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Maternal metabolism during pregnancy shapes offspring health via in utero programming. In the Healthy Start study, we identified five subgroups of pregnant women based on conventional metabolic biomarkers: Reference (n = 360); High HDL-C (n = 289); Dyslipidemic–High TG (n = 149); Dyslipidemic–High FFA (n = 180); Insulin Resistant (IR)–Hyperglycemic (n = 87). These subgroups not only captured metabolic heterogeneity among pregnant participants but were also associated with offspring obesity in early childhood, even among women without obesity or diabetes. Here, we utilize metabolomics data to enrich characterization of the metabolic subgroups and identify key compounds driving between-group differences. We analyzed fasting blood samples from 1065 pregnant women at 18 gestational weeks using untargeted metabolomics. We used weighted gene correlation network analysis (WGCNA) to derive a global network based on the Reference subgroup and characterized distinct metabolite modules representative of the different metabolomic profiles. We used the mummichog algorithm for pathway enrichment and identified key compounds that differed across the subgroups. Eight metabolite modules representing pathways such as the carnitine–acylcarnitine translocase system, fatty acid biosynthesis and activation, and glycerophospholipid metabolism were identified. A module that included 189 compounds related to DHA peroxidation, oxidative stress, and sex hormone biosynthesis was elevated in the Insulin Resistant–Hyperglycemic vs. the Reference subgroup. This module was positively correlated with total cholesterol (R:0.10; p-value < 0.0001) and free fatty acids (R:0.07; p-value < 0.05). Oxidative stress and inflammatory pathways may underlie insulin resistance during pregnancy, even below clinical diabetes thresholds. These findings highlight potential therapeutic targets and strategies for pregnancy risk stratification and reveal mechanisms underlying the developmental origins of metabolic disease risk. [ABSTRACT FROM AUTHOR]

Introduction background to metabolomicsMetabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates.Objectives of white paper—expected treatment outcomes and metabolomics enabling tool for precision medicineWe anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine.Conclusions key scientific concepts and recommendations for precision medicineOur metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its "Precision Medicine and Pharmacometabolomics Task Group", with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.

Beta-alanine, caffeine, and nitrate are dietary supplements generally recognized by the sport and exercise science community as evidence-based ergogenic performance aids. Evidence supporting the efficacy of these supplements, however, is greatly skewed due to research being conducted primarily in men. The physiological differences between men and women, most notably in sex hormones and menstrual cycle fluctuations, make generalizing male data to the female athlete inappropriate, and potentially harmful to women. This narrative review outlines the studies conducted in women regarding the efficacy of beta-alanine, caffeine, and nitrate supplementation for performance enhancement. Only nine studies on beta-alanine, 15 on caffeine, and 10 on nitrate in healthy women under the age of 40 years conducted in normoxia conditions were identified as relevant to this research question. Evidence suggests that beta-alanine may lower the rate of perceived exertion and extend training bouts in women, leading to greater functional adaptations. Studies of caffeine in women suggest the physiological responder status and caffeine habituation may contribute to caffeine's efficacy, with a potential plateau in the dose–response relationship of performance enhancement. Nitrate appears to vary in influence based on activity type and primary muscle group examined. However, the results summarized in the limited literature for each of these three supplements provide no consensus on dosage, timing, or efficacy for women. Furthermore, the literature lacks considerations for hormonal status and its role in metabolism. This gap in sex-based knowledge necessitates further research on these ergogenic supplements in women with greater considerations for the effects of hormonal status. [ABSTRACT FROM AUTHOR]

Background: Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods: We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results: We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations: While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test-retest assessment within the same individual and the relatively small sample size. Conclusion: Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism., Introduction Autism (OMIM:209850) is a neurodevelopmental disorder that presents in childhood with clinical manifestations of impairment in language and communication, social interaction and responsiveness, and restricted and repetitive patterns of [...]

