ArticleEndocrine connections2020
Association of n-6 PUFAs with the risk of diabetic retinopathy in diabetic patients.
Article in Endocrine connections, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Association between omega-6 fatty acids and diabetic retinopathy risk: a systematic review and meta-analysis.Nutrition & diabetes · 2026Pooled it
- Dietary and Formulation Potential of Natural Oils and Fats in Ocular Health and Disease: Mechanisms, Evidence, and Future Directions.Nutrients · 2026Review
- [Establishment and application of a knowledge-directed pseudo-targeted analytical method for diabetic retinopathy].Se pu = Chinese journal of chromatography · 2026Article
- Article
- Associations of abdominal obesity and plasma fatty acids with microvascular diseases.Communications medicine · 2026Article
- Relationship between free fatty acids and diabetic retinopathy in male patients with type 2 diabetes.Scientific reports · 2025Article
- Nutritional Approach to Diabetic Sarcopenia: A Comprehensive Review.Current nutrition reports · 2025Review
- Deciphering the role of oleic acid in diabetic retinopathy: an empirical analysis of monounsaturated fatty acids.Nutrition & metabolism · 2024Article
- Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Article
- Polyunsaturated fatty acids and diabetic microvascular complications: a Mendelian randomization study.Frontiers in endocrinology · 2024Article
- Mendelian Randomization Analysis Reveals Causal Effects of Polyunsaturated Fatty Acids on Subtypes of Diabetic Retinopathy Risk.Nutrients · 2023Article
- Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study.Nutrition & diabetes · 2022Article
- Individual and joint effects of trehalose and glutamate on diabetic retinopathy: a propensity score-matched case-control study.Endocrine connections · 2022Article
- Metabolomic comparison followed by cross-validation of enzyme-linked immunosorbent assay to reveal potential biomarkers of diabetic retinopathy in Chinese with type 2 diabetes.Frontiers in endocrinology · 2022Article
- Plasma acylcarnitine and diabetic retinopathy: A study from Eastern China.Frontiers in endocrinology · 2022Article
- Serum Untargeted Metabolomics Reveal Potential Biomarkers of Progression of Diabetic Retinopathy in Asians.Frontiers in molecular biosciences · 2022Article
- Chinmedomics Strategy for Elucidating the Pharmacological Effects and Discovering Bioactive Compounds From Keluoxin Against Diabetic Retinopathy.Frontiers in pharmacology · 2022Article
- Serum ω-6/ω-3 polyunsaturated fatty acids ratio and diabetic retinopathy: A propensity score matching based case-control study in China.EClinicalMedicine · 2021Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic retinopathy (DR), the most common microvascular complication of diabetes and leading cause of visual impairment in adults worldwide, is suggested to be linked to abnormal lipid metabolism. The present study aims to comprehensively investigate the relationship between n-6 polyunsaturated fatty acids (PUFAs) and DR. This was a propensity score matching based case-control study, including 69 pairs of DR patients and type 2 diabetic patients without DR with mean age of 56.7 ± 9.2 years. Five n-6 PUFAs were determined by UPLC-ESI-MS/MS system. Principle component regression (PCR) and multiple conditional logistic regression models were used to investigate the association of DR risk with n-6 PUFAs depending on independent training and testing sets, respectively. According to locally weighted regression model, we observed obvious negative correlation between levels of five n-6 PUFAs (linoleic acid, γ-linolenic acid, eicosadienoic acid, dihomo-γ-linolenic acid and arachidonicacid) and DR. Based on multiple PCR model, we also observed significant negative association between the five n-6 PUFAs and DR with adjusted OR (95% CI) as 0.62 (0.43,0.87). When being evaluated depending on the testing set, the association was still existed, and PCR model had excellent classification performance, in which area under the curve (AUC) was 0.88 (95% CI: 0.78, 0.99). In addition, the model also had valid calibration with a non-significant Hosmer-Lemeshow Chi-square of 9.44 (P = 0.307) in the testing set. n-6 PUFAs were inversely associated with the presence of DR, and the principle component could be potential indicator in distinguishing DR from other T2D patients.
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