Metabolomic and genetic architecture of gestational diabetes subtypes.

AIMS/HYPOTHESIS: Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes. METHODS: This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM). RESULTS: Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM. CONCLUSIONS/INTERPRETATION: This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes.

BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). 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 randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.

Epidemic-specific association of maternal exposure to per- and polyfluoroalkyl substances (PFAS) and their components with maternal glucose metabolism: A cross-sectional analysis in a birth cohort from Hong Kong.

Per- and polyfluoroalkyl substances (PFAS) are persistent chemicals that have been linked to increased risk of gestational diabetes mellitus (GDM) and may affect glucose metabolisms during pregnancy. We examined the associations between maternal PFAS exposure and maternal glucose metabolisms and GDM risk among 1601 mothers who joined the Hyperglycaemia-and-Adverse-Pregnancy-Outcome (HAPO) Study in Hong Kong in 2001-2006. All mothers underwent a 75 g-oral-glucose-tolerance test at 24-32 weeks of gestation. We measured serum concentrations of six PFAS biomarkers using high-performance liquid-chromatography-coupled-with-tandem-mass-spectrometry (LC-MS-MS). We fitted conventional and advanced models (quantile-g-computation [qgcomp] and Bayesian-kernel machine regression [BKMR]) to assess the associations of individual and a mixture of PFAS with glycaemic traits. Subgroup analyses were performed based on the enrollment period by the severe-acute-respiratory-syndrome (SARS) epidemic periods in Hong Kong between March 2003 and May 2004. PFOS and PFOA were the main components of PFAS mixture among 1601 pregnant women in the Hong Kong HAPO study, with significantly higher median PFOS concentrations (19.09 ng/mL), compared to Chinese pregnant women (9.40 ng/mL) and US women (5.27 ng/mL). Maternal exposure to PFAS mixture was associated with higher HbA1c in the qgcomp (ß = 0.04, 95 % CI: 0.01-0.06) model. We did not observe significant associations of PFAS mixture with fasting plasma glucose (PG), 1-h and 2-h PG in either model, except for 2-h PG in the qgcmop model (ß = 0.074, 95 % CI: 0.01-0.15). PFOS was the primary contributor to the overall positive effects on HbA1c. Epidemic-specific analyses showed specific associations between PFAS exposure and the odds of GDM in the pre-SARS epidemic period. The median concentration of PFOS was highest during the peri-SARS epidemic (21.2 [14.5-43.6] ng/mL) compared with the pre-SARS (12.3 [9.2-19.9] ng/mL) and post-SARS (20.3 [14.2-46.3] ng/mL) epidemic periods. Potential interactions and exposure-response relationships between PFOA and PFNA with elevated HbA1c were observed in the peri-SARS period in BKMR model. Maternal exposure to PFAS mixture was associated with altered glucose metabolism during pregnancy. SARS epidemic-specific associations call for further studies on its long-term adverse health effects, especially potential modified associations by lifestyle changes during the COVID-19 pandemic.

Leptin and adiposity measures from birth to later childhood: Findings from the Hyperglycemia and Adverse Pregnancy Outcomes Follow-Up Study.

BACKGROUND: Cord blood (CB) leptin is positively associated with adiposity at birth, but the association with child adiposity is unclear. OBJECTIVES: We hypothesized that CB leptin is positively associated with adiposity in peripubertal children and with childhood leptin. METHODS: Leptin was measured in 986 CB and 931 childhood stored samples from a prospective birth cohort. Adiposity measures were collected at birth and mean age 11.5 years. Linear and logistic regression analyses were used to evaluate associations between log-transformed CB leptin and neonatal and childhood adiposity measures as continuous and categorical variables, respectively. RESULTS: CB leptin was positively associated with neonatal and childhood adiposity. Childhood associations were attenuated when adjusted for maternal body mass index (BMI) and glucose, but remained statistically significant for childhood body fat percentage (ß = 1.15%, confidence interval [CI] = 0.46-1.84), body fat mass (ß = 0.69 kg, 95% CI = 0.16-1.23), sum of skin-folds (ß = 1.77 mm, 95% CI = 0.31-3.24), log-transformed child serum leptin (ß = 0.13, 95% CI = 0.06-0.20), overweight/obesity (OR = 1.21, 95% CI = 1.03-1.42), obesity (OR = 1.31, 95% CI = 1.04-1.66) and body fat percentage >85th percentile (OR = 1.38, 95% CI = 1.12-1.73). Positive associations between newborn adiposity measures and CB leptin confirmed previous reports. CONCLUSION: CB leptin is positively associated with neonatal and childhood adiposity and child leptin levels, independent of maternal BMI and maternal hyperglycemia. CB leptin may be a biomarker of future adiposity risk.

The Association of Prenatal Vitamin D Status With Pregnancy and Neonatal Outcomes.

