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Wang WC, Huang CH, Chung HH, Chen PL, Hu FR, Yang CH, Yang CM, Lin CW, Hsu CC, Chen TC. Metabolomics facilitates differential diagnosis in common inherited retinal degenerations by exploring their profiles of serum metabolites. Nat Commun 2024; 15:3562. [PMID: 38670966 PMCID: PMC11053129 DOI: 10.1038/s41467-024-47911-3] [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] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
The diagnosis of inherited retinal degeneration (IRD) is challenging owing to its phenotypic and genotypic complexity. Clinical information is important before a genetic diagnosis is made. Metabolomics studies the entire picture of bioproducts, which are determined using genetic codes and biological reactions. We demonstrated that the common diagnoses of IRD, including retinitis pigmentosa (RP), cone-rod dystrophy (CRD), Stargardt disease (STGD), and Bietti's crystalline dystrophy (BCD), could be differentiated based on their metabolite heatmaps. Hundreds of metabolites were identified in the volcano plot compared with that of the control group in every IRD except BCD, considered as potential diagnosing markers. The phenotypes of CRD and STGD overlapped but could be differentiated by their metabolomic features with the assistance of a machine learning model with 100% accuracy. Moreover, EYS-, USH2A-associated, and other RP, sharing considerable similar characteristics in clinical findings, could also be diagnosed using the machine learning model with 85.7% accuracy. Further study would be needed to validate the results in an external dataset. By incorporating mass spectrometry and machine learning, a metabolomics-based diagnostic workflow for the clinical and molecular diagnoses of IRD was proposed in our study.
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Affiliation(s)
- Wei-Chieh Wang
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
| | - Chu-Hsuan Huang
- Department of Ophthalmology, Cathay General Hospital, Taipei, Taiwan
- School of Medicine, National Tsing Hua University, Hsinchu, Taiwan
| | | | - Pei-Lung Chen
- Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan
| | - Fung-Rong Hu
- Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Ophthalmology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chang-Hao Yang
- Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Ophthalmology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chung-May Yang
- Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Ophthalmology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chao-Wen Lin
- Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan
| | - Cheng-Chih Hsu
- Department of Chemistry, National Taiwan University, Taipei, Taiwan.
- Leeuwenhoek Laboratories Co. Ltd, Taipei, Taiwan.
| | - Ta-Ching Chen
- Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
- Center of Frontier Medicine, National Taiwan University Hospital, Taipei, Taiwan.
- Research Center for Developmental Biology and Regenerative Medicine, National Taiwan University, Taipei, Taiwan.
- Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan.
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Pucchio A, Krance SH, Pur DR, Bhatti J, Bassi A, Manichavagan K, Brahmbhatt S, Aggarwal I, Singh P, Virani A, Stanley M, Miranda RN, Felfeli T. Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review. Graefes Arch Clin Exp Ophthalmol 2024; 262:1041-1091. [PMID: 37421481 DOI: 10.1007/s00417-023-06100-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 04/25/2023] [Accepted: 05/06/2023] [Indexed: 07/10/2023] Open
Abstract
PURPOSE This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and their predictive accuracies. We also evaluate the integration of bioinformatics with AI tools. METHODS This scoping review was conducted across five electronic databases including EMBASE, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics were included. RESULTS A total of 10,262 articles were retrieved from all databases and 177 studies met the inclusion criteria. The most commonly studied ocular diseases were diabetic eye diseases, with 50 papers (28%), while glaucoma was explored in 25 studies (14%), age-related macular degeneration in 20 (11%), dry eye disease in 10 (6%), and uveitis in 9 (5%). Supervised learning was used in 91 papers (51%), unsupervised AI in 83 (46%), and bioinformatics in 85 (48%). Ninety-eight papers (55%) used more than one class of AI (e.g. > 1 of supervised, unsupervised, bioinformatics, or statistical techniques), while 79 (45%) used only one. Supervised learning techniques were often used to predict disease status or prognosis, and demonstrated strong accuracy. Unsupervised AI algorithms were used to bolster the accuracy of other algorithms, identify molecularly distinct subgroups, or cluster cases into distinct subgroups that are useful for prediction of the disease course. Finally, bioinformatic tools were used to translate complex biomarker profiles or findings into interpretable data. CONCLUSION AI analysis of biofluid markers displayed diagnostic accuracy, provided insight into mechanisms of molecular etiologies, and had the ability to provide individualized targeted therapeutic treatment for patients. Given the progression of AI towards use in both research and the clinic, ophthalmologists should be broadly aware of the commonly used algorithms and their applications. Future research may be aimed at validating algorithms and integrating them in clinical practice.
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Affiliation(s)
- Aidan Pucchio
- Department of Ophthalmology, Queen's University, Kingston, ON, Canada
- Queens School of Medicine, Kingston, ON, Canada
| | - Saffire H Krance
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Daiana R Pur
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Jasmine Bhatti
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Arshpreet Bassi
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Shaily Brahmbhatt
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Priyanka Singh
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Aleena Virani
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Rafael N Miranda
- The Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Tina Felfeli
- The Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
- Department of Ophthalmology and Vision Sciences, University of Toronto, 340 College Street, Suite 400, Toronto, ON, M5T 3A9, Canada.
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Rahimi Y, Rabizadeh S, Seifouri S, Seifouri K, Salarvand S, Nakhjavani M. A case report of malignant struma ovarii with papillary thyroid carcinoma. Clin Case Rep 2024; 12:e8610. [PMID: 38617068 PMCID: PMC11014801 DOI: 10.1002/ccr3.8610] [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: 07/01/2023] [Revised: 02/05/2024] [Accepted: 02/08/2024] [Indexed: 04/16/2024] Open
Abstract
Key clinical message Struma ovarii (SO), is a rare and specialized ovarian teratoma. The treatment is controversial depending on the risk of recurrence and metastasis. Here a SO with papillary thyroid carcinoma is reported and the approach is thoroughly discussed. Abstract Struma ovarii (SO) is a highly specialized ovarian teratoma primarily composed of thyroid tissue. Clinical features associated with SO include lower abdominal discomfort, unusual vaginal bleeding, ascites, and hyperthyroidism. While SO rarely transforms into malignancy, the optimal degree of treatment remains controversial due to the varying risks of recurrence and metastasis. In this report, we present the case of a 64-year-old woman experiencing abdominal pain and diagnosed with SO, accompanied by papillary thyroid carcinoma. We thoroughly discuss the evaluation and management of this rare condition.
