甲基丙二酸与膳食复合抗氧化指数与糖尿病视网膜病变的关系：来自全国健康与营养检查调查的数据。

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2025-06-03 DOI:10.1186/s12986-025-00953-w

Xue Pan

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The combined effect of MMA and CDAI on DR risk was also explored.Results: A total of 2,373 patients with diabetes were included and 547 (20.48%) patients had DR. MMA levels ≥ 250 nmol/L (OR = 1.47, 95%CI: 1.01-2.13) (vs. <250 nmol/L) were associated with higher odds of DR in patients with diabetes, whereas there was no significant difference in the effect of CDAI >-0.5 and CDAI ≤-0.5 on DR risk (P > 0.05). There was an interaction between MMA and CDAI that increased the risk of DR (OR = 2.24, 95%CI: 1.15-4.35; Pinteraction=0.018), and this interaction was only in patients with a CDAI ≤-0.5. 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引用次数: 0

摘要

背景：氧化应激和线粒体功能障碍在糖尿病视网膜病变（DR）中起重要作用，血清甲基丙二酸（MMA）水平与氧化应激和线粒体功能障碍有关。我们旨在探讨MMA水平和膳食复合抗氧化指数（CDAI）对糖尿病患者发生DR风险的影响。方法：将1999-2004年和2011-2014年国家健康与营养调查（NHANES）数据集中的糖尿病患者数据纳入本横断面研究。采用Logistic回归分析（考虑NHANES调查权重）探讨MMA（-0.5,≤-0.5）与DR风险的相关性，并以比值比（OR）和95%置信区间（CI）报告相关性。并探讨了MMA和CDAI对DR风险的联合影响。结果：共纳入2373例糖尿病患者，547例（20.48%）患者DR MMA水平≥250 nmol/L (OR = 1.47, 95%CI: 1.01 ~ 2.13) (DR风险vs -0.5和CDAI≤-0.5)（P < 0.05）。MMA和CDAI之间的相互作用增加了DR的风险(OR = 2.24, 95%CI: 1.15-4.35；p交互作用=0.018)，且这种交互作用仅发生在CDAI≤-0.5的患者中。亚组分析显示，2例患者（OR = 2.26, 95%CI: 1.11 ~ 4.61）、高血压患者（OR = 2.13, 95%CI: 1.04 ~ 4.36）和使用降糖药患者（OR = 2.42, 95%CI: 1.13 ~ 5.20）存在MMA与CDAI的相互作用。结论：MMA和CDAI之间存在相互作用，可增加DR的风险，而CDAI在这种关联中起调节作用。

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Association between methylmalonic acid and composite dietary antioxidant index and diabetic retinopathy: data from National Health and Nutrition Examination Survey.

Background: Oxidative stress and mitochondrial dysfunction play an important role in diabetic retinopathy (DR), and serum methylmalonic acid (MMA) levels are related to oxidative stress and mitochondrial dysfunction. We aimed to explore the impact of MMA levels and the composite dietary antioxidant index (CDAI) on DR risk in patients with diabetes.

Methods: Data on patients with diabetes from the 1999-2004 and 2011-2014 National Health and Nutrition Examination Survey (NHANES) datasets were included in this cross-sectional study. Logistic regression analysis (accounting for NHANES survey weights) was used to explore the association of MMA (< 250, ≥ 250 nmol/L) and CDAI (>-0.5, ≤-0.5) with DR risk, and the association was reported as odds ratio (OR) and 95% confidence interval (CI). The combined effect of MMA and CDAI on DR risk was also explored.

Results: A total of 2,373 patients with diabetes were included and 547 (20.48%) patients had DR. MMA levels ≥ 250 nmol/L (OR = 1.47, 95%CI: 1.01-2.13) (vs. <250 nmol/L) were associated with higher odds of DR in patients with diabetes, whereas there was no significant difference in the effect of CDAI >-0.5 and CDAI ≤-0.5 on DR risk (P > 0.05). There was an interaction between MMA and CDAI that increased the risk of DR (OR = 2.24, 95%CI: 1.15-4.35; P_interaction=0.018), and this interaction was only in patients with a CDAI ≤-0.5. Subgroup analysis revealed that the interaction between MMA and CDAI was observed in patients < 65 years of age (OR = 5.43, 95%CI: 1.80-16.36), with a body mass index ≥ 25 kg/m² (OR = 2.26, 95%CI: 1.11-4.61), with hypertension (OR = 2.13, 95%CI: 1.04-4.36), and with anti-diabetic drug use (OR = 2.42, 95%CI: 1.13-5.20).

Conclusion: There is an interaction between MMA and CDAI that increases the risk of DR, and CDAI plays a moderating role in this association.

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.