Large-Scale Longitudinal Metabolomics Study Reveals Different Trimester-Specific Alterations of Metabolites in Relation to Gestational Diabetes Mellitus

Longitudinal Plasma Metabolome Patterns and Relation to Kidney Function and Proteinuria in Pediatric CKD

Key Points

Longitudinal untargeted metabolomics. Children with CKD have a circulating metabolome that changes over time.

Background

Understanding plasma metabolome patterns in relation to changing kidney function in pediatric CKD is important for continued research for identifying novel biomarkers, characterizing biochemical pathophysiology, and developing targeted interventions. There are a limited number of studies of longitudinal metabolomics and virtually none in pediatric CKD.

Methods

The CKD in Children study is a multi-institutional, prospective cohort that enrolled children aged 6 months to 16 years with eGFR 30–90 ml/min per 1.73 m2. Untargeted metabolomics profiling was performed on plasma samples from the baseline, 2-, and 4-year study visits. There were technologic updates in the metabolomic profiling platform used between the baseline and follow-up assays. Statistical approaches were adopted to avoid direct comparison of baseline and follow-up measurements. To identify metabolite associations with eGFR or urine protein-creatinine ratio (UPCR) among all three time points, we applied linear mixed-effects (LME) models. To identify metabolites associated with time, we applied LME models to the 2- and 4-year follow-up data. We applied linear regression analysis to examine associations between change in metabolite level over time (∆level) and change in eGFR (∆eGFR) and UPCR (∆UPCR). We reported significance on the basis of both the false discovery rate (FDR) <0.05 and P < 0.05.

Results

There were 1156 person-visits (N : baseline=626, 2-year=254, 4-year=276) included. There were 622 metabolites with standardized measurements at all three time points. In LME modeling, 406 and 343 metabolites associated with eGFR and UPCR at FDR <0.05, respectively. Among 530 follow-up person-visits, 158 metabolites showed differences over time at FDR <0.05. For participants with complete data at both follow-up visits (n =123), we report 35 metabolites with ∆level–∆eGFR associations significant at FDR <0.05. There were no metabolites with significant ∆level–∆UPCR associations at FDR <0.05. We report 16 metabolites with ∆level–∆UPCR associations at P < 0.05 and associations with UPCR in LME modeling at FDR <0.05.

Conclusions

We characterized longitudinal plasma metabolomic patterns associated with eGFR and UPCR in a large pediatric CKD population. Many of these metabolite signals have been associated with CKD progression, etiology, and proteinuria in previous CKD Biomarkers Consortium studies. There were also novel metabolite associations with eGFR and proteinuria detected.

ÁP, Alvarez AM. From gut to placenta: understanding how the maternal microbiome models life-long conditions

The microbiome -defined as the microbiota (bacteria, archaea, lower and higher eukaryotes), their genomes, and the surrounding environmental conditions- has a well-described range of physiological functions. Thus, an imbalance of the microbiota composition -dysbiosis- has been associated with pregnancy complications or adverse fetal outcomes. Although there is controversy about the existence or absence of a microbiome in the placenta and fetus during healthy pregnancy, it is known that gut microbiota can produce bioactive metabolites that can enter the maternal circulation and may be actively or passively transferred through the placenta. Furthermore, the evidence suggests that such metabolites have some effect on the fetus. Since the microbiome can influence the epigenome, and modifications of the epigenome could be responsible for fetal programming, it can be experimentally supported that the maternal microbiome and its metabolites could be involved in fetal programming. The developmental origin of health and disease (DOHaD) approach looks to understand how exposure to environmental factors during periods of high plasticity in the early stages of life (e.g., gestational period) influences the program for disease risk in the progeny. Therefore, according to the DOHaD approach, the influence of maternal microbiota in disease development must be explored. Here, we described some of the diseases of adulthood that could be related to alterations in the maternal microbiota. In summary, this review aims to highlight the influence of maternal microbiota on both fetal development and postnatal life, suggesting that dysbiosis on this microbiota could be related to adulthood morbidity.

Untargeted metabolomics reveals dynamic changes in metabolic profiles of rat supraspinatus tendon at three different time points after diabetes induction

Objective

To investigate the dynamic changes of metabolite composition in rat supraspinatus tendons at different stages of diabetes by untargeted metabolomics analysis.

