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1.
The Influence of the Duration of Breastfeeding on the Infant's Metabolic Epigenome.
Pauwels, S, Symons, L, Vanautgaerden, EL, Ghosh, M, Duca, RC, Bekaert, B, Freson, K, Huybrechts, I, Langie, SAS, Koppen, G, et al
Nutrients. 2019;(6)
Abstract
Nutrition in the postnatal period is associated with metabolic programming. One of the presumed underlying mechanisms involves epigenetic modifications (e.g., DNA methylation). Breastfeeding has an unknown impact on DNA methylation at a young age. Within the Maternal Nutrition and Offspring's Epigenome (MANOE) study, we assessed the effect of breastfeeding duration on infant growth and buccal methylation in obesity-related genes (n = 101). A significant difference was found between infant growth and buccal RXRA and LEP methylation at 12 months of breastfeeding. For RXRA CpG2 methylation, a positive association was found with duration of breastfeeding (slope = 0.217; 95% confidence interval (CI) 1.03, 0.330; p < 0.001). For RXRA CpG3 and CpG, mean methylation levels were significantly lower when children were breastfed for 4-6 months compared to non-breastfed children (only CpG3), and those breastfed for 7-9 months, 10-12 months, or 1-3 months. On the other hand, higher LEP CpG3 methylation was observed when mothers breastfed 7-9 months (6.1%) as compared to breastfeeding for 1-3 months (4.3%; p = 0.007) and 10-12 months (4.6%; p = 0.04). In addition, we observed that infant weight was significantly lower when children were breastfed for 10-12 months. Breastfeeding duration was associated with epigenetic variations in RXRA and LEP at 12 months and with infant biometry/growth. Our results support the hypothesis that breastfeeding could induce epigenetic changes in infants.
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2.
The plasma metabolome of women in early pregnancy differs from that of non-pregnant women.
Handelman, SK, Romero, R, Tarca, AL, Pacora, P, Ingram, B, Maymon, E, Chaiworapongsa, T, Hassan, SS, Erez, O
PloS one. 2019;(11):e0224682
Abstract
BACKGROUND In comparison to the non-pregnant state, the first trimester of pregnancy is characterized by systemic adaptation of the mother. The extent to which these adaptive processes are reflected in the maternal blood metabolome is not well characterized. OBJECTIVE To determine the differences between the plasma metabolome of non-pregnant and pregnant women before 16 weeks gestation. STUDY DESIGN This study included plasma samples from 21 non-pregnant women and 50 women with a normal pregnancy (8-16 weeks of gestation). Combined measurements by ultrahigh performance liquid chromatography/tandem mass spectrometry and by gas chromatography/mass spectrometry generated molecular abundance measurements for each sample. Molecular species detected in at least 10 samples were included in the analysis. Differential abundance was inferred based on false discovery adjusted p-values (FDR) from Mann-Whitney-Wilcoxon U tests <0.1 and a minimum median abundance ratio (fold change) of 1.5. Alternatively, metabolic data were quantile normalized to remove sample-to-sample differences in the overall metabolite abundance (adjusted analysis). RESULTS Overall, 637 small molecules met the inclusion criteria and were tested for association with pregnancy; 44% (281/637) of small molecules had significantly different abundance, of which 81% (229/281) were less abundant in pregnant than in non-pregnant women. Eight percent (14/169) of the metabolites that remained significant in the adjusted analysis also changed as a function of gestational age. A pathway analysis revealed enrichment in steroid metabolites related to sex hormones, caffeine metabolites, lysolipids, dipeptides, and polypeptide bradykinin derivatives (all, FDR < 0.1). CONCLUSIONS This high-throughput mass spectrometry study identified: 1) differences between pregnant vs. non-pregnant women in the abundance of 44% of the profiled plasma metabolites, including known and novel molecules and pathways; and 2) specific metabolites that changed with gestational age.
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The clinical effects of purslane (Portulaca oleracea) seeds on metabolic profiles in patients with nonalcoholic fatty liver disease: A randomized controlled clinical trial.
