Associations of air pollution exposures in preconception and pregnancy with birth outcomes and infant neurocognitive development: analysis of the Complex Lipids in Mothers and Babies (CLIMB) prospective cohort in Chongqing, China.

OBJECTIVES: To investigate the associations of traffic-related air pollution exposures in early pregnancy with birth outcomes and infant neurocognitive development. DESIGN: Cohort study. SETTING: Eligible women attended six visits in the maternity clinics of two centres, the First Affiliated Hospital of Chongqing Medical University and Chongqing Health Centre for Women and Children. PARTICIPANTS: Women who were between 20 and 40 years of age and were at 11-14 weeks gestation with a singleton pregnancy were eligible for participation. Women were excluded if they had a history of premature delivery before 32 weeks of gestation, maternal milk allergy or aversion or severe lactose intolerance. 1273 pregnant women enrolled in 2015-2016 and 1174 live births were included in this analysis. EXPOSURES: Air pollution concentrations at their home addresses, including particulate matter with diameter ≤2.5 µm (PM2.5) and nitrogen dioxide (NO2), during pre-conception and each trimester period were estimated using land-use regression models. OUTCOME MEASURES: Birth outcomes (ie, birth weight, birth length, preterm birth, low birth weight, large for gestational age and small for gestational age (SGA) status) and neurodevelopment outcomes measured by the Chinese version of Bayley Scales of Infant Development. RESULTS: An association between SGA and per-IQR increases in NO2 was found in the first trimester (OR: 1.57, 95% CI: 1.06 to 2.32) and during the whole pregnancy (OR: 1.33, 99% CI: 1.01 to 1.75). Both PM2.5 and NO2 exposure in the 90 days prior to conception were associated with lower Psychomotor Development Index scores (ß: -6.15, 95% CI: -8.84 to -3.46; ß: -2.83, 95% CI: -4.27 to -1.39, respectively). Increased NO2 exposure was associated with an increased risk of psychomotor development delay during different trimesters of pregnancy. CONCLUSIONS: Increased exposures to NO2 during pregnancy were associated with increased risks of SGA and psychomotor development delay, while increased exposures to both PM2.5 and NO2 pre-conception were associated with adverse psychomotor development outcomes at 12 months of age. TRIAL REGISTRATION NUMBER: ChiCTR-IOR-16007700.

Excessive palmitic acid disturbs macrophage α-ketoglutarate/succinate metabolism and causes adipose tissue insulin resistance associated with gestational diabetes mellitus.

Abnormal polarization of adipose tissue macrophages (ATMs) results in low-grade systemic inflammation and insulin resistance (IR), potentially contributing to the development of diabetes. However, the underlying mechanisms that regulate the polarization of ATMs associated with gestational diabetes mellitus (GDM) remain unclear. Thus, we aimed to determine the effects of abnormal fatty acids on macrophage polarization and development of insulin resistance in GDM. Levels of fatty acids and inflammation were assessed in the serum samples and adipose tissues of patients with GDM. An in vitro cell model treated with palmitic acid was established, and the mechanisms of palmitic acid in regulating macrophage polarization was clarified. The effects of excessive palmitic acid on the regulation of histone methylations and IR were also explored in the high-fat diet induced GDM mice model. We found that pregnancies with GDM were associated with increased levels of serum fatty acids, and inflammation and IR in adipose tissues. Increased palmitic acid could induce mitochondrial dysfunction and excessive ROS levels in macrophages, leading to abnormal cytoplasmic and nuclear metabolism of succinate and α-ketoglutarate (αKG). Specifically, a decreased nuclear αKG/succinate ratio could attenuate the enrichment of H3K27me3 at the promoters of pro-inflammatory cytokines, such as IL-1ß, IL-6, and TNF-α, leading to cytokine secretion. Importantly, GDM mice treated with GSK-J4, an inhibitor of histone lysine demethylase, were protected from abnormal pro-inflammatory macrophage polarization and excessive production of pro-inflammatory cytokines. Our findings highlight the importance of the metabolism of αKG and succinate as transcriptional modulators in regulating the polarization of ATMs and the insulin sensitivity of adipose tissue, ensuring a normal pregnancy. This novel insight sheds new light on gestational fatty acid metabolism and epigenetic alterations associated with GDM.