Methods

A total of 80 Sprague-Dawley rats were randomly divided into normal (NG, n = 20) and type 2 diabetes mellitus groups (T2DM, n = 60) and subdivided into three groups according to the duration of diabetes: T2DM-4w, T2DM-12w, and T2DM-24w groups; the duration was calculated from the time point of T2DM rat model establishment. The three comparison groups were set up in this study, T2DM-4w group vs. NG, T2DM-12w group vs. T2DM-4w group, and T2DM-24w group vs. T2DM-12w group. The metabolite profiles of supraspinatus tendon were obtained using tandem mass spectrometry. Metabolomics multivariate statistics were used for metabolic data analysis and differential metabolite (DEM) determination. The intersection of the three comparison groups' DEMs was defined as key metabolites that changed consistently in the supraspinatus tendon after diabetes induction; then, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed.

Results

T2DM-4w group vs. NG, T2DM-12w group vs. T2DM-4w group, and T2DM-24w group vs. T2DM-12w group detected 94 (86 up-regulated and 8 down-regulated), 36 (13 up-regulated and 23 down-regulated) and 86 (24 up-regulated and 62 down-regulated) DEMs, respectively. Seven key metabolites of sustained changes in the supraspinatus tendon following induction of diabetes include D-Lactic acid, xanthine, O-acetyl-L-carnitine, isoleucylproline, propoxycarbazone, uric acid, and cytidine, which are the first identified biomarkers of the supraspinatus tendon as it progresses through the course of diabetes. The results of KEGG pathway enrichment analysis showed that the main pathway of supraspinatus metabolism affected by diabetes (p < 0.05) was purine metabolism. The results of the KEGG metabolic pathway vs. DEMs correlation network graph revealed that uric acid and xanthine play a role in more metabolic pathways.

Conclusion

Untargeted metabolomics revealed the dynamic changes of metabolite composition in rat supraspinatus tendons at different stages of diabetes, and the newly discovered seven metabolites, especially uric acid and xanthine, may provide novel research to elucidate the mechanism of diabetes-induced tendinopathy.

Associations of early pregnancy serum uric acid levels with risk of gestational diabetes and birth outcomes: a retrospective cohort study

BACKGROUND

Previous evidence suggests that higher blood uric acid (UA) levels are associated with adverse cardiovascular outcomes during pregnancy and subsequent birth outcomes. However, it has been relatively unclear whether these associations persist in normotensive pregnant women.

METHODS

The study was based on a retrospective analysis of 18,250 mother-infant pairs in a large obstetric center in China. Serum UA concentrations in early pregnancy (median: 17.6, IQR: 16.3, 18.6 gestational weeks) were assessed. Hyperuricemia was defined as ≥ one standard deviation (SD) of the reference value for the corresponding gestational age. Outcomes of gestational diabetes mellitus (GDM), preterm birth (PB), low birth weight (LBW), macrosomia, small for gestational age (SGA) and large for gestational age (LGA) were extracted from the medical records.

RESULTS

The mean maternal UA level was 0.22 ± 0.05 mmol/L, and 2,896 (15.9%) subjects had hyperuricemia. After adjustment for several covariates, UA was associated with several adverse outcomes. The ORs (95%CI) per one SD increase in serum UA concentration were 1.250 (1.136, 1.277) for GDM, 1.137 (1.060, 1.221) for PB, 1.134 (1.051, 1.223) for LBW, and 1.077 (1.020, 1.137) for SGA, respectively. Similar adverse associations were found between hyperuricemia and GDM, PB (ORs: 1.394 and 1.385, P < 0.001), but not for LBW, macrosomia, SGA, and LGA. Adverse associations tended to be more pronounced in subjects with higher BMI for outcomes including PB, LBW, and SGA (P interaction = 0.001-0.028).

CONCLUSION

Higher UA levels in early pregnancy were associated with higher risk of GDM, PB, LBW, and SGA in normotensive Chinese women.

Serum uric acid and the risk of gestational diabetes mellitus: a systematic review and meta-analysis

AIMS

Serum uric acid (SUA) is considered as a risk factor for gestational diabetes mellitus (GDM). However, current studies showed inconsistent results. This study aimed to explore the relationship between SUA levels and GDM risk.

