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Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking

BACKGROUND: Diabetic retinopathy (DR), a neurovascular disease, is a leading cause of visual loss worldwide and severely affects quality of life. Several studies have shown that ferroptosis plays an important role in the pathogenesis of DR; however, its molecule mechanism remains incompletely elucid...

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Autores principales: Liu, Jingying, Li, Xiaozhuang, Cheng, Yanhua, Liu, Kangcheng, Zou, Hua, You, Zhipeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9729554/
https://www.ncbi.nlm.nih.gov/pubmed/36506045
http://dx.doi.org/10.3389/fendo.2022.988506
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author Liu, Jingying
Li, Xiaozhuang
Cheng, Yanhua
Liu, Kangcheng
Zou, Hua
You, Zhipeng
author_facet Liu, Jingying
Li, Xiaozhuang
Cheng, Yanhua
Liu, Kangcheng
Zou, Hua
You, Zhipeng
author_sort Liu, Jingying
collection PubMed
description BACKGROUND: Diabetic retinopathy (DR), a neurovascular disease, is a leading cause of visual loss worldwide and severely affects quality of life. Several studies have shown that ferroptosis plays an important role in the pathogenesis of DR; however, its molecule mechanism remains incompletely elucidated. Hence, this study aimed to investigate the pathogenesis of ferroptosis and explore potential ferroptosis-related gene biomarkers and a pharmacological compound for treating DR. METHODS: Ferroptosis-related differentially expressed genes (DEGs) were identified in the GSE102485 dataset. Functional enrichment analyses were then performed and a protein-protein interaction (PPI) network was constructed to screen candidates of ferroptosis-related hub genes (FRHGs). FRHGs were further screened based on least absolute shrinkage and selection operator (LASSO) regression and random forest algorithms, and were then validated with the GSE60436 dataset and previous studies. A receiver operating characteristic (ROC) curve monofactor analysis was conducted to evaluate the diagnostic performance of the FRHGs, and immune infiltration analysis was performed. Moreover, the pharmacological compound targeting the FRHGs were verified by molecular docking. Finally, the FRHGs were validated using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. RESULTS: The 40 ferroptosis-related DEGs were extracted, and functional enrichment analyses mainly implicated apoptotic signaling, response to oxidative stress, ferroptosis, and lipid and atherosclerosis pathways. By integrating the PPI, LASSO regression, and random forest analyses to screen the FRHGs, and through validation, we identified five FRHGs that performed well in the diagnosis (CAV1, CD44, NOX4, TLR4, and TP53). Immune infiltration analysis revealed that immune microenvironment changes in DR patients may be related to these five FRHGs. Molecular docking also showed that glutathione strongly bound the CAV1 and TLR4 proteins. Finally, the upregulated expression of FRHGs (CD44, NOX4, TLR4, and TP53) was validated by qRT-PCR analysis in human retinal capillary endothelial cells cultured under high-glucose environment. CONCLUSIONS: CAV1, CD44, NOX4, TLR4, and TP53 are potential biomarkers for DR and may be involved in its occurrence and progression by regulating ferroptosis and the immune microenvironment. Further, glutathione exhibits potential therapeutic efficacy on DR by targeting ferroptosis. Our study provides new insights into the ferroptosis-related pathogenesis of DR, as well as its diagnosis and treatment.
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spelling pubmed-97295542022-12-09 Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking Liu, Jingying Li, Xiaozhuang Cheng, Yanhua Liu, Kangcheng Zou, Hua You, Zhipeng Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Diabetic retinopathy (DR), a neurovascular disease, is a leading cause of visual loss worldwide and severely affects quality of life. Several studies have shown that ferroptosis plays an important role in the pathogenesis of DR; however, its molecule mechanism remains incompletely elucidated. Hence, this study aimed to investigate the pathogenesis of ferroptosis and explore potential ferroptosis-related gene biomarkers and a pharmacological compound for treating DR. METHODS: Ferroptosis-related differentially expressed genes (DEGs) were identified in the GSE102485 dataset. Functional enrichment analyses were then performed and a protein-protein interaction (PPI) network was constructed to screen candidates of ferroptosis-related hub genes (FRHGs). FRHGs were further screened based on least absolute shrinkage and selection operator (LASSO) regression and random forest algorithms, and were then validated with the GSE60436 dataset and previous studies. A receiver operating characteristic (ROC) curve monofactor analysis was conducted to evaluate the diagnostic performance of the FRHGs, and immune infiltration analysis was performed. Moreover, the pharmacological compound targeting the FRHGs were verified by molecular docking. Finally, the FRHGs were validated using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. RESULTS: The 40 ferroptosis-related DEGs were extracted, and functional enrichment analyses mainly implicated apoptotic signaling, response to oxidative stress, ferroptosis, and lipid and atherosclerosis pathways. By integrating the PPI, LASSO regression, and random forest analyses to screen the FRHGs, and through validation, we identified five FRHGs that performed well in the diagnosis (CAV1, CD44, NOX4, TLR4, and TP53). Immune infiltration analysis revealed that immune microenvironment changes in DR patients may be related to these five FRHGs. Molecular docking also showed that glutathione strongly bound the CAV1 and TLR4 proteins. Finally, the upregulated expression of FRHGs (CD44, NOX4, TLR4, and TP53) was validated by qRT-PCR analysis in human retinal capillary endothelial cells cultured under high-glucose environment. CONCLUSIONS: CAV1, CD44, NOX4, TLR4, and TP53 are potential biomarkers for DR and may be involved in its occurrence and progression by regulating ferroptosis and the immune microenvironment. Further, glutathione exhibits potential therapeutic efficacy on DR by targeting ferroptosis. Our study provides new insights into the ferroptosis-related pathogenesis of DR, as well as its diagnosis and treatment. Frontiers Media S.A. 2022-11-24 /pmc/articles/PMC9729554/ /pubmed/36506045 http://dx.doi.org/10.3389/fendo.2022.988506 Text en Copyright © 2022 Liu, Li, Cheng, Liu, Zou and You 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
Liu, Jingying
Li, Xiaozhuang
Cheng, Yanhua
Liu, Kangcheng
Zou, Hua
You, Zhipeng
Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
title Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
title_full Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
title_fullStr Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
title_full_unstemmed Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
title_short Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
title_sort identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9729554/
https://www.ncbi.nlm.nih.gov/pubmed/36506045
http://dx.doi.org/10.3389/fendo.2022.988506
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