Search

BackgroundAmong people with gestational diabetes mellitus (GDM), there is inter-individual variability in clinical outcomes that appears to be related to factors beyond glycemia. However, the precise factors (information on the unique pathophysiology within a person, environment, and/or context) that may help refine the diagnosis of GDM remain unclear. To determine if a precision medicine approach could refine the diagnosis of GDM, we conducted a systematic review of a variety of potential precision markers analyzed in studies among individuals with GDM.MethodsSystematic literature searches were performed in PubMed (https://pubmed.ncbi.nlm.nih.gov/) and EMBASE (https://www.embase.com) databases from inception to March 2022 for observational studies and controlled trials. Studies were included if they reported data on, and compared outcomes between, individuals with GDM. The following categories of precision markers were included in the current search: non-glycemic biochemical markers (cholesterol, insulin profiles); genetics/genomics or other -omics (proteomics, lipidomics, metabolomics, metagenomics); maternal/fetal anthropometric (eg., maternal BMI, gestational weight gain, fetal biometry ultra-sound measures); clinical risk factors (medical/familial history, prior delivery complicated by macrosomia or a large for gestational age [LGA] neonate); sociocultural or environmental modifiers (diet, smoking, race/ethnicity, socioeconomic status).ResultsWe focused on synthesizing the literature on genetics, -omics, non-glycemic biomarkers, maternal anthropometry/fetal biometry, and clinical/sociocultural risk factors. A total of 5,905 titles and abstracts were screened, 775 underwent full-text review, and 137 studies that included a total of 432,156 GDM cases were synthesized. Of the studies on non-glycemic biomarkers (n=33), lipids and insulin sensitivity/secretion indices were the two most common precision markers, with elevated maternal triglycerides and insulin resistance generally associated with greater risk of LGA and macrosomia. Studies of genetics or other -omics were scarce (n=5); however, differences in genetic variants in adiponectin or adiponutrient genes and non-coding RNAs accounted for variability in perinatal outcomes. The majority of studies (n=77) evaluated maternal anthropometry or fetal biometry as a precision marker, and these studies demonstrate that individuals with adiposity who develop GDM are at a substantially higher risk of LGA or macrosomia than those with GDM and lower adiposity. There were 49 studies evaluating GDM risk factors or sociocultural markers, with only six studies examining multiple risk factors as a composite marker. There were inconsistent findings that GDM risk factors, such as older maternal age, accounted for variation in adverse outcomes.ConclusionsOur review demonstrates that a major gap exists in studies examining non-glycemic biochemical, genetic, or other ‘omic precision markers among individuals with GDM. Given that people meeting current diagnostic criteria for GDM may have different risk profiles, our review identifies several factors (including obesity, insulin resistance, hypertriglyceridemia) that may be useful in risk stratification of GDM, setting the stage for a precision approach to its diagnosis.

Background Higher birthweight is associated with higher adult body mass index (BMI). Alleles that predispose to greater adult adiposity might act in fetal life to increase fetal growth and birthweight. Whether there are fetal effects of recently identified adult metabolically favorable adiposity alleles on birthweight is unknown. Aim We aimed to test the effect on birthweight of fetal genetic predisposition to higher metabolically favorable adult adiposity and compare that with the effect of fetal genetic predisposition to higher adult BMI. Methods We used published genome wide association study data (n = upto 406 063) to estimate fetal effects on birthweight (adjusting for maternal genotype) of alleles known to raise metabolically favorable adult adiposity or BMI. We combined summary data across single nucleotide polymorphisms (SNPs) with random effects meta-analyses. We performed weighted linear regression of SNP-birthweight effects against SNP-adult adiposity effects to test for a dose-dependent association. Results Fetal genetic predisposition to higher metabolically favorable adult adiposity and higher adult BMI were both associated with higher birthweight (3 g per effect allele (95% CI: 1–5) averaged over 14 SNPs; P = 0.002; 0.5 g per effect allele (95% CI: 0–1) averaged over 76 SNPs; P = 0.042, respectively). SNPs with greater effects on metabolically favorable adiposity tended to have greater effects on birthweight (R2 = 0.2912, P = 0.027). There was no dose-dependent association for BMI (R2 = −0.0019, P = 0.602). Conclusions Fetal genetic predisposition to both higher adult metabolically favorable adiposity and BMI is associated with birthweight. Fetal effects of metabolically favorable adiposity-raising alleles on birthweight are modestly proportional to their effects on future adiposity, but those of BMI-raising alleles are not.

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.