METHODS

Eligible studies were retrieved from PubMed, Web of Science, Embase, China National Knowledge Infrastructure, and Wanfang databases up to November 1, 2022. The pooled standardized mean difference (SMD) and 95% confidence interval (CI) were used to represent the difference in SUA levels between GDM women and controls. The combined odds ratios (OR) and 95% CI were applied to assess association between SUA levels and GDM risk. Subgroup analyses were conducted on study continents, design, and quality, detection time of SUA, and GDM diagnostic criteria.

RESULTS

Totally 11 studies including five case-control and six cohort studies, in which 80,387 pregnant women with 9815 GDM were included. The overall meta-analysis showed that the mean SUA level in GDM group was significantly higher than in controls (SMD = 0.423, 95%CI = 0.019-0.826, p = .040, I² = 93%). Notably, pregnant women with elevated levels of SUA had a significantly increased risk of GDM (OR = 1.670, 95%CI = 1.184-2.356, p = .0035, I² = 95%). Furthermore, subgroup analysis performed on the detection time of SUA showed a significant difference in the association between SUA and GDM risk within different trimesters (1st trimester: OR = 3.978, 95%CI = 2.177-7.268; 1st to 2nd trimester: OR = 1.340, 95%CI = 1.078-1.667; p between subgroups <.01).

CONCLUSIONS

Elevated SUA was positively associated with GDM risk, particularly in the 1st trimester of pregnancy. Further studies with high quality are required to validate the findings of this study.

UHPLC-MS/MS-Based Metabolomics and Clinical Phenotypes Analysis Reveal Broad-Scale Perturbations in Early Pregnancy Related to Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is the most common metabolic disturbance during pregnancy, with adverse effects on both mother and fetus. The establishment of early diagnosis and risk assessment model is of great significance for preventing and reducing adverse outcomes of GDM. In this study, the broad-scale perturbations related to GDM were explored through the integration analysis of metabolic and clinical phenotypes. Maternal serum samples from the first trimester were collected for targeted metabolomics analysis by using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Statistical analysis was conducted based on the levels of the 184 metabolites and 76 clinical indicators from GDM women ( $n$  =60) and matched healthy controls ( $n$  =90). Metabolomics analysis revealed the down-regulation of fatty acid oxidation in the first trimester of GDM women, which was supposed to be related to the low serum level of dehydroepiandrosterone.While the significantly altered clinical phenotypes were mainly related to the increased risk of cardiovascular disease, abnormal iron metabolism, and inflammation. A phenotype panel established from the significantly changed serum indicators can be used for the early prediction of GDM, with the area under the receiver-operating characteristic curve (ROC) 0.83. High serum uric acid and C-reaction protein levels were risk factors for GDM independent of body mass indexes, with ORs 4.76 (95% CI: 2.08-10.90) and 3.10 (95% CI: 1.38-6.96), respectively. Predictive phenotype panel of GDM, together with the risk factors of GDM, will provide novel perspectives for the early clinical warning and diagnosis of GDM.

Maternal and Fetal Metabolites in Gestational Diabetes Mellitus: A Narrative Review

Gestational diabetes mellitus (GDM) is a major public health issue of our century due to its increasing prevalence, affecting 5% to 20% of all pregnancies. The pathogenesis of GDM has not been completely elucidated to date. Increasing evidence suggests the association of environmental factors with genetic and epigenetic factors in the development of GDM. So far, several metabolomics studies have investigated metabolic disruptions associated with GDM. The aim of this review is to highlight the usefulness of maternal metabolites as diagnosis markers of GDM as well as the importance of both maternal and fetal metabolites as prognosis biomarkers for GDM and GDM’s transition to type 2 diabetes mellitus T2DM.

The effects of gestational diabetes mellitus with maternal age between 35 and 40 years on the metabolite profiles of plasma and urine

Background

Gestational diabetes mellitus (GDM) is defined as impaired glucose tolerance in pregnancy and without a history of diabetes mellitus. While there are limited metabolomic studies involving advanced maternal age in China, we aim to investigate the metabolomic profiling of plasma and urine in pregnancies complicated with GDM aged at 35–40 years at early and late gestation.

Methods

Twenty normal and 20 GDM pregnant participants (≥ 35 years old) were enlisted from the Complex Lipids in Mothers and Babies (CLIMB) study. Maternal plasma and urine collected at the first and third trimester were detected using gas chromatography-mass spectrometry (GC-MS).

