Metabolomic and genetic associations with insulin resistance in pregnancy

Genetics of glucose homeostasis in pregnancy and postpartum

AIMS/HYPOTHESIS

Pregnancy is accompanied by maternal metabolic adaptations to ensure fetal growth and development, including insulin resistance, which occurs primarily during the second and third trimesters of pregnancy, and a decrease in fasting blood sugar levels over the course of pregnancy. Glucose-related traits are regulated by genetic and environmental factors and modulated by physiological variations throughout the life course. We addressed the hypothesis that there are both overlaps and differences between genetic variants associated with glycaemia-related traits during and outside of pregnancy.

METHODS

Genome-wide SNP data were used to identify genetic variations associated with glycaemia-related traits measured during an OGTT performed at ~28 weeks' gestation in 8067 participants in the Hyperglycaemia and Adverse Pregnancy Outcome (HAPO) Study. Associations outside of pregnancy were determined in 3977 individuals who also participated in the HAPO Follow-Up Study at 11-14 years postpartum. A Bayesian classification algorithm was used to determine whether SNPs associated with fasting and 2 h glucose and fasting C-peptide during pregnancy had a pregnancy-predominant effect vs a similar effect during pregnancy and postpartum.

RESULTS

SNPs in six loci (GCKR, G6PC2, GCK, PPP1R3B, PCSK1 and MTNR1B) were significantly associated with fasting glucose during pregnancy, while SNPs in CDKAL1 and MTNR1B were associated with 1 h glucose and SNPs in MTNR1B and HKDC1 were associated with 2 h glucose. Variants in CDKAL1 and MTNR1B were associated with insulin secretion during pregnancy. Variants in multiple loci were associated with fasting C-peptide during pregnancy, including GCKR, IQSEC1, PPP1R3B, IGF1 and BACE2. GCKR and BACE2 were associated with 1 h C-peptide and GCKR, IQSEC1 and BACE2 with insulin sensitivity during pregnancy. The associations of MTNR1B with 2 h glucose, BACE2 with fasting and 1 h C-peptide and insulin sensitivity, and IQSEC1 with fasting C-peptide and insulin sensitivity that we identified during pregnancy have not been previously reported in non-pregnancy cohorts. The Bayesian classification algorithm demonstrated that the magnitude of effect of the lead SNP was greater during pregnancy compared with 11-14 years postpartum in PCSK1 and PPP1R3B with fasting glucose, in three loci, including MTNR1B, with 2 h glucose, and in six loci, including IGF1, with fasting C-peptide.

CONCLUSIONS/INTERPRETATION

Our findings support the hypothesis that there are both overlaps and differences between the genetic architecture of glycaemia-related traits during and outside of pregnancy. Genetic variants at several loci, including PCSK1, PPP1R3B, MTNR1B and IGF1, appear to influence glycaemic regulation in a unique fashion during pregnancy. Future studies in larger cohorts will be needed to replicate the present findings, fully characterise the genetics of maternal glycaemia during pregnancy and determine similarities to and differences from the non-gravid state.

Placental mitochondrial impairment and its association with maternal metabolic dysfunction

The placenta plays an essential role in pregnancy, leading to proper fetal development and growth. As an organ with multiple physiological functions for both mother and fetus, it is a highly energetic and metabolically demanding tissue. Mitochondrial physiology plays a crucial role in the metabolism of this organ and thus any alteration leading to mitochondrial dysfunction has a severe outcome in the development of the fetus. Pregnancy-related pathological states with a mitochondrial dysfunction outcome include preeclampsia and gestational diabetes mellitus. In this review, we address the role of mitochondrial morphology, metabolism and physiology of the placenta during pregnancy, highlighting the roles of the cytotrophoblast and syncytiotrophoblast. We also describe the relationship between preeclampsia, gestational diabetes, gestational diabesity and pre-pregnancy maternal obesity with mitochondrial dysfunction.

iTRAQ proteomics analysis of placental tissue with gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus is an endocrine and metabolic disorder that appears for the first time during pregnancy and causes varying degrees of short- and/or long-term effects on the mother and child. The etiology of the disease is currently unknown and isobaric tags for relative and absolute quantitation proteomics approach, the present study attempted to identify potential proteins in placental tissues that may be involved in the pathogenesis of GDM and adverse foetal pregnancy outcomes.