Epigenetic signatures of trophoblast lineage and their biological functions.

Trophoblasts play a crucial role in embryo implantation and in interacting with the maternal uterus. The trophoblast lineage develops into a substantial part of the placenta, a temporary extra-embryonic organ, capable of undergoing distinctive epigenetic events during development. The critical role of trophoblast-specific epigenetic signatures in regulating placental development has become known, significantly advancing our understanding of trophoblast identity and lineage development. Scientific efforts are revealing how trophoblast-specific epigenetic signatures mediate stage-specific gene regulatory programming during the development of the trophoblast lineage. These epigenetic signatures have a significant impact on blastocyst formation, placental development, as well as the growth and survival of embryos and fetuses. In evolution, DNA hypomethylation in the trophoblast lineage is conserved, and there is a significant disparity in the control of epigenetic dynamics and the landscape of genomic imprinting. Scientists have used murine and human multipotent trophoblast cells as in vitro models to recapitulate the essential epigenetic processes of placental development. Here, we review the epigenetic signatures of the trophoblast lineage and their biological functions to enhance our understanding of placental evolution, development, and function.

Gut dysbiosis contributes to SCFAs reduction-associated adipose tissue macrophage polarization in gestational diabetes mellitus.

AIMS: The prevalence of gestational diabetes mellitus (GDM) has spurred investigations into various interconnected factors, among which gut dysbiosis is notably prominent. Although gut dysbiosis is strongly associated with GDM, the specific role of the gut microbiome in the pathogenesis of GDM remains unknown. This study aims to explore the pathogenesis of GDM from gut microbiota. MATERIALS AND METHODS: In our study, we constructed two GDM mice models: one induced by a high-fat diet (HFD) and the other through fecal microbiota transplantation (FMT) from GDM patients. In vitro, we used a co-culture system of RAW264.7 and 3T3-L1 adipocytes. KEY FINDINGS: We induced a GDM-like state in pregnant mice by FMT from GDM patients, which was consistent with the HFD model. A potential mechanism identified involves the diminished abundance of SCFA-producing microbiota, which reduces SCFAs, particularly propionic acid and butyric acid. In vitro, butyric and propionic acids were observed to alleviate LPS-induced TLR4-NF-κB activation, thereby reducing inflammation levels and inhibiting adipose insulin resistance via the PI3K/AKT signaling pathway. This reduction appears to trigger the polarization of adipose tissue macrophages toward M1 and promote insulin resistance in adipose tissue. SIGNIFICANCE: Our study fills this knowledge gap by finding that alterations in gut microbiota have an independent impact on hyperglycemia and insulin resistance in the GDM state. In vivo and in vitro, gut dysbiosis is linked to adipose tissue inflammation and insulin resistance via the bacterial product SCFAs in the GDM state, providing new insights into the pathogenesis of GDM.

The metabolic role of the CD73/adenosine signaling pathway in HTR-8/SVneo cells: A Double-Edged Sword?

The ecto-5'-nucleotidase (CD73)/adenosine signaling pathway has been reported to regulate tumor epithelial-mesenchymal transition (EMT), migration and proliferation. However, little is known about the metabolic mechanisms underlying its role in trophoblast proliferation and migration. In this study, we aimed to investigate the metabolic role of the CD73/adenosine signaling pathway on the proliferation and migration of trophoblast. We found that CD73 levels were upregulated in preeclamptic placentas compared with the placentas of normotensive pregnant women. EMT and migration of HTR-8/SVneo cells were enhanced when treated with a CD73 inhibitor (100 µM) in vitro. Conversely, excessive adenosine (25 or 50 µM) suppressed trophoblast cell EMT, migration and proliferation. RNA-seq, metabolomics and seahorse findings showed that adenosine treatment resulted in increased expression of PDK1, suppression of aerobic respiration, glycolysis and amino acids synthesis, as well as increased utilization of short-chain fatty acids (SCFAs). Furthermore, the 13C-adenosine isotope tracking experiment demonstrated that adenosine served as a carbon source for the tricarboxylic acid (TCA) cycle. Our results reveal the role of adenosine in regulating trophoblast energy metabolism is like a double-edged sword - either inhibiting aerobic respiration or supplementing carbon sources into metabolic flux. CD73/adenosine signaling regulated trophoblast EMT, migration, and proliferation by modulating energy metabolism. This study indicates that CD73/adenosine signaling potentially plays a role in the occurrence of placenta-derived diseases, including preeclampsia.