Results

One hundred sixty-five metabolites and 192 metabolites were found in plasma and urine respectively. Urine metabolomic profiles were incapable to distinguish GDM from controls, in comparison, there were 14 and 39 significantly different plasma metabolites between the two groups in first and third trimester respectively. Especially, by integrating seven metabolites including cysteine, malonic acid, alanine, 11,14-eicosadienoic acid, stearic acid, arachidic acid, and 2-methyloctadecanoic acid using multivariant receiver operating characteristic models, we were capable of discriminating GDM from normal pregnancies with an area under curve of 0.928 at first trimester.

Conclusion

This study explores metabolomic profiles between GDM and normal pregnancies at the age of 35–40 years longitudinally. Several compounds have the potential to be biomarkers to predict GDM with advanced maternal age. Moreover, the discordant metabolome profiles between the two groups could be useful to understand the etiology of GDM with advanced maternal age.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04416-5.

Dynamic changes and early predictive value of branched-chain amino acids in gestational diabetes mellitus during pregnancy

OBJECTIVE

Branched-chain amino acids (BCAAs) are closely associated with type 2 diabetes mellitus, but their roles in gestational diabetes mellitus (GDM) are still controversial. This study aims to explore the dynamic changes of BCAAs during pregnancy and identify potential early biomarkers for GDM.

METHODS

This study is a nested case-control study involved 49 women with GDM and 50 age- and body mass index (BMI)-matched healthy pregnant women. The dynamic changes of valine (Val), isoleucine (Ile), and leucine (Leu) were detected in the first (8-12 weeks) and second trimesters (24-28 weeks) by liquid chromatography-mass spectrometry.

RESULTS

Serum Val, Ile, and Leu were higher in GDM patients than in controls in the first trimester. Compared with the first trimester, the serum Val, Ile, and Leu in GDM patients were decreased in the second trimester. In addition, Val, Ile, and Leu in the first trimester were the risk factors for GDM, and Ile presented a high predictive value for GDM. Ile + age (≥ 35) + BMI (≥ 24) exhibited the highest predictive value for GDM (AUC = 0.902, sensitivity = 93.9%, specificity = 80%).

CONCLUSION

Maternal serum Ile in the first trimester was a valuable biomarker for GDM. Ile combined with advanced maternal age and overweight may be used for the early prediction of GDM.

Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnant women. The early detection of GDM provides an opportunity for the effective treatment of hyperglycemia in pregnancy, thus decreasing the risk of adverse perinatal outcomes for mothers and newborns. Metabolomics, an emerging technique, offers a novel point of view in understanding the onset and development of diseases and has been repeatedly used in various gestational periods in recent studies of GDM. Moreover, metabolomics provides varied opportunities in the different diagnoses of GDM from prediabetes or predisposition to diabetes, the diagnosis of GDM at a gestational age several weeks earlier than that used in the traditional method, and the assessment of prognosis considering the physiologic subtypes of GDM and clinical indexes. Longitudinal metabolomics truly facilitates the dynamic monitoring of metabolic alterations over the course of pregnancy. Herein, we review recent advancements in metabolomics and summarize evidence from studies on the application of metabolomics in GDM, highlighting the aspects of the diagnosis and differential diagnoses of GDM in an early stage. We also discuss future study directions concerning the physiologic subtypes, prognosis, and limitations of metabolomics.

Metabolites involved in purine degradation, insulin resistance, and fatty acid oxidation are associated with prediction of Gestational diabetes in plasma

INTRODUCTION

Gestational diabetes mellitus (GDM) significantly increases maternal and fetal health risks, but factors predictive of GDM are poorly understood.

OBJECTIVES

Plasma metabolomics analyses were conducted in early pregnancy to identify potential metabolites associated with prediction of GDM.

METHODS

Sixty-eight pregnant women with overweight/obesity from a clinical trial of a lifestyle intervention were included. Participants who developed GDM (n = 34; GDM group) were matched on treatment group, age, body mass index, and ethnicity with those who did not develop GDM (n = 34; Non-GDM group). Blood draws were completed early in pregnancy (10-16 weeks). Plasma samples were analyzed by UPLC-MS using three metabolomics assays.