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Affiliation(s)
- Yekta Rahimi
- University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Soghra Rabizadeh
- Endocrinology and Metabolism Research Center (EMRC), Vali‐Asr HospitalTehran University of Medical SciencesTehranIran
| | | | - Kiana Seifouri
- Endocrinology and Metabolism Research Center (EMRC), Vali‐Asr HospitalTehran University of Medical SciencesTehranIran
| | - Samane Salarvand
- Department of pathology Cancer InstituteTehran University of Medical SciencesTehranIran
| | - Manouchehr Nakhjavani
- Endocrinology and Metabolism Research Center (EMRC), Vali‐Asr HospitalTehran University of Medical SciencesTehranIran
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Song Y, Wei H, Zhou Z, Wang H, Hang W, Wu J, Wang DW. Gut microbiota-dependent phenylacetylglutamine in cardiovascular disease: current knowledge and new insights. Front Med 2024; 18:31-45. [PMID: 38424375 DOI: 10.1007/s11684-024-1055-9] [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: 08/28/2023] [Accepted: 12/04/2023] [Indexed: 03/02/2024]
Abstract
Phenylacetylglutamine (PAGln) is an amino acid derivate that comes from the amino acid phenylalanine. There are increasing studies showing that the level of PAGln is associated with the risk of different cardiovascular diseases. In this review, we discussed the metabolic pathway of PAGln production and the quantitative measurement methods of PAGln. We summarized the epidemiological evidence to show the role of PAGln in diagnostic and prognostic value in several cardiovascular diseases, such as heart failure, coronary heart disease/atherosclerosis, and cardiac arrhythmia. The underlying mechanism of PAGln is now considered to be related to the thrombotic potential of platelets via adrenergic receptors. Besides, other possible mechanisms such as inflammatory response and oxidative stress could also be induced by PAGln. Moreover, since PAGln is produced across different organs including the intestine, liver, and kidney, the cross-talk among multiple organs focused on the function of this uremic toxic metabolite. Finally, the prognostic value of PAGln compared to the classical biomarker was discussed and we also highlighted important gaps in knowledge and areas requiring future investigation of PAGln in cardiovascular diseases.
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Affiliation(s)
- Yaonan Song
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China
| | - Haoran Wei
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China
| | - Zhitong Zhou
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China
| | - Huiqing Wang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China
| | - Weijian Hang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China
| | - Junfang Wu
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China.
| | - Dao Wen Wang
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
- Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Wuhan, 430030, China
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Demicheva E, Dordiuk V, Polanco Espino F, Ushenin K, Aboushanab S, Shevyrin V, Buhler A, Mukhlynina E, Solovyova O, Danilova I, Kovaleva E. Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review. Metabolites 2024; 14:54. [PMID: 38248857 PMCID: PMC10820779 DOI: 10.3390/metabo14010054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/05/2024] [Accepted: 01/12/2024] [Indexed: 01/23/2024] Open
Abstract
Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.
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Affiliation(s)
- Ekaterina Demicheva
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Vladislav Dordiuk
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
| | - Fernando Polanco Espino
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
| | - Konstantin Ushenin
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Autonomous Non-Profit Organization Artificial Intelligence Research Institute (AIRI), Moscow 105064, Russia
| | - Saied Aboushanab
- Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia; (S.A.); (V.S.); (E.K.)
| | - Vadim Shevyrin
- Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia; (S.A.); (V.S.); (E.K.)
| | - Aleksey Buhler
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
| | - Elena Mukhlynina
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Olga Solovyova
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Irina Danilova
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Elena Kovaleva
- Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia; (S.A.); (V.S.); (E.K.)
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Fernandes Silva L, Hokkanen J, Vangipurapu J, Oravilahti A, Laakso M. Metabolites as Risk Factors for Diabetic Retinopathy in Patients With Type 2 Diabetes: A 12-Year Follow-up Study. J Clin Endocrinol Metab 2023; 109:100-106. [PMID: 37560996 PMCID: PMC10735554 DOI: 10.1210/clinem/dgad452] [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: 04/17/2023] [Revised: 06/29/2023] [Accepted: 08/09/2023] [Indexed: 08/11/2023]
Abstract
CONTEXT Diabetic retinopathy (DR) is a specific microvascular complication in patients with diabetes and the leading cause of blindness. Recent advances in omics, especially metabolomics, offer the possibility identifying novel potential biomarkers for DR. OBJECTIVE The aim was to identify metabolites associated with DR. METHODS We performed a 12-year follow-up study including 1349 participants with type 2 diabetes (1021 without DR, 328 with DR) selected from the METSIM cohort. Individuals who had retinopathy before the baseline study were excluded (n = 63). The diagnosis of retinopathy was based on fundus photography examination. We performed nontargeted metabolomics profiling to identify metabolites. RESULTS We found 17 metabolites significantly associated with incident DR after adjustment for confounding factors. Among amino acids, N-lactoyl isoleucine, N-lactoyl valine, N-lactoyl tyrosine, N-lactoyl phenylalanine, N-(2-furoyl) glycine, and 5-hydroxylysine were associated with an increased risk of DR, and citrulline with a decreased risk of DR. Among the fatty acids N,N,N-trimethyl-5-aminovalerate was associated with an increased risk of DR, and myristoleate (14:1n5), palmitoleate (16:1n7), and 5-dodecenoate (12:1n7) with a decreased risk of DR. Sphingomyelin (d18:2/24:2), a sphingolipid, was significantly associated with a decreased risk of DR. Carboxylic acid maleate and organic compounds 3-hydroxypyridine sulfate, 4-vinylphenol sulfate, 4-ethylcatechol sulfate, and dimethyl sulfone were significantly associated with an increased risk of DR. CONCLUSION Our study is the first large population-based longitudinal study to identify metabolites for DR. We found multiple metabolites associated with an increased and decreased risk for DR from several different metabolic pathways.
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Affiliation(s)
- Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70211 Kuopio, Finland
| | - Jenna Hokkanen
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70211 Kuopio, Finland
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70211 Kuopio, Finland
| | - Anniina Oravilahti
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70211 Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70211 Kuopio, Finland
- Department of Internal Medicine, Kuopio University Hospital, 70211 Kuopio, Finland
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He S, Sun L, Chen J, Ouyang Y. Recent Advances and Perspectives in Relation to the Metabolomics-Based Study of Diabetic Retinopathy. Metabolites 2023; 13:1007. [PMID: 37755287 PMCID: PMC10536395 DOI: 10.3390/metabo13091007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 09/03/2023] [Accepted: 09/05/2023] [Indexed: 09/28/2023] Open
Abstract
Diabetic retinopathy (DR), a prevalent microvascular complication of diabetes, is a major cause of acquired blindness in adults. Currently, a clinical diagnosis of DR primarily relies on fundus fluorescein angiography, with a limited availability of effective biomarkers. Metabolomics, a discipline dedicated to scrutinizing the response of various metabolites within living organisms, has shown noteworthy advancements in uncovering metabolic disorders and identifying key metabolites associated with DR in recent years. Consequently, this review aims to present the latest advancements in metabolomics techniques and comprehensively discuss the principal metabolic outcomes derived from analyzing blood, vitreous humor, aqueous humor, urine, and fecal samples.
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Affiliation(s)
| | | | | | - Yang Ouyang
- Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou 350122, China; (S.H.)