Metabolic Patterns of High-Invasive and Low-Invasive Oral Squamous Cell Carcinoma Cells Using Quantitative Metabolomics and 13C-Glucose Tracing.

Most current metabolomics studies of oral squamous cell carcinoma (OSCC) are mainly focused on identifying potential biomarkers for early screening and diagnosis, while few studies have investigated the metabolic profiles promoting metastasis. In this study, we aimed to explore the altered metabolic pathways associated with metastasis of OSCC. Here, we identified four OSCC cell models (CAL27, HN6, HSC-3, SAS) that possess different invasive heterogeneity via the transwell invasion assay and divided them into high-invasive (HN6, SAS) and low-invasive (CAL27, HSC-3) cells. Quantitative analysis and stable isotope tracing using [U-13C6] glucose were performed to detect the altered metabolites in high-invasive OSCC cells, low-invasive OSCC cells and normal human oral keratinocytes (HOK). The metabolic changes in the high-invasive and low-invasive cells included elevated glycolysis, increased fatty acid metabolism and an impaired TCA cycle compared with HOK. Moreover, pathway analysis demonstrated significant differences in fatty acid biosynthesis; arachidonic acid (AA) metabolism; and glycine, serine and threonine metabolism between the high-invasive and low-invasive cells. Furthermore, the high-invasive cells displayed a significant increase in the percentages of 13C-glycine, 13C-palmitate, 13C-stearic acid, 13C-oleic acid, 13C-AA and estimated FADS1/2 activities compared with the low-invasive cells. Overall, this exploratory study suggested that the metabolic differences related to the metastatic phenotypes of OSCC cells were concentrated in glycine metabolism, de novo fatty acid synthesis and polyunsaturated fatty acid (PUFA) metabolism, providing a comprehensive understanding of the metabolic alterations and a basis for studying related molecular mechanisms in metastatic OSCC cells.

Alteration of Metabolic Profiles during the Progression of Alzheimer's Disease.

(1) Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that threatens the population health of older adults. However, the mechanisms of the altered metabolism involved in AD pathology are poorly understood. The aim of the study was to identify the potential biomarkers of AD and discover the metabolomic changes produced during the progression of the disease. (2) Methods: Gas chromatography-mass spectrometry (GC-MS) was used to measure the concentrations of the serum metabolites in a cohort of subjects with AD (n = 88) and a cognitively normal control (CN) group (n = 85). The patients were classified as very mild (n = 25), mild (n = 27), moderate (n = 25), and severe (n = 11). The serum metabolic profiles were analyzed using multivariate and univariate approaches. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify the potential biomarkers of AD. Biofunctional enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. (3) Results: Our results revealed considerable separation between the AD and CN groups. Six metabolites were identified as potential biomarkers of AD (AUC > 0.85), and the diagnostic model of three metabolites could predict the risk of AD with high accuracy (AUC = 0.984). The metabolic enrichment analysis revealed that carbohydrate metabolism deficiency and the disturbance of amino acid, fatty acid, and lipid metabolism were involved in AD progression. Especially, the pathway analysis highlighted that l-glutamate participated in four crucial nervous system pathways (including the GABAergic synapse, the glutamatergic synapse, retrograde endocannabinoid signaling, and the synaptic vesicle cycle). (4) Conclusions: Carbohydrate metabolism deficiency and amino acid dysregulation, fatty acid, and lipid metabolism disorders were pivotal events in AD progression. Our study may provide novel insights into the role of metabolic disorders in AD pathogenesis and identify new markers for AD diagnosis.

Hair and cord blood element levels and their relationship with air pollution, dietary intake, gestational diabetes mellitus, and infant neurodevelopment.