ImportanceHigher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, which of these associations are causal remains unclear.ObjectiveTo explore the relation of maternal pre-pregnancy BMI with pregnancy and perinatal outcomes by integrating evidence from three different methods (i.e. multivariable regression, Mendelian randomization, and paternal negative control analyses).DesignTriangulation of multivariable regression, Mendelian randomization and paternal negative control results from up to 14 studies in the MR-PREG collaboration.SettingEurope and North America.ParticipantsUp to 497,932 women of European ancestry.ExposureMaternal pre- or early-pregnancy BMI based on self-reported or measured weight and height.Main outcomes and MeasuresMiscarriage, stillbirth, hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, maternal anaemia, perinatal depression, pre-labour rupture of membranes, induction of labour, caesarean section, preterm birth, small- and large-for-gestational age, low and high birthweight, low Apgar score at 1 and 5 minutes, neonatal intensive care unit admission, and no initiation of breastfeeding.ResultsMultivariable regression, Mendelian randomization and paternal negative control analyses supported an association of higher maternal BMI with lower risk of small-for-gestational age and higher risk of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, large-for-gestational age, and high birthweight. As an example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR: 1.67; 95% CI: 1.64, 1.71 per standard unit in BMI) and Mendelian randomization (OR: 1.58; 95% CI: 1.29, 1.93), which was not seen for paternal BMI (OR: 1.02; 95% CI: 0.99, 1.05). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomization.Conclusions and RelevanceOur findings support a causal role for maternal pre-/early-pregnancy BMI on a range of adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications.KEY POINTSQuestionWhat is the effect of higher maternal pre-/early-pregnancy body mass index (BMI) on adverse pregnancy and perinatal outcomes?FindingsWe found consistent evidence that higher maternal BMI was related to higher risk of gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, and having a large-for-gestational-age baby, lower risk of having a small-for-gestational-age baby, and not related to perinatal depression.MeaningThese findings highlight the importance of supporting women to achieve/maintain a healthy pre-conception BMI to reduce the burden of obstetric and neonatal complications.

The goal of this study was to examine associations of measures of maternal glucose metabolism and blood pressure during pregnancy with blood pressure at follow-up in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) cohort. The HAPO Follow-Up Study included 4747 women who had a 75-g oral glucose tolerance test (OGTT) at ~28 weeks' gestation. Of these, 4572 women who did not have chronic hypertension during their pregnancy or other excluding factors, had blood pressure evaluation 10-14 years after the birth of their HAPO child. Primary outcomes were systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (SBP ≥ 140 and/or DBP ≥ 90 or treatment for hypertension) at follow-up. Blood pressure during pregnancy was associated with all blood pressure outcomes at follow-up independent of glucose and insulin sensitivity during pregnancy. The sum of glucose z-scores was associated with blood pressure outcomes at follow-up but associations were attenuated in models that included pregnancy blood pressure measures. Associations with SBP were significant in adjusted models, while associations with DBP and hypertension were not. Insulin sensitivity during pregnancy was associated with all blood pressure outcomes at follow-up, and although attenuated after adjustments, remained statistically significant (hypertension OR 0.79, 95%CI 0.68-0.92; SBP beta -0.91, 95% CI -1.34 to -0.49; DBP beta -0.50, 95% CI -0.81 to -0.19). In conclusion, maternal glucose values at the pregnancy OGTT were not independently associated with maternal blood pressure outcomes 10-14 years postpartum; however, insulin sensitivity during pregnancy was associated independently of blood pressure, BMI, and other covariates measured during pregnancy.

AIMS/HYPOTHESIS: We aimed to examine associations of newborn anthropometric measures with childhood glucose metabolism with the hypothesis that greater newborn birthweight, adiposity and cord C-peptide are associated with higher childhood glucose levels and lower insulin sensitivity. METHODS: Data from the international, multi-ethnic, population-based Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and the HAPO Follow-Up Study were used. The analytic cohort included 4155 children (mean age [SD], 11.4 [1.2] years; 51.0% male). Multiple linear regression was used to examine associations of primary predictors, birthweight, newborn sum of skinfolds (SSF) and cord C-peptide, from HAPO with continuous child glucose outcomes from the HAPO Follow-Up Study. RESULTS: In an initial model that included family history of diabetes and maternal BMI during pregnancy, birthweight and SSF demonstrated a significant, inverse association with 30 min and 1 h plasma glucose levels. In the primary model, which included further adjustment for maternal sum of glucose z scores from an oral glucose tolerance test during pregnancy, the associations were strengthened, and birthweight and SSF were inversely associated with fasting, 30 min, 1 h and 2 h plasma glucose levels. Birthweight and SSF were also associated with higher insulin sensitivity (Matsuda index) (β = 1.388; 95% CI 0.870, 1.906; p

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.

Background Construction of networks from cross-sectional biological data is increasingly common. Many recent methods have been based on Gaussian graphical modeling, and prioritize estimation of conditional pairwise dependencies among nodes in the network. However, challenges remain on how specific paths through the resultant network contribute to overall ‘network-level’ correlations. For biological applications, understanding these relationships is particularly relevant for parsing structural information contained in complex subnetworks. Results We propose the pair-path subscore (PPS), a method for interpreting Gaussian graphical models at the level of individual network paths. The scoring is based on the relative importance of such paths in determining the Pearson correlation between their terminal nodes. PPS is validated using human metabolomics data from the Hyperglycemia and adverse pregnancy outcome (HAPO) study, with observations confirming well-documented biological relationships among the metabolites. We also highlight how the PPS can be used in an exploratory fashion to generate new biological hypotheses. Our method is implemented in the R package , available at https://github.com/nathan-gill/pps. Conclusions The PPS can be used to probe network structure on a finer scale by investigating which paths in a potentially intricate topology contribute most substantially to marginal behavior. Adding PPS to the network analysis toolkit may enable researchers to ask new questions about the relationships among nodes in network data.

