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Brian T Layden1, Sudha K Yalamanchi1, Thomas MS Wolever2, Andrea Dunaif1, William L Lowe Jr11Division of Endocrinology, Metabolism and Molecular Medicine (BTL, SKY, AD, WLL), Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; 2Department of Nutritional Sciences (TMSW), University of Toronto, Toronto, CanadaBackground: The composition of gut flora has been proposed as a cause of obesity, a major risk factor for type 2 diabetes. The objective of this study was to assess whether serum short chain fatty acids, a major by-product of fermentation in gut flora, are associated with obesity and/or diabetes-related traits (insulin sensitivity and secretion).Methods: The association of serum short chain fatty acids levels with measures of obesity was assessed using body mass index, computerized tomography scan, and dual photon X-ray absorptiometry scan. Insulin sensitivity and insulin secretion were both determined from an oral glucose tolerance test and insulin sensitivity was also determined from a hyperinsulinemic euglycemic clamp.Results: In this population of young, obese women, acetate was negatively associated with visceral adipose tissue determined by computerized tomography scan and dual photon X-ray absorptiometry scan, but not body mass index. The level of the short chain fatty acids acetate, but not propionate or butyrate, was also negatively associated with fasting serum insulin and 2 hour insulin levels in the oral glucose tolerance test.Conclusions: In this population, serum acetate was negatively associated with visceral adipose tissue and insulin levels. Future studies need to verify these findings and expand on these observations in larger cohorts of subjects.Keywords: obesity, insulin, gut flora, short chain fatty acids

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P

Maternal metabolites influence the size of newborns independently of maternal body mass index (BMI) and glycemia, highlighting the importance of maternal metabolism on offspring outcomes. This study examined associations of maternal metabolites during pregnancy with childhood adiposity, and cord blood metabolites with childhood adiposity using phenotype and metabolomic data from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and the HAPO Follow-Up Study. The maternal metabolites analyses included 2324 mother–offspring pairs, while the cord blood metabolites analyses included 937 offspring. Multiple logistic and linear regression were used to examine associations between primary predictors, maternal or cord blood metabolites, and childhood adiposity outcomes. Multiple maternal fasting and 1 hr metabolites were significantly associated with childhood adiposity outcomes in Model 1 but were no longer significant after adjusting for maternal BMI and/or maternal glycemia. In the fully adjusted model, fasting lactose levels were negatively associated with child BMI z-scores and waist circumference, while fasting urea levels were positively associated with waist circumference. One-hour methionine was positively associated with fat-free mass. There were no significant associations between cord blood metabolites and childhood adiposity outcomes. Few metabolites were associated with childhood adiposity outcomes after adjusting for maternal BMI and glucose, suggesting that maternal BMI accounts for the association between maternal metabolites and childhood adiposity. [ABSTRACT FROM AUTHOR]

Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26–30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done. [ABSTRACT FROM AUTHOR]

The in utero environment is important for newborn size at birth, which is associated with childhood adiposity. We examined associations between maternal metabolite levels and newborn birthweight, sum of skinfolds (SSF), and cord C-peptide in a multinational and multi-ancestry cohort of 2337 mother–newborn dyads. Targeted and untargeted metabolomic assays were performed on fasting and 1 h maternal serum samples collected during an oral glucose tolerance test performed at 24–32 week gestation in women participating in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Anthropometric measurements were obtained on newborns at birth. Following adjustment for maternal BMI and glucose, per-metabolite analyses demonstrated significant associations between maternal metabolite levels and birthweight, SSF, and cord C-peptide. In the fasting state, triglycerides were positively associated and several long-chain acylcarnitines were inversely associated with birthweight and SSF. At 1 h, additional metabolites including branched-chain amino acids, proline, and alanine were positively associated with newborn outcomes. Network analyses demonstrated distinct clusters of inter-connected metabolites significantly associated with newborn phenotypes. In conclusion, numerous maternal metabolites during pregnancy are significantly associated with newborn birthweight, SSF, and cord C-peptide independent of maternal BMI and glucose, suggesting that metabolites in addition to glucose contribute to newborn size at birth and adiposity. [ABSTRACT FROM AUTHOR]