BACKGROUND & AIMS: Exposure to a range of elements, air pollution, and specific dietary components in pregnancy has variously been associated with gestational diabetes mellitus (GDM) risk or infant neurodevelopmental problems. We measured a range of pregnancy exposures in maternal hair and/or infant cord serum and tested their relationship to GDM and infant neurodevelopment. METHODS: A total of 843 pregnant women (GDM = 224, Non-GDM = 619) were selected from the Complex Lipids in Mothers and Babies cohort study. Forty-eight elements in hair and cord serum were quantified using inductively coupled plasma-mass spectrometry analysis. Binary logistic regression was used to estimate the associations between hair element concentrations and GDM risk, while multiple linear regression was performed to analyze the relationship between hair/cord serum elements and air pollutants, diet exposures, and Bayley Scales of infant neurodevelopment at 12 months of age. RESULTS: After adjusting for maternal age, BMI, and primiparity, we observed that fourteen elements in maternal hair were associated with a significantly increased risk of GDM, particularly Ta (OR = 9.49, 95% CI: 6.71, 13.42), Re (OR = 5.21, 95% CI: 3.84, 7.07), and Se (OR = 5.37, 95% CI: 3.48, 8.28). In the adjusted linear regression model, three elements (Rb, Er, and Tm) in maternal hair and infant cord serum were negatively associated with Mental Development Index scores. For dietary exposures, elements were positively associated with noodles (Nb), sweetened beverages (Rb), poultry (Cs), oils and condiments (Ca), and other seafood (Gd). In addition, air pollutants PM2.5 (LUR) and PM10 were negatively associated with Ta and Re in maternal hair. CONCLUSIONS: Our findings highlight the potential influence of maternal element exposure on GDM risk and infant neurodevelopment. We identified links between levels of these elements in both maternal hair and infant cord serum related to air pollutants and dietary factors.

Probiotic Escherichia coli Nissle 1917-derived outer membrane vesicles modulate the intestinal microbiome and host gut-liver metabolome in obese and diabetic mice.

Introduction: Obesity and diabetes are common chronic metabolic disorders which can cause an imbalance of the intestinal flora and gut-liver metabolism. Several studies have shown that probiotics, including Escherichia coli Nissle 1917 (EcN), promote microbial balance and metabolic health. However, there are no studies on how EcN outer membrane vesicles (EcN-OMVs) influence the intestinal microflora and affect the metabolic disorders of obesity and diabetes. Methods: In this study, we evaluated the effects of EcN-OMVs on high-fat diet (HFD)-induced obesity and HFD + streptozotocin (STZ)-induced diabetes. Results: EcN-OMVs could reduce body weight, decrease blood glucose, and increase plasma insulin in obese mice. Similarly, EcN-OMVs treatment could modify the ratio of Firmicutes/Bacteroidetes in the gut, elevate intestinal short-chain fatty acid (SCFA)-producing flora, and influence the SCFA content of the intestine. Furthermore, the intestinal metabolites ornithine and fumaric acid, hepatic ω-6 unsaturated fatty acids, and SCFAs were significantly increased after administering EcN-OMVs. Discussion: Overall, this study showed that EcN-OMVs might act as post-biotic agents that could modulate gut-liver metabolism and ameliorate the pathophysiology of obesity and diabetes.

Metabolomics analysis of serum metabolites during endometrial transformation: association with recurrent implantation failure in hormonal replacement therapy-frozen embryo transfers cycles.