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Ren J, Ren A, Huang Z, Deng X, Jiang Z, Xue Y, Fu Z, Smith LE, Ke M, Gong Y. Metabolomic Profiling of Long-Chain Polyunsaturated Fatty Acid Oxidation in Adults with Retinal Vein Occlusion: A Case-Control Study. Am J Clin Nutr 2023; 118:579-590. [PMID: 37454758 DOI: 10.1016/j.ajcnut.2023.07.006] [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: 01/06/2023] [Revised: 07/04/2023] [Accepted: 07/10/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Long-chain polyunsaturated fatty acids (LCPUFAs) and their metabolites are closely related to neovascular eye diseases. However, the clinical significance of their oxylipins in retinal vein occlusion (RVO) remains inconclusive. OBJECTIVES This case-control study aimed to explore metabolomic profiles of LCPUFA oxidation in RVO and to identify potential indicators for diagnosis and pathologic progression. METHODS The plasma concentrations of ω-3 (n-3) and ω-6 (n-6) LCPUFA and their oxylipins in 44 adults with RVO and 36 normal controls were analyzed using ultraperformance liquid chromatography tandem mass spectrometry. Univariate analysis combined with principal component and orthogonal projections to latent structure discriminant analysis was used to screen differential metabolites. Aortic ring and choroidal explant sprouting assays were used to investigate the effects of 5-oxo-eicosatetraenoic acids (ETE) on angiogenesis ex vivo. Tubule formation and wound healing assays were performed to verify its effects on human retinal microvascular endothelial cell functions. RESULTS Higher ω-6 and lower ω-3 LCPUFA plasma concentrations were measured in the adults with RVO compared with control (odds ratio [OR]: 2.34; 95% confidence interval [CI]: 1.42, 3.86; P < 0.001; OR: 0.28; 95% CI: 0.15, 0.51; P < 0.001). Metabolomic analysis revealed 20 LCPUFA and their oxylipins dysregulated in RVO, including increased arachidonic acid (ω-6, OR: 1.85; 95% CI: 1.18, 2.90; P < 0.001) and its lipoxygenase product 5-oxo-ETE (OR: 11.76; 95% CI: 3.73, 37.11; P < 0.001), as well as decreased docosahexaenoic acid (ω-3, OR: 0.13; 95% CI: 0.05, 0.33; P < 0.001). Interestingly, 5-oxo-ETE was downregulated in ischemic compared with nonischemic central RVO. Exogenous 5-oxo-ETE attenuated aortic ring and choroidal explant sprouting and inhibited tubule formation and migration of human retinal microvascular endothelial cells in a dose-dependent manner, possibly via suppressing the vascular endothelial growth factor signaling pathway. CONCLUSIONS The plasma concentrations of ω-6 and ω-3 LCPUFA and their oxylipins were associated with RVO. The ω-6 LCPUFA-derived metabolite 5-oxo-ETE was a potential marker of RVO development and progression.
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Affiliation(s)
- Jiangbo Ren
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China; Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Anli Ren
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China; Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhengrong Huang
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China; Tumor Precision Diagnosis and Treatment Technology and Translational Medicine, Hubei Engineering Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xizhi Deng
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ziyu Jiang
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China; Tumor Precision Diagnosis and Treatment Technology and Translational Medicine, Hubei Engineering Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China; Human Genetics Resource Preservation Center of Wuhan University, Wuhan University, Wuhan, China
| | - Yanni Xue
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhongjie Fu
- Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
| | - Lois Eh Smith
- Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
| | - Min Ke
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, China.
| | - Yan Gong
- Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China; Tumor Precision Diagnosis and Treatment Technology and Translational Medicine, Hubei Engineering Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China; Human Genetics Resource Preservation Center of Wuhan University, Wuhan University, Wuhan, China.
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9
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Wen X, Ng TK, Liu Q, Wu Z, Zhang G, Zhang M. Azelaic acid and guanosine in tears improve discrimination of proliferative from non-proliferative diabetic retinopathy in type-2 diabetes patients: A tear metabolomics study. Heliyon 2023; 9:e16109. [PMID: 37305454 PMCID: PMC10256905 DOI: 10.1016/j.heliyon.2023.e16109] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 05/02/2023] [Accepted: 05/05/2023] [Indexed: 06/13/2023] Open
Abstract
Background Diabetic retinopathy (DR) is the microvascular ocular complication of diabetes mellitus (DM), which can lead to irreversible blindness and visual impairment if not properly treated. Tears can be collected non-invasively, and the compositions of tears could be the potential biomarkers for ocular diseases. Here we aimed to delineate the metabolomics signature in tears collected from Chinese type-2 DM patients with DR. Methods The metabolomics profiles of tear samples from 41 Chinese type-2 DM patients with DR and 21 non-diabetic subjects were determined by the untargeted liquid chromatography-mass spectrometry. The associated pathways of the differentially abundant metabolites were delineated, and the receiver operating characteristic curve analysis was conducted to identify the metabolites differentiating non-proliferative DR (NPDR) from proliferative DR (PDR). Results Total 14 differentially abundant metabolites were identified between total DR and non-diabetic subjects, and 17 differentially abundant metabolites were found between the NPDR and PDR subjects. Moreover, total 18 differentially abundant metabolites were identified between the NPDR and PDR subjects with stratification in DR duration and blood glucose level. d-Glutamine and d-glutamate metabolism was significantly highlighted in the PDR group as compared to the non-diabetic group. For the predictive performance, azelaic acid combined with guanosine achieved the area under receiver operating characteristic curve of 0.855 in the comparison between NPDR and PDR groups. Conclusion This study revealed the metabolomics changes in tear samples of DR patients. The metabolites in tears could be the potential biomarkers in the DR analysis.
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Affiliation(s)
- Xin Wen
- Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou, Guangdong, China
- Shantou University Medical College, Shantou, Guangdong, China
| | - Tsz Kin Ng
- Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou, Guangdong, China
- Shantou University Medical College, Shantou, Guangdong, China
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Qingping Liu
- Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou, Guangdong, China
| | - Zhenggen Wu
- Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou, Guangdong, China
| | - Guihua Zhang
- Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou, Guangdong, China
| | - Mingzhi Zhang
- Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou, Guangdong, China
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10
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Inulin and Chinese Gallotannin Affect Meat Quality and Lipid Metabolism on Hu Sheep. Animals (Basel) 2022; 13:ani13010160. [PMID: 36611769 PMCID: PMC9817504 DOI: 10.3390/ani13010160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/26/2022] [Accepted: 12/29/2022] [Indexed: 01/03/2023] Open
Abstract
The aim of this study was to investigate the impacts of inulin and Chinese gallotannin on the meat fatty acids and urinary metabolites in sheep. Twenty-four healthy (25.80 ± 3.85 kg) weaned Hu lambs of approximately 4.5 months old were equally divided into four groups: control group (basal diet), treatment group I (basal diet + 0.1% inulin), treatment group II (basal diet + 0.1% inulin + 2% Chinese gallotannin), and treatment group III (basal diet + 0.1% inulin + 2% Chinese gallotannin + 4% PEG). The contents of myristic acid (C14:0) and palmitic acid (C16:0) were found to be lower in treatment group II than in the control group (p < 0.05). Moreover, the palmitoleic acid (C16:1) content in treatment group II was notably higher than that in the control group (p < 0.05), while the elaidic acid (C18:1n9t) content in treatment group II was higher than that in other groups (p < 0.05). Besides, the linoleic acid (C18:2n6c) content was higher in the treatment II and control groups than in the treatment I and III groups. Furthermore, compared with the control group, both 4-pyridoxic acid and creatinine in treatment groups I and II were upregulated (p < 0.05), while other metabolites, such as nicotinuric acid, l-threonine, palmitic acid, and oleic acid, were drastically downregulated (p < 0.05). These differential metabolites were found to be mainly involved in nicotinate and nicotinamide metabolism (ko00760), vitamin B6 metabolism (ko00750), and the fatty acid biosynthesis pathway (ko00061). It is concluded that the combination of inulin and Chinese gallotannin in the diet could improve the energy and lipid metabolism of sheep, which may improve both mutton quality and production performance.