Context Leukocyte telomere length (LTL) is a biomarker of biological aging and is associated with metabolic diseases such as type 2 diabetes. Insufficient maternal vitamin D was associated with increased risk for many diseases and adverse later life outcomes. Objective This study investigates the relationship between vitamin D levels and offspring LTL at early life. Methods This observational, longitudinal, hospital-based cohort study included eligible mother-child pairs from the HAPO Hong Kong Field Centre, with 853 offspring at age 6.96 ± 0.44 (mean ± SD) years. LTL was measured using real-time polymerase chain reaction while serum vitamin D metabolites 25(OH)D2, 25(OH)D3, and 3-epi-25(OH)D3 were measured in maternal blood (at gestation 24-32 weeks) and cord blood by liquid chromatography–mass spectrometry. Results LTL at follow-up was significantly shorter in boys compared with girls (P Conclusion Our findings suggest 25(OH)D3 and 3-epi-25(OH)D3 in utero may impact on childhood LTLs, highlighting a potential link between maternal vitamin D and biological aging.

Data availability: Our study uses two-sample MR. We used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data: journal-published and website summary data were used for sample one of the two-sample MR (published GWAS of BMI and body fat percentage). The references to the published data sources are provided in the main paper. The data for the GWAS of BMI are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files. The data for the GWAS of body fat percentage are available at https://walker05.u.hpc.mssm.edu. We used individual participant data for the second MR sample and for undertaking sensitivity analyses from the UKB, ALSPAC, BiB, EFSOCH and HAPO cohorts. The data in UKB, ALSPAC and BiB are fully available, via managed systems, to any researchers. The managed system for both studies is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. Researchers have to pay for a dataset to be prepared for them. Full information on how to access UKB data can be found at www.ukbiobank.ac.uk/using-the-resource/. The ALSPAC data management plan (www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-management-plan.pdf) describes, in detail, the policy regarding data sharing, which is through a system of managed open access. The following steps highlight how to apply for access to the data included in this paper and all other ALSPAC data: (1) please read the ALSPAC access policy (PDF, 627 kB), which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so; (2) you may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011; (3) please submit your research proposal for consideration by the ALSPAC Executive Committee and you will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please e-mail alspac-data@bristol.ac.uk. Full information on how to access BiB data can be found at https://borninbradford.nhs.uk/research/how-to-access-data/. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility (crf@exeter.ac.uk). Copyright © The Author(s) 2022. Aims/hypothesis: Higher maternal BMI during pregnancy is associated with higher offspring birthweight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity, coupled with a favourable metabolic profile, in a Mendelian randomisation (MR) study comparing the effect of maternal ‘metabolically favourable adiposity’ on offspring birthweight with the effect of maternal general adiposity (as indexed by BMI). Methods: To test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birthweight, we performed two-sample MR. We used variants identified in large, published genetic-association studies as being associated with either higher adiposity and a favourable metabolic profile, or higher BMI (n = 442,278 and n = 322,154 for metabolically favourable adiposity and BMI, respectively). We then extracted data on the metabolically favourable adiposity and BMI variants from a large, published genetic-association study of maternal genotype and offspring birthweight controlling for fetal genetic effects (n = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total n = 9323 mother–child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birthweight and cord-blood biomarkers. Results: Higher maternal adiposity with a favourable metabolic profile was associated with lower offspring birthweight (−94 [95% CI −150, −38] g per 1 SD [6.5%] higher maternal metabolically favourable adiposity, p = 0.001). By contrast, higher maternal BMI was associated with higher offspring birthweight (35 [95% CI 16, 53] g per 1 SD [4 kg/m2] higher maternal BMI, p = 0.0002). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures; their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that a higher maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels while a higher maternal BMI increases them. The effects on neonatal anthropometric traits were consistent with the overall effect on birthweight but the smaller sample sizes for these analyses meant that the effects were imprecisely estimated. We also found evidence to suggest that higher maternal metabolically favourable adiposity decreases cord-blood leptin while higher maternal BMI increases it. Conclusions/interpretation: Our results show that higher adiposity in mothers does not necessarily lead to higher offspring birthweight. Higher maternal adiposity can lead to lower offspring birthweight if accompanied by a favourable metabolic profile. US National Institute of Health (R01 DK10324); European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no 669545; British Heart Foundation (CS/16/4/32482 and AA/18/7/34219); NIHR Biomedical Centre at the University Hospitals Bristol NHS Foundation Trust; University of Bristol.