PURPOSE: The purpose of this study was to investigate alterations in serum metabolites during endometrial transformation and possible associations with recurrent implantation failure (RIF) in hormonal replacement therapy (HRT)-frozen embryo transfer (FET) cycles. METHODS: We performed a prospective study involving 100 patients scheduled for HRT-FET cycles during January 2022 to April 2022. Blood serum samples were collected on the day of progesterone administration (dPA) and on the third day of progesterone administration (d3PA). Gas chromatography-mass spectrometry (GC-MS) analysis was performed to identify and quantify serum metabolites. A nested case-control study including 19 RIF patients and 19 matching controls was conducted to explore the predictive value of serum metabolites for RIF. Partial least squares discriminant analysis (PLS-DA) and receiver operating characteristic (ROC) curve analysis were performed to establish prediction models. MAIN RESULTS: We identified 105 serum metabolites, with 76 of them exhibiting significant alterations during the initial 3 days of endometrial transformation. Metabolites involved in amino acid metabolism and tricarboxylic acid (TCA) cycle showed lower levels during endometrial transformation. In the nested case-control study, the prediction model based on the ratio of serum metabolites between d3PA and dPA showed the highest area under the ROC curve (AUC), accuracy, and R2 and Q2 values. Eight metabolites, including indol-3-propionic acid, beta-alanine, myristoleic acid, malic acid, indole, DL-isocitric acid, proline, and itaconic acid, exhibited high predictive values for RIF. CONCLUSION: This study demonstrates alterations in serum metabolites during endometrial transformation, particularly in amino acid metabolism and TCA cycle. The identified metabolites, especially indol-3-propionic acid and malic acid, show potential as predictive markers for RIF. These findings contribute to a better understanding of the metabolic changes associated with endometrial receptivity and provide insights for the development of personalized approaches to improve implantation outcomes in FET cycles.

Chorionicity-associated variation in metabolic phenotype of cord blood in twin.

BACKGROUND: Monochorionic (MC) twins present a higher incidence of unfavorable clinical perinatal outcomes than dichorionic (DC) twins, often in association with placental vascular anastomosis. In this study, we profiled the umbilical cord plasma metabolomes of uncomplicated MC and DC twin pregnancies and related these to several offspring outcomes, previously associated with birthweight. METHODS: Umbilical vein blood samples were collected at birth from 25 pairs of uncomplicated MC twins and 24 pairs of uncomplicated DC twins. The samples were subjected to gas chromatography-mass spectrometry-based metabolomics. 152 metabolites were identified from the cord plasma samples of MC and DC twins. Partial least squares discriminant analysis and pathway analysis were performed to compare within DC/MC twin pairs and between DC and MC twins. A generalized estimating equation (GEE) model was utilized to explore the correlation between metabolic differences and birthweight discordance within and between twin pairs. RESULTS: Our study revealed clear differences between the metabolite profiles of umbilical cord plasma of MC and DC twins. Metabolite profiles in MC within twin pairs and DC within twin pairs were characterized by the differences in 2 - hydroxyglutaramic acid levels and nicotinamide levels, respectively. The metabolic pathways of GSH, tryptophan, and fatty acid metabolism, were significantly downregulated in MC twins compared to DC twins. In addition, the concentration of caffeine and decamethyl-cyclopentasiloxane (D5) was positively correlated with birthweight in MC and DC twins. CONCLUSION: This study demonstrated that the altered metabolites in umbilical plasma made contributions to the different chorionicities between uncomplicated MC twins and DC twins. The chorionicity of twins seems to affect the metabolic cross-talk between co-twin pairs and be related to birthweight discordance of twins.

The effect of growth hormone on the metabolome of follicular fluid in patients with diminished ovarian reserve.

BACKGROUND: Increasing evidence supports that the co-treatment with growth hormone (GH) enhances ovarian response and oocyte quality during controlled ovarian stimulation (COS) in patients with diminished ovarian reserve (DOR). The composition of follicular fluid (FF) plays an essential role in oocyte development and mirrors the communication occurring between the oocyte and follicular microenvironment. However, the effect of GH on the FF metabolome remains unclear. METHODS: This prospective observational study recruited DOR patients undergoing in vitro fertilization (IVF) cycles with minimal stimulation protocol for COS. Each patient receiving GH co-treatment was matched to a patient without GH co-treatment by propensity score matching. The FF was collected after isolating oocytes and assayed by gas chromatograph-mass spectrometry (GC-MS) metabolomics. The Pearson correlation was performed to evaluate the relationship between the number of oocytes retrieved and the levels of differential metabolites. The KEGG database was used to map differential metabolites onto various metabolic pathways. RESULTS: One hundred thirty-four FF metabolites were identified by GC-MS metabolomics. Twenty-four metabolites, including glutathione, itaconic acid and S-adenosylmethionin (SAM) showed significant differences between the GH and control groups (p-value < 0.05 and q-value < 0.1). In addition, the number of oocytes retrieved was significantly higher in the GH group compared to the control group (3 vs 2, p = 0.04) and correlated with the levels of five differential metabolites. Among them, the levels of antioxidant metabolite itaconic acid were upregulated by GH administration, while SAM levels were downregulated. CONCLUSIONS: The co-treatment with GH during COS may improve oocyte development by altering FF metabolite profiles in DOR patients. However, given the downregulation of SAM, a regulator of genomic imprinting, the potential risk of imprinting disturbances should not be neglected.