The integration of genetics and metabolomics data demands careful accounting of complex dependencies, particularly when modelling familial omics data, e.g., to study fetal programming of related maternal–offspring phenotypes. Efforts to identify genetically determined metabotypes using classic genome wide association approaches have proven useful for characterizing complex disease, but conclusions are often limited to a series of variant–metabolite associations. We adapt Bayesian network models to integrate metabotypes with maternal–offspring genetic dependencies and metabolic profile correlations in order to investigate mechanisms underlying maternal–offspring phenotypic associations. Using data from the multiethnic Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, we demonstrate that the strategic specification of ordered dependencies, pre-filtering of candidate metabotypes, incorporation of metabolite dependencies, and penalized network estimation methods clarify potential mechanisms for fetal programming of newborn adiposity and metabolic outcomes. The exploration of Bayesian network growth over a range of penalty parameters, coupled with interactive plotting, facilitate the interpretation of network edges. These methods are broadly applicable to integration of diverse omics data for related individuals. [ABSTRACT FROM AUTHOR]

The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines. [ABSTRACT FROM AUTHOR]

Context: Gestational diabetes is associated with a long-term risk of developing a disorder of glucose metabolism. However, neither the metabolic changes characteristic of gestational diabetes in a large, multi-ancestry cohort nor the ability of metabolic changes during pregnancy, beyond glucose levels, to identify women at high risk for progression to a disorder of glucose metabolism has been examined.Objective: This work aims to identify circulating metabolites present at approximately 28 weeks' gestation associated with gestational diabetes mellitus (GDM) and development of a disorder of glucose metabolism 10 to 14 years later.Methods: Conventional clinical and targeted metabolomics analyses were performed on fasting and 1-hour serum samples following a 75-g glucose load at approximately 28 weeks' gestation from 2290 women who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Postpartum metabolic traits included fasting and 2-hour plasma glucose following a 75-g glucose load, insulin resistance estimated by the homeostasis model assessment of insulin resistance, and disorders of glucose metabolism (prediabetes and type 2 diabetes) during the HAPO Follow-Up Study.Results: Per-metabolite analyses identified numerous metabolites, ranging from amino acids and carbohydrates to fatty acids and lipids, before and 1-hour after a glucose load that were associated with GDM as well as development of a disorder of glucose metabolism and metabolic traits 10 to 14 years post partum. A core group of fasting and 1-hour metabolites mediated, in part, the relationship between GDM and postpartum disorders of glucose metabolism, with the fasting and 1-hour metabolites accounting for 15.7% (7.1%-30.8%) and 35.4% (14.3%-101.0%) of the total effect size, respectively. For prediction of a postpartum disorder of glucose metabolism, the addition of circulating fasting or 1-hour metabolites at approximately 28 weeks' gestation showed little improvement in prediction performance compared to clinical factors alone.Conclusion: The results demonstrate an association of multiple metabolites with GDM and postpartum metabolic traits and begin to define the underlying pathophysiology of the transition from GDM to a postpartum disorder of glucose metabolism. [ABSTRACT FROM AUTHOR]

Objective: Excessive childhood adiposity is a risk factor for adverse metabolic health. The objective was to investigate associations of newborn body composition and cord C-peptide with childhood anthropometrics and explore whether these newborn measures mediate associations of maternal midpregnancy glucose and BMI with childhood adiposity.Research Design and Methods: Data on mother/offspring pairs (N = 4,832) from the epidemiological Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and HAPO Follow-up Study (HAPO FUS) were analyzed. Linear regression was used to study associations between newborn and childhood anthropometrics. Structural equation modeling was used to explore newborn anthropometric measures as potential mediators of the associations of maternal BMI and glucose during pregnancy with childhood anthropometric outcomes.Results: In models including maternal glucose and BMI adjustments, newborn adiposity as measured by the sum of skinfolds was associated with child outcomes (adjusted mean difference, 95% CI, P value) BMI (0.26, 0.12-0.39, <0.001), BMI z-score (0.072, 0.033-0.11, <0.001), fat mass (kg) (0.51, 0.26-0.76, <0.001), percentage of body fat (0.61, 0.27-0.95, <0.001), and sum of skinfolds (mm) (1.14, 0.43-1.86, 0.0017). Structural equation models demonstrated significant mediation by newborn sum of skinfolds and cord C-peptide of maternal BMI effects on childhood BMI (proportion of total effect 2.5% and 1%, respectively), fat mass (3.1%, 1.2%), percentage of body fat (3.6%, 1.8%), and sum of skinfolds (2.9%, 1.8%), and significant mediation by newborn sum of skinfolds and cord C-peptide of maternal glucose effects on child fat mass (proportion of total association 22.0% and 21.0%, respectively), percentage of body fat (15.0%, 18.0%), and sum of skinfolds (15.0%, 20.0%).Conclusions: Newborn adiposity is independently associated with childhood adiposity and, along with fetal hyperinsulinemia, mediates, in part, associations of maternal glucose and BMI with childhood adiposity. [ABSTRACT FROM AUTHOR]

