Maternal Lipids as Strong Determinants of Fetal Environment and Growth in Pregnancies With Gestational Diabetes Mellitus

Jovanovska

et al. 2016

Prilozi

Aim: During diabetic pregnancy, complex metabolic changes occur in the lipid profile. The aim of the study was to determine the predictive values of maternal serum lipid levels on large-for-gestational age newborns during the third trimester in pregnancies of women with type 2 diabetes mellitus (DM2) and gestational diabetes mellitus (GDM). Material and methods: Data of forty three pregnancies of women with DM2 and two hundred women with GDM were analyzed. The analysis encompassed the following parameters: age, body mass index (BMI), lipid parameters, HbA1c in first, second and third trimester of pregnancy, preeclampsia and baby birth weight. Results: DM2 and GDM groups showed statistically significant differences in the following variables: total lipids, triglycerides, total cholesterol, BMI, age, baby birth weight, incidence of SGA and preterm delivery (9.4 ± 2.3 vs. 11.0 ± 2.3 mmol/L, 2.4 ± 1.4 vs. 3.4 ± 1.6 mmol/L, 5.5 ± 1.2 vs. 6.4 ± 1.4 mmol/L, 30.6 ± 5.4 vs. 26.9 ± 5.2 kg/m 2 , 34 ± 7.8 vs. 31.5 ± 5.6 years, 3183 ± 972 vs. 3533 ± 699 g., 20% vs. 7.5%, 27.9 vs. 14%, respectively, p < 0.05). Linear multiple regression analysis demonstrated that triglycerides, LDL-C and total cholesterol were independent predictors of LGA (p < 0.05). Conclusion: Triglycerides and LDL-C in the third trimester of pregnancy are independent predictors for fetal macrosomia in DM2 and GDM pregnancies. Thus, the maternal serum triglycerides and LDL-C levels determined in the maternal blood taken in the third trimester of pregnancy may indentify women who will give birth to LGA newborns.

Section: Discussionsupporting

confidence: 81%

Maternal Lipids May Predict Fetal Growth in Type 2 Diabetes Mellitus and Gestational Diabetes Mellitus Pregnancies

Jovanovska

et al. 2016

Prilozi

“…Furthermore, Black et al recently demonstrated that the risk for adverse pregnancy outcomes differs between women with impaired fasting glucose and abnormal glucose values during the OGTT, providing evidence that women with elevated fasting levels particularly suffer from delivering LGA infants [28]. Our results might corroborate this important observation as the presented risk algorithm, which uses a maximum of information from the FPG measurement, was strongly associated with postnatal macrosomia, even when the model was adjusted for other OGTT values and moreover for GDM status as well as other variables associated with macrosomia of the offspring, such as preconception BMI [29] or maternal triacylglycerol levels [30,31].…”

Section: Discussionsupporting

confidence: 79%

A two-step screening algorithm including fasting plasma glucose measurement and a risk estimation model is an accurate strategy for detecting gestational diabetes mellitus

et al. 2012

Aims/hypothesis It is currently not clear how to construct a time-and cost-effective screening strategy for gestational diabetes mellitus (GDM). Thus, we elaborated a simple screening algorithm combining (1) fasting plasma glucose (FPG) measurement; and (2) a multivariable risk estimation model focused on individuals with normal FPG levels to decide if a further OGTT is indicated. Methods A total of 1,336 women were prospectively screened for several risk factors for GDM within a multicentre study conducted in Austria. Of 714 women (53.4%) who developed GDM using recent diagnostic guidelines, 461 were sufficiently screened with FPG. A risk prediction score was finally developed using data from the remaining 253 women with GDM and 622 healthy women. The screening algorithm was validated with a further 258 pregnant women.Results A risk estimation model including history of GDM, glycosuria, family history of diabetes, age, preconception dyslipidaemia and ethnic origin, in addition to FPG, was accurate for detecting GDM in participants with normal FPG. Including an FPG pretest, the receiver operating Diabetologia (2012) 55:3173-3181 DOI 10.1007/s00125-012-2726 characteristic AUC of the screening algorithm was 0.90 (95% CI 0.88, 0.91

“…In this study, the BMI of the fathers was similar in both groups. Overall, these findings suggest that maternal obesity impacts on offspring glucose homoeostasis, but also raises the potential importance of other nutrients in pregnancy regulated by insulin such as triglycerides, free fatty acids and amino acids which also regulate foetal growth (Schaefer-Graf et al 2008).…”

Section: Glucose/insulin Homoeostasis and Pancreatic Functionmentioning

confidence: 98%

Impact of maternal obesity on offspring obesity and cardiometabolic disease risk

Drake¹,

Reynolds²

2010

Reproduction

445

308

The prevalence of obesity among pregnant women is increasing. In addition to the short-term complications of obesity during pregnancy in both mother and child, it is now recognised that maternal obesity has long-term adverse outcomes for the health of her offspring in later life. Evidence from both animal and human studies indicates that maternal obesity increases the risk for the offspring in developing obesity and altering body composition in child-and adulthood and, additionally, it also has an impact on the offspring's cardiometabolic health with dysregulation of metabolism including glucose/insulin homoeostasis, and development of hypertension and vascular dysfunction. Potential mechanisms include effects on the development and function of adipose tissue, pancreas, muscle, liver, the vasculature and the brain. Further studies are required to elucidate the mechanisms underpinning the programming of disease risk in the offspring as a consequence of maternal obesity. The ultimate aim is to identify potential targets, which may be amenable to prevention or early intervention in order to improve the health of this and future generations.