RESULTS

One hundred thirty moieties were identified. Thirteen metabolites including pyrimidine/purine derivatives involved in uric acid metabolism, carboxylic acids, fatty acylcarnitines, and sphingomyelins (SM) were different when comparing the GDM vs. the Non-GDM groups (p < 0.05). The most significant differences were elevations in the metabolites' hypoxanthine, xanthine and alpha-hydroxybutyrate (p < 0.002, adjusted p < 0.02) in GDM patients. A panel consisting of four metabolites: SM 14:0, hypoxanthine, alpha-hydroxybutyrate, and xanthine presented the highest diagnostic accuracy with an AUC = 0.833 (95% CI: 0.572686-0.893946), classifying as a "very good panel".

CONCLUSION

Plasma metabolites mainly involved in purine degradation, insulin resistance, and fatty acid oxidation, were altered in early pregnancy in connection with subsequent GDM development.

Potential biomarkers identified in plasma of patients with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common complication during pregnancy. Looking for reliable diagnostic markers for early diagnosis can reduce the impact of the disease on the fetus OBJECTIVE: The present study is designed to find plasma metabolites that can be used as potential biomarkers for GDM, and to clarify GDM-related mechanisms METHODS: By non-target metabolomics analysis, compared with their respective controls, the plasma metabolites of GDM pregnant women at 12-16 weeks and 24-28 weeks of pregnancy were analyzed. Multiple reaction monitoring (MRM) analysis was performed to verify the potential marker RESULTS: One hundred and seventy-two (172) and 478 metabolites were identified as differential metabolites in the plasma of GDM pregnant women at 12-16 weeks and 24-28 weeks of pregnancy, respectively. Among these, 40 metabolites were overlapped. Most of them are associated with the mechanism of diabetes, and related to short-term and long-term complications in the perinatal period. Among them, 7 and 10 differential metabolites may serve as potential biomarkers at the 12-16 weeks and 24-28 weeks of pregnancy, respectively. By MRM analysis, compared with controls, increased levels of 17(S)-HDoHE and sebacic acid may serve as early prediction biomarkers of GDM. At 24-28 weeks of pregnancy, elevated levels of 17(S)-HDoHE and L-Serine may be used as auxiliary diagnostic markers for GDM CONCLUSION: Abnormal amino acid metabolism and lipid metabolism in patients with GDM may be related to GDM pathogenesis. Several differential metabolites identified in this study may serve as potential biomarkers for GDM prediction and diagnosis.

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.

Current progress in metabolomics of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders of pregnancy and can cause short- and long-term adverse effects in both pregnant women and their offspring. However, the etiology and pathogenesis of GDM are still unclear. As a metabolic disease, GDM is well suited to metabolomics study, which can monitor the changes in small molecular metabolites induced by maternal stimuli or perturbations in real time. The application of metabolomics in GDM can be used to discover diagnostic biomarkers, evaluate the prognosis of the disease, guide the application of diet or drugs, evaluate the curative effect, and explore the mechanism. This review provides comprehensive documentation of metabolomics research methods and techniques as well as the current progress in GDM research. We anticipate that the review will contribute to identifying gaps in the current knowledge or metabolomics technology, provide evidence-based information, and inform future research directions in GDM.

A non-targeted LC-MS metabolic profiling of pregnancy: longitudinal evidence from healthy and pre-eclamptic pregnancies

INTRODUCTION

Maternal metabolism changes substantially during pregnancy. However, few studies have used metabolomics technologies to characterize changes across gestation.

OBJECTIVES AND METHODS

We applied liquid chromatography-mass spectrometry (LC-MS) based non-targeted metabolomics to determine whether the metabolic profile of serum differs throughout the pregnancy between pre-eclamptic and healthy women in the FINNPEC (Finnish Genetics of Preeclampsia Consortium) Study. Serum samples were available from early and late pregnancy.

RESULTS

Progression of pregnancy had large-scale effects to the serum metabolite profile. Altogether 50 identified metabolites increased and 49 metabolites decreased when samples of early pregnancy were compared to samples of late pregnancy. The metabolic signatures of pregnancy were largely shared in pre-eclamptic and healthy women, only urea, monoacylglyceride 18:1 and glycerophosphocholine were identified to be increased in the pre-eclamptic women when compared to healthy controls.

CONCLUSIONS

Our study highlights the need of large-scale longitudinal metabolomic studies in non-complicated pregnancies before more detailed understanding of metabolism in adverse outcomes could be provided. Our findings are one of the first steps for a broader metabolic understanding of the physiological changes caused by pregnancy per se.

