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Peng H, Li H, Ma B, Sun X, Chen B. DJ-1 regulates mitochondrial function and promotes retinal ganglion cell survival under high glucose-induced oxidative stress. Front Pharmacol 2024; 15:1455439. [PMID: 39323632 PMCID: PMC11422208 DOI: 10.3389/fphar.2024.1455439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 09/02/2024] [Indexed: 09/27/2024] Open
Abstract
Purpose This study aimed to investigate the antioxidative and neuroprotective effects of DJ-1 in mitigating retinal ganglion cell (RGC) damage induced by high glucose (HG). Methods A diabetic mouse model and an HG-induced R28 cell model were employed for loss- and gain-of-function experiments. The expression levels of apoptosis and oxidative stress-related factors, including Bax, Bcl-2, caspase3, Catalase, MnSOD, GCLC, Cyto c, and GPx-1/2, were assessed in both animal and cell models using Western blotting. Retinal structure and function were evaluated through HE staining, electroretinogram, and RGC counting. Mitochondrial function and apoptosis were determined using JC-1 and TUNEL staining, and reactive oxygen species (ROS) measurement. Results In the mouse model, hyperglycemia resulted in reduced retinal DJ-1 expression, retinal structural and functional damage, disrupted redox protein profiles, and mitochondrial dysfunction. Elevated glucose levels induced mitochondrial impairment, ROS generation, abnormal protein expression, and apoptosis in R28 cells. Augmenting DJ-1 expression demonstrated a restoration of mitochondrial homeostasis and alleviated diabetes-induced morphological and functional impairments both in vivo and in vitro. Conclusion This study provides novel insights into the regulatory role of DJ-1 in mitochondrial dynamics, suggesting a potential avenue for enhancing RGC survival in diabetic retinopathy.
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Affiliation(s)
- Hanhan Peng
- Department of Ophthalmology, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Clinical Research Centre of Ophthalmic Disease, Changsha, China
| | - Haoyu Li
- Department of Ophthalmology, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Clinical Research Centre of Ophthalmic Disease, Changsha, China
| | - Benteng Ma
- Department of Ophthalmology, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Clinical Research Centre of Ophthalmic Disease, Changsha, China
| | - Xinyue Sun
- Department of Ophthalmology, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Clinical Research Centre of Ophthalmic Disease, Changsha, China
| | - Baihua Chen
- Department of Ophthalmology, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Clinical Research Centre of Ophthalmic Disease, Changsha, China
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Cheng B, Wu A, Zhou X. Association Between VEGF-460C/T Gene Polymorphism and Risk of Diabetic Retinopathy in Type 2 Diabetes Mellitus: A Meta-Analysis. Horm Metab Res 2024; 56:214-222. [PMID: 38052425 DOI: 10.1055/a-2223-2790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
The aim of the study was to investigate the relationship between VEGF-460C/T polymorphism and susceptibility to diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) by meta-analysis. A comprehensive search was conducted across six databases until September 2023 to identify studies examining the association between VEGF-460C/T polymorphism and susceptibility to DR. Data process was performed by Stata 15.0 software. Eight studies were included, involving 1463 patients with DR. In the overall analysis, the difference was statistically significant only in the homozygous model (CC vs. TT: OR=1.86, p=0.048). A subgroup analysis of 6 papers with genotype frequency satisfying HWE in the control group indicated significant differences among the allele (C vs. T: OR=1.34, p=0.037), recessive (CC vs. CT+TT: OR=1.96, p=0.022) and homozygous (CC vs. TT: OR=2.28, p=0.015) models. However, in the dominant and heterozygous models, the difference was not statistically significant. The sensitivity of the HWE-based subgroup analysis showed that the conclusions in other gene models except the heterozygote model were not robust. This meta-analysis indicated that VEGF-460C/T gene polymorphism is associated with susceptibility to DR in T2DM. Allele C and genotype CC at the VEGF-460C/T locus are associated with an increased risk of DR in T2DM. However, considering that the results are not robust, more trials involving more rigorous design are needed to verify the findings of this review in the future.
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Affiliation(s)
- Bo Cheng
- Department of Ophthalmology, The People's Hospital of Fenghua, Ningbo, China
| | - Aimin Wu
- Department of Ophthalmology, The People's Hospital of Fenghua, Ningbo, China
| | - Xuewei Zhou
- Department of Ophthalmology, The People's Hospital of Fenghua, Ningbo, China
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3
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Wang Z, Zhang N, Lin P, Xing Y, Yang N. Recent advances in the treatment and delivery system of diabetic retinopathy. Front Endocrinol (Lausanne) 2024; 15:1347864. [PMID: 38425757 PMCID: PMC10902204 DOI: 10.3389/fendo.2024.1347864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
Diabetic retinopathy (DR) is a highly tissue-specific neurovascular complication of type 1 and type 2 diabetes mellitus and is among the leading causes of blindness worldwide. Pathophysiological changes in DR encompass neurodegeneration, inflammation, and oxidative stress. Current treatments for DR, including anti-vascular endothelial growth factor, steroids, laser photocoagulation, and vitrectomy have limitations and adverse reactions, necessitating the exploration of novel treatment strategies. This review aims to summarize the current pathophysiology, therapeutic approaches, and available drug-delivery methods for treating DR, and discuss their respective development potentials. Recent research indicates the efficacy of novel receptor inhibitors and agonists, such as aldose reductase inhibitors, angiotensin-converting enzyme inhibitors, peroxisome proliferator-activated receptor alpha agonists, and novel drugs in delaying DR. Furthermore, with continuous advancements in nanotechnology, a new form of drug delivery has been developed that can address certain limitations of clinical drug therapy, such as low solubility and poor penetration. This review serves as a theoretical foundation for future research on DR treatment. While highlighting promising therapeutic targets, it underscores the need for continuous exploration to enhance our understanding of DR pathogenesis. The limitations of current treatments and the potential for future advancements emphasize the importance of ongoing research in this field.