METHODS

Pregnant women with GDM hospitalised were selected as the experimental group, and pregnant women with normal glucose metabolism as the control group. The iTRAQ protein quantification technology was used to screen the differentially expressed proteins between the GDM group and the normal control group, and the differentially expressed proteins were analysed by GO, KEGG, PPI, etc., and the key proteins were subsequently verified by western blot.

RESULTS

Based on the proteomics of iTRAQ, we experimented with three different samples of placental tissues from GDM and normal pregnant women, and the total number of identified proteins were 5906, 5959, and 6017, respectively, which were similar in the three different samples, indicating that the results were reliable. Through the Wayne diagram, we found that the total number of proteins coexisting in the three groups was 4475, and 91 differential proteins that could meet the quantification criteria were strictly screened, of which 32 proteins were up-regulated and 59 proteins were down-regulated. By GO enrichment analysis, these differential proteins are widely distributed in extracellular membrane-bounded organelle, mainly in extracellular exosome, followed by intracellular vesicle, extracellular organelle. It not only undertakes protein binding, protein complex binding, macromolecular complex binding, but also involves molecular biological functions such as neutrophil degranulation, multicellular organismal process, developmental process, cellular component organization, secretion, regulated exocytosis. Through the analysis of the KEGG signaling pathway, it is found that these differential proteins are mainly involved in HIF-1 signaling pathway, Glycolysis/Gluconeogenesis, Central carbon metabolism in cancer, AMPK signaling pathway, Proteoglycans in cancer, Protein processing in endoplasmic reticulum, Thyroid cancer, Alcoholism, Glucagon signaling pathway.

DISCUSSION

This preliminary study helps us to understand the changes in the placental proteome of GDM patients, and provides new insights into the pathophysiology of GDM.

Improvement of insulin sensitivity by dietary fiber consumption during late pregnant sows is associated with gut microbiota regulation of tryptophan metabolism

BACKGROUND

Dietary fiber (DF) consumption was reported to improve insulin sensitivity, change the tryptophan metabolism, and alter the gut microbiota. Herein, this study aimed to investigate the effects of DF consumption on insulin sensitivity, tryptophan metabolism, and gut microbiota composition in sows during late pregnancy, and explore the relationship between tryptophan metabolites and insulin sensitivity regulated by DF supplementation.

RESULTS

Twelve sows were randomly assigned to two dietary treatment groups (six/group): the low-fiber (LF) group, which was fed a basal diet, and the high-fiber (HF) group, which was fed the basal diet supplemented with 22.60 g/kg inulin and 181.60 g/kg cellulose. During late pregnancy, meal test, glucose tolerance test, and insulin challenge test were used to investigate the insulin sensitivity of sows, using the percutaneous brachiocephalic vein catheterization technique. High DF consumption resulted in improved insulin sensitivity, especially during the second and third trimesters, and promoted serotonin production from tryptophan. Additionally, plasma serotonin concentration was positively correlated with the insulin sensitivity index during late pregnancy. Moreover, DF consumption elevated fecal short-chain fatty acid (SCFA) concentrations, altered fecal microbial diversity, and increased the abundances of Rikenellaceae_RC9_gut_group, Alloprevotella, Parabacteroides, Roseburia, and Sphaerochaeta, which were positively correlated to plasma serotonin concentration.

CONCLUSIONS

DF consumption improved insulin sensitivity during late pregnancy in sows, which improved microbial diversity in fecal samples and increased fecal SCFA concentrations, resulting in a positive correlation with plasma serotonin level.

Maternal Serum Polyols and Its Link to Gestational Diabetes Mellitus: A Population-Based Nested Case-Control Study

CONTEXT

Sugar alcohols (also called polyols) are regarded as a "healthy" sugar substitute. One of the possible reasons for their safe use in pregnant women is their natural origin and the presence of polyols in maternal and fetal samples during normal human gestation. But little is known about the association between circulating sugar alcohols levels and maternal metabolic disorders during pregnancy.

OBJECTIVE

We aimed to detect the concentration of the polyols in participants with and without gestational diabetes mellitus (GDM), and to investigate the association between maternal serum levels of polyols and GDM, as well as newborn outcomes.