Markers of branched-chain amino acid catabolism are not affected by exercise training in pregnant women with obesity

Despite the role of branched-chain amino acids (BCAAs) in physiological processes such as nutrient signaling and protein synthesis, there is ongoing debate about the link between circulating BCAAs and insulin resistance (IR) in various populations. In healthy women, IR mildly increases during pregnancy, whereas both BCAAs and markers of BCAA catabolism decrease, indicating that fetal growth is being prioritized. Exercise reduces IR in nonpregnant adults, but less is known about the effect of exercise during pregnancy in women with obesity on IR and BCAA breakdown. The aim of this study was to determine the effect of a moderate-intensity exercise intervention during pregnancy on maternal circulating BCAAs and markers of BCAA catabolism [short-chain acylcarnitines (ACs)], and their associations with IR. Healthy obese [n = 80, means ± SD; body mass index (BMI): 36.9 ± 5.7 kg/m²] pregnant women were randomized into an exercise (n = 40, aerobic/resistance 3×/wk, ∼13th gestation week until birth) or a nonexercise control (n = 40) group. Blood was collected at 12.2 ± 0.5 and 36.0 ± 0.4 gestation weeks and analyzed for BCAA-derived acylcarnitine concentrations as markers of BCAA breakdown toward oxidative pathways, and glucose and insulin concentrations [updated homeostatic model assessment of IR (HOMA2-IR)]. After adjusting for HOMA2-IR, there were no interaction effects of group by time. In addition, there was a main positive effect of time on HOMA2-IR (12 wk: 2.3 ± 0.2, 36 wk: 3.0 ± 0.2, P = 0.003). A moderate-intensity exercise intervention during pregnancy in women with obesity was not associated with changes in BCAA-derived ACs versus standard of care. The decrease in BCAA-derived ACs throughout gestation could not be explained by IR.NEW & NOTEWORTHY This research showed an increase in insulin resistance (IR) and decrease in branched-chain amino acid catabolism throughout gestation in women with obesity, and addition of a moderate exercise intervention (known to attenuate IR in nonpregnant populations) did not alter these shifts. Findings provide support for metabolic safety of exercise during pregnancy.

Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population

OBJECTIVE

Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy.

METHODS

A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10-13⁺⁶ weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis.

RESULTS

A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR < 0.1) correction. In the GDM group, the levels of L-pyroglutamic acid, L-glutamic acid, phenylacetic acid, pantothenic acid, and xanthine were significantly higher and the levels of 1,5-anhydro-D-glucitol, calcitriol, and 4-oxoproline were significantly lower than those in the control group. These metabolites were involved in multiple metabolic pathways, including those for amino acid, carbohydrate, lipid, energy, nucleotide, cofactor, and vitamin metabolism.

CONCLUSIONS

We identified significant differentially expressed metabolites associated with the risk of GDM, providing insight into the mechanisms underlying GDM in early pregnancy and candidate predictive markers.

FGF21 Serum Levels in the Early Second Trimester Are Positively Correlated With the Risk of Subsequent Gestational Diabetes Mellitus: A Propensity-Matched Nested Case-Control Study

BACKGROUND

As an important endocrine hormone regulating glucose metabolism, fibroblast growth factor 21 (FGF21) is increased in individuals with gestational diabetes mellitus (GDM) after 24 gestational weeks. However, it is unknown whether the increase in FGF21 precedes the diagnosis of GDM.

METHODS

In this nested case-control study, 133 pregnant women with GDM and 133 pregnant women with normal glucose tolerance (NGT) were identified through propensity score matching, and serum FGF21 levels were measured at 14 to 21 gestational weeks, before GDM is routinely identified. The differences in FGF21 levels were compared. The association between FGF21 and the occurrence of GDM was evaluated using logistic regression models with adjustment for confounders.

RESULTS

The serum FGF21 levels of the GDM group at 14 to 21 gestational weeks were significantly higher than those of the NGT group overall (P < 0.001), with similar results observed between the corresponding BMI subgroups (P < 0.05). The 2nd (OR 1.224, 95% CI 0.603-2.485), 3rd (OR 2.478, 1.229-5.000), and 4th (OR 3.419, 95% CI 1.626-7.188) FGF21 quartiles were associated with greater odds of GDM occurrence than the 1st quartile after multivariable adjustments.

