一种用于预测 2 型糖尿病患者并发糖尿病视网膜病变风险的新模型及二甲双胍对氨基酸的影响。

A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids.

机构信息

Department of Obstetrics and Gynecology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.

Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China.

出版信息

Front Endocrinol (Lausanne). 2022 Aug 18;13:985776. doi: 10.3389/fendo.2022.985776. eCollection 2022.

DOI:10.3389/fendo.2022.985776

PMID:36060930

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9434554/

Abstract

OBJECTIVE

This study established a model to predict the risk of diabetic retinopathy (DR) with amino acids selected by partial least squares (PLS) method, and evaluated the effect of metformin on the effect of amino acids on DR in the model.

METHODS

In Jinzhou, Liaoning Province, China, we retrieved 1031 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University. After sorting the amino acids using the PLS method, the top 10 amino acids were included in the model. Multivariate logistic regression was used to analyze the relationship between different amino acids and DR. And then the effects of metformin on amino acids were explored through interaction. Finally, Spearman's rank correlation analysis was used to analyze the correlation between different amino acids.

RESULTS

After sorting by PLS, Gly, Pro, Leu, Lyr, Glu, Phe, Tyr, His, Val and Ser were finally included in the DR risk prediction model. The predictive model after adding amino acids was statistically different from the model that only included traditional risk factors (p=0.001). Metformin had a significant effect on the relationship between DR and 7 amino acids (Gly, Glu, Phe, Tyr, His, Val, Ser, p<0.05), and the population who are not using metformin and have high levels of Glu (OR: 0.44, 95%CI: 0.27-0.71) had an additive protection effect for the occurrence of DR. And the similar results can be seen in high levels of Gly (OR: 0.46, 95%CI: 0.29-0.75), Leu (OR: 0.48, 95%CI: 0.29-0.8), His (OR: 0.46, 95%CI: 0.29-0.75), Phe (OR: 0.24, 95%CI: 0.14-0.42) and Tyr (OR: 0.41, 95%CI: 0.24 -0.68) in population who are not using metformin.

CONCLUSIONS

We established a prediction model of DR by amino acids and found that the use of metformin reduced the protective effect of amino acids on DR developing, suggesting that amino acids as biomarkers for predicting DR would be affected by metformin use.

摘要

目的

本研究采用偏最小二乘法（PLS）筛选氨基酸建立预测糖尿病视网膜病变（DR）风险的模型，并评估二甲双胍对模型中氨基酸对 DR 影响的作用。

方法

在中国辽宁省锦州市，我们从辽宁医科大学第一附属医院检索了 1031 例 2 型糖尿病（T2D）患者。使用 PLS 方法对氨基酸进行排序后，将前 10 个氨基酸纳入模型。采用多变量 logistic 回归分析不同氨基酸与 DR 的关系。然后通过交互作用探索二甲双胍对氨基酸的作用。最后，采用 Spearman 秩相关分析不同氨基酸之间的相关性。

结果

经 PLS 排序后，Gly、Pro、Leu、Lyr、Glu、Phe、Tyr、His、Val 和 Ser 最终纳入 DR 风险预测模型。加入氨基酸后的预测模型与仅包含传统危险因素的模型在统计学上有差异（p=0.001）。二甲双胍对 DR 与 7 种氨基酸（Gly、Glu、Phe、Tyr、His、Val、Ser）之间的关系有显著影响（p<0.05），且不使用二甲双胍且 Glu 水平较高的人群（OR：0.44，95%CI：0.27-0.71）对 DR 的发生有附加保护作用。在高水平 Gly（OR：0.46，95%CI：0.29-0.75）、Leu（OR：0.48，95%CI：0.29-0.8）、His（OR：0.46，95%CI：0.29-0.75）、Phe（OR：0.24，95%CI：0.14-0.42）和 Tyr（OR：0.41，95%CI：0.24-0.68）的人群中也观察到类似的结果，这些人群不使用二甲双胍。