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Affiliation(s)
| | | | | | - Yiqiao Xing
- Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Ning Yang
- Department of Ophthalmology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
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4
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Zhu J, Huang J, Sun Y, Xu W, Qian H. Emerging role of extracellular vesicles in diabetic retinopathy. Theranostics 2024; 14:1631-1646. [PMID: 38389842 PMCID: PMC10879872 DOI: 10.7150/thno.92463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
Diabetic retinopathy (DR), a complex complication of diabetes mellitus (DM), is a leading cause of adult blindness. Hyperglycemia triggers DR, resulting in microvascular damage, glial apoptosis, and neuronal degeneration. Inflammation and oxidative stress play crucial roles during this process. Current clinical treatments for DR primarily target the advanced retinal disorder but offer limited benefits with inevitable side effects. Extracellular vesicles (EVs) exhibit unique morphological features, contents, and biological properties and can be found in cell culture supernatants, various body fluids, and tissues. In DR, EVs with specific cargo composition would induce the reaction of receptor cell once internalized, mediating cellular communication and disease progression. Increasing evidence indicates that monitoring changes in EV quantity and content in DR can aid in disease diagnosis and prognosis. Furthermore, extensive research is investigating the potential of these nanoparticles as effective therapeutic agents in preclinical models of DR. This review explores the current understanding of the pathological effects of EVs in DR development, discusses their potential as biomarkers and therapeutic strategies, and paves the way for further research and therapeutic advancements.
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Affiliation(s)
- Junyan Zhu
- Department of Gynecology and obstetrics, The Affiliated Yixing Hospital of Jiangsu University, 214200, China
- Jiangsu Province Key Laboratory of Medical Science and Laboratory Medicine, Department of Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Jin Huang
- Department of Gynecology and obstetrics, The Affiliated Yixing Hospital of Jiangsu University, 214200, China
| | - Yaoxiang Sun
- Department of clinical laboratory, The Affiliated Yixing Hospital of Jiangsu University, Yixing, 214200, China
| | - Wenrong Xu
- Department of Gynecology and obstetrics, The Affiliated Yixing Hospital of Jiangsu University, 214200, China
- Jiangsu Province Key Laboratory of Medical Science and Laboratory Medicine, Department of Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu 212013, China
| | - Hui Qian
- Jiangsu Province Key Laboratory of Medical Science and Laboratory Medicine, Department of Laboratory Medicine, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu 212013, China
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5
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Dai L, Sheng B, Chen T, Wu Q, Liu R, Cai C, Wu L, Yang D, Hamzah H, Liu Y, Wang X, Guan Z, Yu S, Li T, Tang Z, Ran A, Che H, Chen H, Zheng Y, Shu J, Huang S, Wu C, Lin S, Liu D, Li J, Wang Z, Meng Z, Shen J, Hou X, Deng C, Ruan L, Lu F, Chee M, Quek TC, Srinivasan R, Raman R, Sun X, Wang YX, Wu J, Jin H, Dai R, Shen D, Yang X, Guo M, Zhang C, Cheung CY, Tan GSW, Tham YC, Cheng CY, Li H, Wong TY, Jia W. A deep learning system for predicting time to progression of diabetic retinopathy. Nat Med 2024; 30:584-594. [PMID: 38177850 PMCID: PMC10878973 DOI: 10.1038/s41591-023-02702-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 11/10/2023] [Indexed: 01/06/2024]
Abstract
Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system. Subsequently, we trained and validated the system with a multiethnic dataset comprising 118,868 images from 29,868 participants with diabetes. For predicting time to DR progression, the system achieved concordance indexes of 0.754-0.846 and integrated Brier scores of 0.153-0.241 for all times up to 5 years. Furthermore, we validated the system in real-world cohorts of participants with diabetes. The integration with clinical workflow could potentially extend the mean screening interval from 12 months to 31.97 months, and the percentage of participants recommended to be screened at 1-5 years was 30.62%, 20.00%, 19.63%, 11.85% and 17.89%, respectively, while delayed detection of progression to vision-threatening DR was 0.18%. Altogether, the DeepDR Plus system could predict individualized risk and time to DR progression over 5 years, potentially allowing personalized screening intervals.