AIMS: To examine associations of pregnancy glycemia with future dyslipidemia. METHODS: We analyzed data from Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study participants. We examined associations of gestational diabetes (GDM), sum of fasting, 1-hour, and 2-hour glucose z-scores after 75-g load, insulin sensitivity, and lipid levels at 24–32 weeks’ gestation with dyslipidemia 10–14 years postpartum. RESULTS: Among 4,693 women, 14.3% had GDM. At follow-up, mean (SD) age was 41.7 (5.7) years, 32.3% had total cholesterol (TC)≥5.17, 27.2% had HDL cholesterol

Background Little is known about the presence of 3-epi-25 hydroxyvitamin D in maternal and neonatal circulation, the extent of its contribution to total 25 hydroxyvitamin D, or factors influencing its levels. Methods A total of 1502 and 1321 archived maternal and umbilical cord serum samples from the Hyperglycemia and Adverse Pregnancy Outcome Study cohort from Hong Kong were assayed for 25(OH)D2, 25(OH)D3, and isomeric form of 25(OH)D3 (3-epi-25(OH)D3) by a liquid chromatography-tandem mass spectrometry method. Results Vitamin D deficiency (total serum 25(OH)D level < 50 nmol/L) and severe vitamin D deficiency (total serum 25(OH)D level < 25 nmol/L) occurred in 590 (39.3%) and 25 (1.7%) mothers, respectively. 3-epi-25(OH)D3 could be detected in 94.5% of maternal and 92.1% of neonatal umbilical sera, with the highest 3-epi-25(OH)D3 levels contributing to 19.9% and 15.3% of the maternal and umbilical cord sera 25(OH)D3 levels, respectively. Pregnancy with a male fetus, ambient solar radiation, and maternal glycemia and 25(OH)D3 levels were independent factors associated with maternal 3-epi-25(OH)D3 level. Advanced maternal age, multiparity, maternal gestational weight gain below the Institute of Medicine recommendation, maternal glycemic status, and earlier gestational age at delivery were significantly associated with higher umbilical cord serum 3-epi-25(OH)D3. Conclusions 3-epi-25(OH)D3 accounted for a significant portion of total 25(OH)D in maternal and neonatal circulations. Further study is needed to determine the possible mechanism underlying this observation.

Leukocyte telomere length (LTL) is a biomarker of biological aging, and has been associated with metabolic diseases such as type 2 diabetes (T2DM). Insufficient maternal vitamin D (25(OH)D) has also been associated with increased disease risk for many diseases and adverse later life outcomes. The association between maternal and cord blood total 25(OH)D and LTL was examined in mother-child pairs from the HAPO Hong Kong Field Centre, including 815 offspring at age (mean±SD) 6.96 ± 0.44 years. LTL was measured using real-time polymerase chain reaction and serum 25(OH)D2, 25(OH)D3 and 3-epi-25(OH)D3 were measured in maternal blood (at gestation 24-32 weeks) and cord blood by liquid chromatography-mass spectrometry. Children LTL at follow-up was significantly shorter in boys compared to girls (p Disclosure K. Wong: None. B. E. Metzger: None. W. Lowe: None. W. H. Tam: None. R. C. Ma: Other Relationship; Self; AstraZeneca, Medtronic, Research Support; Self; AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Novo Nordisk, Pfizer Inc., Sanofi-Aventis, Tricida, Inc. F. Cheng: None. D. Mao: None. C. K. P. Lim: Stock/Shareholder; Self; GemVCare Ltd. R. Wang: None. C. H. Tam: None. M. A. Joglekar: None. A. A. Hardikar: None. A. Jenkins: Advisory Panel; Self; Abbott Diabetes, Sanofi-Aventis, Other Relationship; Self; Amgen Inc., Research Support; Self; Abbott, International Diabetes Federation, JDRF, Medtronic, Mylan N. V.

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10−14). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality., Gestational duration depends on both maternal and fetal genetic influences. Here, the authors perform a fetal genome-wide association meta-analysis and find that a locus on 2q13 is associated with pregnancy duration and further show that the lead SNP rs7594852 changes the binding properties of transcriptional repressor HIC1.

Motivation High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA. Results We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters. Availability and implementation The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080 Supplementary information Supplementary data are available at Bioinformatics online.

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.

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.

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 mid-pregnancy glucose and BMI with childhood adiposity. RESEARCH DESIGN AND METHODS Data on mother/offspring pairs (N=4832) 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 sum of skinfolds was associated with child outcomes (adjusted mean difference, 95% CI, p-value) BMI(0.26,0.12-0.39, 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.

