Circulating LncRNA Serve as Fingerprint for Gestational Diabetes Mellitus Associated with Risk of Macrosomia

• Published in: Cellular physiology and biochemistry Vol. 48; no. 3; pp. 1012 - 1018
• Main Authors: Lu, Jianfeng, Wu, Jinbao, Zhao, Ziyu, Wang, Jinmei, Chen, Zhong
• Format: Journal Article
• Language: English
• Published: Basel, Switzerland S. Karger AG 01.08.2018; Cell Physiol Biochem Press GmbH & Co KG
• Subjects: Adult; Area Under Curve; Biomarker; Biomarkers; Biomarkers - blood; Candidates; Case-Control Studies; Childrens health; Diabetes; Diabetes, Gestational - blood; Diabetes, Gestational - diagnosis; Female; Fetal Macrosomia - diagnosis; Fetal Macrosomia - etiology; Gestational diabetes; Glucose; Glucose Tolerance Test; Glycated Hemoglobin A - analysis; Gynecology; Humans; Insulin; Liver cancer; Lncrna; Macrosomia; Metastasis; Obstetrics; Original Paper; Plasma; Pregnancy; Pregnancy Complications; Risk Factors; RNA, Long Noncoding - blood; ROC; ROC Curve; Umbilical cord; Womens health; United States > US; Plasma; Lncrna; Biomarker; ROC; Macrosomia
• ISSN: 1015-8987; 1421-9778
• DOI: 10.1159/000491969

Abstract Background/Aims: Fetal macrosomia and its associated complications are the most frequent and serious morbidities for infants associated with gestational diabetes mellitus (GDM). The aim of this study was to evaluate the lncRNAs involvement in GDM, especially for the prediction of risk for fetal overgrowth. Methods: The peripheral blood obtained from four group including healthy control (NC), healthy volunteers with pregnancy (NC-P), GDM patients with and without macrosomia were screened by lncRNA microarray and validated by quantitative real-time PCR (RT-qPCR) arranged in the training and a two-stage validation sets. The positive and negative prediction ability for candidate lncRNAs were analyzed by risk score analysis. Results: A multiple venny analysis was performed revealed five candidate lncRNA including XLOC_014172, RP11-230G5.2, PCBP1-AS1, LOC149086 and RP11-160H22.5 which was consistence with the following parameter: i, increased in GDM patients with macrosomia (GDM-M) comparing with patients without macrosomia; ii, increased in GDM-M comparing with NC-P group; iii, increased in GDM-M comparing with NC. Further validation found XLOC_014172 and RP11-230G5.2 was final consistence with these parameter in 150 samples each group. Further receiver operating characteristic curve (ROC) analysis, with the combined two stably expressed lncRNAs indicated a high diagnostic ability an area under ROC curve value (AUC) of 0.955 and 0.962 in training set and validation set respectively. Conclusions: Circulating XLOC_014172 and RP11-230G5.2 may act as novel biomarkers in GDM patients as fingerprint for the risk of macrosomia outcome.