CONCLUSIONS

The serum FGF21 levels in GDM groups increased in the early second trimester, regardless of whether participants were stratified according to BMI. After adjusting for confounding factors, the FGF21 levels in the highest quartile were associated with more than three times higher probability of the diagnosis of GDM in the pregnancy as compared to levels in the first quartile.

Regulation of maternal-fetal metabolic communication

Pregnancy may be the most nutritionally sensitive stage in the life cycle, and improved metabolic health during gestation and early postnatal life can reduce the risk of chronic disease in adulthood. Successful pregnancy requires coordinated metabolic, hormonal, and immunological communication. In this review, maternal-fetal metabolic communication is defined as the bidirectional communication of nutritional status and metabolic demand by various modes including circulating metabolites, endocrine molecules, and other secreted factors. Emphasis is placed on metabolites as a means of maternal-fetal communication by synthesizing findings from studies in humans, non-human primates, domestic animals, rabbits, and rodents. In this review, fetal, placental, and maternal metabolic adaptations are discussed in turn. (1) Fetal macronutrient needs are summarized in terms of the physiological adaptations in place to ensure their proper allocation. (2) Placental metabolite transport and maternal physiological adaptations during gestation, including changes in energy budget, are also discussed. (3) Maternal nutrient limitation and metabolic disorders of pregnancy serve as case studies of the dynamic nature of maternal-fetal metabolic communication. The review concludes with a summary of recent research efforts to identify metabolites, endocrine molecules, and other secreted factors that mediate this communication, with particular emphasis on serum/plasma metabolomics in humans, non-human primates, and rodents. A better understanding of maternal-fetal metabolic communication in health and disease may reveal novel biomarkers and therapeutic targets for metabolic disorders of pregnancy.

Whole transcriptome expression profiles in placenta samples from women with gestational diabetes mellitus

AIMS/INTRODUCTION

Non-coding ribonucleic acids (ncRNAs) have recently been shown to be involved in various biological processes. However, most of these ncRNAs are of unknown function or without annotation. This study first investigated the whole transcriptome profiles of placentas to identify the potential functions that ncRNAs exerted in gestational diabetes mellitus (GDM).

MATERIALS AND METHODS

Six placenta samples from healthy pregnant women (n = 3) and GDM (n = 3) were collected to analyze the whole transcriptome profiles by high-throughput sequencing. Differentially expressed ncRNAs were further validated by quantitative real-time polymerase chain reaction on an independent set of normal (n = 20) and GDM (n = 20) placenta samples.

RESULTS

A total of 2,817 microRNAs (miRNAs), 23,339 long non-coding RNAs (lncRNAs) and 9,513 circular RNAs (circRNAs) were identified. There were 290 differentially expressed ncRNAs in GDM placentas compared with the placentas of healthy pregnant women. Two miRNAs, 86 lncRNAs and 55 circRNAs were upregulated, while two miRNAs, 86 lncRNAs and 59 circRNAs were downregulated in GDM. The expression of the selected ncRNAs, which were further validated by quantitative real-time polymerase chain reaction, was consistent with the sequencing results. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the major targets of these ncRNAs were associated with insulin resistance, and abnormal glucose and lipid metabolism. A GDM-related competing endogenous RNA network suggested the interactions between lncRNAs, circRNAs, messenger RNAs and miRNAs.

CONCLUSIONS

The whole transcriptome profiles significantly differed in GDM placentas compared with the placentas of healthy pregnant women, which might be valuable for detecting novel ncRNAs, and providing new research insights into exploring the pathogenic mechanisms of GDM.

Divergent Changes in Serum Branched-Chain Amino Acid Concentrations and Estimates of Insulin Resistance throughout Gestation in Healthy Women

BACKGROUND

Branched-chain amino acid (BCAA) concentrations in the blood have been correlated with insulin resistance, but this relation throughout gestation (period in which insulin resistance typically increases) is unclear.

OBJECTIVE

The objective of this study was to determine the associations between changes in BCAA concentrations and estimates of insulin resistance throughout gestation.