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Grants
- the National Key Research and Development Program of China (2022YFA1004804), the Shanghai Municipal Key Clinical Specialty, Shanghai Research Center for Endocrine and Metabolic Diseases (2022ZZ01002), and the Chinese Academy of Engineering (2022-XY-08)
- the General Program of NSFC (62272298), the National Key Research and Development Program of China (2022YFC2407000), the Interdisciplinary Program of Shanghai Jiao Tong University (YG2023LC11 and YG2022ZD007), National Natural Science Foundation of China (62272298 and 62077037), the College-level Project Fund of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital (ynlc201909), and the Medical-industrial Cross-fund of Shanghai Jiao Tong University (YG2022QN089)
- the Clinical Special Program of Shanghai Municipal Health Commission (20224044) and Three-year action plan to strengthen the construction of public health system in Shanghai (GWVI-11.1-28)
- the National Natural Science Foundation of China (82100879)
- the National Key Research and Development Program of China (2022YFA1004804), Excellent Young Scientists Fund of NSFC (82022012), General Fund of NSFC (81870598), Innovative research team of high-level local universities in Shanghai (SHSMU-ZDCX20212700)
- the National Key R & D Program of China (2022YFC2502800) and National Natural Science Fund of China (8238810007)
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Affiliation(s)
- Ling Dai
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Bin Sheng
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China.
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
| | - Tingli Chen
- Department of Ophthalmology, Huadong Sanatorium, Wuxi, China
| | - Qiang Wu
- Department of Ophthalmology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruhan Liu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chun Cai
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Liang Wu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Dawei Yang
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Haslina Hamzah
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Yuexing Liu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Xiangning Wang
- Department of Ophthalmology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhouyu Guan
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Shujie Yu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Tingyao Li
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ziqi Tang
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Anran Ran
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Haoxuan Che
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Hao Chen
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Yingfeng Zheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Jia Shu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Shan Huang
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chan Wu
- Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Shiqun Lin
- Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Dan Liu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Jiajia Li
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zheyuan Wang
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ziyao Meng
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jie Shen
- Medical Records and Statistics Office, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuhong Hou
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Chenxin Deng
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Ruan
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Lu
- National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Miaoli Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ten Cheer Quek
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ramyaa Srinivasan
- Shri Bhagwan Mahavir Vitreoretinal Services, Medical Research Foundation, Sankara Nethralaya, Chennai, India
| | - Rajiv Raman
- Shri Bhagwan Mahavir Vitreoretinal Services, Medical Research Foundation, Sankara Nethralaya, Chennai, India
| | - Xiaodong Sun
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Laboratory, Beijing, China
| | - Jiarui Wu
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
- Center for Excellence in Molecular Science, Chinese Academy of Sciences, Shanghai, China
| | - Hai Jin
- National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Rongping Dai
- Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Dinggang Shen
- School of Biomedical Engineering, Shanghai Tech University, Shanghai, China
- Shanghai United Imaging Intelligence, Shanghai, China
- Shanghai Clinical Research and Trial Center, Shanghai, China
| | - Xiaokang Yang
- MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Minyi Guo
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Cuntai Zhang
- Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Carol Y Cheung
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Gavin Siew Wei Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Centre for Innovation and Precision Eye Health; and Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
- Centre for Innovation and Precision Eye Health; and Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Huating Li
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China.
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
- Tsinghua Medicine, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China.
| | - Weiping Jia
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China.
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6
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Xu X, Wang M, Zhang S, Wang J, Li X, Ma X, Luo Y, Sun X. Compound Danshen dripping pills prevent early diabetic retinopathy: roles of vascular protection and neuroprotection. Front Pharmacol 2024; 15:1294620. [PMID: 38318138 PMCID: PMC10839082 DOI: 10.3389/fphar.2024.1294620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 01/10/2024] [Indexed: 02/07/2024] Open
Abstract
Introduction: Diabetic retinopathy (DR) represents a major cause of adult blindness, and early discovery has led to significant increase in the number of patients with DR. The drugs currently used for treatment, such as ranibizumab, mainly focus on the middle and late periods of DR, and thus do not meet the clinical need. Here, the potential mechanisms by which compound Danshen Dripping Pills (CDDP) might protect against early DR were investigated. Methods: Db/db mice were used to establish a DR model. The initial weights and HbA1c levels of the mice were monitored, and retinal pathology was assessed by hematoxylin-eosin (HE) staining. The vascular permeability of the retina and thickness of each retinal layer were measured, and electroretinogram were performed together with fundus fluorescein angiography and optical coherence tomography. The levels of inflammatory factors were examined in retinal tissue, as well as those of intercellular adhesion molecule 1 (ICAM-1), IL-6, and monocyte chemoattractant protein 1 (MCP-1) in the serum using ELISA. Immunohistochemistry was used to evaluate levels of vascular endothelial growth factor (VEGF), B-cell lymphoma 2 (Bcl-2), and Bclassociated X protein (Bax). Retinal cell injury and apoptosis were examined by TdT-mediated dUTP Nick End Labeling (TUNEL) assays. Results: The data showed that CDDP significantly improved cellular disarrangement. Imaging data indicated that CDDP could reduce vascular permeability and the amplitude of oscillatory potentials (OPs), and restore the thickness of the ganglion cell layer. Moreover, CDDP reduced the expression levels of inflammatory factors in both the retina and serum. Conclusion: These findings strongly suggest that CDDP prevents early DR through vascular and neuroprotection.
