Hsa_circRNA_102682 is closely related to lipid metabolism in gestational diabetes mellitus. (2nd January 2022)

• Record Type: Journal Article
• Authors: Wu, Hangyu; Zheng, Xufeng; Liu, Yan; Shen, Jun; Ye, Mei; Zhang, Yisheng
• Is Part Of: Gynecological endocrinology. Volume 38:Number 1(2022)
• Page Start: 50
• Page End: 54
• Publication Date: 2022-01-02
• Subjects: Hsa_circRNA_102682 -- circular RNA -- gestational diabetes mellitus -- lipid metabolism -- biomarker; Endocrine gynecology -- Periodicals; Generative organs, Female -- Diseases -- Periodicals; 618.1
• DOI: 10.1080/09513590.2021.1991911
• Languages: English
• ISSNs: 0951-3590

Abstract

Abstract: Objective: To explore the relationship between circular RNA (circRNA) in gestational diabetes mellitus (GDM) and the metabolic profile at the molecular level, and find a biological marker that can predict GDM early. Methods: A retrospective case–control study was conducted using data and samples from women treated at a hospital in China between January 10 2018 and February 20 2019. Reverse transcription polymerase chain reaction (qRT-PCR) was used to evaluate the expression level of hsa_circRNA_102682 in serum and analyze its correlation with lipid metabolism parameters. Results: Advanced age and higher pre-pregnancy body mass index (BMI) during pregnancy are risk factors for GDM. The expression level of hsa_circ_102682 was lower among the cases than the controls ( p =.000). The levels of triglyceride, apolipoprotein A1 (APOA1), APOB, and high-density lipoprotein cholesterol (HDL-C) were different between the controls and cases ( p <.05). Hsa_circRNA_102682 was significantly correlated with triglycerides, APOA1, APOB, 1-h blood glucose in the serum of GDM patients, and the correlation coefficients were 0.319, 0.314, 0.286, and 0.311, respectively ( p <.05). The area under the receiver operating characteristic curve is 0.684 (95% confidence interval 0.611–0.756, p =.0001). Conclusions: Hsa_circRNA_102682 may regulate lipid metabolism, participate in the pathogenesis of GDM. It can be used as a marker to predict GDM.