METHODS

Serum BCAA (Leu, Ile, Val) concentrations and insulin resistance/sensitivity [i.e., homeostatic model assessment-2 of insulin resistance (HOMA2-IR), estimated metabolic clearance rate (MCR) of glucose, and estimated first- and second-phase insulin responses] were assessed at early (EP; 8.5 ± 0.2 wk) and/or late (LP; 29.2 ± 0.8 wk) pregnancy in 53 healthy women from the Glowing cohort. Adjusted Spearman correlations were used to evaluate the association between BCAA and insulin resistance/sensitivity measures at EP and LP, adjusted for body fat percentage and gestational weight gain (GWG). A multiple linear regression analysis was used to assess the association between changes in HOMA2-IR and BCAAs throughout gestation. Groups were made post hoc based on the mean percentage change (10% decrease) in Leu throughout gestation, creating a group with a ≥10% decrease in LeuLP-EP (BELOW) and a <10% decrease in LeuLP-EP (ABOVE), and Student's t tests were performed to assess differences between groups.

RESULTS

Leu and Ile concentrations positively correlated with HOMA2-IR at both time points, but these relations at EP disappeared/weakened when adjusted for body fat percentage. From EP to LP, the change in Leu (LeuLP-EP) was negatively associated with the change in HOMA2-IR (HOMA2-IRLP-EP) (β = -0.037, P = 0.006). MCR was lower in the BELOW group compared with the ABOVE group, whereas there was no difference in HOMA2-IR between groups.

CONCLUSIONS

In this pregnancy cohort, BCAA concentrations decreased throughout gestation, whereas the mean insulin resistance did not change. These data do not support a connection between changes in blood BCAA concentrations and estimates of insulin resistance in pregnant women. This trial is registered at clinicaltrials.gov as NCT01131117.

Paraben Exposure Related To Purine Metabolism and Other Pathways Revealed by Mass Spectrometry-Based Metabolomics

Parabens are widely used as common preservatives in the pharmaceutical and cosmetic industries. Exposure to parabens has been found to be associated with metabolic alterations of human and an increased risk of metabolic disease, such as diabetes. However, limited information is available about metabolic pathways related to paraben exposure. In this study, three parabens were determined in the urine samples of 88 pregnant women by using ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ MS). The samples were divided into different groups based on tertile distribution of urinary paraben concentrations. Metabolic profiling of the 88 urine samples was performed by using UHPLC coupled with Orbitrap high-resolution MS. Differential metabolites were screened by comparing the profiles of urine samples from different paraben-exposure groups. The identified metabolites included purines, acylcarnitines, etc., revealing that metabolic pathways such as purine metabolism, fatty acid β-oxidation, and other pathways were disturbed by parabens. Eighteen and three metabolites were correlated (Spearman correlation analysis, p < 0.05) with the exposure levels of methyparaben and propylparaben, respectively. This is the first MS-based nontargeted metabolomics study on pregnant women with paraben exposure. The findings reveal the potential health risk of exposure to parabens and might help one to understand the link between paraben exposure and some metabolic diseases.

N-3 Polyunsaturated Fatty Acids Decrease Long-Term Diabetic Risk of Offspring of Gestational Diabetes Rats by Postponing Shortening of Hepatic Telomeres and Modulating Liver Metabolism

The long-term influence of gestational diabetes mellitus (GDM) on offspring and the effect of omega-3 polyunsaturated fatty acids (n-3 PUFA) on GDM offspring are poorly understood. We studied the long-term diabetic risk in GDM offspring and evaluated the effect of n-3 PUFA intervention. Healthy offspring rats were fed standard diet (soybean oil) after weaning. GDM offspring were divided into three groups: GDM offspring (soybean oil), n-3 PUFA adequate offspring (fish oil), and n-3 PUFA deficient offspring (safflower oil), fed up to 11 months old. The diabetic risk of GDM offspring gradually increased from no change at weaning to obvious impaired glucose and insulin tolerance at 11 months old. n-3 PUFA decreased oxidative stress and inflammation in the liver of older GDM offspring. There was a differential effect of n-3 PUFA and n-6 PUFA on hepatic telomere length in GDM offspring. Non-targeted metabolomics showed that n-3 PUFA played a modulating role in the liver, in which numerous metabolites and metabolic pathways were altered when GDM offspring grew to old age. Many metabolites were related to diabetes risk, such as α-linolenic acid, palmitic acid, ceramide, oxaloacetic acid, tocotrienol, tetrahydro-11-deoxycortisol, andniacinamide. In summary, GDM offspring exhibited obvious diabetes risk at old age, whereas n-3 PUFA decreased this risk.