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Affiliation(s)
- Xiaoyu Xu
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Diabetes Research Center, Chinese Academy of Medical Sciences, Beijing, China
- Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
| | - Mengchen Wang
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Diabetes Research Center, Chinese Academy of Medical Sciences, Beijing, China
- Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
| | - Shuxia Zhang
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Diabetes Research Center, Chinese Academy of Medical Sciences, Beijing, China
- Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
| | - Jing Wang
- State Key Laboratory of Core Technology in Innovative Chinese Medicine, Tasly Pharmaceutical Group Co., Ltd., Tianjin, China
| | - Xinxin Li
- State Key Laboratory of Core Technology in Innovative Chinese Medicine, Tasly Pharmaceutical Group Co., Ltd., Tianjin, China
| | - Xiaohui Ma
- State Key Laboratory of Core Technology in Innovative Chinese Medicine, Tasly Pharmaceutical Group Co., Ltd., Tianjin, China
| | - Yun Luo
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Diabetes Research Center, Chinese Academy of Medical Sciences, Beijing, China
- Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
| | - Xiaobo Sun
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Diabetes Research Center, Chinese Academy of Medical Sciences, Beijing, China
- Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
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7
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Alharbi KS. GAS5: A pivotal lncRNA in diabetes mellitus pathogenesis and management. Pathol Res Pract 2024; 253:154955. [PMID: 38016351 DOI: 10.1016/j.prp.2023.154955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 11/30/2023]
Abstract
The long non-coding RNA (lncRNA), GAS5, has garnered significant attention recently for its multifaceted involvement in cellular processes, particularly within the context of diabetes. This comprehensive review delves into the intricate molecular interactions associated with GAS5 and their profound implications for understanding, diagnosing, and effectively managing diabetes mellitus. The article begins by highlighting the global prevalence of diabetes and the urgent need for innovative insights into its underlying mechanisms and therapeutic approaches. It introduces GAS5 as a crucial regulator of gene expression, with emerging significance in the context of diabetes-related processes. The core of this review unravels the regulatory network of GAS5 in diabetes, elucidating its impact on various aspects of the disease. It explores how GAS5 influences insulin signaling pathways, glucose metabolism, and the function of β-cells, shedding light on its role in hyperglycemia and insulin resistance. Moreover, the article underscores the clinical relevance of GAS5's interactions by discussing their associations with different diabetes subtypes, predictive value, and potential applications as both diagnostic tools and therapeutic targets. It provides insights into ongoing research endeavours aimed at harnessing the potential of GAS5 for innovative disease management strategies, including the development of RNA-based therapeutics. Concluding with a forward-looking perspective, the abstract highlights the broader implications of GAS5 in the field of diabetes, such as its connection to diabetic complications and its potential for personalized approaches in disease management.
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Affiliation(s)
- Khalid Saad Alharbi
- Department of Pharmacology and Toxicology, Unaizah College of Pharmacy, Qassim University, Qassim 51452, Saudi Arabia.
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8
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Olivier E, Rat P. Role of Oxysterols in Ocular Degeneration Mechanisms and Involvement of P2X7 Receptor. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1440:277-292. [PMID: 38036885 DOI: 10.1007/978-3-031-43883-7_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
Ocular degeneration, including cataracts, glaucoma, macular degeneration, and diabetic retinopathy, is a major public health challenge, as it affects the quality of life of millions of people worldwide and, in its advanced stages, leads to blindness. Ocular degeneration, although it can affect different parts of the eye, shares common characteristics such as oxysterols and the P2X7 receptor. Indeed, oxysterols, which are cholesterol derivatives, are associated with ocular degeneration pathogenesis and trigger inflammation and cell death pathways. Activation of the P2X7 receptor is also linked to ocular degeneration and triggers the same pathways. In age-related macular degeneration, these two key players have been associated, but further studies are needed to extrapolate this interrelationship to other ocular degenerations.
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Affiliation(s)
| | - Patrice Rat
- Université Paris Cité, CNRS, CiTCoM, Paris, France
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Bao T, Zhang X, Xie W, Wang Y, Li X, Tang C, Yang Y, Sun J, Gao J, Yu T, Zhao L, Tong X. Natural compounds efficacy in complicated diabetes: A new twist impacting ferroptosis. Biomed Pharmacother 2023; 168:115544. [PMID: 37820566 DOI: 10.1016/j.biopha.2023.115544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 09/13/2023] [Accepted: 09/18/2023] [Indexed: 10/13/2023] Open
Abstract
Ferroptosis, as a way of cell death, participates in the body's normal physiological and pathological regulation. Recent studies have shown that ferroptosis may damage glucose-stimulated islets β Insulin secretion and programmed cell death of T2DM target organs are involved in the pathogenesis of T2DM and its complications. Targeting suppression of ferroptosis with specific inhibitors may provide new therapeutic opportunities for previously untreated T2DM and its target organs. Current studies suggest that natural bioactive compounds, which are abundantly available in drugs, foods, and medicinal plants for the treatment of T2DM and its target organs, have recently received significant attention for their various biological activities and minimal toxicity, and that many natural compounds appear to have a significant role in the regulation of ferroptosis in T2DM and its target organs. Therefore, this review summarized the potential treatment strategies of natural compounds as ferroptosis inhibitors to treat T2DM and its complications, providing potential lead compounds and natural phytochemical molecular nuclei for future drug research and development to intervene in ferroptosis in T2DM.
