Serum ω-6/ω-3 polyunsaturated fatty acids ratio and diabetic retinopathy: A propensity score matching based case-control study in China

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.

Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study

“…To avoid various types of bias due to confounding factors or uneven data distribution, PSM was used to match the DR and DM groups according to a 1:1 ratio for age, sex, body mass index (BMI) and glycated hemoglobin (HbA1c), and to match the DM and healthy control groups were matched for age, sex and BMI, and 69 blocks were obtained for inclusion in the analysis. The sample size was sufficient to meet statistical requirements and guarantee the reliability of our findings, and the sample size and power estimations were specifically described in our previous studies [ 14 , 15 ].…”

Plasma acylcarnitine and diabetic retinopathy: A study from Eastern China

“…This was a two-center case-control study, which is a propensity score matching (PSM) based lipidomics study conducted in China between August 2017 and June 2018. Detailed information on this study design and participants can be found in our previous works ( 15 – 17 ). In brief, a total of 195 patients with type 2 diabetes (T2D) patients (83 with DR and 112 without DR) aged over 35 years and free from type 1 diabetes, cardiovascular diseases, cerebrovascular diseases, hyperkalemia, cancers, infectious diseases, or other chronic systemic diseases were recruited from two affiliated hospitals of Wenzhou Medical University and Anhui Medical University.…”

Impact of sarcosine on diabetic retinopathy: Findings based on weighted gene co‐expression network analysis and machine learning techniques

“…Details of the study design, enrolment of participants and other information are reported in our previous work. 10,15,16 Briefly, in this two-centre, PSMbased case-control study, a total of 195 patients with type 2 diabetes (T2D) were enrolled from the departments of endocrinology in the Second Affiliated Hospital of Wenzhou Medical University and the First Affiliated Hospital of Anhui Medical University from August 2017 to June 2018. Among them, 83 cases (T2D with DR) and 112 controls (T2D without DR) were diagnosed by two professional experienced ophthalmologists using clinical diagnostic criteria and fundus examination images.…”

“…1,2 It has been confirmed that DR silently progresses over several years without the individual's awareness, ultimately leading to severe vision impairments and a significant reduction in their overall quality of life. 3 Previous studies have revealed that DR can be detected in more than 35% of patients with diabetes, [4][5][6] and has become a major health problem worldwide, as well as continuously leading to an apparently elevated global disease burden. 7 The exact mechanism of DR remains unclear; however, evidence suggests that several biological processes, including immune response, oxidative stress, metabolic disorders, neuronal apoptosis and the release of inflammatory mediators, play a crucial role in both the initiation and progression of DR. [8][9][10] Weighted gene co-expression network analysis (WGCNA) has become an important, valuable and frequently used bioinformatics analytical approach, 11 after being proposed by Zhang and Horvath in 2005.…”

“…With the prevalence of diabetes experiencing a dramatic increase, coupled with the rapid ageing of the population and longer lifespans for individuals living with diabetes, diabetic retinopathy (DR) has emerged as the leading cause of vision loss and preventable blindness worldwide 1,2 . It has been confirmed that DR silently progresses over several years without the individual's awareness, ultimately leading to severe vision impairments and a significant reduction in their overall quality of life 3 . Previous studies have revealed that DR can be detected in more than 35% of patients with diabetes, 4–6 and has become a major health problem worldwide, as well as continuously leading to an apparently elevated global disease burden 7 .…”