Erythrocyte microvesicles and cell-free nucleic acids as biomarkers of gestational diabetes in the third trimester: A comparative study

Authors

  • М.D. Toylybaeva
  • T.M. Tleubaeva
  • А.D. Uvasheva
  • D.E. Omertaeva Karaganda Medical University
  • М.М. Mugazov
  • Zh.T. Amirbekova

DOI:

https://doi.org/10.37800/RM.4.2025.607

Keywords:

erythrocyte microvesicles , cell-free nucleic acids, biomarkers, gestational diabetes mellitus , pregnancy complications

Abstract

Relevance: Gestational diabetes mellitus (GDM) affects 7-14% of pregnancies, causing hyperglycemia with maternal (cesarean, preeclampsia) and fetal (macrosomia, hypoglycemia) risks, plus long-term type 2 diabetes and offspring obesity. Pathogenesis involves oxidative stress, inflammation, and apoptosis. Erythrocyte microvesicles (EMVs), cell-free nucleic acids (cfNAs: DNA, RNA, CRF), and advanced oxidation protein products (AOPP) reflect these processes but are underexplored as biomarkers in GDM without preeclampsia/hypertension.

The study aimed to evaluate the diagnostic/prognostic value of EMVs, cfNAs, and AOPP in GDM (no preeclampsia/hypertension) in the third trimester and correlate them with clinical parameters.

Materials and Methods: This cross-sectional study included 24 GDM women (IADPSG criteria, 28-40 weeks) and 24 matched healthy controls from Karaganda Perinatal Centers (2020-2025). Blood was processed for plasma/erythrocytes, and the samples were stored at -80°C. EMVs were quantified by flow cytometry (CD235a); cfNAs by fluorescence; AOPP by spectrophotometry. Statistical analysis included t-tests and Mann-Whitney tests, Pearson correlations, and ROC analysis (p < 0.05).

Results: Groups matched for gestational age (34.2 vs. 33.5 weeks, p = 0.552); GDM older (31.4 vs. 25.2 years, p = 0.010). GDM had higher BP (SBP 145 vs. 110 mmHg; DBP 95 vs. 72 mmHg, p < 0.001) but normal proteinuria. EMVs were elevated (44.3 vs. 15.0 units/mL, p < 0.001). Erythrocyte DNA (0.0203 vs. 0.0109 a.u., p < 0.001), RNA (0.0147 vs. 0.0033 a.u., p = 0.014); CRF lower (0.0057 vs. 0.0250 a.u., p = 0.004). Plasma DNA trended higher (p = 0.092). AOPP increased (0.258 vs. 0.170 a.u., p = 0.001). Correlations: EMV-erythrocyte DNA (r = 0.62), EMV-glucose (r = 0.55), DNA-HOMA-IR (r = 0.46). ROC: EMV AUC 0.90 (sensitivity – 88%, specificity – 83%); erythrocyte DNA AUC 0.87 (sensitivity – 85%, specificity – 80%).

Conclusion: Elevated EMVs, erythrocyte cfNAs, and AOPP in uncomplicated GDM highlight metabolic stress/inflammation, showing strong diagnostic potential. A combination may improve early detection/monitoring.

References

1. Paulo MS, Abdo NM, Bettencourt-Silva R, Al-Rifai RH. Gestational Diabetes Mellitus in Europe: A Systematic Review and Meta-Analysis of Prevalence Studies. Front Endocrinol (Lausanne). 2021;12:691033.

https://doi.org/10.3389/fendo.2021.691033

2. Мейрамова Т., Мурзашева Г., Омертаева Д., Мугазов М., Алпысова А., Матаева Л. Биомаркеры окислительного стресса у беременных в третьем триместре: предикторы тяжелой хронической артериальной гипертензии (оригинальное исследование). Репродуктивная медицина (Центральная Азия). 2025;2:133-143.