METHODS

A nested population-based case-control study was conducted in 109 women with and without GDM. Maternal concentrations of serum erythritol, sorbitol, and xylitol in the fasting state were quantified using a time of flight mass spectrometry system.

RESULT

In women with GDM, serum concentrations of erythritol and sorbitol were higher, but serum concentrations of xylitol were lower than those in women without GDM. Per 1-SD increment of Box-Cox-transformed concentrations of erythritol and sorbitol were associated with the increased odds of GDM by 43% and 155% (95% CI 1.07-1.92 and 95% CI 1.77-3.69), while decreased odds were found for xylitol by 25% (95% CI 0.57-1.00). Additionally, per 1-SD increase of Box-Cox-transformed concentrations of serum sorbitol was associated with a 52% increased odds of large for gestational age newborns controlling for possible confounders (95% CI 1.00-2.30).

CONCLUSION

Maternal circulating sugar alcohols levels during pregnancy were significantly associated with GDM. These findings provide the potential roles of polyols on maternal metabolic health during pregnancy.

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.

Liver ChREBP deficiency inhibits fructose-induced insulin resistance in pregnant mice and female offspring

High fructose intake during pregnancy increases insulin resistance (IR) and gestational diabetes mellitus (GDM) risk. IR during pregnancy primarily results from elevated hormone levels. We aim to determine the role of liver carbohydrate response element binding protein (ChREBP) in insulin sensitivity and lipid metabolism in pregnant mice and their offspring. Pregnant C57BL/6J wild-type mice and hepatocyte-specific ChREBP-deficient mice were fed with a high-fructose diet (HFrD) or normal chow diet (NC) pre-delivery. We found that the combination of HFrD with pregnancy excessively activates hepatic ChREBP, stimulating progesterone synthesis by increasing MTTP expression, which exacerbates IR. Increased progesterone levels upregulated hepatic ChREBP via the progesterone-PPARγ axis. Placental progesterone activated the progesterone-ChREBP loop in female offspring, contributing to IR and lipid accumulation. In normal dietary conditions, hepatic ChREBP modestly affected progesterone production and influenced IR during pregnancy. Our findings reveal the role of hepatic ChREBP in regulating insulin sensitivity and lipid homeostasis in both pregnant mice consuming an HFrD and female offspring, and suggest it as a potential target for managing gestational metabolic disorders, including GDM.

GCKR and ADIPOQ gene polymorphisms in women with gestational diabetes mellitus

AIMS

To investigate the associations of GCKR and ADIPOQ variants with the risk of gestational diabetes mellitus (GDM) in Chinese women.

METHODS

GCKR rs1260326, ADIPOQ rs266729, and rs1501299 were selected and genotyped in 519 GDM patients and 498 controls. Candidate SNPs were genotyped using multiplex polymerase chain reaction (PCR) combined with next-generation sequencing methods, and the association of these SNPs with GDM was analyzed.

RESULTS

We found that GCKR rs1260326 was significantly associated with an increased risk of GDM in the allele model, the codominant model (CC vs. TT), the dominant model, the recessive model, and the genotypic model distributions (p = 0.0029, p = 0.0022, p = 0.0402, p = 0.0038, and p = 0.0028, respectively). The rs1260326 polymorphism was shown to be associated with 1 h-OGTT level and gravidity in GDM patients (CC vs. TT: p = 0.0475 and p = 0.0220, respectively). Diastolic blood pressure (DBP) was significantly higher in the GDM patients with the rs266729 GG genotype compared to those with the CC or CG genotype (p = 0.0444 and p = 0.0339, respectively). The DBP of the GDM patients with the rs1501299 GT genotype was lower than that of those with the GG genotype (p = 0.0197). There was a weak linkage disequilibrium value between the GCKR and ADIPOQ SNPs.

CONCLUSIONS

The genes GCKR and ADIPOQ may be involved in the pathophysiology of GDM.

Metabolomic insights into maternal and neonatal complications in pregnancies affected by type 1 diabetes

AIMS/HYPOTHESIS

Type 1 diabetes in pregnancy is associated with suboptimal pregnancy outcomes, attributed to maternal hyperglycaemia and offspring hyperinsulinism (quantifiable by cord blood C-peptide). We assessed metabolomic patterns associated with risk factors (maternal hyperglycaemia, diet, BMI, weight gain) and perinatal complications (pre-eclampsia, large for gestational age [LGA], neonatal hypoglycaemia, hyperinsulinism) in the Continuous Glucose Monitoring in Women with Type 1 Diabetes in Pregnancy Trial (CONCEPTT).