Context: Vitamin D inadequacy is globally prevalent among pregnant women; however, its impact on pregnancy remains inconclusive. Objective: This study aims to explore the associations of maternal and umbilical cord serum 25-hydroxyvitamin D (25(OH)D) levels with pregnancy and neonatal outcomes. Method: We used archived serum samples from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study participants in the Hong Kong center and assayed maternal 25(OH)D levels at midgestation and umbilical cord 25(OH)D at birth using liquid chromatography-tandem mass spectroscopy. Data regarding pregnancy and perinatal outcomes were extracted from the HAPO study dataset and the hospital computerized medical system. Results: Only 247 (16.4%) mothers and 66 (5.0%) neonates met the criteria for vitamin D sufficiency (ie, 25(OH)D ≥ 75 nmol/L). The ratio of umbilical cord to maternal vitamin D levels was positively associated with maternal age and ambient solar radiation at the month of delivery, while negatively associated with maternal serum total 25(OH)D at midgestation (all P < .001). Umbilical cord serum 25(OH)D was independently associated with a lower primary cesarean section rate (OR 0.990, 95% CI 0.982-0.999; P = .032). There were no associations of maternal and umbilical cord 25(OH)D levels with other adverse pregnancy and neonatal outcomes. Conclusion: Placental vitamin D transfer was found to be higher with a lower maternal vitamin D level, older maternal age, and higher ambient solar radiation at the time of the delivery. The protective effect of sufficient vitamin D in a cesarean section will require further studies.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis.

BACKGROUND: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM. METHODS: Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA). RESULTS: A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers. CONCLUSIONS: Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Gestational Diabetes (GDM) is high blood sugar that develops during pregnancy and may cause complications. GDM diagnosis is centered on blood sugar levels. Despite everyone receiving standard treatment, the clinical outcomes may vary from one individual to another. This indicates a need to identify factors that may help GDM diagnosis and result in improved classification of those at greatest risk for complications. Here, we systematically analyzed all published evidence for potential markers that could identify those with GDM who have greater risk of complications. We find that high maternal weight is a risk factor for offspring born larger for their gestational age. Other promising markers were identified, but further analysis is needed before they can be applied in the clinic.

Use of fasting plasma glucose to determine the approach for diagnosing gestational diabetes mellitus.

AIMS: Estimate the impact of OGTTs only on women with a screening FPG of 4.5-5.0 mmol/L using data from HAPO. METHODS: HAPO participants had 75-g OGTTs (24-32 weeks' gestation). At follow-up, children had adiposity assessed (overweight/obesity, obesity) and mothers and children had OGTTs. GDM was defined retrospectively using IADPSG criteria. Odds for neonatal (birthweight, percent neonatal fat, sum of skinfolds, cord C-peptide > 90th percentiles) and follow-up outcomes were assessed in those with HAPO FPG ≤ 4.4 or > 4.4 mmol/L and GDM or no GDM focusing on women with FPG > 4.4 and no GDM (Group 3) vs women with GDM and FPG ≤ 4.4 (Group 2). RESULTS: This strategy would miss a diagnosis of GDM in 14.7%. Odds for neonatal outcomes in Groups 2 and 3 were not different (ORs: 1.14 to 1.29). Odds at follow-up for type 2 diabetes and disorders of glucose metabolism in mothers were higher in Group 2 (ORs: 3.51, 2.57). Odds for childhood impaired glucose tolerance or adiposity outcomes were not different for Groups 2 and 3. CONCLUSIONS: HAPO mothers whose GDM diagnosis would be missed were not at greater risk for adverse neonatal and childhood outcomes than mothers with FPG of 4.5-5.0 without GDM.

Racial and ethnic differences in the association between pregnancy dysglycemia and cardiometabolic risk factors 10-14 years' postpartum in the HAPO follow-up study.

Associations between pregnancy dysglycemia and subsequent maternal cardiometabolic factors 10-14 years postpartum were largely similar across self-identified racial and ethnic groups among birthing people in the U.S. enrolled in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Follow-up Study.

Maternal and Cord Blood Serum Metabolite Associations with Childhood Adiposity and Body Composition Outcomes.

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.

Association of Maternal Metabolites and Metabolite Networks with Newborn Outcomes in a Multi-Ancestry Cohort.

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.

Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes.

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.

Urinary metal profiles in mother-offspring pairs and their association with early dysglycemia in the International Hyperglycemia and Adverse Pregnancy Outcome Follow Up Study (HAPO-FUS).

