genes were described by means of functional enrichment analysis (FEA). The enriched gene sets were analyzed utilizing gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Identification of hub genes was performed utilizing protein–protein interaction (PPI) analysis. mRNA–miRNA, mRNA–transcription factors (TF), mRNA–drugs, mRNA–RNA-binding proteins (RBP) interaction networks were constructed. In addition, datasets GSE60436 and GSE94019 were utilized for validation. The diagnostic performance of FRDEGs was assessed by means of receiver-operating characteristic curve monofactor analysis, followed by immune infiltration analysis. Lastly, quantitative real-time polymerase chain reaction (qRT-PCR) was implemented to analyze the validation of genes. RESULTS: In total, the identification of eight FRDEGs was completed utilizing differential expression analysis. FEA mainly implicated the autophagy of mitochondrion, mitochondrion disassembly, autophagosome assembly, and organization pathways. GSEA and GSVA mainly implicated the interferon alpha response, ultraviolet response up, interferon gamma response, apical junction, pical surface, and allograft rejection pathways. BECN1 and HERC2 displayed high diagnostic accuracies in validation sets. Immune infiltration analysis revealed that several immune cells related to ferritinophagy may be play potential roles in DR. Finally, qRT-PCR was utilized to validate the upregulated expression of BECN1 as well as the downregulated expression of BCAT2 and ATG7 in the DR model. CONCLUSION: BECN1, HERC2, ATG7, and BCAT2 act as potential biomarkers for DR and might regulate ferritinophagy and the immune microenvironment to influence its development and progression. This research can provide new insights into pathogenesis of DR related to ferritinophagy.
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spelling pubmed-103776612023-07-29 Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy Yu, Fenfen Wang, Congyao Su, Yihua Chen, Tingting Zhu, Wenhui Dong, Xia Ke, Wanyi Cai, Leqi Yang, Shasha Wan, Pengxia Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Diabetic retinopathy (DR) is deemed a microangiopathy and neurodegenerative disorder, which is a primary reason of visual impairment in the world. Ferritinophagy is a critical regulator of ferroptosis and has a vital part in the etiopathogenesis of DR. Nevertheless, its molecular mechanism in DR remains to be expounded. METHODS: The GSE146615 dataset was adopted to identify ferritinophagy-related differentially expressed genes (FRDEGs). The interactions and biological functions of the genes were described by means of functional enrichment analysis (FEA). The enriched gene sets were analyzed utilizing gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Identification of hub genes was performed utilizing protein–protein interaction (PPI) analysis. mRNA–miRNA, mRNA–transcription factors (TF), mRNA–drugs, mRNA–RNA-binding proteins (RBP) interaction networks were constructed. In addition, datasets GSE60436 and GSE94019 were utilized for validation. The diagnostic performance of FRDEGs was assessed by means of receiver-operating characteristic curve monofactor analysis, followed by immune infiltration analysis. Lastly, quantitative real-time polymerase chain reaction (qRT-PCR) was implemented to analyze the validation of genes. RESULTS: In total, the identification of eight FRDEGs was completed utilizing differential expression analysis. FEA mainly implicated the autophagy of mitochondrion, mitochondrion disassembly, autophagosome assembly, and organization pathways. GSEA and GSVA mainly implicated the interferon alpha response, ultraviolet response up, interferon gamma response, apical junction, pical surface, and allograft rejection pathways. BECN1 and HERC2 displayed high diagnostic accuracies in validation sets. Immune infiltration analysis revealed that several immune cells related to ferritinophagy may be play potential roles in DR. Finally, qRT-PCR was utilized to validate the upregulated expression of BECN1 as well as the downregulated expression of BCAT2 and ATG7 in the DR model. CONCLUSION: BECN1, HERC2, ATG7, and BCAT2 act as potential biomarkers for DR and might regulate ferritinophagy and the immune microenvironment to influence its development and progression. This research can provide new insights into pathogenesis of DR related to ferritinophagy. Frontiers Media S.A. 2023-07-14 /pmc/articles/PMC10377661/ /pubmed/37522124 http://dx.doi.org/10.3389/fendo.2023.1177488 Text en Copyright © 2023 Yu, Wang, Su, Chen, Zhu, Dong, Ke, Cai, Yang and Wan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Yu, Fenfen
Wang, Congyao
Su, Yihua
Chen, Tingting
Zhu, Wenhui
Dong, Xia
Ke, Wanyi
Cai, Leqi
Yang, Shasha
Wan, Pengxia
Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
title Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
title_full Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
title_fullStr Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
title_full_unstemmed Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
title_short Comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
title_sort comprehensive analysis of ferritinophagy-related genes and immune infiltration landscape in diabetic retinopathy
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377661/
https://www.ncbi.nlm.nih.gov/pubmed/37522124
http://dx.doi.org/10.3389/fendo.2023.1177488
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