METHODS

A total of 174 CONCEPTT participants gave ≥1 non-fasting serum sample for the biorepository at 12 gestational weeks (147 women), 24 weeks (167 women) and 34 weeks (160 women) with cord blood from 93 infants. Results from untargeted metabolite analysis (ultrahigh performance LC-MS) are presented as adjusted logistic/linear regression of maternal and cord blood metabolites, risk factors and perinatal complications using a modified Bonferroni limit of significance for dependent variables.

RESULTS

Maternal continuous glucose monitoring time-above-range (but not BMI or excessive gestational weight gain) was associated with increased triacylglycerols in maternal blood and increased carnitines in cord blood. LGA, adiposity, neonatal hypoglycaemia and offspring hyperinsulinism showed distinct metabolite profiles. LGA was associated with increased carnitines, steroid hormones and lipid metabolites, predominantly in the third trimester. However, neonatal hypoglycaemia and offspring hyperinsulinism were both associated with metabolite changes from the first trimester, featuring triacylglycerols or dietary phenols. Pre-eclampsia was associated with increased abundance of phosphatidylethanolamines, a membrane phospholipid, at 24 weeks.

CONCLUSIONS/INTERPRETATION

Altered lipid metabolism is a key pathophysiological feature of type 1 diabetes pregnancy. New strategies for optimising maternal diet and insulin dosing from the first trimester are needed to improve pregnancy outcomes in type 1 diabetes.

Towards Precision Medicine in Gestational Diabetes: Pathophysiology and Glycemic Patterns in Pregnant Women With Obesity

AIMS

Precision medicine has revolutionized our understanding of type 1 diabetes and neonatal diabetes but has yet to improve insight into gestational diabetes mellitus (GDM), the most common obstetric complication and strongly linked to obesity. Here we explored if patterns of glycaemia (fasting, 1 hour, 2 hours) during the antenatal oral glucose tolerance test (OGTT), reflect distinct pathophysiological subtypes of GDM as defined by insulin secretion/sensitivity or lipid profiles.

METHODS

867 pregnant women with obesity (body mass index ≥ 30 kg/m2) from the UPBEAT trial (ISRCTN 89971375) were assessed for GDM at 28 weeks' gestation (75 g oral glucose tolerance test OGTT; World Health Organization criteria). Lipid profiling of the fasting plasma OGTT sample was undertaken using direct infusion mass spectrometry and analyzed by logistic/linear regression, with and without adjustment for confounders. Insulin secretion and sensitivity were characterized by homeostatic model assessment 2b and 2s, respectively.

RESULTS

In women who developed GDM (n = 241), patterns of glycaemia were associated with distinct clinical and biochemical characteristics and changes to lipid abundance in the circulation. Severity of glucose derangement, rather than pattern of postload glycaemia, was most strongly related to insulin action and lipid abundance/profile. Unexpectedly, women with isolated postload hyperglycemia had comparable insulin secretion and sensitivity to euglycemic women, potentially indicative of a novel mechanistic pathway.

CONCLUSIONS

Patterns of glycemia during the OGTT may contribute to a precision approach to GDM as assessed by differences in insulin resistance/secretion. Further research is indicated to determine if isolated postload hyperglycemia reflects a different mechanistic pathway for targeted management.

Causal effect of early life adiposity on gestational diabetes mellitus and mediating roles of lipidomic biomarkers

Objective

The causal relationship between early life adiposity and gestational diabetes mellitus (GDM) and the underlying mechanisms remains unclear. This study aimed to investigate the independent causal association between early life adiposity and GDM and identify potential metabolic mediators and their mediating effects on this relationship.

Methods

Using genome-wide association study (GWAS) summary statistics from the publicly available database of early life adiposity (5,530 cases and 8,318 controls) and GDM (11,279 cases and 179,600 controls), a two-step, two-sample Mendelian randomization (MR) was conducted to estimate the causal mediation effects of lipidomic biomarkers including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride, apolipoprotein A-Ι, and apolipoprotein B on the relationship between early life adiposity and GDM.