Hundreds of common genetic variants acting through distinguishable physiologic pathways influence the risk of type 2 diabetes (T2D). It is unknown to what extent the physiology underlying gestational diabetes mellitus (GDM) is distinct from that underlying T2D. In this study of >5,000 pregnant women from three cohorts, we aimed to identify physiologically related groups of maternal variants associated with GDM using two complementary approaches that were based on Bayesian nonnegative matrix factorization (bNMF) clustering. First, we tested five bNMF clusters of maternal T2D-associated variants grouped on the basis of physiology outside of pregnancy for association with GDM. We found that cluster polygenic scores representing genetic determinants of reduced β-cell function and abnormal hepatic lipid metabolism were associated with GDM; these clusters were not associated with infant birth weight. Second, we derived bNMF clusters of maternal variants on the basis of pregnancy physiology and tested these clusters for association with GDM. We identified a cluster that was strongly associated with GDM as well as associated with higher infant birth weight. The effect size for this cluster's association with GDM appeared greater than that for T2D. Our findings imply that the genetic and physiologic pathways that lead to GDM differ, at least in part, from those that lead to T2D. [ABSTRACT FROM AUTHOR]

Objective: Whether hyperglycemia in utero less than overt diabetes is associated with altered childhood glucose metabolism is unknown. We examined associations of gestational diabetes mellitus (GDM) not confounded by treatment with childhood glycemia in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) cohort.Research Design and Methods: HAPO Follow-up Study (FUS) included 4,160 children ages 10-14 years who completed all or part of an oral glucose tolerance test (OGTT) and whose mothers had a 75-g OGTT at ∼28 weeks of gestation with blinded glucose values. The primary predictor was GDM by World Health Organization criteria. Child outcomes were impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and type 2 diabetes. Additional measures included insulin sensitivity and secretion and oral disposition index.Results: For mothers with GDM, 10.6% of children had IGT compared with 5.0% of children of mothers without GDM; IFG frequencies were 9.2% and 7.4%, respectively. Type 2 diabetes cases were too few for analysis. Odds ratios (95% CI) adjusted for family history of diabetes, maternal BMI, and child BMI z score were 1.09 (0.78-1.52) for IFG and 1.96 (1.41-2.73) for IGT. GDM was positively associated with child's 30-min, 1-h, and 2-h but not fasting glucose and inversely associated with insulin sensitivity and oral disposition index (adjusted mean difference -76.3 [95% CI -130.3 to -22.4] and -0.12 [-0.17 to -0.064]), respectively, but not insulinogenic index.Conclusions: Offspring exposed to untreated GDM in utero are insulin resistant with limited β-cell compensation compared with offspring of mothers without GDM. GDM is significantly and independently associated with childhood IGT. [ABSTRACT FROM AUTHOR]

Objective: This study examined associations of maternal glycemia during pregnancy with childhood glucose outcomes in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) cohort.Research Design and Methods: HAPO was an observational international investigation that established associations of maternal glucose with adverse perinatal outcomes. The HAPO Follow-up Study included 4,832 children ages 10-14 years whose mothers had a 75-g oral glucose tolerance test (OGTT) at ∼28 weeks of gestation. Of these, 4,160 children were evaluated for glucose outcomes. Primary outcomes were child impaired glucose tolerance (IGT) and impaired fasting glucose (IFG). Additional outcomes were glucose-related measures using plasma glucose (PG), A1C, and C-peptide from the child OGTT.Results: Maternal fasting plasma glucose (FPG) was positively associated with child FPG and A1C; maternal 1-h and 2-h PG were positively associated with child fasting, 30 min, 1-h, and 2-h PG, and A1C. Maternal FPG, 1-h, and 2-h PG were inversely associated with insulin sensitivity, whereas 1-h and 2-h PG were inversely associated with disposition index. Maternal FPG, but not 1-h or 2-h PG, was associated with child IFG, and maternal 1-h and 2-h PG, but not FPG, were associated with child IGT. All associations were independent of maternal and child BMI. Across increasing categories of maternal glucose, frequencies of child IFG and IGT, and timed PG measures and A1C were higher, whereas insulin sensitivity and disposition index decreased.Conclusions: Across the maternal glucose spectrum, exposure to higher levels in utero is significantly associated with childhood glucose and insulin resistance independent of maternal and childhood BMI and family history of diabetes. [ABSTRACT FROM AUTHOR]