Gheflati, A, Adelnia, E, Nadjarzadeh, A
Phytotherapy research : PTR. 2019;(5):1501-1509
Abstract
Nonalcoholic fatty liver disease (NAFLD) is the most common form of chronic liver diseases associated with unfavorable metabolic profiles and oxidative stress parameters. This study was designed to determine the effects of purslane seeds consumption with a low-calorie diet on insulin resistance, lipid profile, and oxidative stress indices in patients with NAFLD. This randomized controlled clinical trial was conducted on 54 individuals with NAFLD. Subjects were randomly assigned to consume either 10 g/day of purslane seeds sachet before breakfast and dinner in addition to a low-calorie diet (n = 27) or only the low-calorie diet (n = 27) for 8 weeks. Fasting blood samples were collected at the beginning and end of the study to measure relevant variables. Intake of purslane seeds with the low-calorie diet led to a significant decrease in serum concentrations of fasting blood sugar (FBS; -3.52 ± 10.45 compared with 3.03 ± 9.01 mg/dl, P = 0.017), quantitative insulin sensitivity check index (QUICKI; 0.13 ± 0.27 compared with -0.002 ± 0.016, P = 0.017), total cholesterol (4.33 ± 34.04 compared with 23.48 ± 29.47 mg/dl, P = 0.032), and low-density lipoprotein cholesterol (LDL-C; -4.35 ± 22.65 compared with 11.82 ± 16.08 mg/dl, P = 0.004) after intervention. Compared with the control group, purslane seeds consumption with adherence to a low-calorie diet had beneficial effects on FBS, HOMA-IR, QUICKI, serum total, and LDL-C in patients with NAFLD but did not affect other glycemic, lipid profile, and oxidative stress parameters.
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Metabolomic signature of exposure and response to citalopram/escitalopram in depressed outpatients.
Bhattacharyya, S, Ahmed, AT, Arnold, M, Liu, D, Luo, C, Zhu, H, Mahmoudiandehkordi, S, Neavin, D, Louie, G, Dunlop, BW, et al
Translational psychiatry. 2019;(1):173
Abstract
Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD17) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline. Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD17 scores. In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure. In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine-homogentisic acid and methionine-tyrosine interactions associated with HRSD17. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.
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Metabolome-wide association study of anti-epileptic drug treatment during pregnancy.
Walker, DI, Perry-Walker, K, Finnell, RH, Pennell, KD, Tran, V, May, RC, McElrath, TF, Meador, KJ, Pennell, PB, Jones, DP
Toxicology and applied pharmacology. 2019;:122-130
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Abstract
Pregnant women with epilepsy (PWWE) require continuous anti-epileptic drug (AED) treatment to avoid risk to themselves and fetal risks secondary to maternal seizures, resulting in prolonged AED exposure to the developing embryo and fetus. The objectives of this study were to determine whether high-resolution metabolomics is able to link the metabolite profile of PWWE receiving lamotrigine or levetiracetam for seizure control to associated pharmacodynamic (PD) biological responses. Untargeted metabolomic analysis of plasma obtained from 82 PWWE was completed using high-resolution mass spectrometry. Biological alterations due to lamotrigine or levetiracetam monotherapy were determined by a metabolome-wide association study that compared patients taking either drug to those who did not require AED treatment. Metabolic changes associated with AED use were then evaluated by testing for drug-dose associated metabolic variations and pathway enrichment. AED therapy resulted in drug-associated metabolic profiles recognizable within maternal plasma. Both the parent compounds and major metabolites were detected, and each AED was correlated with other metabolic features and pathways. Changes in metabolites and metabolic pathways important to maternal health and linked to fetal neurodevelopment were detected for both drugs, including changes in one‑carbon metabolism, neurotransmitter biosynthesis and steroid metabolism. In addition, decreased levels of 5-methyltetrahydrofolate and tetrahydrofolate were detected in women taking lamotrigine, which is consistent with recent findings showing increased risk of autism spectrum disorder traits in PWWE using AED. These results represent a first step in development of pharmacometabolomic framework with potential to detect adverse AED-related metabolic changes during pregnancy.
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Metabolomic profiling for the identification of novel diagnostic markers and therapeutic targets in prostate cancer: an update.
Lucarelli, G, Loizzo, D, Ferro, M, Rutigliano, M, Vartolomei, MD, Cantiello, F, Buonerba, C, Di Lorenzo, G, Terracciano, D, De Cobelli, O, et al
Expert review of molecular diagnostics. 2019;(5):377-387
Abstract
An altered metabolic regulation is involved in the development and progression of different cancer types. As well as this, many genes associated with tumors are shown to have an important role in control of the metabolism. The incidence of prostate cancer (PCa) is increased in men with metabolic disorders. In particular, obesity is an established risk factor for PCa. An increased body mass index correlates with aggressive disease, and a higher risk of biochemical recurrence and prostate cancer-specific mortality. Increased lipogenesis is also one of the most significant events in PCa metabolism reprogramming. Areas covered: In this article, we provide an updated review of the current understanding of the PCa metabolome and evaluate the possibility of unveiling novel therapeutic targets. Expert opinion: Obesity is an established risk factor for PCa, and an increased BMI correlates with aggressive disease, and a higher risk of biochemical recurrence and prostate cancer-specific mortality. PCa metabolome is characterized by the accumulation of metabolic intermediates and an increased expression of genes in the tricarboxylic acid cycle, the induction of de novo lipogenesis and cholesterogenesis. PCa cells can induce different alterations in their microenvironment by modulating the crosstalk between cancer and stromal cells.
