不同体成分的糖尿病患者心血管危险标志物谱的变化

IF 1 Q4 PRIMARY HEALTH CARE
Aratrika Sau, Nivedita Nanda, Jayaprakash Sahoo, S Velkumary
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引用次数: 0

摘要

背景:尽管接受了治疗,2型糖尿病(T2D)患者仍有发生心血管疾病(CVD)的风险。肥胖是胰岛素抵抗和心血管疾病的单独危险因素。脂肪因子脂素与肥胖、胰岛素抵抗和炎症有关。心脏型脂肪酸结合蛋白(FABP3)可预防代谢综合征。此前,在接受治疗的糖尿病患者中,脂肪素和FABP3与身体成分之间的联系尚未得到解决。因此,在本研究中,我们基于亚洲肥胖标准,比较了高BMI和正常BMI的t2dm患者的FABP3、脂肪素水平及其与炎症和体成分的关系。材料与方法:采用ELISA法测定Adipsin和FABP3。身体成分被数字记录在生理学系。采用单因素方差分析(one-way-ANOVA)与健康对照进行比较。结果:高BMI t2dm组Adipsin、TNF α显著升高,FABP3显著降低。正常的BMI T2D有明显的中心性肥胖,这解释了他们较高的脂肪素水平。结论:T2D患者表现出不同的CVD风险特征,与不同水平的脂肪素和FABP3等标志物相关。与单独的BMI相比,身体脂肪分布的差异可以更好地解释这一点。治疗的目标应该是基于新的标志物和身体成分的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Variation in cardiovascular risk marker profile in treated diabetes mellitus patients with different body composition.

Background: Despite treatment, patients with type 2 diabetes mellitus (T2D) are at risk of cardiovascular disease (CVD). Obesity is a separate risk factor of insulin resistance and CVD. The adipokine adipsin links adiposity, insulin resistance and inflammation. Heart type fatty acid binding protein (FABP3) protects against metabolic syndrome. Previously, the link between adipsin and FABP3 with body composition in diabetes patients on treatment has not been addressed. Therefore, in the present study, we have compared the levels of FABP3, adipsin, and their association with inflammation and body composition in T2D patients with high and normal BMI based on the Asian criteria of obesity.

Materials and methods: Adipsin and FABP3 were estimated by ELISA. Body composition was digitally recorded in Department of Physiology. Comparison was done by one-way-ANOVA against healthy controls.

Results: Adipsin and TNF α were significantly increased, while FABP3 was decreased in high BMI T2D than healthy control. Normal BMI T2D had significant central obesity which explains their higher adipsin level.

Conclusion: T2D patients exhibit different CVD risk profile linked to different levels markers such as adipsin and FABP3. This is explained better by the difference in body fat distribution compared to BMI alone. The treatment should target improvement based on new markers and body composition.

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