Many common genetic polymorphisms are associated with glycemic traits and type 2 diabetes (T2D), but knowledge about genetic determinants of glycemic traits in pregnancy is limited. We tested genetic variants known to be associated with glycemic traits and T2D in the general population for associations with glycemic traits in pregnancy and gestational diabetes mellitus (GDM). Participants in two cohorts (Genetics of Glucose regulation in Gestation and Growth [Gen3G] and Hyperglycemia and Adverse Pregnancy Outcome [HAPO]) underwent oral glucose tolerance testing at 24-32 weeks' gestation. We built genetic risk scores (GRSs) for elevated fasting glucose and insulin, reduced insulin secretion and sensitivity, and T2D, using variants discovered in studies of nonpregnant individuals. We tested for associations between these GRSs, glycemic traits in pregnancy, and GDM. In both cohorts, the fasting glucose GRS was strongly associated with fasting glucose. The insulin secretion and sensitivity GRSs were also significantly associated with these traits in Gen3G, where insulin measurements were available. The fasting insulin GRS was weakly associated with fasting insulin (Gen3G) or C-peptide (HAPO). In HAPO (207 GDM case subjects), all five GRSs (T2D, fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity) were significantly associated with GDM. In Gen3G (43 GDM case subjects), both the T2D and insulin secretion GRSs were associated with GDM; effect sizes for the other GRSs were similar to those in HAPO. Thus, despite the profound changes in glycemic physiology during pregnancy, genetic determinants of fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity discovered outside of pregnancy influence GDM risk. [ABSTRACT FROM AUTHOR]

Maternal glycemia is a key determinant of birth weight, but recent large-scale genome-wide association studies demonstrated an important contribution of fetal genetics. It is not known whether fetal genotype modifies the impact of maternal glycemia or whether it acts through insulin-mediated growth. We tested the effects of maternal fasting plasma glucose (FPG) and a fetal genetic score for birth weight on birth weight and fetal insulin in 2,051 European mother-child pairs from the Exeter Family Study of Childhood Health (EFSOCH) and the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study. The fetal genetic score influenced birth weight independently of maternal FPG and impacted growth at all levels of maternal glycemia. For mothers with FPG in the top tertile, the frequency of large for gestational age (birth weight ≥90th centile) was 31.1% for offspring with the highest tertile genetic score and only 14.0% for those with the lowest tertile genetic score. Unlike maternal glucose, the fetal genetic score was not associated with cord insulin or C-peptide. Similar results were seen for HAPO participants of non-European ancestry (n = 2,842 pairs). This work demonstrates that for any level of maternal FPG, fetal genetics has a major impact on fetal growth and acts predominantly through independent mechanisms. [ABSTRACT FROM AUTHOR]

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Objective: We used targeted metabolomics to determine associations of maternal BMI and glucose levels with cord blood metabolites and associations of cord blood metabolites with newborn birth weight and adiposity in mother-offspring dyads.Research Design and Methods: Targeted metabolomic assays were performed on cord blood serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American newborns (400 from each ancestry group) whose mothers participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and who had anthropometric measurements at birth.Results: Meta-analysis across the four cohorts demonstrated significant correlation of all cord blood metabolites analyzed with maternal fasting levels of the same metabolites at ∼28 weeks' gestation except for triglycerides, asparagine/aspartate, arginine, and the acylcarnitine C14-OH/C12-DC. Meta-analyses also demonstrated that maternal BMI with or without adjustment for maternal glucose was associated with cord blood metabolites including the branched-chain amino acids and their metabolites as well as phenylalanine. One-hour but not fasting glucose was associated with cord blood 3-hydroxybutyrate and its carnitine ester, a medium-chain acylcarnitine, and glycerol. A number of cord blood metabolites were associated with newborn birth weight and sum of skinfolds, including a negative association of triglycerides and positive association of 3-hydroxybutyrate, its carnitine ester, and serine with both newborn outcomes.Conclusions: Maternal BMI and glycemia are associated with different components of the newborn metabolome, consistent with their independent effects on newborn size at birth. Maternal BMI is associated with a newborn metabolic signature characteristic of insulin resistance and risk of type 2 diabetes in adults. [ABSTRACT FROM AUTHOR]