Results

Genetically predicted childhood adiposity was positively associated with risk of GDM (OR: 1.21, 95%CI: 1.09-1.34, p = 4.58 × 10-4). This causal relationship remained after accounting for adult adiposity traits in the multivariable MR analyses. Two-step MR identified three candidate mediators that partially mediated the effect of early life adiposity on GDM, including HDL-C (5.81, 95%CI: 3.05-8.57%), apolipoprotein A-Ι (4.16, 95%CI: 1.64-6.69%), and triglyceride (2.20, 95%CI: 0.48-3.92%).

Conclusion

This MR study demonstrated that the causal effect of childhood obesity on future GDM risk was independent of adult adiposity. We identified three mediators, including HDL-C, apolipoprotein A-Ι, and triglyceride, in this association pathway. Our results provide insights into the pathogenesis of GDM and suggest additional prevention and treatment targets for GDM related to early life adiposity.

Parity and incident type 2 diabetes in older Chinese women: Guangzhou Biobank Cohort Study

This study examined the association between parity and incident type 2 diabetes in older Chinese women and estimated the mediation effect of adiposity indicators. A total of 11,473 women without diabetes at baseline from 2003 to 2008 were followed up until 2012. We used Cox proportional hazards regression to assess the association between parity and incident type 2 diabetes, and mediation analysis to estimate the mediation effect of adiposity indicators. Compared to women with one parity, the hazard ratio (HR) (95% confidence interval (CI)) for incident type 2 diabetes was 0.85 (0.44-1.63), 1.20 (1.11-1.30), 1.28 (1.16-1.41) and 1.27 (1.14-1.42) for women with parity of 0, 2, 3, and ≥ 4, respectively. The proportion of indirect effect (95% CI) mediated by body mass index, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio and body fat percentage was 26.5% (19.2-52.2%), 54.5% (39.4-108.7%), 25.1% (18.2-49.1%), 35.9% (25.6-74.1%), 50.3% (36.5-98.6%) and 15.1% (- 66.4 to 112.3%), respectively. Compared to women with one parity, women with multiparity (≥ 2) had a higher risk of incident type 2 diabetes and up to half of the association was mediated by abdominal obesity.

Metabolic drivers of dysglycemia in pregnancy: ethnic-specific GWAS of 146 metabolites and 1-sample Mendelian randomization analyses in a UK multi-ethnic birth cohort

Introduction

Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required.

Methods

To address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P ≤ 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted.

Results

This study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia.

Discussion

In summary, we confirm and demonstrate the presence of ethnic-specific causal relationships between metabolites and dysglycemia in mid-pregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies.

Distinct maternal metabolites are associated with obesity and glucose-insulin axis in the first trimester of pregnancy

BACKGROUND/OBJECTIVES

Obesity in pregnancy associates with changes in the glucose-insulin axis. We hypothesized that these changes affect the maternal metabolome already in the first trimester of human pregnancy and, thus, aimed to identify these metabolites.

PATIENTS/METHODS

We performed untargeted metabolomics (HPLC-MS/MS) on maternal serum (n = 181, gestational weeks 4⁺⁰-11⁺⁶). For further analysis, we included only non-smoking women as assessed by serum cotinine levels (ELISA) (n = 111). In addition to body mass index (BMI) and leptin as measures of obesity and adiposity, we metabolically phenotyped women by their fasting glucose, C-peptide and insulin sensitivity (IS_HOMA index). To identify metabolites (outcome) associated with BMI, leptin, glucose, C-peptide and/or IS_HOMA (exposures), we used a combination of univariable and multivariable regression analyses with multiple confounders and machine learning methods (Partial Least Squares Discriminant Analysis, Random Forest and Support Vector Machine). Additional statistical tests confirmed robustness of results. Furthermore, we performed network analyses (MoDentify package) to identify sets of correlating metabolites that are coordinately regulated by the exposures.

RESULTS

We detected 2449 serum features of which 277 were annotated. After stringent analysis, 15 metabolites associated with at least one exposure (BMI, leptin, glucose, C-peptide, IS_HOMA). Among these, palmitoleoyl ethanolamine (POEA), an endocannabinoid-like lipid endogenously synthesized from palmitoleic acid, and N-acetyl-L-alanine were consistently associated with C-peptide in all the analyses (95% CI: 0.10-0.34; effect size: 21%; p < 0.001; 95% CI: 0.04-0.10; effect size: 7%; p < 0.001). In network analysis, most features correlating with palmitoleoyl ethanolamide and N-acetyl-L-alanine and associated with C-peptide, were amino acids or dipeptides (n = 9, 35%), followed by lipids (n = 7, 27%).