Meiramova T, Murzasheva G, Omertayeva D, Mugazov M, Alpysova A, Matayeva L. Biomarkers of oxidative stress in pregnant women in the third trimester: Predictors of severe chronic arterial hypertension (original research). Reproductive Medicine (Central Asia). 2025;2:133-143. Russian.

https://doi.org/10.37800/RM.2.2025.497

3. Pinto Y, Frishman S, Turjeman S, Eshel A, Nuriel-Ohayon M, Shrossel O, Ziv O, Walters W, Parsonnet J, Ley C, Johnson EL, Kumar K, Schweitzer R, Khatib S, Magzal F, Muller E, Tamir S, Tenenbaum-Gavish K, Rautava S, Salminen S, Isolauri E, Yariv O, Peled Y, Poran E, Pardo J, Chen R, Hod M, Borenstein E, Ley RE, Schwartz B, Louzoun Y, Hadar E, Koren O. Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis. Gut. 2023;72(5):918-928.

https://doi.org/10.1136/gutjnl-2022-328406

4. Ye D, Huang J, Wu J, Xie K, Gao X, Yan K, Zhang P, Tao Y, Li Y, Zang S, Rong X, Li J, Guo J. Integrative metagenomic and metabolomic analyses reveal gut microbiota-derived multiple hits connected to development of gestational diabetes mellitus in humans. Gut Microbes. 2023;15(1):2154552.

https://doi.org/10.1080/19490976.2022.2154552

5. Tranidou A, Tsakiridis I, Apostolopoulou A, Xenidis T, Pazaras N, Mamopoulos A, Athanasiadis A, Chourdakis M, Dagklis T. Prediction of Gestational Diabetes Mellitus in the First Trimester of Pregnancy Based on Maternal Variables and Pregnancy Biomarkers. Nutrients. 2023;16(1):120.

https://doi.org/10.1007/s40618-020-01464-6

6. Fonseca L, Saraiva M, Amado A, Paredes S, Pichel F, Pinto C, Vilaverde J, Dores J. Third trimester HbA1c and the association with large-for-gestational-age neonates in women with gestational diabetes. Arch Endocrinol Metab. 2021;65(3):328-335.

https://doi.org/10.20945/2359-3997000000366

7. Nguyen Dao V, Lee AH, Zhang X, Wang L, Damm P, Mathiesen ER. Cell-free DNA methylation as a predictive biomarker in gestational diabetes mellitus. Brief Bioinform. 2024;25(1):bbad492.

https://doi.org/10.1093/bib/bbad492

8. Nguyen Dao V, Zhang X, Lee AH, Wang L, Damm P, Mathiesen ER. Machine learning-based prediction of gestational diabetes using cell-free DNA. Cell Rep Med. 2024;5(8):101660.

https://doi.org/10.1016/j.xcrm.2024.101660

9. Pan Y, Gu R, Li Q, Wang J, Zhang Y, Zhao L, Wu Y, Wei L. Glycated albumin levels in the third trimester of women with gestational diabetes mellitus are associated with adverse pregnancy-related outcomes. BMC Pregnancy Childbirth. 2024;24(1):774.

https://doi.org/10.1186/s12884-024-06994-y

10. Hromadnikova I, Kotlabova K, Krofta L. Cardiovascular Disease-Associated MicroRNAs as Novel Biomarkers of First-Trimester Screening for Gestational Diabetes Mellitus in the Absence of Other Pregnancy-Related Complications. Int J Mol Sci. 2022;23(18):10635.

https://doi.org/10.3390/ijms231810635

11. Lu W, Luo M, Fang X, Zhang R, Li S, Tang M, Yu X, Hu C. Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population. Nutr Metab (Lond). 2021;18(1):79

https://doi.org/10.1186/s12986-021-00606-8

12. Zhang TN, Wang W, Huang XM, Gao SY. Non-Coding RNAs and Extracellular Vehicles: Their Role in the Pathogenesis of Gestational Diabetes Mellitus. Front Endocrinol (Lausanne). 2021;12:664287.