IMPORTANCE: Pregnancy may be a key window to optimize cardiovascular health (CVH) for the mother and influence lifelong CVH for her child. OBJECTIVE: To examine associations between maternal gestational CVH and offspring CVH. DESIGN, SETTING, AND PARTICIPANTS: This cohort study used data from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study (examinations: July 2000-April 2006) and HAPO Follow-Up Study (examinations: February 2013-December 2016). The analyses included 2302 mother-child dyads, comprising 48% of HAPO Follow-Up Study participants, in an ancillary CVH study. Participants were from 9 field centers across the United States, Barbados, United Kingdom, China, Thailand, and Canada. EXPOSURES: Maternal gestational CVH at a target of 28 weeks’ gestation, based on 5 metrics: body mass index, blood pressure, total cholesterol level, glucose level, and smoking. Each metric was categorized as ideal, intermediate, or poor using pregnancy guidelines. Total CVH was categorized as follows: all ideal metrics, 1 or more intermediate (but 0 poor) metrics, 1 poor metric, or 2 or more poor metrics. MAIN OUTCOMES AND MEASURES: Offspring CVH at ages 10 to 14 years, based on 4 metrics: body mass index, blood pressure, total cholesterol level, and glucose level. Total CVH was categorized as for mothers. RESULTS: Among 2302 dyads, the mean (SD) ages were 29.6 (2.7) years for pregnant mothers and 11.3 (1.1) years for children. During pregnancy, the mean (SD) maternal CVH score was 8.6 (1.4) out of 10. Among pregnant mothers, the prevalence of all ideal metrics was 32.8% (95% CI, 30.6%-35.1%), 31.7% (95% CI, 29.4%-34.0%) for 1 or more intermediate metrics, 29.5% (95% CI, 27.2%-31.7%) for 1 poor metric, and 6.0% (95% CI, 3.8%-8.3%) for 2 or more poor metrics. Among children of mothers with all ideal metrics, the prevalence of all ideal metrics was 42.2% (95% CI, 38.4%-46.2%), 36.7% (95% CI, 32.9%-40.7%) for 1 or more intermediate metrics, 18.4% (95% CI, 14.6%-22.4%) for 1 poor metric, and 2.6% (95% CI, 0%-6.6%) for 2 or more poor metrics. Among children of mothers with 2 or more poor metrics, the prevalence of all ideal metrics was 30.7% (95% CI, 22.0%-40.4%), 28.3% (95% CI, 19.7%-38.1%) for 1 or more intermediate metrics, 30.7% (95% CI, 22.0%-40.4%) for 1 poor metric, and 10.2% (95% CI, 1.6%-20.0%) for 2 or more poor metrics. The adjusted relative risks associated with 1 or more intermediate, 1 poor, and 2 or more poor (vs all ideal) metrics, respectively, in mothers during pregnancy were 1.17 (95% CI, 0.96-1.42), 1.66 (95% CI, 1.39-1.99), and 2.02 (95% CI, 1.55-2.64) for offspring to have 1 poor (vs all ideal) metrics, and the relative risks were 2.15 (95% CI, 1.23-3.75), 3.32 (95% CI,1.96-5.62), and 7.82 (95% CI, 4.12-14.85) for offspring to have 2 or more poor (vs all ideal) metrics. Additional adjustment for categorical birth factors (eg, preeclampsia) did not fully explain these significant associations (eg, relative risk for association between 2 or more poor metrics among mothers during pregnancy and 2 or more poor metrics among offspring after adjustment for an extended set of birth factors, 6.23 [95% CI, 3.03-12.82]). RESULTS: Among 2302 dyads, the mean (SD) ages were 29.6 (2.7) years for pregnant mothers and 11.3 (1.1) years for children. During pregnancy, the mean (SD) maternal CVH score was 8.6 (1.4) out of 10. As shown in the Table, 32.8% of pregnant mothers had all ideal metrics, whereas 6.0% had 2 or more poor metrics, and the distribution of CVH categories among offspring varied by maternal CVH category. In adjusted models, poorer maternal CVH categories (vs all ideal maternal metrics) were associated with higher relative risks for offspring to have 1 poor and 2 or more poor metrics (vs all ideal metrics). Additional adjustment for categorical birth factors (eg, preeclampsia) did not fully explain these significant associations (eg, relative risk for association between 2 or more poor metrics among mothers during pregnancy and 2 or more poor metrics among offspring after adjustment for an extended set of birth factors, 6.23 [95% CI, 3.03-12.82]). [Table: see text] CONCLUSIONS AND RELEVANCE: In this multinational cohort, better maternal CVH at 28 weeks’ gestation was significantly associated with better offspring CVH at ages 10 to 14 years.

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 (GDM) is distinct from that underlying T2D. In this study of over 5,000 pregnant women from three cohorts, we aimed to identify physiologically related groups of maternal variants associated with GDM using two complementary approaches based on Bayesian non-negative matrix factorization (bNMF) clustering. First, we tested five bNMF clusters of maternal T2D-associated variants grouped based on physiology outside of pregnancy for association with GDM. We found that cluster polygenic scores representing genetic determinants of reduced beta-cell function and abnormal hepatic lipid metabolism were associated with GDM; these clusters were not associated with infant birthweight. Second, we derived bNMF clusters of maternal variants based on pregnancy physiology and tested these clusters for association with GDM. We identified a cluster which was strongly associated with GDM and also associated with higher infant birthweight. 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.

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, 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.