CONCLUSIONS

We conclude that the metabolome of pregnant women with overweight/obesity is already altered early in pregnancy because of associated changes of C-peptide. Changes of palmitoleoyl ethanolamide concentration in pregnant women with obesity-associated hyperinsulinemia may reflect dysfunctional endocannabinoid-like signalling.

Insulin Resistance Is Associated with an Unfavorable Serum Lipoprotein Lipid Profile in Women with Newly Diagnosed Gestational Diabetes

Background: Gestational diabetes (GDM) is associated with various degrees of insulin resistance—a feature related to increased risk of adverse perinatal outcomes. We aimed to determine the previously poorly investigated associations between maternal insulin resistance and serum fasting metabolome at the time of GDM diagnosis. Methods: Serum lipoprotein and amino acid profile was analyzed in 300 subjects with newly diagnosed GDM using a validated nuclear magnetic resonance spectroscopy protocol. Associations between insulin resistance (homeostasis model assessment of insulin resistance, HOMA2-IR) and serum metabolites were examined with linear regression. Results: We found insulin resistance to be associated with a distinct lipid pattern: increased concentration of VLDL triglycerides and phospholipids and total triglycerides. VLDL size was positively related and LDL and HDL sizes were inversely related to insulin resistance. Of fatty acids, increased total fatty acids, relative increase in saturated and monounsaturated fatty acids, and relative decrease in polyunsaturated and omega fatty acids were related to maternal insulin resistance. Conclusions: In newly diagnosed GDM, the association between maternal insulin resistance and serum lipoprotein profile was largely as described in type 2 diabetes. Lifestyle interventions aiming to decrease insulin resistance from early pregnancy could benefit pregnancy outcomes via more advantageous lipid metabolism.

Three categories of similarities between the placenta and cancer that can aid cancer treatment: Cells, the microenvironment, and metabolites

Cancer is one of the most harmful diseases, while pregnancy is a common condition of females. Placenta is the most important organ for fetal growth, which has not been fully understand. It's well known that placenta and solid tumor have some similar biological behaviors. What's more, decidua, the microenvironment of placenta, and metabolism all undergo adaptive shift for healthy pregnancy. Interestingly, decidua and the tumor microenvironment (TME); metabolism changes during pregnancy and cancer cachexia all have underlying links. However, whether the close link between pregnancy and cancer can bring some new ideas to treat cancer is still unclear. So, in this review we note that pregnancy may offer clues to treat cancer related to three categories: from cell perspective, through the shared development process of the placenta and cancer; from microenvironment perspective, though the shared features of the decidua and TME; and from metabolism perspective, through shared metabolites changes during pregnancy and cancer cachexia. Firstly, comparing gene mutations of both placenta and cancer, which is the underlying mechanism of many similar biological behaviors, helps us understand the origin of cancer and find the key factors to restore tumorigenesis. Secondly, exploring how decidua affect placenta development and similarities of decidua and TME is helpful to reshape TME, then to inhibit cancer. Thirdly, we also illustrate the possibility that the altered metabolites during pregnancy may reverse cancer cachexia. So, some key molecules changed in circulation of pregnancy may help relieve cachexia and make survival with cancer realized.

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.

Validation of a Microwave-Assisted Derivatization Gas Chromatography-Mass Spectrometry Method for the Quantification of 2-Hydroxybutyrate in Human Serum as an Early Marker of Diabetes Mellitus

Circulating levels of 2-hydroxybutyrate (2HB) are highly related to glycemic status in different metabolomic studies. According to recent evidence, 2HB is an early biomarker of the future development of dysglycemia and type 2 diabetes mellitus and may be causally related to the progression of normal subjects to impaired fasting glucose or insulin resistance. In the present study, we developed and validated a simple, specific and sensitive gas chromatography-mass spectrometry (GC-MS) method specifically intended to quantify serum levels of 2HB. Liquid–liquid extraction with ethyl acetate was followed by 2 min of microwave-assisted derivatization. The method presented acceptable accuracy, precision and recovery, and the limit of quantification was 5 µM. Levels of 2HB were found to be stable in serum after three freeze-thaw cycles, and at ambient temperature and at a temperature of 4 °C for up to 24 h. Extracts derivatized under microwave irradiation were stable for up to 96 h. No differences were found in 2HB concentrations measured in serum or plasma EDTA samples. In summary, the method is useful for a rapid, precise and accurate quantification of 2HB in serum samples assessed for the evaluation of dysglycemia and diabetes mellitus.