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Affiliation(s)
- Tingting Bao
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China; Graduate school, Beijing University of Traditional Chinese Medicine, Beijing 100029, China
| | - Xiangyuan Zhang
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China; Graduate school, Beijing University of Traditional Chinese Medicine, Beijing 100029, China
| | - Weinan Xie
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China; Graduate school, Beijing University of Traditional Chinese Medicine, Beijing 100029, China
| | - Ying Wang
- Changchun University of Chinese Medicine, No. 1035, Boshuo Road, Jingyue National High-tech Industrial Development Zone, Changchun 130117, China
| | - Xiuyang Li
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China
| | - Cheng Tang
- Changchun University of Chinese Medicine, No. 1035, Boshuo Road, Jingyue National High-tech Industrial Development Zone, Changchun 130117, China
| | - Yingying Yang
- National Center for Integrated Traditional and Western Medicine, China-Japan Friendship Hospital, Beijing 100029, China
| | - Jun Sun
- Affiliated Hospital of Changchun University of Traditional Chinese Medicine, No. 1478, Gongnong Road, Chaoyang District, Changchun 130021, China
| | - Jiaqi Gao
- School of Qi-Huang Chinese Medicine, Beijing University of Chinese Medicine, No. 11, North 3rd Ring East Roa, Chaoyang Distric, Beijing 10010, China
| | - Tongyue Yu
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China
| | - Linhua Zhao
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China.
| | - Xiaolin Tong
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, No.5 BeiXianGe Street, Xicheng District, Beijing 100053, China.
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Gong D, Fang L, Cai Y, Chong I, Guo J, Yan Z, Shen X, Yang W, Wang J. Development and evaluation of a risk prediction model for diabetes mellitus type 2 patients with vision-threatening diabetic retinopathy. Front Endocrinol (Lausanne) 2023; 14:1244601. [PMID: 37693352 PMCID: PMC10484608 DOI: 10.3389/fendo.2023.1244601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 08/02/2023] [Indexed: 09/12/2023] Open
Abstract
Objective This study aims to develop and evaluate a non-imaging clinical data-based nomogram for predicting the risk of vision-threatening diabetic retinopathy (VTDR) in diabetes mellitus type 2 (T2DM) patients. Methods Based on the baseline data of the Guangdong Shaoguan Diabetes Cohort Study conducted by the Zhongshan Ophthalmic Center (ZOC) in 2019, 2294 complete data of T2DM patients were randomly divided into a training set (n=1605) and a testing set (n=689). Independent risk factors were selected through univariate and multivariate logistic regression analysis on the training dataset, and a nomogram was constructed for predicting the risk of VTDR in T2DM patients. The model was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) in the training and testing datasets to assess discrimination, and Hosmer-Lemeshow test and calibration curves to assess calibration. Results The results of the multivariate logistic regression analysis showed that Age (OR = 0.954, 95% CI: 0.940-0.969, p = 0.000), BMI (OR = 0.942, 95% CI: 0.902-0.984, p = 0.007), systolic blood pressure (SBP) (OR =1.014, 95% CI: 1.007-1.022, p = 0.000), diabetes duration (10-15y: OR =3.126, 95% CI: 2.087-4.682, p = 0.000; >15y: OR =3.750, 95% CI: 2.362-5.954, p = 0.000), and glycated hemoglobin (HbA1C) (OR = 1.325, 95% CI: 1.221-1.438, p = 0.000) were independent risk factors for T2DM patients with VTDR. A nomogram was constructed using these variables. The model discrimination results showed an AUC of 0.7193 for the training set and 0.6897 for the testing set. The Hosmer-Lemeshow test results showed a high consistency between the predicted and observed probabilities for both the training set (Chi-square=2.2029, P=0.9742) and the testing set (Chi-square=7.6628, P=0.4671). Conclusion The introduction of Age, BMI, SBP, Duration, and HbA1C as variables helps to stratify the risk of T2DM patients with VTDR.
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Affiliation(s)
- Di Gong
- Shenzhen Eye Hospital, Jinan University, Shenzhen, Guangdong, China
- The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China
| | - Lyujie Fang
- The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China
| | - Yixian Cai
- The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China
| | - Ieng Chong
- Macau University Hospital, Macao, Macao SAR, China
| | - Junhong Guo
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China
| | - Zhichao Yan
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China
| | - Xiaoli Shen
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China
| | - Weihua Yang
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China
| | - Jiantao Wang
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China
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11
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Oshitari T. Neurovascular Cell Death and Therapeutic Strategies for Diabetic Retinopathy. Int J Mol Sci 2023; 24:12919. [PMID: 37629100 PMCID: PMC10454228 DOI: 10.3390/ijms241612919] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023] Open
Abstract
Diabetic retinopathy (DR) is a major complication of diabetes and a leading cause of blindness worldwide. DR was recently defined as a neurovascular disease associated with tissue-specific neurovascular impairment of the retina in patients with diabetes. Neurovascular cell death is the main cause of neurovascular impairment in DR. Thus, neurovascular cell protection is a potential therapy for preventing the progression of DR. Growing evidence indicates that a variety of cell death pathways, such as apoptosis, necroptosis, ferroptosis, and pyroptosis, are associated with neurovascular cell death in DR. These forms of regulated cell death may serve as therapeutic targets for ameliorating the pathogenesis of DR. This review focuses on these cell death mechanisms and describes potential therapies for the treatment of DR that protect against neurovascular cell death.
