Transcriptomic Dysregulation of Inflammation-Related Genes in Leukocytes of Patients with Gestational Diabetes Mellitus (GDM) during and after Pregnancy: Identifying Potential Biomarkers Relevant to Glycemic Abnormality.

Abstract

Although the immune system has been implicated in the pathophysiology of gestational diabetes mellitus (GDM) and postpartum abnormal glucose tolerance (AGT), little is known about the transcriptional response of inflammation-related genes linked to metabolic phenotypes of GDM women during and after pregnancy, which may be potential diagnostic classifiers for GDM and biomarkers for predicting AGT. To address these questions, gene expression of IL6, IL8, IL10, IL13, IL18, TNFA, and the nuclear factor κB (NFκB)/RELA transcription factor were quantified in leukocytes of 28 diabetic women at GDM diagnosis (GDM group) and 1-year postpartum (pGDM group: 10 women with AGT and 18 normoglycemic women), using a nested RT-PCR method. Control pregnancies with normal glucose tolerance (NGT group; n = 31) were closely matched for maternal age, gestational age, pre-pregnancy BMI, pregnancy weight, and gestational weight gain. Compared with the NGT group, IL8 was downregulated in the GDM group, and IL13 and RELA were upregulated in the pGDM group, whereas IL6, IL10, and IL18 were upregulated in the GDM and pGDM groups. The TNFA level did not change from pregnancy to postpartum. Associations of some cytokines with glycemic measures were detected in pregnancy (IL6 and RELA) and postpartum (IL10) (p < 0.05). Receiver operating characteristic (ROC) curves showed that IL6, IL8, and IL18, if employed alone, can discriminate GDM patients from NGT individuals at GDM diagnosis, with the area under the ROC curves (AUCs) of 0.844, (95% CI 0.736−0.953), 0.771 (95% CI 0.651−0.890), and 0.714 (95% CI 0.582−0.846), respectively. By the logistic regression method, we also identified a three-gene panel (IL8, IL13, and TNFA) for postpartum AGT prediction. This study demonstrates a different transcriptional response of the studied genes in clinically well-characterized women with GDM at GDM diagnosis and 1-year postpartum, and provides novel transcriptomic biomarkers for future efforts aimed at diagnosing GDM and identifying the high risk of postpartum AGT groups.