Objective: We used targeted metabolomics in pregnant mothers to compare maternal metabolite associations with maternal BMI, glycemia, and insulin sensitivity.Research Design and Methods: Targeted metabolomic assays of clinical metabolites, amino acids, and acylcarnitines were performed on fasting and 1-h postglucose serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American mothers (400 from each ancestry group) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and underwent an oral glucose tolerance test at ∼28 weeks gestation.Results: K-means clustering, which identified patterns of metabolite levels across ancestry groups, demonstrated that, at both fasting and 1-h, levels of the majority of metabolites were similar across ancestry groups. Meta-analyses demonstrated association of a broad array of fasting and 1-h metabolites, including lipids and amino acids and their metabolites, with maternal BMI, glucose levels, and insulin sensitivity before and after adjustment for the different phenotypes. At fasting and 1 h, a mix of metabolites was identified that were common across phenotypes or associated with only one or two phenotypes. Partial correlation estimates, which allowed comparison of the strength of association of different metabolites with maternal phenotypes, demonstrated that metabolites most strongly associated with different phenotypes included some that were common across as well as unique to each phenotype.Conclusions: Maternal BMI and glycemia have metabolic signatures that are both shared and unique to each phenotype. These signatures largely remain consistent across different ancestry groups and may contribute to the common and independent effects of these two phenotypes on adverse pregnancy outcomes. [ABSTRACT FROM AUTHOR]

Background: Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/ mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. Results: To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. Conclusions: When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data. [ABSTRACT FROM AUTHOR]

In addition to maternal genes and environmental exposures, variation in fetal imprinted genes could also affect maternal blood pressure during pregnancy. Our objective was to test the associations between polymorphic variants in 16 imprinted genes and maternal mean arterial blood pressures in 1160 DNA trios from 2 established birth cohorts (the Cambridge Baby Growth and Wellbeing Studies) and seek replication in 1367 Hyperglycemia and Adverse Pregnancy Outcome Study participants. Significant univariate associations, all independent of fetal sex, were observed in the Cambridge cohorts, including FAM99A rs1489945 transmitted from the mother (P=2×10-4), DLK1 rs10139403 (mother; P=9×10-4), DLK1 rs12147008 (mother; P=1×10-3), H19 rs217222 (father; P=1×10-3), SNRPN rs1453556 (father; P=1×10-3), IGF2 rs6356 (father; P=1×10-3), and NNAT rs6066671 (father; P=1×10-3). In meta-analysis including additional independent Hyperglycemia and Adverse Pregnancy Outcome Study data, the association with maternally transmitted fetal DLK1 rs10139403 reached genome-wide significance (P=6.3×10-10). With the exception of fetal rs1489945 and rs217222, all of other associations were unidirectional and most were statistically significant. To further explore the significance of these relationships, we developed an allele score based on the univariate findings. The score was strongly associated with maternal blood pressure at 31 weeks (P=4.1×10-8; adjusted r2=5.6%) and 37 weeks of pregnancy (P=1.1×10-4; r2=3.6%), and during the last 2 weeks before parturition (P=1.1×10-10; r2=8.7%). It was also associated with gestational hypertension (odds ratio, 1.54 [range, 1.14-2.09] per allele; P=0.005; 45 cases and 549 controls). These data support the concept that fetal imprinted genes are related to the development of gestational hypertension. [ABSTRACT FROM AUTHOR]

Maternal metabolites and metabolic networks underlying associations between maternal glucose during pregnancy and newborn birth weight and adiposity demand fuller characterization. We performed targeted and nontargeted gas chromatography/mass spectrometry metabolomics on maternal serum collected at fasting and 1 h following glucose beverage consumption during an oral glucose tolerance test (OGTT) for 400 northern European mothers at ∼28 weeks' gestation in the Hyperglycemia and Adverse Pregnancy Outcome Study. Amino acids, fatty acids, acylcarnitines, and products of lipid metabolism decreased and triglycerides increased during the OGTT. Analyses of individual metabolites indicated limited maternal glucose associations at fasting, but broader associations, including amino acids, fatty acids, carbohydrates, and lipids, were found at 1 h. Network analyses modeling metabolite correlations provided context for individual metabolite associations and elucidated collective associations of multiple classes of metabolic fuels with newborn size and adiposity, including acylcarnitines, fatty acids, carbohydrates, and organic acids. Random forest analyses indicated an improved ability to predict newborn size outcomes by using maternal metabolomics data beyond traditional risk factors, including maternal glucose. Broad-scale association of fuel metabolites with maternal glucose is evident during pregnancy, with unique maternal metabolites potentially contributing specifically to newborn birth weight and adiposity. [ABSTRACT FROM AUTHOR]