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已发表论文
CD44、ACAN、PLVAP 和 HBEGF 成为糖尿病视网膜病变的潜在生物标志物
Authors Li Q, Zhou X, Wang Y, Peng Y, Liu J , Li X, Shao Y
Received 9 August 2025
Accepted for publication 19 September 2025
Published 3 October 2025 Volume 2025:18 Pages 3731—3750
DOI https://doi.org/10.2147/DMSO.S557119
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Jae Woong Sull
Qingbo Li,1,* Xu Zhou,1,* Ying Wang,2,* Yi Peng,1 Juping Liu,1 Xiaorong Li,1 Yan Shao1,2
1Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, 300384, People’s Republic of China; 2Modern Medical Teaching and Research Section, Department of Tibetan Medicine, University of Tibetan Medicine, Lhasa, Tibet Autonomous Region, 850000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yan Shao, Email sytmueh@163.com
Background: DNA methylation was critically involved in the occurrence and development of diabetic retinopathy (DR), but the clinical diagnostic value and mechanism remains unclear. This study aimed to identify and validate the biomarkers associated with DNA methylation in DR.
Methods: Public databases provided the data used in this study. The biomarkers associated with DNA methylation in proliferative diabetic retinopathy (PDR) and non-proliferative diabetic retinopathy (NPDR) were identified by differential expression analysis, protein-protein interaction network construction, mendelian randomization, and 2 machine learning algorithms, respectively. Gene set enrichment analysis was utilized to determine the functional roles of these biomarkers. The cell-specific expression patterns of biomarkers were analyzed at the single-cell level. Immune infiltration analysis was performed to further study the relationship between biomarkers, and 28 types of immune cell infiltration. The diagnostic power of biomarkers was assessed by the receiver operating curve (ROC) and nomogram.
Results: CD44 was preliminarily identified as a biomarker linked to PDR, whereas ACAN, PLVAP, and HBEGF emerged as biomarkers associated with NPDR. The biomarkers were involved ibosome, lysosome, oxidative phosphorylation, aminoacyl tRNA biosynthesis, P53 signaling pathway, and other pathways. In the retina of diabetic mice, PLVAP and HBEGF were mainly enriched in neutrophils. In the retinal fibroproliferative membranes of PDR patients, CD44 were mainly enriched in monocytes/macrophages. Moreover, CD44 was positively correlated with the remaining differential immune cells except for type 2 T helper cells. Effector memory CD4 T cells showed the strongest positive correlation with ACAN and the largest negative correlation with HBEGF. Finally, the ROC and nomogram validated biomarkers had an excellent diagnostic efficacy.
Conclusion: This study identified 4 genes (CD44, ACAN, PLVAP, and HBEGF) associated with DNA methylation may serve as biomarkers of DR, offering new insights into potential therapeutic strategies for DR.
Keywords: diabetic retinopathy, DNA methylation, transcriptome, single-cell RNA sequencing analysis, Mendelian randomization, machine learning
1Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, 300384, People’s Republic of China; 2Modern Medical Teaching and Research Section, Department of Tibetan Medicine, University of Tibetan Medicine, Lhasa, Tibet Autonomous Region, 850000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yan Shao, Email sytmueh@163.com
Background: DNA methylation was critically involved in the occurrence and development of diabetic retinopathy (DR), but the clinical diagnostic value and mechanism remains unclear. This study aimed to identify and validate the biomarkers associated with DNA methylation in DR.
Methods: Public databases provided the data used in this study. The biomarkers associated with DNA methylation in proliferative diabetic retinopathy (PDR) and non-proliferative diabetic retinopathy (NPDR) were identified by differential expression analysis, protein-protein interaction network construction, mendelian randomization, and 2 machine learning algorithms, respectively. Gene set enrichment analysis was utilized to determine the functional roles of these biomarkers. The cell-specific expression patterns of biomarkers were analyzed at the single-cell level. Immune infiltration analysis was performed to further study the relationship between biomarkers, and 28 types of immune cell infiltration. The diagnostic power of biomarkers was assessed by the receiver operating curve (ROC) and nomogram.
Results: CD44 was preliminarily identified as a biomarker linked to PDR, whereas ACAN, PLVAP, and HBEGF emerged as biomarkers associated with NPDR. The biomarkers were involved ibosome, lysosome, oxidative phosphorylation, aminoacyl tRNA biosynthesis, P53 signaling pathway, and other pathways. In the retina of diabetic mice, PLVAP and HBEGF were mainly enriched in neutrophils. In the retinal fibroproliferative membranes of PDR patients, CD44 were mainly enriched in monocytes/macrophages. Moreover, CD44 was positively correlated with the remaining differential immune cells except for type 2 T helper cells. Effector memory CD4 T cells showed the strongest positive correlation with ACAN and the largest negative correlation with HBEGF. Finally, the ROC and nomogram validated biomarkers had an excellent diagnostic efficacy.
Conclusion: This study identified 4 genes (CD44, ACAN, PLVAP, and HBEGF) associated with DNA methylation may serve as biomarkers of DR, offering new insights into potential therapeutic strategies for DR.
Keywords: diabetic retinopathy, DNA methylation, transcriptome, single-cell RNA sequencing analysis, Mendelian randomization, machine learning