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11
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Amino Acids Metabolism in Retinopathy: From Clinical and Basic Research Perspective. Metabolites 2022; 12:metabo12121244. [PMID: 36557282 PMCID: PMC9781488 DOI: 10.3390/metabo12121244] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/22/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
Retinopathy, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP), are the leading cause of blindness among seniors, working-age populations, and children. However, the pathophysiology of retinopathy remains unclear. Accumulating studies demonstrate that amino acid metabolism is associated with retinopathy. This study discusses the characterization of amino acids in DR, AMD, and ROP by metabolomics from clinical and basic research perspectives. The features of amino acids in retinopathy were summarized using a comparative approach based on existing high-throughput metabolomics studies from PubMed. Besides taking up a large proportion, amino acids appear in both human and animal, intraocular and peripheral samples. Among them, some metabolites differ significantly in all three types of retinopathy, including glutamine, glutamate, alanine, and others. Studies on the mechanisms behind retinal cell death caused by glutamate accumulation are on the verge of making some progress. To develop potential therapeutics, it is imperative to understand amino acid-induced retinal functional alterations and the underlying mechanisms. This review delineates the significance of amino acid metabolism in retinopathy and provides possible direction to discover therapeutic targets for retinopathy.
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12
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Jian Q, Wu Y, Zhang F. Metabolomics in Diabetic Retinopathy: From Potential Biomarkers to Molecular Basis of Oxidative Stress. Cells 2022; 11:cells11193005. [PMID: 36230967 PMCID: PMC9563658 DOI: 10.3390/cells11193005] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/22/2022] [Indexed: 11/18/2022] Open
Abstract
Diabetic retinopathy (DR), the leading cause of blindness in working-age adults, is one of the most common complications of diabetes mellitus (DM) featured by metabolic disorders. With the global prevalence of diabetes, the incidence of DR is expected to increase. Prompt detection and the targeting of anti-oxidative stress intervention could effectively reduce visual impairment caused by DR. However, the diagnosis and treatment of DR is often delayed due to the absence of obvious signs of retina imaging. Research progress supports that metabolomics is a powerful tool to discover potential diagnostic biomarkers and therapeutic targets for the causes of oxidative stress through profiling metabolites in diseases, which provides great opportunities for DR with metabolic heterogeneity. Thus, this review summarizes the latest advances in metabolomics in DR, as well as potential diagnostic biomarkers, and predicts molecular targets through the integration of genome-wide association studies (GWAS) with metabolomics. Metabolomics provides potential biomarkers, molecular targets and therapeutic strategies for controlling the progress of DR, especially the interventions at early stages and precise treatments based on individual patient variations.
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Affiliation(s)
- Qizhi Jian
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
| | - Yingjie Wu
- Institute for Genome Engineered Animal Models of Human Diseases, National Center of Genetically Engineered Animal Models for International Research, Liaoning Provence Key Laboratory of Genome Engineered Animal Models, Dalian Medical University, Dalian 116000, China
- Shandong Provincial Hospital, School of Laboratory Animal & Shandong Laboratory Animal Center, Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250021, China
- Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY 10010, USA
- Correspondence: (Y.W.); (F.Z.)
| | - Fang Zhang
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai 200080, China
- Correspondence: (Y.W.); (F.Z.)
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13
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Study on BCVA, CMT, CME, Curative Effect, and Prognostic Value of DR Sufferers Based on Surgical Therapy Combined with VEGF Therapy at Different Times. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:1415659. [PMID: 36017028 PMCID: PMC9388298 DOI: 10.1155/2022/1415659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 07/11/2022] [Accepted: 07/13/2022] [Indexed: 11/18/2022]
Abstract
In order to explore the efficacy and prognostic value of best corrected visual acuity (BCVA), central macular retinal thickness (CMT), and cystoid macular edema (CME) in diabetic retinopathy (DR) sufferers based on surgical therapy combined with vascular endothelial growth factor (VEGF) therapy at different times, a total of 170 cases of DR sufferers who visited our hospital from March 2019 to March 2021 are analyzed. All patients are randomly divided into control group and study group, with 85 cases and 85 eyes in each group. In addition, the contrast set received 2 therapies for 1.5 months/time, and the study set received 3 therapies for 1 month/time. The experimental results show that the BCVA of the two sets is notoriously enhanced. Besides, CMT and CME in the study set decrease more than those in the contrast set, and the blood vessel density of retinal capillaries in the contrast set and the examination set is notoriously enhanced. For DR sufferers, 1 month/time of anti-VEGF therapy can effectively enhance the sufferers’ visual acuity, CMT and CME. It is suggested that the clinical application of 1 month/time of anti-VEGF to DR sufferers can enhance the clinical therapeutic effect of sufferers and reduce the prognosis and recurrence.
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14
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Li J, Guo C, Wang T, Xu Y, Peng F, Zhao S, Li H, Jin D, Xia Z, Che M, Zuo J, Zheng C, Hu H, Mao G. Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study. Nutr Diabetes 2022; 12:36. [PMID: 35931671 PMCID: PMC9355962 DOI: 10.1038/s41387-022-00216-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 07/10/2022] [Accepted: 07/18/2022] [Indexed: 01/20/2023] Open
Abstract
Objective Early identification of diabetic retinopathy (DR) is key to prioritizing therapy and preventing permanent blindness. This study aims to propose a machine learning model for DR early diagnosis using metabolomics and clinical indicators. Methods From 2017 to 2018, 950 participants were enrolled from two affiliated hospitals of Wenzhou Medical University and Anhui Medical University. A total of 69 matched blocks including healthy volunteers, type 2 diabetes, and DR patients were obtained from a propensity score matching-based metabolomics study. UPLC-ESI-MS/MS system was utilized for serum metabolic fingerprint data. CART decision trees (DT) were used to identify the potential biomarkers. Finally, the nomogram model was developed using the multivariable conditional logistic regression models. The calibration curve, Hosmer–Lemeshow test, receiver operating characteristic curve, and decision curve analysis were applied to evaluate the performance of this predictive model. Results The mean age of enrolled subjects was 56.7 years with a standard deviation of 9.2, and 61.4% were males. Based on the DT model, 2-pyrrolidone completely separated healthy controls from diabetic patients, and thiamine triphosphate (ThTP) might be a principal metabolite for DR detection. The developed nomogram model (including diabetes duration, systolic blood pressure and ThTP) shows an excellent quality of classification, with AUCs (95% CI) of 0.99 (0.97–1.00) and 0.99 (0.95–1.00) in training and testing sets, respectively. Furthermore, the predictive model also has a reasonable degree of calibration. Conclusions The nomogram presents an accurate and favorable prediction for DR detection. Further research with larger study populations is needed to confirm our findings.