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Affiliation(s)
- Toshiyuki Oshitari
- Department of Ophthalmology and Visual Science, Chiba University Graduate School of Medicine, Inohana 1-8-1, Chuo-ku, Chiba 260-8670, Japan; ; Tel.: +81-43-226-2124; Fax: +81-43-224-4162
- Department of Ophthalmology, School of Medicine, International University of Health and Welfare, 4-3 Kozunomori, Narita 286-8686, Japan
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12
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Bikbova G, Oshitari T, Bikbov M. Diabetic Neuropathy of the Retina and Inflammation: Perspectives. Int J Mol Sci 2023; 24:ijms24119166. [PMID: 37298118 DOI: 10.3390/ijms24119166] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/21/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023] Open
Abstract
A clear connection exists between diabetes and atherosclerotic cardiovascular disease. Consequently, therapeutic approaches that target both diseases are needed. Clinical trials are currently underway to explore the roles of obesity, adipose tissue, gut microbiota, and pancreatic beta cell function in diabetes. Inflammation plays a key role in diabetes pathophysiology and associated metabolic disorders; thus, interest has increased in targeting inflammation to prevent and control diabetes. Diabetic retinopathy is known as a neurodegenerative and vascular disease that occurs after some years of poorly controlled diabetes. However, increasing evidence points to inflammation as a key figure in diabetes-associated retinal complications. Interconnected molecular pathways, such as oxidative stress, and the formation of advanced glycation end-products, are known to contribute to the inflammatory response. This review describes the possible mechanisms of the metabolic changes in diabetes that involve inflammatory pathways.
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Affiliation(s)
- Guzel Bikbova
- Department of Ophthalmology and Visual Science, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba 260-8670, Japan
- Ufa Eye Research Institute, Pushkin Street 90, Ufa 450077, Russia
| | - Toshiyuki Oshitari
- Department of Ophthalmology and Visual Science, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba 260-8670, Japan
- Department of Ophthalmology, School of Medicine, International University of Health and Welfare, 4-3 Kozunomori, Narita 286-8686, Japan
| | - Mukharram Bikbov
- Ufa Eye Research Institute, Pushkin Street 90, Ufa 450077, Russia
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13
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Zheng X, Wan J, Tan G. The mechanisms of NLRP3 inflammasome/pyroptosis activation and their role in diabetic retinopathy. Front Immunol 2023; 14:1151185. [PMID: 37180116 PMCID: PMC10167027 DOI: 10.3389/fimmu.2023.1151185] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/11/2023] [Indexed: 05/15/2023] Open
Abstract
In the working-age population worldwide, diabetic retinopathy (DR), a prevalent complication of diabetes, is the main cause of vision impairment. Chronic low-grade inflammation plays an essential role in DR development. Recently, concerning the pathogenesis of DR, the Nod-Like Receptor Family Pyrin Domain Containing 3 (NLRP3) inflammasome in retinal cells has been determined as a causal factor. In the diabetic eye, the NLRP3 inflammasome is activated by several pathways (such as ROS and ATP). The activation of NPRP3 leads to the secretion of inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18), and leads to pyroptosis, a rapid inflammatory form of lytic programmed cell death (PCD). Cells that undergo pyroptosis swell and rapture, releasing more inflammatory factors and accelerating DR progression. This review focuses on the mechanisms that activate NLRP3 inflammasome and pyroptosis leading to DR. The present research highlighted some inhibitors of NLRP3/pyroptosis pathways and novel therapeutic measures concerning DR treatment.
