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

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

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1628156

DOI=10.3389/fmed.2025.1628156

ISSN=2296-858X

ABSTRACT=IntroductionLeukocyte 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.AimThis 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 methodsIn 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 (n = 44) and patients who did not develop PCS (n = 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.ResultsWe 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; p = 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 (p = 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 D3, 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.ConclusionShorter 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.