https://doi.org/10.3389/fendo.2021.664287

13. Al-Ofi E, Alrafiah A, Maidi S, Almaghrabi S, Hakami N. Altered Expression of Angiogenic Biomarkers in Pregnancy Associated with Gestational Diabetes. Int J Gen Med. 2021;14:3367-3375.

https://doi.org/10.2147/IJGM.S316670

14. Milionis C, Ilias I, Lekkou A, Venaki E, Koukkou E. Future clinical prospects of C-peptide testing in the early diagnosis of gestational diabetes. World J Exp Med. 2024;14(1):89320.

https://doi.org/10.5493/wjem.v14.i1.89320

15. Xu M, Tang L, Wang Y. Fluctuation trend of inflammatory indexes related to gestational diabetes mellitus from second trimester to third trimester of pregnancy. BMC Pregnancy Childbirth. 2024;24(1):665.

https://doi.org/10.1186/s12884-024-06846-9

16. Faurø KK, Obel LM, Christesen HT, Jensen DM, Jensen TK, Glintborg D, Andersen MS, Overgaard M. Apolipoprotein Profile in Early Pregnancy and the Link to Gestational Diabetes Mellitus: Insights From Odense Child Cohort. Endocr Pract. 2025;31(6):805-812.

https://doi.org/10.1016/j.eprac.2025.02.009

17. Тайжанова Д., Зубков Д., Комличенко Э., Магалов И., Сорокина М., Амирбекова Ж., Турдунова Г., Беспалова Н., Майданова З. Оценка параметров коагулограммы для прогнозирования потери беременности на ранних сроках. Репродуктивная медицина (Центральная Азия). 2024;3:82-91.

Taizhanova D, Zubkov D, Komlichenko E, Magalov I, Sorokina M, Amirbekova Zh, Turdunova G, Bespalova N, Maidanova Z. Evaluation of coagulogram parameters for predicting early pregnancy loss. Reproductive Medicine (Central Asia). 2024;3:82-91. Russian.

https://doi.org/10.37800/RM.3.2024.82-91

18. James-Allan LB, Whitley GS, Leslie K, Wallace AE, Cartwright JE. Placental extracellular vesicles in normal and diabetic pregnancy. Placenta. 2021;102:46-53.

https://doi.org/10.1016/j.placenta.2020.09.008

19. Омертаева Д., Мугазов М., Вазенмиллер Д., Шыхалиева К., Кайбасова А. Влияние показателей среднего объема тромбоцитов, среднего объема эритроцитов и гемоглобина на риск развития тяжелой преэклампсии у беременных женщин. Репродуктивная медицина (Центральная Азия). 2024;4:75-80.

Omertayeva D, Mugazov M, Vazenmiller D, Shykhaliyeva K, Kaibassova A. Mean platelet volume, corpuscular volume, and hemoglobin levels impact the risk of severe preeclampsia in pregnancy. Reproductive Medicine (Central Asia). 2024;4:75-80. Russian.

https://doi.org/10.37800/RM.4.2024.412

20. Salomon C, Rice GE, Jansson T, Nair S, Jayabalan N. Exosomes in pregnancy: a new frontier for biomarker discovery. Mol Ther. 2022;30(5):1905-1920.

https://doi.org/10.1016/j.ymthe.2022.03.008

21. James-Allan LB, Whitley GS, Leslie K, Wallace AE, Cartwright JE. Placental extracellular vesicles in normal and diabetic pregnancy. Placenta. 2021;102:46-53.

https://doi.org/10.1016/j.placenta.2020.09.008

Downloads

Published

30.12.2025

How to Cite

Toylybaeva М., Tleubaeva , T., Uvasheva А., Omertaeva, D., Mugazov М., & Amirbekova, Z. (2025). Erythrocyte microvesicles and cell-free nucleic acids as biomarkers of gestational diabetes in the third trimester: A comparative study. Reproductive Medicine (Central Asia) , (4), 149–158. https://doi.org/10.37800/RM.4.2025.607

Most read articles by the same author(s)

1 2 3 > >> 

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.