PM2.5 and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China

BACKGROUND

Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of <2.5μm (PM2.5)] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which PM2.5 contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of PM2.5, gut microbiota, and metabolic diseases are unclear.

OBJECTIVES

We investigated the associations between personal exposure to PM2.5 and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between PM2.5 and insulin resistance and the mediating effects between PM2.5 and sphingolipid metabolism.

METHODS

We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between PM2.5 and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures (PM2.5) and featured metabolism outcomes.

RESULTS

Our prospective panel study illustrated that exposure to PM2.5 was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that PM2.5 exposure may contribute to systemic inflammation and altered sphingolipid metabolism.

DISCUSSION

Our findings demonstrated that PM2.5 was associated with the genera of the gut microbiota, which partially mediated the association between PM2.5 and sphingolipid metabolism. These findings may extend our current understanding of the pathways of PM2.5 and IR. https://doi.org/10.1289/EHP9688.

Transcriptome analysis in comparing carcass and meat quality traits of Jiaxing Black Pig and Duroc × Duroc × Berkshire × Jiaxing Black Pig crosses

This study compares two typical strains: Chinese local excellent meat quality of Jiaxing Black (JXB) Pig and quadratic crossbred pig strain Duroc × Duroc × Berkshire × Jiaxing Black (DDBJ). It was found that between the two pig strains, carcass traits and meat quality traits differed significantly. This is exemplified by the leanness and dressing out percent of DDBJ that were significantly higher than JXB pigs of the same age (P < 0.05) and the better growth rate of DDBJ pigs as to JXB pigs was shown by quantifying muscle proliferation and differentiation of longissimus dorsi muscle employing Hematoxylin and Eosin staining of longissimus dorsi muscle. Nutrients such as inosinic acid, intramuscular fat, and free amino acids in the longissimus dorsi muscle were significantly higher in JXB pigs than DDBJ pigs (p < 0.0001); saturated fatty acids were higher in JXB than in DDBJ pigs (p = 0.0097); essential amino acids and fresh taste amino acids (serine, glutamic acid, proline, glycine, alanine) of JXB pigs was higher than that of DDBJ pigs (p < 0.0001) and amino acids in longissimus dorsi muscle of JXB pigs surpasses the amino acid concentration of DDBJ pigs (p < 0.0001), thus showing the superiority of JXB in terms of meat quality. However, the content of polyunsaturated fatty acids, which is responsible for poor meat quality, was significantly higher in the longissimus dorsi muscle of DDBJ pig than JXB pigs (p < 0.0001); RNA-seq analysis of 5 biological replicates from two of the strains was performed. The screening of 164 up-regulated genes and 183 down-regulated genes found in longissimus dorsi muscle of DDBJ was done and the results identified differentially expressed genes related to muscle development, adipogenesis, amino acid metabolism, fatty acid metabolism and inosine synthesis. In conclusion, the study identified functional genes, elucidated the mechanisms associated with carcass quality traits, meat quality traits and other related traits, and provided means of genetic enhancement to improve meat quality traits and carcass traits in Chinese commercial pigs.

Association of glucose metabolism and blood pressure during pregnancy with subsequent maternal blood pressure

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.

Maternal Metabolites Associated With Gestational Diabetes Mellitus and a Postpartum Disorder of Glucose Metabolism

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.