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Affiliation(s)
- Jushuang Li
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Chengnan Guo
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Tao Wang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yixi Xu
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Fang Peng
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shuzhen Zhao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Huihui Li
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Dongzhen Jin
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhezheng Xia
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Mingzhu Che
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Jingjing Zuo
- Center on Clinical Research, School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Chao Zheng
- The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Honglin Hu
- Department of Endocrinology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
| | - Guangyun Mao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China. .,Center on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China. .,Center on Clinical Research, School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China.
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15
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Wang Z, Tang J, Jin E, Zhong Y, Zhang L, Han X, Liu J, Cheng Y, Hou J, Shi X, Qi H, Qian T, Yuan L, Hou X, Yin H, Liang J, Zhao M, Huang L, Qu J. Serum Untargeted Metabolomics Reveal Potential Biomarkers of Progression of Diabetic Retinopathy in Asians. Front Mol Biosci 2022; 9:871291. [PMID: 35755823 PMCID: PMC9224596 DOI: 10.3389/fmolb.2022.871291] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/25/2022] [Indexed: 12/16/2022] Open
Abstract
Purpose: To reveal molecular mechanisms of diabetic retinopathy (DR) in Asians and facilitate the identification of new therapeutic targets through untargeted metabolomics. To determine the differences in serum metabolites and metabolic pathways between different stages of diabetic retinopathy in patients with type 2 diabetic mellitus (T2DM) and proliferative DR (PDR) and non-proliferative DR (NPDR) and identify differential metabolites between T2DM and DR (NPDR and PDR) patients. Methods: This prospective observational registration study described the differential metabolites between 45 T2DM patients and 15 control cases with no significant differences in clinical characteristics. Their biospecimens and clinical information were collected and recorded in their medical reports. DR phenotypes of the subjects were verified by retina specialists. Serum metabolites were analyzed using high-resolution mass spectrometry with liquid chromatography. Untargeted metabolomics was performed on serum samples from 15 T2DM patients, 15 non-proliferative diabetic retinopathy patients, 15 proliferative diabetic retinopathy patients, and 15 diabetic controls. Discriminatory metabolic features were identified through partial least squares discriminant analysis (PLS-DA), hierarchical clustering analysis (HCA), and generalized linear regression models. Result: Through untargeted metabolomics, 931 features (523 in positive and 408 in negative modes) with 102 common metabolites highly relevant to the presence of DR were detected. In the adjusted analysis, 67 metabolic features differed significantly between T2DM and NPDR patients. Pathway analysis revealed alterations in metabolisms of amino acids and fatty acids. Glutamate, phosphatidylcholine, and 13-hydroperoxyoctadeca-9,11-dienoic acid (13-PHODE) were key contributors to these pathway differences. A total of 171 features distinguished PDR patients from T2DM patients, and pathway analysis revealed alterations in amino acid metabolism, fatty acid metabolism, nitrogen metabolism, and tricarboxylic acid cycle. Aspartate, glutamate, glutamine, ornithine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, citrate, succinate, N-(L-arginino)succinate, 2-oxoglutarate, 13-hydroperoxyoctadeca-9,11-dienoic acid, methionine, lysine, threonine, phenylalanine, N(pi)-methyl-l-histidine, phosphatidylcholine, and linoleate were major contributors to the pathway differences. Between NPDR patients and PDR patients, there were 79 significant differential metabolites. Enrichment pathway analysis showed changes in amino acid metabolism, fatty acid metabolism, pantothenate, and CoA biosynthesis. Aspartate, glutamine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, pantothenate, dihomo-gamma-linolenate, docosahexaenoic acid, and icosapentaenoic acid were key factors for the differences of these pathways. Conclusion: This study demonstrated that the pathways of arginine biosynthesis metabolism, linoleic acid metabolism, alanine, aspartate, and glutamate metabolism, as well as d-glutamine and d-glutamate metabolism, were dysregulated in DR patients of the Asian population. Increased levels of glutamate, aspartate, glutamine, N-acetyl-l-glutamate, and N-acetyl-l-aspartate and decreased levels of dihomo-gamma-linolenate, docosahexaenoic, and icosapentaenoic were considered as the metabolic profile that could distinguish PDR from NPDR in Asians. Phosphatidylcholine and 13-PHODE were identified as two major novel metabolite markers in advanced stages of DR in our study.
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Affiliation(s)
- Zongyi Wang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jiyang Tang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Enzhong Jin
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yusheng Zhong
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Linqi Zhang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Xinyao Han
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jia Liu
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yong Cheng
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jing Hou
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Xuan Shi
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Huijun Qi
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Tong Qian
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Li Yuan
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Xianru Hou
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Hong Yin
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jianhong Liang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Mingwei Zhao
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Lvzhen Huang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jinfeng Qu
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
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16
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Guo C, Jiang D, Xu Y, Peng F, Zhao S, Li H, Jin D, Xu X, Xia Z, Che M, Lai M, Huang R, Wang H, Zheng C, Mao G. High-Coverage Serum Metabolomics Reveals Metabolic Pathway Dysregulation in Diabetic Retinopathy: A Propensity Score-Matched Study. Front Mol Biosci 2022; 9:822647. [PMID: 35372500 PMCID: PMC8970305 DOI: 10.3389/fmolb.2022.822647] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 02/07/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Diabetic retinopathy (DR) is a major diabetes-related disease linked to metabolism. However, the cognition of metabolic pathway alterations in DR remains scarce. We aimed to corroborate alterations of metabolic pathways identified in prior studies and investigate novel metabolic dysregulations that may lead to new prevention and treatment strategies for DR. Methods: In this case-control study, we tested 613 serum metabolites in 69 pairs of type 2 diabetic patients (T2DM) with DR and propensity score-matched T2DM without DR via ultra-performance liquid chromatography-tandem mass spectrometry system. Metabolic pathway dysregulation in DR was thoroughly investigated by metabolic pathway analysis, chemical similarity enrichment analysis (ChemRICH), and integrated pathway analysis. The associations of ChemRICH-screened key metabolites with DR were further estimated with restricted cubic spline analyses. Results: A total of 89 differentially expressed metabolites were identified by paired univariate analysis and partial least squares discriminant analysis. We corroborated biosynthesis of unsaturated fatty acids, glycine, serine and threonine metabolism, glutamate and cysteine-related pathways, and nucleotide-related pathways were significantly perturbed in DR, which were identified in prior studies. We also found some novel metabolic alterations associated with DR, including the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives in DR. Conclusions: The results suggest that the metabolism disorder in DR can be better understood through integrating multiple biological knowledge databases. The progression of DR is associated with the disturbance of thiamine metabolism and tryptophan metabolism, decreased trehalose, and increased choline and indole derivatives.