Aims/HypothesisHigher maternal BMI during pregnancy results in higher offspring birth weight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity coupled with a favourable metabolic profile, in a Mendelian Randomisation (MR) study comparing the effect of maternal “metabolically favourable adiposity” on offspring birth weight with the effect of maternal general adiposity (as indexed by BMI).MethodsTo test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birth weight, we performed two sample MR. We used variants identified in large genetic association studies as associated with either higher adiposity and a favourable metabolic profile, or higher BMI (N = 442,278 and N = 322,154 for metabolically favourable adiposity and BMI, respectively). We then used data from the same variants in a large genetic study of maternal genotype and offspring birth weight independent of fetal genetic effects (N = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total N = 9,323 mother-child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birth weight and cord-blood biomarkers.ResultsHigher maternal adiposity with a favourable metabolic profile was associated with lower offspring birth weight (−94 (95% CI: −150 to −38) grams per 1 SD (6.5%) higher maternal metabolically favourable adiposity). By contrast, higher maternal BMI was associated with higher offspring birth weight (35 (95% CI: 16 to 53) grams per 1 SD (4 kg/m2) higher maternal BMI). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures and their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels whilst maternal BMI increases them.The effects on neonatal anthropometric traits were consistent with the overall effect on birth weight, but the smaller sample sizes for these analyses meant the effects were imprecisely estimated. We also found evidence to suggest that maternal metabolically favourable adiposity decreases cord-blood leptin whilst maternal BMI increases it.Conclusions/InterpretationOur results show that higher adiposity in mothers does not necessarily lead to higher offspring birth weight. Higher maternal adiposity can lead to lower offspring birth weight if accompanied by a favourable metabolic profile.Research in ContextWhat is already known about this subject?Studies in non-pregnant people with obesity suggest many people can have a “metabolically healthy” form of obesity, but effects in pregnancy and on offspring are not known.Multiple lines of evidence show that higher maternal BMI is causally associated with higher offspring birth weight, and that this may be mediated by the fetal insulin response to higher maternal gestational glucose.Recently, genetic variants have been identified, where one allele is associated with higher adiposity but lower risk of type II diabetes and favourable metabolic profile, including lower insulin and glucose levels, so called “metabolically favourable adiposity”; the mechanism is thought to be due to greater subcutaneous adipose storage capacity that leads to higher insulin sensitivity.What is the key question?What is the effect of maternal metabolically favourable adiposity on birth weight, and how does it compare with the effect of maternal BMI on birth weight?What are the new findings?Higher maternal adiposity can lead to lower, not higher birth weight, if it is also associated with a metabolically favourable profile; this contrasts with the effect of higher maternal general adiposity (BMI), on higher birth weight.Higher maternal metabolically favourable adiposity causes lower maternal fasting plasma glucose levels, most likely due to higher insulin sensitivity; in contrast higher maternal general adiposity leads to higher maternal fasting plasma glucose levels, most likely due to lower insulin sensitivity.How might this impact on clinical practice in the foreseeable future?Identifying ways of stratifying overweight and obese pregnant women into those with and without metabolically favourable adiposity could allow for targeted management to obtain healthy fetal growth and birth weight.

BACKGROUND: The American Heart Association’s formal characterization of “cardiovascular health” combines several metrics in a health-oriented, rather than disease-oriented, framework. Although cardiovascular health assessment during pregnancy has been recommended, its significance for pregnancy outcomes is unknown. OBJECTIVE: The purpose of this study was to examine the association of gestational cardiovascular health—formally characterized by a combination of five metrics—with adverse maternal and newborn outcomes. STUDY DESIGN: We analyzed data from the Hyperglycemia and Adverse Pregnancy Outcome Study, including 2,304 mother-newborn dyads from six countries. Maternal cardiovascular health was defined by the combination of five metrics measured at a mean of 28 (24–32) weeks’ gestation: body mass index, blood pressure, lipids, glucose, and smoking. Levels of each metric were categorized using pregnancy guidelines, and total cardiovascular health was scored (0–10 points; 10 most favorable). Cord blood was collected at delivery, newborn anthropometrics were measured within 72 hours, and medical records were abstracted for obstetric outcomes. Modified Poisson and multinomial logistic regression were utilized to test associations of gestational cardiovascular health with pregnancy outcomes, adjusted for center and maternal and newborn characteristics. RESULTS: Women averaged 29.6 years old and delivered at a mean gestational age of 39.8 weeks. The mean total gestational cardiovascular health score was 8.6 (of 10); 36.3% had all ideal metrics and 7.5% had 2+ poor metrics. In fully adjusted models, each 1 point higher (more favorable) cardiovascular health score was associated with lower risks for preeclampsia (relative risk 0.67 [95% confidence interval, 0.61–0.73]), unplanned primary cesarean section (0.88 [0.82–0.95]), and newborn birthweight >90(th) percentile (0.81 [0.75–0.87]), sum of skinfolds >90(th) percentile (0.84 [0.77–0.92]), and insulin sensitivity