Metabolomic profiling identifies hair as a robust biological sample for identifying women with cervical cancer.

Metabolomics serves as a useful tool for identifying biomarkers of disease and uncovering pathogenic mechanisms. However, most metabolomic studies use biological fluids such as blood and urine as biospecimens, which could be dramatically influenced by daily activities and dietary variation, resulting in measurement fluctuations. In contrast, hair may serve as a robust source of stable longitudinal metabolite information. Here, we conducted a pilot study to investigate the possibility of using hair as a biospecimen for the metabolomic analysis of cervical cancer. Hair, plasma, urine, and cervical tissue samples from cervical cancer and benign tumor patients were collected. Biospecimens were then tested using a gas chromatography-mass spectrometry-based metabolomic platform. The expressions of enzymatic genes related to metabolic changes were validated using qPCR. Statistical analyses were calculated via the R-console platform. Metabolite profiles in both hair and cervical tissue samples were significantly different between cancer and control groups, while no difference was observed in plasma and urine samples. Further analysis showed that most of the altered metabolites in hair were upregulated, and they had a negative correlation with those in the cervical tissue. Eight common metabolites showed an area under the Receiver Operating Characteristic curve greater than 0.95. These metabolites primarily participated in amino acid metabolism, cofactor synthesis, ferroptosis, and glycolysis. The gene expressions (IDH1, OGDH, GLUD1, ENO1, GSS, and GPX4) associated with the shortlisted metabolic pathways were also upregulated. Our study is the first to reveal metabolomic changes of hair in cervical cancer patients and demonstrates the potential for the hair metabolome to be used for biomarker identification in cervical cancer.

Intrafollicular fluid metabolic abnormalities in relation to ovarian hyperstimulation syndrome: Follicular fluid metabolomics via gas chromatography-mass spectrometry.

INTRODUCTION: Ovarian hyperstimulation syndrome (OHSS) is the most serious iatrogenic complication of ovulation stimulation during assisted reproductive technology. The main objective of this study was to investigate intrafollicular fluid metabolic change profiles of OHSS in non-ovarian etiologic infertility women (CON) and polycystic ovarian syndrome patients (PCOS). METHODS: 87 infertile women were divided into four subgroups: CON-Norm (CON with normal ovarian response), CON-OHSS (CON with OHSS), PCOS-Norm (PCOS with normal ovarian response), and PCOS-OHSS (PCOS with OHSS). The intrafollicular fluid metabolic profiles were analyzed with gas chromatography-mass spectrometry. The multivariable-adjusted conditional logistic regression was applied to assess the association of metabolites with OHSS risk. RESULTS: We identified 17 and 3 metabolites that related to OHSS risk in CON and PCOS, respectively. 13 OHSS risk-related metabolites in CON were unsaturated fatty acids, 8 of which were also the significantly altered metabolites between all PCOS and CON-Norm. CONCLUSION: Our study may shed light on the role of intrafollicular fluid metabolic abnormalities in the pathophysiology of OHSS. The findings suggested that there might be some metabolic heterogeneities underlying the development of OHSS in CON and PCOS women and indicated possible shared etiological factors in the development of PCOS and OHSS.

AMPK regulates homeostasis of invasion and viability in trophoblasts by redirecting glucose metabolism: Implications for pre-eclampsia.