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Affiliation(s)
- Chengnan Guo
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Depeng Jiang
- Department of Community Health Sciences, College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Yixi Xu
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Fang Peng
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Shuzhen Zhao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Huihui Li
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Dongzhen Jin
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Xin Xu
- Department of Nursing, School of Nursing, Wenzhou Medical University, Wenzhou, China
| | - Zhezheng Xia
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Mingzhu Che
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Mengyuan Lai
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Ruogu Huang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Hui Wang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Chao Zheng
- The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Chao Zheng, , orcid org/0000-0003-3814-4643; Guangyun Mao, , orcid.org/0000-0002-4548-7524
| | - Guangyun Mao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Evidence-Based Medicine and Clinical Epidemiological Research, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Center on Clinical Research, The Eye Hospital of Wenzhou Medical University, Wenzhou, China
- *Correspondence: Chao Zheng, , orcid org/0000-0003-3814-4643; Guangyun Mao, , orcid.org/0000-0002-4548-7524
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Guo C, Xu Y, Ma Y, Xu X, Peng F, Li HH, Jin D, Zhao SZ, Xia Z, Lai M, Che M, Huang R, Wang Y, Jiang D, Zheng C, Mao G. Individual and joint effects of trehalose and glutamate on diabetic retinopathy: a propensity score-matched case-control study. Endocr Connect 2022; 11:e210474. [PMID: 35029545 PMCID: PMC8859951 DOI: 10.1530/ec-21-0474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 01/14/2022] [Indexed: 11/21/2022]
Abstract
Although previous studies demonstrate that trehalose can help maintain glucose homeostasis in healthy humans, its role and joint effect with glutamate on diabetic retinopathy (DR) remain unclear. We aimed to comprehensively quantify the associations of trehalose and glutamate with DR. This study included 69 pairs of DR and matched type 2 diabetic (T2D) patients. Serum trehalose and glutamate were determined via ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry system. Covariates were collected by a standardized questionnaire, clinical examinations and laboratory assessments. Individual and joint association of trehalose and glutamate with DR were quantified by multiple conditional logistic regression models. The adjusted odds of DR averagely decreased by 86% (odds ratio (OR): 0.14; 95% CI: 0.06, 0.33) with per interquartile range increase of trehalose. Comparing with the lowest quartile, adjusted OR (95% CI) were 0.20 (0.05, 0.83), 0.14 (0.03, 0.63) and 0.01 (<0.01, 0.05) for participants in the second, third and fourth quartiles of trehalose, respectively. In addition, as compared to their counterparts, T2D patients with lower trehalose (<median) and higher glutamate (≥median) had the highest odds of DR (OR: 36.81; 95% CI: 6.75, 200.61). An apparent super-multiplicative effect of trehalose and glutamate on DR was observed, whereas relative excess risk due to interaction was not significant. The study suggests that trehalose is beneficial to inhibit the occurrence of DR and synergistically decreases the risk of DR with reduced glutamate. Our findings also provide new insights into the mechanisms of DR and further longitudinal studies are required to confirm these findings.
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Affiliation(s)
- Chengnan Guo
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yixi Xu
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yange Ma
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Correspondence should be addressed to C Zheng or G Mao: or
| | - Xin Xu
- Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Fang Peng
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Hui-hui Li
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Dongzhen Jin
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shu-zhen Zhao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhezheng Xia
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Mengyuan Lai
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Mingzhu Che
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Ruogu Huang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yanan Wang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Depeng Jiang
- Department of Community Health Sciences, College of Medicine, University of Manitoba, Winnipeg, Canada
| | - Chao Zheng
- The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Correspondence should be addressed to C Zheng or G Mao: or
| | - Guangyun Mao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
- National Clinical Research Center for Ocular Diseases, Wenzhou, Zhejiang, China
- Correspondence should be addressed to C Zheng or G Mao: or
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Izundegui DG, Nayor M. Metabolomics of Type 1 and Type 2 Diabetes: Insights into Risk Prediction and Mechanisms. Curr Diab Rep 2022; 22:65-76. [PMID: 35113332 PMCID: PMC8934149 DOI: 10.1007/s11892-022-01449-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/21/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE OF REVIEW Metabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding. RECENT FINDINGS Findings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses. Metabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.
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Affiliation(s)
| | - Matthew Nayor
- Sections of Cardiology and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, 72 E Concord Street, Suite L-516, Boston, MA, 02118, USA.
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It is time for a moonshot to find “Cures” for diabetic retinal disease. Prog Retin Eye Res 2022; 90:101051. [DOI: 10.1016/j.preteyeres.2022.101051] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 01/19/2022] [Accepted: 01/31/2022] [Indexed: 12/13/2022]
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Jin D, Zhao S, Li H, Xia Z, Che M, Huang R, Lai M, Wang Y, Zhang Z, Wang H, Zuo J, Zheng C, Mao G. Plasma acylcarnitine and diabetic retinopathy: A study from Eastern China. Front Endocrinol (Lausanne) 2022; 13:977428. [PMID: 36387885 PMCID: PMC9646944 DOI: 10.3389/fendo.2022.977428] [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: 06/24/2022] [Accepted: 10/17/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND AND PURPOSE Acylcarnitines (ACars) are important for insulin resistance and type 2 diabetes (T2D). However, their roles in diabetic retinopathy (DR) remain controversial. In this study, we aimed to investigate the association of ACars with DR and their values in DR detection. METHODS This was a two-center case-control study based on the propensity score matching approach between August 2017 to June 2018 in Eastern China. Multivariable logistic regression models were applied to estimate the association of plasma ACars with DR. Differential ACars were screened by models of least absolute shrinkage and selection operator, elastic net, and weighted quantile sum regression, and their roles in DR identification were further evaluated by the area under the receiver operating curve (AUC). RESULTS Eight of twenty plasma ACars (8:0, 12:0, 12:1, 14:1, 16:2, 18:0, 18:2 and 18:3) were associated with DR, while only ACar 8:0 was selected by three variable selection methods. As compared to those with the 1st tertile of ACar 8:0, the adjusted odds ratio (OR) and 95% confidence interval (CI) of DR were 0.22 (0.08, 0.59) and 0.12 (0.04, 0.36) for subjects in the 2nd and 3rd tertiles, respectively (P for trend < 0.001). Consistent associations were also observed in both restricted cubic spline regression models and subgroup analyses. AUC (95% CI) were 0.74 (0.66, 0.82) for ACar 8:0 alone and 0.77 (0.70, 0.85) for ACar 8:0 combined with covariates. CONCLUSIONS Our findings suggest higher ACar 8:0 is significantly associated with a decreased risk of DR, which provides a unique window for early identification of DR.