BACKGROUND: Variations in dietary intake and environmental exposure patterns of essential and non-essential trace metals influence many aspects of human health throughout the life span. OBJECTIVE: To examine the relationship between urine profiles of essential and non-essential metals in mother-offspring pairs and their association with early dysglycemia. METHODS: Herein, we report findings from an ancillary study to the international Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study (HAPO-FUS) that examined urinary essential and non-essential metal profiles from mothers and offspring ages 10-14 years (1012 mothers, 1013 offspring, 968 matched pairs) from 10 international sites. RESULTS: Our analysis demonstrated a diverse exposure pattern across participating sites. In multiple regression modelling, a positive association between markers of early dysglycemia and urinary zinc was found in both mothers and offspring after adjustment for common risk factors for diabetes. The analysis showed weaker, positive, and negative associations of the 2-h glucose value with urinary selenium and arsenic respectively. A positive association between 2-h glucose values and cadmium was found only in mothers in the fully adjusted model when participants with established diabetes were excluded. There was a high degree of concordance between mother and offspring urinary metal profiles. Mother-to-offspring urinary metal ratios were unique for each metal, providing insights into changes in their homeostasis across the lifespan. SIGNIFICANCE: Urinary levels of essential and non-essential metals are closely correlated between mothers and their offspring in an international cohort. Urinary levels of zinc, selenium, arsenic, and cadmium showed varying degrees of association with early dysglycemia in a comparatively healthy cohort with a low rate of preexisting diabetes. IMPACT STATEMENT: Our data provides novel evidence for a strong correlation between mother and offspring urinary metal patterns with a unique mother-to-offspring ratio for each metal. The study also provides new evidence for a strong positive association between early dysglycemia and urinary zinc, both in mothers and offspring. Weaker positive associations with urinary selenium and cadmium and negative associations with arsenic were also found. The low rate of preexisting diabetes in this population provides the unique advantage of minimizing the confounding effect of preexisting, diabetes related renal changes that would alter the relationship between dysglycemia and renal metal excretion.

Early emergence of sexual dimorphism in offspring leukocyte telomere length was associated with maternal and children's glucose metabolism-a longitudinal study.

BACKGROUND: Leukocyte telomere length (LTL) is suggested to be a biomarker of biological age and reported to be associated with metabolic diseases such as type 2 diabetes. Glucose metabolic traits including glucose and insulin levels have been reported to be associated with LTL in adulthood. However, there is relatively little research focusing on children's LTL and the association with prenatal exposures. This study investigates the relationship between maternal and offspring glucose metabolism with offspring LTL in early life. METHODS: This study included 882 mother-child pairs from the HAPO Hong Kong Field Centre, with children evaluated at age 7.0 ± 0.4 (mean ± SD) years. Glucose metabolic traits including maternal post-load glucose during pregnancy, children's glucose and insulin levels, and their derived indices at follow-up were measured or calculated. Offspring LTL was assessed using real-time polymerase chain reaction. RESULTS: Sex- and age-adjusted children's LTL was found to be associated with children's HOMA-IR (ß=-0.046 ± 0.016, p=0.005). Interestingly, both children's and maternal post-load glucose levels were positively associated with children's LTL. However, negative associations were observed between children's LTL and children's OGTT insulin levels. In addition, the LTL in females was more strongly associated with pancreatic beta-cell function whilst LTL in males was more strongly associated with OGTT glucose levels. CONCLUSIONS: Our findings suggest a close association between maternal and offspring glucose metabolic traits with early life LTL, with the offspring sex as an important modifier of the disparate relationships in insulin production and response.

Network Approaches to Integrate Analyses of Genetics and Metabolomics Data with Applications to Fetal Programming Studies.

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.

Vitamin D Levels During Pregnancy Are Associated With Offspring Telomere Length: A Longitudinal Mother-Child Study.

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 ±â€…0.44 (mean ±â€…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 < 0.001) at age 7. Childhood LTL was negatively associated with childhood BMI (ß ±â€…SE = -0.016 ±â€…0.007)(P = 0.02) and HOMA-IR (ß ±â€…SE = -0.065 ±â€…0.021)(P = 0.002). Multiple linear regression was used to evaluate the relationship between 25(OH)D and LTL, with covariate adjustments. Childhood LTL was positively correlated with total maternal 25(OH)D (0.048 ±â€…0.017) (P = 0.004) and maternal 3-epi-25(OH)D3 (0.05 ±â€…0.017) (P = 0.003), even after adjustment for covariates. A similar association was also noted for cord 3-epi-25(OH)D3 (0.037 ±â€…0.018) (P = 0.035) after adjustment for offspring sex and age. 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.

Associations of glycemia and lipid levels in pregnancy with dyslipidemia 10-14 years later: The HAPO follow-up study.

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 < 1.29, 22.4% had LDL cholesterol (LDL-C) ≥ 3.36, 10.9% had triglycerides ≥ 1.69 mmol/L, and 2.9% had type 2 diabetes. After covariate adjustment, pregnancy glycemic measures were associated with all follow-up dyslipidemias. After additional adjustment for pregnancy lipids, GDM remained associated with TC ≥ 5.17 mmol/L (odds ratio [95% CI], 1.63 [1.22-2.18]) and LDL-C ≥ 3.36 mmol/L (1.63 [1.20-2.22]), even in the absence of type 2 diabetes development (1.55 [1.15-2.10] and 1.56 [1.13-2.16], respectively). Continuous glycemic measures in pregnancy were significantly associated with all follow-up dyslipidemias, independent of pregnancy lipids and type 2 diabetes. CONCLUSIONS: Pregnancy glycemia was associated with dyslipidemia 10-14 years later, independent of pregnancy lipid levels and in the absence of type 2 diabetes development. Lipid screening after GDM deserves special consideration.

Path-level interpretation of Gaussian graphical models using the pair-path subscore.

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 pps, 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.