Context An obesogenic perinatal environment contributes to adverse offspring metabolic health. Previous studies have been limited by lack of direct adiposity measurements and failure to account for potential confounders. Objective Examine the joint associations of maternal midpregnancy body mass index (BMI) and glycemia with direct adiposity measures in 10-14 year old offspring. Design and Setting International, epidemiological study: Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and HAPO Follow-up Study, conducted between 2000-2006 and 2013-2016, respectively. Participants and Main Outcome Measures In 4832 children, adiposity measures for body mass index (BMI), body fat with air displacement plethysmography, skinfold thickness, and waist circumference were obtained at mean age 11.4 years. Results Maternal BMI and glucose, as continuous and categorical variables, were the primary predictors. In fully adjusted models controlling for child age, sex, field center, and maternal characteristics, maternal BMI had significant, positive associations with all childhood adiposity outcomes, while maternal glycemia had significant, positive associations with childhood adiposity outcomes except BMI. In joint analyses, and compared with a nonobese, nongestational diabetes mellitus (GDM) reference group, maternal obesity and GDM were associated with higher odds (maternal obesity odds ratio; OR [95% confidence interval; CI], GDM OR [95% CI]; combined OR [95% CI]) of childhood overweight/obese BMI (3.00 [2.42-3.74], 1.39 [1.14-1.71], 3.55 [2.49-5.05]), obese BMI (3.54 [2.70-4.64], 1.73 [1.29-2.30], 6.10 [4.14-8.99]), percent body fat >85th percentile (2.15 [1.68-2.75], 1.33 [1.03-1.72], 3.88 [2.72-5.55]), sum of skinfolds >85th percentile (2.35 [1.83-3.00], 1.75 [1.37-2.24], 3.66 [2.55-5.27]), and waist circumference >85th percentile (2.52 [1.99-3.21], 1.39 [1.07-1.80], 4.18 [2.93-5.96]). Conclusions Midpregnancy maternal BMI and glycemia are independently and additively associated with direct adiposity measures in 10-14 year old children. The combination of maternal obesity and GDM is associated with the highest odds of childhood adiposity.

Introduction: Gestational hyperlipidemia has traditionally been considered physiologic and benign, but the significance of inter-individual variation in lipid levels for maternal-fetal health are poorly understood. We examined associations of gestational lipids and apolipoproteins with adverse obstetric and neonatal outcomes. Methods: Data from the Hyperglycemia and Adverse Pregnancy Outcome Study were analyzed, including 1,813 mother-child dyads from 9 field centers in 6 countries: US (25%), Barbados (24%), UK (20%), China (16%), Thailand (8%), and Canada (7%). Fasting lipids and apolipoproteins were directly measured at a mean of 28 (range 23-34) weeks’ gestation. Cord blood was collected at delivery, neonatal anthropometrics were measured within 72 hours, and medical records were abstracted for obstetric outcomes. Logistic regression was utilized to test associations of lipids and apolipoproteins (per +1 SD; log-transformed if skewed) with pregnancy outcomes, adjusted for center, demographics, and maternal covariates such as BMI, blood pressure, and glycemia. Results: See Table for lipid and apolipoprotein levels in pregnant mothers. In fully adjusted models ( Table ), 1 SD higher log-triglycerides (i.e., ~2.7-fold higher triglyceride level) in late pregnancy was significantly associated with higher odds for preeclampsia (OR 1.53 [95% CI, 1.15-2.05]), large for gestational age infant (1.42 [1.21-1.67]), and infant insulin sensitivity th percentile (1.25 [1.03-1.50]), but not with unplanned primary cesarean section or infant sum of skinfolds >90 th percentile. There were no significant associations of maternal HDL-C, LDL-C, or log-ApoB/A1 ratio with any outcome. Conclusion: Triglyceride levels in the latter half of pregnancy were uniquely associated with both maternal risks (preeclampsia) and neonatal risks (large for gestational age and insulin resistance), even after adjustment for maternal BMI, blood pressure, and glycemia.

Introduction: Combinations of risk factor levels typically contribute more to population burdens of disease than single adverse risk factors. CVH (as defined by the AHA) characterizes a range of health levels, but its significance in pregnancy for obstetric and neonatal outcomes is unknown. Methods: Data from the Hyperglycemia and Adverse Pregnancy Outcome Study were analyzed, including 1,754 mother-child dyads from 9 field centers in 6 countries: US (26%), Barbados (24%), UK (20%), China (15%), Thailand (8%), and Canada (7%). Maternal CVH was scored (0-10 points, with 10 most favorable) at a mean of 28 (range 23-34) weeks’ gestation using 5 metrics ( Table ). Cord blood was collected at delivery, neonatal anthropometrics were measured within 72 hours, and medical records were abstracted for obstetric outcomes. Logistic regression was utilized to test associations of gestational CVH with obstetric and neonatal outcomes, adjusted for center and maternal and infant characteristics ( Table footnote). Results: The mean gestational CVH score was 8.2 (SD 1.5) out of 10; 18% of mothers had all ideal, 37% had 1+ intermediate, 34% had 1 poor, and 9% had 2+ poor metrics. In fully adjusted models ( Table ), odds ratios per 1 point higher (better) CVH score were 0.65 (95% CI, 0.56-0.76) for preeclampsia, 0.89 (0.78-1.00) for unplanned primary cesarean section (among primiparous mothers), 0.84 (0.77-0.93) for large for gestational age infant, 0.87 (0.79-0.97) for infant sum of skinfolds >90 th percentile, and 0.77 (0.69-0.86) for infant insulin sensitivity index (20/[C-peptide*glucose]) th percentile. CVH categories were also associated with outcomes; for example, compared with mothers with all metrics ideal, odds ratios for preeclampsia were 2.00 (0.71-7.14) for mothers with 1+ intermediate, 4.34 (1.63-15.09) for mothers with 1 poor, and 9.40 (3.22-34.52) for mothers with 2+ poor metrics. Conclusion: More favorable levels of gestational CVH were associated with healthier obstetric and neonatal outcomes in this multinational cohort.