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Affiliation(s)
- Dongzhen Jin
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Shuzhen Zhao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Huihui Li
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Zhezheng Xia
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Mingzhu Che
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Ruogu Huang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Mengyuan Lai
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Yanan Wang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Zejie Zhang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Hui Wang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
| | - Jingjing Zuo
- Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China
- National Clinical Research Center for Ocular Diseases, Wenzhou Medical University, Wenzhou, China
| | - Chao Zheng
- The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Guangyun Mao, ; Chao Zheng,
| | - Guangyun Mao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China
- Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China
- National Clinical Research Center for Ocular Diseases, Wenzhou Medical University, Wenzhou, China
- *Correspondence: Guangyun Mao, ; Chao Zheng,
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21
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Wang Z, Tang J, Jin E, Ren C, Li S, Zhang L, Zhong Y, Cao Y, Wang J, Zhou W, Zhao M, Huang L, Qu J. Metabolomic comparison followed by cross-validation of enzyme-linked immunosorbent assay to reveal potential biomarkers of diabetic retinopathy in Chinese with type 2 diabetes. Front Endocrinol (Lausanne) 2022; 13:986303. [PMID: 36157454 PMCID: PMC9492931 DOI: 10.3389/fendo.2022.986303] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
PURPOSE To identify the biomarkers in the critical period of development in diabetic retinopathy (DR) in Chinese with type 2 diabetes using targeted and untargeted metabolomics, and to explore the feasibility of their clinical application. METHODS This case-control study described the differential metabolites between 83 Chinese type 2 diabetes mellitus (T2DM) samples with disease duration ≥ 10 years and 27 controls matched cases. Targeted metabolomics using high-resolution mass spectrometry with liquid chromatography was performed on plasma samples of subjects. The results were compared to our previous untargeted metabolomics study and ELISA was performed to validate the mutual differential metabolites of targeted and untargeted metabolomics on plasma. Multiple linear regression analyses were performed to adjust for the significance of different metabolites between groups. RESULT Mean age of the subjects was 66.3 years and mean T2DM duration was 16.5 years. By cross-validating with results from previous untargeted metabolomic assays, we found that L-Citrulline (Cit), indoleacetic acid (IAA), 1-methylhistidine (1-MH), phosphatidylcholines (PCs), hexanoylcarnitine, chenodeoxycholic acid (CDCA) and eicosapentaenoic acid (EPA) were the most distinctive metabolites biomarkers to distinguish the severity of DR for two different metabolomic approaches in our study. We mainly found that samples in the DR stage showed lower serum level of Cit and higher serum level of IAA compared with samples in the T2DM stage, while during the progression of diabetic retinopathy, the serum levels of CDCA and EPA in PDR stage were significantly lower than NPDR stage. Among them, 4 differential key metabolites including Cit, IAA, CDCA and EPA were confirmed with ELISA. CONCLUSION This is the first study to compare the results of targeted and untargeted metabolomics via liquid chromatography-mass spectrometry to find the serum biomarkers which could reflect the metabolic variations among different stages of DR in Chinese. The progression of DR in Chinese at different critical stages was related to the serum levels of specific differential metabolites, of which there is a significant correlation between DR progression and increased IAA and decreased Cit, hexanoylcarnitine, CDCA, and EPA. However, larger studies are needed to confirm our results. Based on this study, it could be inferred that the accuracy of targeted metabolomics for metabolite expression in serum is to some extent higher than that of untargeted metabolomics.
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Affiliation(s)
- Zongyi Wang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jiyang Tang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Enzhong Jin
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Chi Ren
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Siying Li
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Linqi Zhang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yusheng Zhong
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yu Cao
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jianmin Wang
- Department of Ophthalmology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wei Zhou
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Mingwei Zhao
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Lvzhen Huang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
- *Correspondence: Jinfeng Qu, ; Lvzhen Huang,
| | - Jinfeng Qu
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
- *Correspondence: Jinfeng Qu, ; Lvzhen Huang,
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Du X, Yang L, Kong L, Sun Y, Shen K, Cai Y, Sun H, Zhang B, Guo S, Zhang A, Wang X. Metabolomics of various samples advancing biomarker discovery and pathogenesis elucidation for diabetic retinopathy. Front Endocrinol (Lausanne) 2022; 13:1037164. [PMID: 36387907 PMCID: PMC9646596 DOI: 10.3389/fendo.2022.1037164] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 10/10/2022] [Indexed: 11/28/2022] Open
Abstract
Diabetic retinopathy (DR) is a universal microvascular complication of diabetes mellitus (DM), which is the main reason for global sight damage/loss in middle-aged and/or older people. Current clinical analyses, like hemoglobin A1c, possess some importance as prognostic indicators for DR severity, but no effective circulating biomarkers are used for DR in the clinic currently, and studies on the latent pathophysiology remain lacking. Recent developments in omics, especially metabolomics, continue to disclose novel potential biomarkers in several fields, including but not limited to DR. Therefore, based on the overview of metabolomics, we reviewed progress in analytical technology of metabolomics, the prominent roles and the current status of biomarkers in DR, and the update of potential biomarkers in various DR-related samples via metabolomics, including tear as well as vitreous humor, aqueous humor, retina, plasma, serum, cerebrospinal fluid, urine, and feces. In this review, we underscored the in-depth analysis and elucidation of the common biomarkers in different biological samples based on integrated results, namely, alanine, lactate, and glutamine. Alanine may participate in and regulate glucose metabolism through stimulating N-methyl-D-aspartate receptors and subsequently suppressing insulin secretion, which is the potential pathogenesis of DR. Abnormal lactate could cause extensive oxidative stress and neuroinflammation, eventually leading to retinal hypoxia and metabolic dysfunction; on the other hand, high-level lactate may damage the structure and function of the retinal endothelial cell barrier via the G protein-coupled receptor 81. Abnormal glutamine indicates a disturbance of glutamate recycling, which may affect the activation of Müller cells and proliferation via the PPP1CA-YAP-GS-Gln-mTORC1 pathway.
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Affiliation(s)
- Xiaohui Du
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Le Yang
- State Key Laboratory of Dampness Syndrome, the Second Affiliated Hospital Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ling Kong
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ye Sun
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
- State Key Laboratory of Dampness Syndrome, the Second Affiliated Hospital Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Kunshuang Shen
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ying Cai
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Hui Sun
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
- *Correspondence: Hui Sun, ; Xijun Wang,
| | - Bo Zhang
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Sifan Guo
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Aihua Zhang
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xijun Wang
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
- State Key Laboratory of Dampness Syndrome, the Second Affiliated Hospital Guangzhou University of Chinese Medicine, Guangzhou, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, Macau SAR, China
- *Correspondence: Hui Sun, ; Xijun Wang,
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23
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Sun Y, Kong L, Zhang AH, Han Y, Sun H, Yan GL, Wang XJ. A Hypothesis From Metabolomics Analysis of Diabetic Retinopathy: Arginine-Creatine Metabolic Pathway May Be a New Treatment Strategy for Diabetic Retinopathy. Front Endocrinol (Lausanne) 2022; 13:858012. [PMID: 35399942 PMCID: PMC8987289 DOI: 10.3389/fendo.2022.858012] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 03/01/2022] [Indexed: 12/31/2022] Open
Abstract
Diabetic retinopathy is one of the serious complications of diabetes, which the leading causes of blindness worldwide, and its irreversibility renders the existing treatment methods unsatisfactory. Early detection and timely intervention can effectively reduce the damage caused by diabetic retinopathy. Metabolomics is a branch of systems biology and a powerful tool for studying pathophysiological processes, which can help identify the characteristic metabolic changes marking the progression of diabetic retinopathy, discover potential biomarkers to inform clinical diagnosis and treatment. This review provides an update on the known metabolomics biomarkers of diabetic retinopathy. Through comprehensive analysis of biomarkers, we found that the arginine biosynthesis is closely related to diabetic retinopathy. Meanwhile, creatine, a metabolite with arginine as a precursor, has attracted our attention due to its important correlation with diabetic retinopathy. We discuss the possibility of the arginine-creatine metabolic pathway as a therapeutic strategy for diabetic retinopathy.