Serum and Amniotic Fluid Metabolic Profile Changes in Response to Gestational Diabetes Mellitus and the Association with Maternal-Fetal Outcomes

This study was designed to identify serum and amniotic fluid (AF) metabolic profile changes in response to gestational diabetes mellitus (GDM) and explore the association with maternal-fetal outcomes. We established the GDM rat models by combining a high-fat diet (HFD) with an injection of low-dose streptozotocin (STZ), detected the fasting plasma glucose (FPG) of pregnant rats in the second and third trimester, and collected AF and fetal rats by cesarean section on gestational day 19 (GD19), as well as measuring the weight and crown-rump length (CRL) of fetal rats. We applied liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the untargeted metabolomics analyses of serum and AF samples and then explored their correlation with maternal-fetal outcomes via the co-occurrence network. The results showed that 91 and 68 metabolites were upregulated and 125 and 78 metabolites were downregulated in serum and AF samples exposed to GDM, respectively. In maternal serum, the obvious alterations emerged in lipids and lipid-like molecules, while there were great changes in carbohydrate and carbohydrate conjugates, followed by amino acids, peptides, and analogs in amniotic fluid. The altered pathways both in serum and AF samples were amino acid, lipid, nucleotide, and vitamin metabolism pathways. In response to GDM, changes in the steroid hormone metabolic pathway occurred in serum, and an altered carbohydrate metabolism pathway was found in AF samples. Among differential metabolites in two kinds of samples, there were 34 common biochemicals shared by serum and AF samples, and a mutual significant association existed. These shared differential metabolites were implicated in several metabolism pathways, including choline, tryptophan, histidine, and nicotinate and nicotinamide metabolism, and among them, N1-methyl-4-pyridone-3-carboxamide, 5'-methylthioadenosine, and kynurenic acid were significantly associated with both maternal FPG and fetal growth. In conclusion, serum and AF metabolic profiles were remarkably altered in response to GDM. N1-Methyl-4-pyridone-3-carboxamide, 5'-methylthioadenosine, and kynurenic acid have the potential to be taken as biomarkers for maternal-fetal health status of GDM. The common and inter-related differential metabolites both in the serum and AF implied the feasibility of predicting fetal health outcomes via detecting the metabolites in maternal serum exposed to GDM.

Obesity Genomics and Metabolomics: a Nexus of Cardiometabolic Risk

PURPOSE OF REVIEW

Obesity is a significant international public health epidemic with major downstream consequences on morbidity and mortality. While lifestyle factors contribute, there is an evolving understanding of genomic and metabolomic pathways involved with obesity and its relationship with cardiometabolic risk. This review will provide an overview of some of these important findings from both a biologic and clinical perspective.

RECENT FINDINGS

Recent studies have identified polygenic risk scores and metabolomic biomarkers of obesity and related outcomes, which have also highlighted biological pathways, such as the branched-chain amino acid (BCAA) pathway that is dysregulated in this disease. These biomarkers may help in personalizing obesity interventions and for mitigation of future cardiometabolic risk. A multifaceted approach is necessary to impact the growing epidemic of obesity and related diseases. This will likely include incorporating precision medicine approaches with genomic and metabolomic biomarkers to personalize interventions and improve risk prediction.

Genetics and Epigenetics: New Insight on Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is the most common metabolic complication of pregnancy, with a prevalence that has increased significantly in the last decade, coming to affect 12-18% of all pregnancies. GDM is believed to be the result of a combination of genetic, epigenetic and environmental factors. Following the identification of susceptibility genes for type 2 diabetes by means of genome-wide association studies, an association has also been demonstrated between some type 2 diabetes susceptibility genes and GDM, suggesting a partial similarity of the genetic architecture behind the two forms of diabetes. More recent genome-wide association studies, focusing on maternal metabolism during pregnancy, have demonstrated an overlap in the genes associated with metabolic traits in gravid and non-gravid populations, as well as in genes apparently unique to pregnancy. Epigenetic changes-such as DNA methylation, histone modifications and microRNA gene silencing-have also been identified in GDM patients. Metabolomics has been used to profile the metabolic state of women during pregnancy, based on the measurement of numerous low-molecular-weight metabolites. Measuring amino acids and conventional metabolites has revealed changes in pregnant women with a higher insulin resistance and high blood glucose levels that resemble the changes seen in non-gravid, insulin-resistant populations. This would suggest similarities in the metabolic profiles typical of insulin resistance and hyperglycemia whether individuals are pregnant or not. Future studies combining data obtained using multiple technologies will enable an integrated systems biology approach to maternal metabolism during a pregnancy complicated by GDM. This review highlights the recent knowledge on the impact of genetics and epigenetics in the pathophysiology of GDM and the maternal and fetal complications associated with this pathology condition.