Objective To describe the metabolic characteristics of gestational diabetes mellitus (GDM) and assess their effects on perinatal outcomes. Methods A two-center nested case‒control study was designed, including 192 pregnant women with GDM and 191 pregnant women with normal glucose tolerance (NGT). Serum glucose and insulin concentrations based upon the 75 g oral glucose tolerance test (OGTT) were measured. Several indices were calculated to describe the metabolic characteristics of the subjects. The relationship between glucose metabolism parameters and pregnancy outcomes was evaluated using stepwise linear regression and binary logistic regression. Results Compared with the NGT group, the GDM group showed significantly higher fasting and postprandial glucose parameters but significantly lower fasting and postprandial insulin responses. Meanwhile, the GDM group had significantly lower HOMA-β, DI and ISI Matsuda but comparable HOMA-IR. The IFG subgroup showed significantly lower FINS/FPG only, while the IGT and IFSG subgroups showed deficiency in both fasting and postprandial insulin response. The IFSG subgroup had the highest glucose parameters and the lowest insulin parameters, as well as significantly lower ISI Matsuda and HOMA-β than the NGT group. FPG had a significant effect on infants’ birth weight, and 1hPG and FINS/FPG had a significant effect on delivery gestational age. AUC-INS, IGI 60 and DI were related to premature delivery risk after adjusting for confounders. The IFG subgroup of GDM was 2.319 times more likely to be subject to cesarean section than the NGT group. FPG, FINS/FPG, AUC-GLU, AUC-INS/AUC-GLU and HOMA-β were related to macrosomia risk. Conclusion Beta cell dysfunction rather than insulin resistance determines the occurrence of GDM in the central Chinese population. Women with predominant insulin secretion defects had a similar risk of adverse perinatal outcomes to women with NGT. Our study provided a basis for the selection of glucose metabolism monitoring indicators useful for the prevention of adverse perinatal outcomes.
Background Gestational diabetes mellitus (GDM) is the most common complication during pregnancy, occurring under the combined action of environmental and genetic factors. Genetic variants of glucagon-like peptide-1 receptor (GLP-1R) have been reported to affect insulin secretion and susceptibility to type 2 diabetes. This study aimed to explore the role of GLP-1R polymorphisms in GDM and glucose metabolism. Methods A two-center nested case‒control study was designed, including 200 pregnant women with GDM and 200 pregnant women without GDM genotyped for five tag SNPs of GLP-1R using Sanger sequencing. Logistic regression was used to evaluate the relationship between GLP-1R polymorphisms and GDM risk. Glucose and insulin concentrations were measured based upon the 75 g oral glucose tolerance test (OGTT). Beta cell function of different genotypes was estimated with the 60 min insulinogenic index (IGI60) and OGTT-derived disposition index (DI). Results Mutant genotype AG + GG of tag SNP rs6458093 nominally increased GDM risk (p = 0.049), especially among subjects younger than 35 years (p = 0.024) and with BMI no less than 24 (p = 0.041), after adjusting for confounders. Meanwhile, compared with subjects with wild genotype AA, subjects with genotype AG + GG of rs6458093 also showed nominally significantly lower IGI60 (p = 0.032) and DI (p = 0.029), as well as significantly higher 75 g OGTT-based 1 h glucose load plasma glucose levels (p = 0.045). Moreover, the mutant heterozygous genotype GA of tag SNP rs3765467 nominally decreased GDM risk among subjects older than 35 years (p = 0.037) but showed no association with insulin secretion and glucose homeostasis. Conclusions Tag SNP rs6458093 of GLP-1R was nominally associated with increased GDM risk and affected beta cell function and postprandial glucose metabolism, while tag SNP rs3765467 of GLP-1R was nominally associated with decreased GDM risk, providing evidence for molecular markers and etiological study of GDM.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.