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Affiliation(s)
- Xiaoqin Zheng
- Department of Ophthalmology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Jia Wan
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Gang Tan
- Department of Ophthalmology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
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14
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Xiao H, Tang J, Zhang F, Liu L, Zhou J, Chen M, Li M, Wu X, Nie Y, Duan J. Global trends and performances in diabetic retinopathy studies: A bibliometric analysis. Front Public Health 2023; 11:1128008. [PMID: 37124794 PMCID: PMC10136779 DOI: 10.3389/fpubh.2023.1128008] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 03/09/2023] [Indexed: 05/02/2023] Open
Abstract
Objective The objective of this study is to conduct a comprehensive bibliometric analysis to identify and evaluate global trends in diabetic retinopathy (DR) research and visualize the focus and frontiers of this field. Methods Diabetic retinopathy-related publications from the establishment of the Web of Science (WOS) through 1 November 2022 were retrieved for qualitative and quantitative analyses. This study analyzed annual publication counts, prolific countries, institutions, journals, and the top 10 most cited literature. The findings were presented through descriptive statistics. VOSviewer 1.6.17 was used to exhibit keywords with high frequency and national cooperation networks, while CiteSpace 5.5.R2 displayed the timeline and burst keywords for each term. Results A total of 10,709 references were analyzed, and the number of publications continuously increased over the investigated period. America had the highest h-index and citation frequency, contributing to the most influence. China was the most prolific country, producing 3,168 articles. The University of London had the highest productivity. The top three productive journals were from America, and Investigative Ophthalmology Visual Science had the highest number of publications. The article from Gulshan et al. (2016; co-citation counts, 2,897) served as the representative and symbolic reference. The main research topics in this area were incidence, pathogenesis, treatment, and artificial intelligence (AI). Deep learning, models, biomarkers, and optical coherence tomography angiography (OCTA) of DR were frontier hotspots. Conclusion Bibliometric analysis in this study provided valuable insights into global trends in DR research frontiers. Four key study directions and three research frontiers were extracted from the extensive DR-related literature. As the incidence of DR continues to increase, DR prevention and treatment have become a pressing public health concern and a significant area of research interest. In addition, the development of AI technologies and telemedicine has emerged as promising research frontiers for balancing the number of doctors and patients.
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Affiliation(s)
- Huan Xiao
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jinfan Tang
- School of Acupuncture-Moxibustion and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Feng Zhang
- School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China
| | - Luping Liu
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jing Zhou
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Meiqi Chen
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Mengyue Li
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xiaoxiao Wu
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yingying Nie
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Junguo Duan
- School of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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15
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Advanced Glycation End-Products and Diabetic Neuropathy of the Retina. Int J Mol Sci 2023; 24:ijms24032927. [PMID: 36769249 PMCID: PMC9917392 DOI: 10.3390/ijms24032927] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 01/29/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
Diabetic retinopathy is a tissue-specific neurovascular impairment of the retina in patients with both type 1 and type 2 diabetes. Several pathological factors are involved in the progressive impairment of the interdependence between cells that consist of the neurovascular units (NVUs). The advanced glycation end-products (AGEs) are one of the major pathological factors that cause the impairments of neurovascular coupling in diabetic retinopathy. Although the exact mechanisms for the toxicities of the AGEs in diabetic retinopathy have not been definitively determined, the AGE-receptor of the AGE (RAGE) axis, production of reactive oxygen species, inflammatory reactions, and the activation of the cell death pathways are associated with the impairment of the NVUs in diabetic retinopathy. More specifically, neuronal cell death is an irreversible change that is directly associated with vision reduction in diabetic patients. Thus, neuroprotective therapies must be established for diabetic retinopathy. The AGEs are one of the therapeutic targets to examine to ameliorate the pathological changes in the NVUs in diabetic retinopathy. This review focuses on the basic and pathological findings of AGE-induced neurovascular abnormalities and the potential therapeutic approaches, including the use of anti-glycated drugs to protect the AGE-induced impairments of the NVUs in diabetic retinopathy.
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16
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Wu S, Mo X. Optic Nerve Regeneration in Diabetic Retinopathy: Potentials and Challenges Ahead. Int J Mol Sci 2023; 24:ijms24021447. [PMID: 36674963 PMCID: PMC9865663 DOI: 10.3390/ijms24021447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 12/31/2022] [Accepted: 01/09/2023] [Indexed: 01/15/2023] Open
Abstract
Diabetic retinopathy (DR), the most common microvascular compilation of diabetes, is the leading cause of vision loss and blindness worldwide. Recent studies indicate that retinal neuron impairment occurs before any noticeable vascular changes in DR, and retinal ganglion cell (RGC) degeneration is one of the earliest signs. Axons of RGCs have little capacity to regenerate after injury, clinically leading the visual functional defects to become irreversible. In the past two decades, tremendous progress has been achieved to enable RGC axon regeneration in animal models of optic nerve injury, which holds promise for neural repair and visual restoration in DR. This review summarizes these advances and discusses the potential and challenges for developing optic nerve regeneration strategies treating DR.
