Identification of angiogenesis-related biomarkers in diabetic retinopathy based on transcriptomics and exploration of their mechanisms affecting dia-betic retinopathy
10.13389/j.cnki.rao.2024.0183
- VernacularTitle:基于转录组学鉴定糖尿病视网膜病变中血管生成相关的生物标志物及其影响糖尿病视网膜病变的机制
- Author:
Fengjuan YUE
1
;
Rong FENG
;
Hui ZHANG
;
Xiaodong LI
Author Information
1. 520002 贵州省贵阳市,贵州省人民医院健康体检中心
- Keywords:
diabetic retinopathy;
angiogenesis;
machine learning;
biomarker;
immune cell infiltration
- From:
Recent Advances in Ophthalmology
2024;44(12):972-980
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the biomarkers associated with angiogenesis-related genes(ARGs)in diabetic reti-nopathy(DR)based on transcriptomics.Methods The differentially expressed genes(DEGs)between the DR patients(DR group)and the healthy population(control group)were identified through differential expression analysis.Weighted gene co-expression network analysis(WGCNA)was used to obtain the key module genes most significantly related to ARGs.Candidate genes were determined by taking the intersection of DEGs and these key module genes obtained.Then,three machine learning algorithms were used to screen potential DR biomarkers from these candidate genes,a nomogram model used for DR diagnosis was constructed based on these biomarkers,and the accuracy of nomogram model prediction was further verified by drawing and analyzing receiver operating characteristic(ROC)curves,calibration curves and deci-sion curve analysis curves.Furthermore,the immune cell infiltration in the DR group and the control group was compared,and the potential biomarker-targeted chemotherapeutics for DR treatment was predicted.Results Based on bioinformat-ics analysis,a total of 153 DEGs and 969 key module genes were identified.Based on the intersection of the above two re-sults,19 candidate genes were determined.Three machine learning algorithms identified four biomarkers[serum amyloid A2(SAA2),endoplasmic reticulum protein 27(ERP27),glutathione peroxidase 8(GPX8),and RAB protein family mem-ber RAB7B)],and the ROC curves confirmed that these four biomarkers have the ability to effectively distinguish DR pa-tients from healthy people.The nomogram model constructed based on these four biomarkers could effectively predict the probability of DR.Immune cell infiltration showed that these four biomarkers were significantly correlated with 28 immune cells.Drug prediction found that dexamethasone,glutathione disulfide and glutathione,which target SAA2 and GPX8,were potential drugs for DR treatment.Conclusion A reliable model for DR diagnosis can be established based on SAA2,ERP27,GPX8 and RAB7B,which are mainly involved in the complement and coagulation cascade,regulation of immune cell infiltration,and other key biological processes.
