Progress in Research on Biomarkers of Gestational Diabetes Mellitus and Preeclampsia

Yang Liu; Dan Yang Li; Alayi Bolatai; Na Wu

doi:10.2147/DMSO.S433179

Progress in Research on Biomarkers of Gestational Diabetes Mellitus and Preeclampsia

Diabetes Metab Syndr Obes. 2023 Nov 22:16:3807-3815. doi: 10.2147/DMSO.S433179. eCollection 2023.

Authors

Yang Liu¹, Dan Yang Li¹, Alayi Bolatai², Na Wu^{1

3}

Affiliations

¹ Department of Endocrinology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People' s Republic of China.
² Department of Student Affairs, Affiliated Hospital of China Medical University, Shenyang, Liaoning, People' s Republic of China.
³ Medical Department, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People' s Republic of China.

Abstract

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common complications in pregnancy, with incidence rates of 1-5% and 9.4%, respectively, in China. Both these phenomena can cause adverse pregnancy outcomes and are extremely harmful to the mother and fetus. In this study, we observed that several predictive factors have important value in GDM and PE. Among the GDM group, abnormal levels of adiponectin (APN), C-reactive protein (CRP), and Leptin were observed. The coexistence of PE and GDM in the pregnant population is not uncommon. Ultimately, we discovered abnormal levels of factors such as Visfatin, Advanced oxidative protein product (AOPP), Fibroblast growth factor 21 (FGF21), and resistin in both GDM and PE groups. Particularly, the FGF21 factor holds significant importance in our research. Therefore, we need to complete the analysis and discussion of relevant predictive factors to enable early prediction and disease monitoring of GDM, PE, and other pregnancy-related disorders, ultimately contributing to the long-term health of pregnant women.

Keywords: gestational diabetes mellitus; predictor of the GDM and PE; preeclampsia.

Publication types

Review

Grants and funding

This research was funded by the National Natural Science Foundation of China, grant number 81700706; the Virtual Simulation Experiment Teaching Project of China Medical University, grant number 2020-47; the 345 Talent Project of Shengjing Hospital; the Natural Science Foundation of Liaoning Province, grant number 2021-MS-182; the Science Foundation of Liaoning Education Department, grant number LK201603; and the Clinical Research Project of Liaoning Diabetes Medical Nutrition Prevention Society, grant number LNSTNBYXYYFZXH-RS01B.