ArticlePloS one2020
Metabolomics profiles associated with diabetic retinopathy in type 2 diabetes patients.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
49 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Blood metabolome of cardiovascular disease, diabetic kidney disease, and diabetic retinopathy in type 2 diabetes patients: A systematic review and meta-analysis.Endocrine research · 2025Pooled it
- Effects of RIPC on the Metabolome in Patients Undergoing Vascular Surgery: A Randomized Controlled Trial.Biomolecules · 2022Trial
- Artificial intelligence in diabetic retinopathy: from automated screening to risk-stratified care.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Review
- Biomarkers in Diabetic Kidney Disease: Early Detection, Prognostic Assessment, and Integration with Multi-Omics Signatures.Life (Basel, Switzerland) · 2026Review
- [Establishment and application of a knowledge-directed pseudo-targeted analytical method for diabetic retinopathy].Se pu = Chinese journal of chromatography · 2026Article
- Metabolic Dysfunction and Inflammation in Diabetic Retinopathy: Insights From Metabolomics and Cytokine Analysis.Mediators of inflammation · 2026Article
- Metabolomic biomarkers in vitreous humor: unveiling the molecular landscape of diabetic retinopathy progression.International journal of retina and vitreous · 2025Article
- Identifying therapeutic target genes for diabetic retinopathy using systematic druggable genome-wide Mendelian randomization.Diabetology & metabolic syndrome · 2025Article
- Insights into the molecular underpinning of type 2 diabetes complications.Human molecular genetics · 2025Review
- Association between dietary niacin intake and diabetic retinopathy in a Catalonian population: a cross-sectional study.Frontiers in nutrition · 2025Article
- New insights of potential biomarkers in diabetic retinopathy: integrated multi-omic analyses.Frontiers in endocrinology · 2025Review
- Aqueous Humor Metabolomics in Different Stages of Diabetic Retinopathy Based on Ultra - Performance Liquid Chromatography - Tandem Mass Spectrometry.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Dysregulation of amino acids balance as potential serum-metabolite biomarkers for diagnosis and prognosis of diabetic retinopathy: a metabolomics study.Journal of diabetes and metabolic disorders · 2024Article
- Therapeutic Effects of Taurine and Histidine Supplementation in Retinal Diseases.Life (Basel, Switzerland) · 2024Review
- Metabolomic Hallmarks of Obesity and Metabolic Dysfunction-Associated Steatotic Liver Disease.International journal of molecular sciences · 2024Review
- Analysis of metabolites associated with ADIPOQ genotypes in individuals with type 2 diabetes mellitus.Scientific reports · 2024Article
- Steps to understanding diabetes kidney disease: a focus on metabolomics.The Korean journal of internal medicine · 2024Review
- Indoxyl sulfate induces retinal microvascular injury via COX-2/PGEJournal of translational medicine · 2024Article
- Identification of key biomarkers for early warning of diabetic retinopathy using BP neural network algorithm and hierarchical clustering analysis.Scientific reports · 2024Article
- Hybrid Explainable Artificial Intelligence Models for Targeted Metabolomics Analysis of Diabetic Retinopathy.Diagnostics (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic retinopathy (DR) is a common complication of diabetes, and it is the consequence of microvascular retinal changes due to high glucose levels over a long time. Metabolomics profiling is a rapidly evolving method used to identify the metabolites in biological fluids and investigate disease progression. In this study, we used a targeted metabolomics approach to quantify the serum metabolites in type 2 diabetes (T2D) patients. Diabetes patients were divided into three groups based on the status of their complications: non-DR (NDR, n = 143), non-proliferative DR (NPDR, n = 123), and proliferative DR (PDR, n = 51) groups. Multiple logistic regression analysis and multiple testing corrections were performed to identify the significant differences in the metabolomics profiles of the different analysis groups. The concentrations of 62 metabolites of the NDR versus DR group, 53 metabolites of the NDR versus NPDR group, and 30 metabolites of the NDR versus PDR group were found to be significantly different. Finally, sixteen metabolites were selected as specific metabolites common to NPDR and PDR. Among them, three metabolites including total DMA, tryptophan, and kynurenine were potential makers of DR progression in T2D patients. Additionally, several metabolites such as carnitines, several amino acids, and phosphatidylcholines also showed a marker potential. The metabolite signatures identified in this study will provide insight into the mechanisms underlying DR development and progression in T2D patients in future studies.
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