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2型糖尿病患者白细胞端粒长度和糖化血红蛋白与新冠后综合征的关联:一项横断面试点研究

Association of leukocyte telomere length and HbA1c with post-COVID-19 syndrome in type 2 diabetes: a cross-sectional pilot study.

作者信息

Matviichuk Anton, Krasnienkov Dmytro, Yerokhovych Viktoriia, Ilkiv Yeva, Korcheva Veronika, Gurbych Oleksandr, Shcherbakova Anna, Botsun Pavlina, Falalyeyeva Tetyana, Sulaieva Oksana, Kobyliak Nazarii

机构信息

Endocrinology Department, Bogomolets National Medical University, Kyiv, Ukraine.

Laboratory of Epigenetics, Institute of Gerontology Academy of Medical Sciences of Ukraine, Kyiv, Ukraine.

出版信息

Front Med (Lausanne). 2025 Aug 29;12:1628156. doi: 10.3389/fmed.2025.1628156. eCollection 2025.

Abstract

INTRODUCTION

Leukocyte telomere length is considered a promising prognostic marker associated with COVID-19 severity, adverse outcomes (hospital admission, need for critical care, and respiratory support), and mortality. However, the contribution of telomere length to post-COVID-19 syndrome (PCS) development is unclear.

AIM

This study aimed to evaluate the association between telomere shortening and the course of PCS in patients with type 2 diabetes (T2D) and to determine whether telomere length is linked to clinical phenotype, gender, and biological age.

MATERIALS AND METHODS

In this cross-sectional study, 66 T2D patients who had recovered from COVID-19 were enrolled. Patients were divided into two groups depending on PCS development: the PCS group ( = 44) and patients who did not develop PCS ( = 22) within 6 months after COVID-19 infection. Relative telomere length was determined using the standardized method proposed by Cawthon et al. A range of machine learning models was developed for PCS prediction. These models underwent training utilizing a cross-validation approach, as well as internal validation.

RESULTS

We observed a significantly lower mean of telomere length in T2D patients with PCS as compared to those without it (1.09 ± 0.19 and 1.28 ± 0.24;  = 0.001). In the sub-analysis, shorter telomeres were observed in female patients and patients of older age in both groups. The mean telomere length did not differ significantly among clinical phenotypes of PCS ( = 0.193). The best model generated for PCS prediction was the gradient boosting machine (GBM), which achieved an AUC of 0.753. The most influential variables across the top 10 models included telomere length, HbA1c, vitamin D, waist circumference, ApoA1, C peptide, ApoB, COVID-19 severity, duration of T2D, IL-6, cholesterol, BMI, and age. Leukocyte telomere length and HbA1c exhibited significantly greater impact than other features.

CONCLUSION

Shorter telomere length and higher HbA1c levels were significantly associated with the presence of PCS in our cohort of individuals with T2D. These factors may represent potential biomarkers that warrant further investigation.

摘要

引言

白细胞端粒长度被认为是一种有前景的预后标志物,与新冠病毒病(COVID-19)的严重程度、不良结局(住院、重症监护需求和呼吸支持)及死亡率相关。然而,端粒长度对COVID-19后综合征(PCS)发展的作用尚不清楚。

目的

本研究旨在评估2型糖尿病(T2D)患者端粒缩短与PCS病程之间的关联,并确定端粒长度是否与临床表型、性别及生物学年龄相关。

材料与方法

在这项横断面研究中,纳入了66例从COVID-19中康复的T2D患者。根据PCS的发生情况将患者分为两组:PCS组(n = 44)和在COVID-19感染后6个月内未发生PCS的患者(n = 22)。采用Cawthon等人提出的标准化方法测定相对端粒长度。开发了一系列机器学习模型用于PCS预测。这些模型采用交叉验证方法进行训练,并进行内部验证。

结果

我们观察到,与未发生PCS的T2D患者相比(1.09 ± 0.19和1.28 ± 0.24;P = 0.001),发生PCS的T2D患者端粒长度的平均值显著更低。在亚组分析中,两组中的女性患者和年龄较大的患者端粒较短。PCS的临床表型之间平均端粒长度无显著差异(P = 0.193)。为PCS预测生成的最佳模型是梯度提升机(GBM),其曲线下面积(AUC)为0.753。前10个模型中最具影响力的变量包括端粒长度、糖化血红蛋白(HbA1c)、维生素D、腰围、载脂蛋白A1(ApoA1)、C肽、载脂蛋白B(ApoB)、COVID-19严重程度、T2D病程、白细胞介素-6(IL-6)、胆固醇、体重指数(BMI)和年龄。白细胞端粒长度和HbA1c的影响显著大于其他特征。

结论

在我们的T2D患者队列中,较短的端粒长度和较高的HbA1c水平与PCS的存在显著相关。这些因素可能代表值得进一步研究的潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3f2/12425890/7543a399b610/fmed-12-1628156-g001.jpg

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