By coupling a single UPLC separation to two different types of mass spectrometer an unbiased comparison of the metabolite profiles produced by each instrument for a set of rat urine samples was obtained. The flow from the UPLC column was split equally and both streams of eluent were simultaneously directed to the inlets of die two mass spectrometers. Mass spectrometry on the eluent was undertaken using a triple quadrupole linear ion trap and a hybrid quadrupole time-of-flight mass spectrometer using both positive and negative ESI. Data from both mass spectrometers were subjected to multivariate statistical analysis, after applying the same data extraction software, and showed the same general pattern of correlation between the samples using both unsupervised and supervised methods of statistical analysis. Based on orthogonal partial least-squares discriminant analysis models a number of ions were recognized as 'responsible' for the separation of the animal groups. From the peaks detected, and denoted as significant by the statistical analysis a number of ions were found to be unique to one data set or the other, a result which may have consequences for biomarker discovery and interlaboratory comparisons. The software package used for data analysis also had an effect on the outcome of the statistical analysis. 10.1021/ac1016612

This study was conducted to investigate the influence of outer diameter (OD) and length (L) of multiwalled carbon nanotubes (MWCNTs) on biodistribution and the perturbation of endogenous metabolite profiles. Three different-sized carboxylated MWCNTs (NIEHS-12-2: L 0.5-2 μm, OD 10-20 nm, NIEHS-13-2: L 0.5-2 μm, OD 30-50 nm, and NIEHS-14-2: L 10-30 μm, OD 10-20 nm) in water were administered to female Sprague-Dawley rats as a single intravenous dose of 1 mg/kg MWCNTs. Biodistribution in liver, lung, spleen, and lymph nodes was evaluated in tissue sections at 1 and 7 days' post-dosing using enhanced darkfield microscopy and hyperspectral imaging. Nuclear magnetic resonance (NMR) analysis was used for biochemical profiling and pathway mapping of endogenous metabolites in urine collected at 24-h intervals prior to dosing, at Day 1 and Day 7. At Day 1 and Day 7, all three MWCNTs were observed in liver. NIEHS-12-2 was observed in spleen, whereas NIEHS-13-2 and NIEHS-14-2 were not. All three MWCNTs were observed in lymph nodes and lung at Day 7. The urinary biochemical profile showed the highest positive fold change (FC) at Day 7 for the metabolites acetate, alanine, and lactate, whereas 1-methylnicotinamide, 2-oxoglutarate, and hippurate had some of the lowest FCs for all three MWCNTs. This study demonstrates that the observed tissue location of MWCNTs is size dependent. Overlaps in the perturbation of endogenous metabolite profiles were found regardless of their size, and the biochemical responses were more profound at Day 7 compared with Day 1, indicating a delayed biological response to MWCNTs. [ABSTRACT FROM AUTHOR]

Background: Nanoparticles (NPs) are increasingly incorporated in everyday products. To investigate the effects of early life exposure to orally ingested TiO2 NP, male and female Sprague–Dawley rat pups received four consecutive daily doses of 10 mg/kg body weight TiO2 NP (diameter: 21 ± 5 nm) or vehicle control (water) by gavage at three different pre-weaning ages: postnatal day (PND) 2–5, PND 7–10, or PND 17–20. Cardiac assessment and basic neurobehavioral tests (locomotor activity, rotarod, and acoustic startle) were conducted on PND 20. Pups were sacrificed at PND 21. Select tissues were collected, weighed, processed for neurotransmitter and metabolomics analyses. Results: Heart rate was found to be significantly decreased in female pups when dosed between PND 7–10 and PND 17–20. Females dosed between PND 2–5 showed decrease acoustic startle response and when dosed between PND 7–10 showed decreased performance in the rotarod test and increased locomotor activity. Male pups dosed between PND 17–20 showed decreased locomotor activity. The concentrations of neurotransmitters and related metabolites in brain tissue and the metabolomic profile of plasma were impacted by TiO2 NP administration for all dose groups. Metabolomic pathways perturbed by TiO2 NP administration included pathways involved in amino acid and lipid metabolism. Conclusion: Oral administration of TiO2 NP to rat pups impacted basic cardiac and neurobehavioral performance, neurotransmitters and related metabolites concentrations in brain tissue, and the biochemical profiles of plasma. The findings suggested that female pups were more likely to experience adverse outcome following early life exposure to oral TiO2 NP than male pups. Collectively the data from this exploratory study suggest oral administration of TiO2 NP cause adverse biological effects in an age- and sex-related manner, emphasizing the need to understand the short- and long-term effects of early life exposure to TiO2 NP. [ABSTRACT FROM AUTHOR]