Body composition estimates are widely used in clinical research and field studies as measures of energy-nutrient balance, functionality and health. Despite their broad relevance and multiple applications, important gaps remain in techniques available for accurately and precisely quantifying body composition in infants and children from birth through 5 years. Identifying these gaps and highlighting research needs in this age group were the topics of a National Institutes of Health workshop held in Bethesda, MD, USA, 30-31 May 2019. Experts reviewed available methods (multicompartment models, air-displacement plethysmography, dual-energy X-ray absorptiometry, weight-length and height indices, bioimpedance analysis, anthropometry-skinfold techniques, quantitative magnetic resonance, optical imaging, omics and D3-creatine dilution), their limitations in this age range and high priority research needs. A summary of their individual and collective workshop deliberations is provided in this report.

Aims/hypothesis Our study aimed to integrate maternal metabolic and genetic data related to insulin sensitivity during pregnancy to provide novel insights into mechanisms underlying pregnancy-induced insulin resistance. Methods Fasting and 1 h serum samples were collected from women in the Hyperglycemia and Adverse Pregnancy Outcome Study who underwent an OGTT at ~28 weeks’ gestation. We obtained targeted and non-targeted metabolomics and genome-wide association data from 1600 and 4528 mothers, respectively, in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai); 1412 of the women had both metabolomics and genome-wide association data. Insulin sensitivity was calculated using a modified insulin sensitivity index that included fasting and 1 h glucose and C-peptide levels after a 75 g glucose load. Results Per-metabolite and network analyses across the four ancestries identified numerous metabolites associated with maternal insulin sensitivity before and 1 h after a glucose load, ranging from amino acids and carbohydrates to fatty acids and lipids. Genome-wide association analyses identified 12 genetic variants in the glucokinase regulatory protein gene locus that were significantly associated with maternal insulin sensitivity, including a common functional missense mutation, rs1260326 (β=−0.2004, p=4.67×10−12 in a meta-analysis across the four ancestries). This SNP was also significantly associated with multiple fasting and 1 h metabolites during pregnancy, including fasting and 1 h triacylglycerols and 2-hydroxybutyrate and 1 h lactate, 2-ketoleucine/ketoisoleucine and palmitoleic acid. Mediation analysis suggested that 1 h palmitoleic acid contributes, in part, to the association of rs1260326 with maternal insulin sensitivity, explaining 13.7% (95% CI 4.0%, 23.3%) of the total effect. Conclusions/interpretation The present study demonstrates commonalities between metabolites and genetic variants associated with insulin sensitivity in the gravid and non-gravid states and provides insights into mechanisms underlying pregnancy-induced insulin resistance., Graphical Abstract

AIMS/HYPOTHESIS: We aimed to determine the association of maternal metabolites with newborn adiposity and hyperinsulinaemia in a multi-ethnic cohort of mother–newborn dyads. METHODS: Targeted and non-targeted metabolomics assays were performed on fasting and 1 h serum samples from a total of 1600 mothers in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, underwent an OGTT at ~28 weeks gestation and whose newborns had anthropometric measurements at birth. RESULTS: In this observational study, meta-analyses demonstrated significant associations of maternal fasting and 1 h metabolites with birthweight, cord C-peptide and/or sum of skinfolds across ancestry groups. In particular, maternal fasting triacylglycerols were associated with newborn sum of skinfolds. At 1 h, several amino acids, fatty acids and lipid metabolites were associated with one or more newborn outcomes. Network analyses revealed clusters of fasting acylcarnitines, amino acids, lipids and fatty acid metabolites associated with cord C-peptide and sum of skinfolds, with the addition of branched-chain and aromatic amino acids at 1 h. CONCLUSIONS/INTERPRETATION: The maternal metabolome during pregnancy is associated with newborn outcomes. Maternal levels of amino acids, acylcarnitines, lipids and fatty acids and their metabolites during pregnancy relate to fetal growth, adiposity and cord C-peptide, independent of maternal BMI and blood glucose levels.

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.

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.