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Affiliation(s)
- Ye Sun
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ling Kong
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ai-Hua Zhang
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ying Han
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Hui Sun
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guang-Li Yan
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xi-Jun Wang
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, Macau SAR, China
- National Engineering Laboratory for the Development of Southwestern Endangered Medicinal Materials, Guangxi Botanical Garden of Medicinal Plant, Nanning, China
- *Correspondence: Xi-Jun Wang,
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Li X, Cai S, He Z, Reilly J, Zeng Z, Strang N, Shu X. Metabolomics in Retinal Diseases: An Update. BIOLOGY 2021; 10:944. [PMID: 34681043 PMCID: PMC8533136 DOI: 10.3390/biology10100944] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/16/2021] [Accepted: 09/18/2021] [Indexed: 12/17/2022]
Abstract
Retinal diseases are a leading cause of visual loss and blindness, affecting a significant proportion of the population worldwide and having a detrimental impact on quality of life, with consequent economic burden. The retina is highly metabolically active, and a number of retinal diseases are associated with metabolic dysfunction. To better understand the pathogenesis underlying such retinopathies, new technology has been developed to elucidate the mechanism behind retinal diseases. Metabolomics is a relatively new "omics" technology, which has developed subsequent to genomics, transcriptomics, and proteomics. This new technology can provide qualitative and quantitative information about low-molecular-weight metabolites (M.W. < 1500 Da) in a given biological system, which shed light on the physiological or pathological state of a cell or tissue sample at a particular time point. In this article we provide an extensive review of the application of metabolomics to retinal diseases, with focus on age-related macular degeneration (AMD), diabetic retinopathy (DR), retinopathy of prematurity (ROP), glaucoma, and retinitis pigmentosa (RP).
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Affiliation(s)
- Xing Li
- School of Basic Medical Sciences, Shaoyang University, Shaoyang 422000, China; (X.L.); (Z.H.)
| | - Shichang Cai
- Department of Human Anatomy, School of Medicine, Hunan University of Medicine, Huaihua 418000, China;
| | - Zhiming He
- School of Basic Medical Sciences, Shaoyang University, Shaoyang 422000, China; (X.L.); (Z.H.)
| | - James Reilly
- Department of Biological and Biomedical Sciences, Glasgow Caledonian University, Glasgow G4 0BA, UK;
| | - Zhihong Zeng
- College of Biological and Environmental Engineering, Changsha University, Changsha 410022, China;
| | - Niall Strang
- Department of Vision Science, Glasgow Caledonian University, Glasgow G4 0BA, UK;
| | - Xinhua Shu
- School of Basic Medical Sciences, Shaoyang University, Shaoyang 422000, China; (X.L.); (Z.H.)
- Department of Biological and Biomedical Sciences, Glasgow Caledonian University, Glasgow G4 0BA, UK;
- Department of Vision Science, Glasgow Caledonian University, Glasgow G4 0BA, UK;
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Zhao S, Jin D, Wang S, Xu Y, Li H, Chang Y, Ma Y, Xu Y, Guo C, Peng F, Huang R, Lai M, Xia Z, Che M, Zuo J, Jiang D, Zheng C, Mao G. Serum ω-6/ω-3 polyunsaturated fatty acids ratio and diabetic retinopathy: A propensity score matching based case-control study in China. EClinicalMedicine 2021; 39:101089. [PMID: 34611616 PMCID: PMC8478674 DOI: 10.1016/j.eclinm.2021.101089] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/25/2021] [Accepted: 07/28/2021] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Optimal ω-6/ω-3 polyunsaturated fatty acids ratio (PUFAR) is reported to exert protective effects against chronic diseases. However, data on PUFAR and diabetic retinopathy (DR) remains scarce. We aimed to thoroughly quantify whether and how PUFAR was related to DR as well as its role in DR detection. METHODS This two-centre case-control study was conducted from August 2017 to June 2018 in China, participants were matched using a propensity score matching algorithm. We adopted multivariable logistic regression models and restricted cubic spline analyses to estimate the independent association of PUFAR with DR, adjusting for confounders identified using a directed acyclic graph. The value of PUFAR as a biomarker for DR identification was further evaluated by receiver operating characteristic analyses and Hosmer-Lemeshow tests. FINDINGS An apparent negative relationship between PUFAR and DR was observed. Adjusted odds of DR decreased by 79% (OR: 0·21, 95% CI: 0·10-0·40) with an interquartile range increase in PUFAR. Similar results were also obtained in tertile analysis. As compared to those in the 1st tertile of PUFAR, the adjusted odds of DR decreased by 76% (OR: 0·24, 95% CI: 0·08-0·66) and 93% (OR: 0·07, 95% CI: 0·03-0·22) for subjects in the 2nd and 3rd tertiles, respectively. Good calibration and discrimination of the PUFAR associated predictive model were detected and PUFAR = 35 would be an ideal cut-off value for DR identification. INTERPRETATION Our results suggest that serum PUAFR is inversely associated with DR. Although PUFAR-alteration is not observed amongst different stages of DR, it can serve as an ideal biomarker in distinguishing patients with DR from those without DR. FUNDING This study was funded by Natural Science Foundation of Zhejiang Province, Zhejiang Basic Public Welfare Research Project, the Major Project of the Eye Hospital of Wenzhou Medical University, and the Academician's Science and Technology Innovation Program in Zhejiang province. Part of this work was also funded by the National Nature Science Foundation of China, and Research Project for College Students in Wenzhou Medical University.
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Affiliation(s)
- Shuzhen Zhao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Dongzhen Jin
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shengyao Wang
- The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yanping Xu
- The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Huihui Li
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yujie Chang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yange Ma
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yixi Xu
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Chengnan Guo
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Fang Peng
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Ruogu Huang
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Mengyuan Lai
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhezheng Xia
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Mingzhu Che
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Jingjing Zuo
- Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
- National Clinical Research Center for Ocular Diseases, Wenzhou, Zhejiang, China
| | - Depeng Jiang
- Department of Community Health Sciences, College of Medicine, University of Manitoba, Winnipeg, Canada
| | - Chao Zheng
- The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
- The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Corresponding author.
| | - Guangyun Mao
- Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Centre on Evidence-Based Medicine & Clinical Epidemiological Research, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Eye Hospital and School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
- National Clinical Research Center for Ocular Diseases, Wenzhou, Zhejiang, China
- Corresponding author at: Division of Epidemiology and Health Statistics, Department of Preventive Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, Zhejiang, China.
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