Pre-eclampsia (PE) is deemed an ischemia-induced metabolic disorder of the placenta due to defective invasion of trophoblasts during placentation; thus, the driving role of metabolism in PE pathogenesis is largely ignored. Since trophoblasts undergo substantial glycolysis, this study aimed to investigate its function and regulatory mechanism by AMPK in PE development. Metabolomics analysis of PE placentas was performed by gas chromatography-mass spectrometry (GC-MS). Trophoblast-specific AMPKα1-deficient mouse placentas were generated to assess morphology. A mouse PE model was established by Reduced Uterine Perfusion Pressure, and placental AMPK was modulated by nanoparticle-delivered A769662. Trophoblast glucose uptake was measured by 2-NBDG and 2-deoxy-d-[3 H] glucose uptake assays. Cellular metabolism was investigated by the Seahorse assay and GC-MS.PE complicated trophoblasts are associated with AMPK hyperactivation due not to energy deficiency. Thereafter, AMPK activation during placentation exacerbated PE manifestations but alleviated cell death in the placenta. AMPK activation in trophoblasts contributed to GLUT3 translocation and subsequent glucose metabolism, which were redirected into gluconeogenesis, resulting in deposition of glycogen and accumulation of phosphoenolpyruvate; the latter enhanced viability but compromised trophoblast invasion. However, ablation of AMPK in the mouse placenta resulted in decreased glycogen deposition and structural malformation. These data reveal a novel homeostasis between invasiveness and viability in trophoblasts, which is mechanistically relevant for switching between the 'go' and 'grow' cellular programs.

The maternal hair metabolome is capable of discriminating intrahepatic cholestasis of pregnancy from uncomplicated pregnancy.

Introduction: Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disease associated with elevated bile acids in the blood. Diagnosis typically only occurs after the manifestation of clinical symptoms and the metabolic mechanisms underlying its development remain unclear. The aim of this study was to investigate potential specific metabolites and the underlying metabolic changes occurring during the development of ICP in the maternal plasma and hair metabolomes of women diagnosed with either ICP or having a healthy pregnancy. Methods: A total of 35 Chinese women with ICP and 42 healthy pregnancies were enrolled in our study. Plasma and hair samples, total bile acid levels (TBA), alanine transaminase levels (ALT), aspartate aminotransferase levels (AST), and additional clinical information were collected during the third trimester. Metabolites from maternal plasma and hair segments collected pre-conception and analyzed using gas chromatography-mass spectrometry (GC-MS). Results: Three plasma metabolites (p < 0.05, q < 0.38) and 21 hair metabolites (p < 0.05, q < 0.05) were significantly different between ICP and healthy pregnancies. A combination of the eight most significant hair metabolites in a multivariate receiver operating characteristic curve model showed the best area under the curve (AUC) was 0.885, whereas the highest AUC using metabolites from plasma samples was only 0.74. Metabolic pathway analysis revealed 32 pathways were significantly (p and q values < 0.05) affected in the hair samples of patients with ICP. Pathways associated with glutathione metabolism and ABC transporters were affected. No metabolic pathways were significantly affected in plasma. Discussion: Overall, this study showed that the hair metabolome could be more useful than the plasma metabolome for distinguishing ICP from normal pregnancy.

Evidence for ethnicity and location as regulators of the newborn blood metabolome: a monozygous twin study.

Introduction: Monochorionic, diamniotic (MCDA) monozygotic twins share nearly all genetic variation and a common placenta in utero. Despite this, MCDA twins are often discordant for a range of common phenotypes, including early growth and birth weight. As such, MCDA twins represent a unique model to explore variation in early growth attributable primarily to in utero environmental factors. Methods: MCDA twins with a range of within-pair birth weight discordance were sampled from the peri/postnatal epigenetic twin study (PETS, Melbourne; n = 26 pairs), Beijing twin study (BTS, Beijing; n = 25), and the Chongqing longitudinal twin study (LoTiS, Chongqing; n = 22). All PETS participants were of European-Australian ancestry, while all Chinese participants had Han ancestry. The average of the birth weight difference between the larger and smaller co-twins for all twin pairs was determined and metabolomic profiles of amino acids, TCA cycle intermediates, fatty acids, organic acids, and their derivatives generated from cord blood plasma by gas chromatograph mass spectrometry. Within and between co-twin pair analyses were performed to identify metabolites specifically associated with discordance in birth weight. Multivariable regression and pathway enrichment analyses between different regions were performed to evaluate the geographical effects on the metabolism of MCDA twin pairs. Results: PETS twins showed a markedly different metabolic profile at birth compared to the two Chinese samples. Within-pair analysis revealed an association of glutathione, creatinine, and levulinic acid with birth weight discordance. Caffeine, phenylalanine, and several saturated fatty acid levels were uniquely elevated in PETS twins and were associated with maternal BMI and average within pair birth weight, in addition to birth weight discordance. LoTiS twins had higher levels of glutathione, tyrosine, and gamma-linolenic acid relative to PETS and BTS twins, potentially associated with eating habits. Conclusion: This study highlights the potential role of underlying genetic variation (shared by MZ twins), in utero (non-shared by MZ twins) and location-specific (shared by MZ twins) environmental factors, in regulating the cord blood metabolome of uncomplicated MCDA twins. Future research is needed to unravel these complex relationships that may play a key role in phenotypic metabolic alterations of twins independent of genetic diversity.