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Affiliation(s)
| | - Xiaofen Mo
- Correspondence: ; Tel.: +86-021-64377134
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17
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Yang Y, Tan J, He Y, Huang H, Wang T, Gong J, Liu Y, Zhang Q, Xu X. Predictive model for diabetic retinopathy under limited medical resources: A multicenter diagnostic study. Front Endocrinol (Lausanne) 2023; 13:1099302. [PMID: 36686423 PMCID: PMC9849672 DOI: 10.3389/fendo.2022.1099302] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 12/19/2022] [Indexed: 01/06/2023] Open
Abstract
Background Comprehensive eye examinations for diabetic retinopathy is poorly implemented in medically underserved areas. There is a critical need for a widely available and economical tool to aid patient selection for priority retinal screening. We investigated the possibility of a predictive model for retinopathy identification using simple parameters. Methods Clinical data were retrospectively collected from 4, 159 patients with diabetes admitted to five tertiary hospitals. Independent predictors were identified by univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and a nomogram was developed based on a multivariate logistic regression model. The validity and clinical practicality of this nomogram were assessed using concordance index (C-index), area under the receiver operating characteristic curve (AUROC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results The predictive factors in the multivariate model included the duration of diabetes, history of hypertension, and cardiovascular disease. The three-variable model displayed medium prediction ability with an AUROC of 0.722 (95%CI 0.696-0.748) in the training set, 0.715 (95%CI 0.670-0.754) in the internal set, and 0.703 (95%CI 0.552-0.853) in the external dataset. DCA showed that the threshold probability of DR in diabetic patients was 17-55% according to the nomogram, and CIC also showed that the nomogram could be applied clinically if the risk threshold exceeded 30%. An operation interface on a webpage (https://cqmuxss.shinyapps.io/dr_tjj/) was built to improve the clinical utility of the nomogram. Conclusions The predictive model developed based on a minimal amount of clinical data available to diabetic patients with restricted medical resources could help primary healthcare practitioners promptly identify potential retinopathy.
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Affiliation(s)
- Yanzhi Yang
- Department of Endocrinology and Metabolism, Chengdu First People’s Hospital, Chengdu, China
| | - Juntao Tan
- Operation Management Office, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China
| | - Yuxin He
- Department of Medical Administration, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China
| | - Huanhuan Huang
- Department of Nursing, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tingting Wang
- College of Medical Informatics, Chongqing Medical University, Chongqing, China
| | - Jun Gong
- Department of Information Center, The University Town Hospital of Chongqing Medical University, Chongqing, China
| | - Yunyu Liu
- Medical Records Department, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Qin Zhang
- Department of Endocrinology and Metabolism, Chengdu First People’s Hospital, Chengdu, China
| | - Xiaomei Xu
- Department of Infectious Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Gastroenterology, Chengdu Fifth People’s hospital, Chengdu, China
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18
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Wei L, Sun X, Fan C, Li R, Zhou S, Yu H. The pathophysiological mechanisms underlying diabetic retinopathy. Front Cell Dev Biol 2022; 10:963615. [PMID: 36111346 PMCID: PMC9468825 DOI: 10.3389/fcell.2022.963615] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/12/2022] [Indexed: 12/04/2022] Open
Abstract
Diabetic retinopathy (DR) is the most common complication of diabetes mellitus (DM), which can lead to visual impairment and even blindness in severe cases. DR is generally considered to be a microvascular disease but its pathogenesis is still unclear. A large body of evidence shows that the development of DR is not determined by a single factor but rather by multiple related mechanisms that lead to different degrees of retinal damage in DR patients. Therefore, this article briefly reviews the pathophysiological changes in DR, and discusses the occurrence and development of DR resulting from different factors such as oxidative stress, inflammation, neovascularization, neurodegeneration, the neurovascular unit, and gut microbiota, to provide a theoretical reference for the development of new DR treatment strategies.
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Affiliation(s)
- Lindan Wei
- Special Key Laboratory of Ocular Diseases of Guizhou Province, Department of Immunology, Zunyi Medical University, Zunyi, China
| | - Xin Sun
- Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, School of Basic Medical Sciences, Zunyi Medical University, Zunyi, China
| | - Chenxi Fan
- Special Key Laboratory of Ocular Diseases of Guizhou Province, Department of Immunology, Zunyi Medical University, Zunyi, China
| | - Rongli Li
- Special Key Laboratory of Ocular Diseases of Guizhou Province, Department of Immunology, Zunyi Medical University, Zunyi, China
| | - Shuanglong Zhou
- Special Key Laboratory of Ocular Diseases of Guizhou Province, Department of Immunology, Zunyi Medical University, Zunyi, China
| | - Hongsong Yu
- Special Key Laboratory of Ocular Diseases of Guizhou Province, Department of Immunology, Zunyi Medical University, Zunyi, China
- *Correspondence: Hongsong Yu,
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Neurovascular Impairment and Therapeutic Strategies in Diabetic Retinopathy. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 19:ijerph19010439. [PMID: 35010703 PMCID: PMC8744686 DOI: 10.3390/ijerph19010439] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 12/25/2021] [Accepted: 12/30/2021] [Indexed: 12/15/2022]
Abstract
Diabetic retinopathy has recently been defined as a highly specific neurovascular complication of diabetes. The chronic progression of the impairment of the interdependence of neurovascular units (NVUs) is associated with the pathogenesis of diabetic retinopathy. The NVUs consist of neurons, glial cells, and vascular cells, and the interdependent relationships between these cells are disturbed under diabetic conditions. Clinicians should understand and update the current knowledge of the neurovascular impairments in diabetic retinopathy. Above all, neuronal cell death is an irreversible change, and it is directly related to vision loss in patients with diabetic retinopathy. Thus, neuroprotective and vasoprotective therapies for diabetic retinopathy must be established. Understanding the physiological and pathological interdependence of the NVUs is helpful in establishing neuroprotective and vasoprotective therapies for diabetic retinopathy. This review focuses on the pathogenesis of the neurovascular impairments and introduces possible neurovascular protective therapies for diabetic retinopathy.
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