The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester.

Background: Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort. Methods: A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites. Results: Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM2.5, PM10, SO2, NO2, CO and the exposure estimates of PM2.5 and NO2, and positively associated with O3. Conclusions: This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.

An Evaluation of Different Digestion Methods for the Quantitation of Inorganic Elements in Human Hair Using ICP-MS.

The inorganic elements have unique properties in biochemical processes in humans. An increasing number of pathologies have been associated with essential element ions, such as lead, mercury, and cadmium. Hair has become an attractive clinical specimen for studying the longitudinal exposure to elements from the external environment. Inductively coupled plasma-mass spectrometry (ICP-MS) coupled with nitric acid (HNO3) digestion is the most common approach for determining inorganic elements from human hair. This study aims to optimize the digestion method for the absolute quantitation of 52 elements using ICP-MS, for a large cohort study in human hair. Five different HNO3 (65%) digestion methods were investigated and evaluated for their internal standard solution stability, reproducibility, element coverage, and standard solution recovery efficiency, namely, room temperature for 24 h (RT), 90°C for 4 h (T90), ultrasonic-assisted digestion (UltraS), programmed digestion of microwave digestion (MicroD), and ordinary microwave oven digestion (O-MicroD). Our results demonstrated that O-MicroD, MicroD, and RT were the best performing digestion methods for coefficient of variation (CV) scores, coverage, and recovery efficiency, respectively. In particular, the O-MicroD method detected multiple elements in a small quantity of hair (3 mg), with minimum nitric acid usage (200 µl) and a short digestion time (30 min). The O-MicroD method had excellent reproducibility, as demonstrated by a continuous thousand injections of hair samples with three internal standards (CV: 103Rh = 3.59%, 115In = 3.61%, and 209Bi = 6.31%). Future studies of the elemental content of hair should carefully select their digestion method to meet the primary purpose of their study.

Evaluating Different Extraction Approaches for GC-MS Based Metabolomics Analysis of the Giant Pandas' Fur.

Giant pandas in zoo captivity are situated in residential areas, where environmental pollutants and anthropogenic factors have an impact on their health. Hair metabolomics has been applied in numerous environmental toxicological studies. Therefore, the panda fur metabolome could be a reliable approach to reflect endogenous and exogenous metabolic changes related to environmental exposure. However, there is no established extraction protocol to study the fur metabolome of pandas. The aim of this research was to optimize the extraction of panda fur metabolome for high-throughput metabolomics analysis using gas chromatography-mass spectrometry. Fur samples were collected from five pandas. Eight different extraction methods were investigated and evaluated for their reproducibility, metabolite coverage, and extraction efficiency, particularly in relation to the biochemical compound classes such as amino acids, tricarboxylic acid cycle derivatives, fatty acids, and secondary metabolites. Our results demonstrated that HCl + ACN were the superior extraction solvents for amino acid and secondary metabolite extraction, and NaOH + MeOH was ideal for fatty acid extraction. Interestingly, the metabolomic analysis of panda fur was capable of discriminating the longitudinal metabolite profile between black and white furs. These extraction protocols can be used in future study protocols for the analysis of the fur metabolome in pandas.