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Traveling Wave Ion Mobility Mass Spectrometry: Metabolomics Applications.
Paglia, G, Astarita, G
Methods in molecular biology (Clifton, N.J.). 2019;:39-53
Abstract
Ion mobility (IM) spectrometry can separate gas-phase ions according to their charge, molecular shape, and size. In recent years, several IM technologies have been integrated with mass spectrometry (MS) and launched as commercially available instrumentation for metabolomics analysis. The addition of IM to MS-based metabolomics workflows provides an additional degree of separation to chromatography and MS resolving power, improving peak capacity and signal-to-noise ratio. Moreover, it makes possible to experimentally derive collision cross section (CCS), which can be used as an additional coordinate for metabolite identification, together with accurate mass and fragmentation information. The addition of CCS to current metabolome database would allow to filter and score molecules based on their CCS values, adding more confidence in the identification process during metabolomics experiments.In this chapter, we present procedures for the integration of travelling-wave (TW)-IM into traditional MS-based metabolomics workflows.
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Effects of dapagliflozin on urinary metabolites in people with type 2 diabetes.
Mulder, S, Heerspink, HJL, Darshi, M, Kim, JJ, Laverman, GD, Sharma, K, Pena, MJ
Diabetes, obesity & metabolism. 2019;(11):2422-2428
Abstract
AIM: To assess the effects of the sodium-glucose co-transporter-2 (SGLT2) inhibitor dapagliflozin on a pre-specified panel of 13 urinary metabolites linked to mitochondrial metabolism in people with type 2 diabetes and elevated urine albumin levels. MATERIALS AND METHODS Urine and plasma samples were used from a double-blind, randomized, placebo-controlled crossover trial in 31 people with type 2 diabetes, with an albumin:creatinine ratio >100 mg/g, and who were on a stable dose of an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Dapagliflozin or placebo treatment periods each lasted 6 weeks, with a 6-week washout period in between. Urinary and plasma metabolites were quantified by gas-chromatography mass spectrometry, corrected for creatinine level, and then combined into a single-valued urinary metabolite index. Fractional excretion of the metabolites was calculated. RESULTS All 13 urinary metabolites were detectable. After 6 weeks of dapagliflozin therapy, nine of the 13 metabolites were significantly increased from baseline. The urinary metabolite index increased by 42% (95% confidence interval [CI] 8.5 to 85.6; P = .01) with placebo versus 121% (95% CI 69 to 189; P < .001) with dapaglifozin. The placebo-adjusted effect was 56% (95% CI 11 to 118; P = .012). In plasma, seven of the 13 metabolites were detectable, and none was modified by dapagliflozin. CONCLUSIONS Dapagliflozin significantly increased a panel of urinary metabolites previously linked to mitochondrial metabolism. These data support the hypothesis that SGLT2 inhibitors improve mitochondrial function, and improvements in mitochondrial function could be a mechanism for kidney protection. Future studies with longer treatment duration and clinical outcomes are needed to confirm the clinical impact of these findings.
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Increased Dairy Product Intake Alters Serum Metabolite Profiles in Subjects at Risk of Developing Type 2 Diabetes.
O'Connor, S, Greffard, K, Leclercq, M, Julien, P, Weisnagel, SJ, Gagnon, C, Droit, A, Bilodeau, JF, Rudkowska, I
Molecular nutrition & food research. 2019;(19):e1900126
Abstract
SCOPE Metabolomics is increasingly used to identify biomarkers of diet or chronic diseases, such as type 2 diabetes. Yet, metabolite signatures following dairy intake in hyperinsulinemic subjects have not been identified. The objective is to evaluate the effects of a high dairy diet (HD) for 6 weeks (4 servings or more per day), compared with an adequate dairy diet (AD) (2 servings or less per day), on serum metabolite profiles in hyperinsulinemic adults. METHODS AND RESULTS In this crossover trial, subjects are randomized to HD or AD for 6 weeks. Serum metabolites are assessed using GC/MS. Twenty-six subjects completed the study. Levels of pentadecanoic acid, tyrosine and lathosterol are increased in HD, while 1,5-anhydrosorbitol, myo-inositol, 3-aminoisobutyric acid and beta-sitosterol are decreased (p < 0.05). Sorbitol levels are increased after AD, while hexanoic acid, lauric acid, l-kynurenine, methionine, and benzoic acid levels are reduced (p < 0.05). Histidine, caprylic acid, nonanoic acid, decanoic acid, lauric acid, heptadecanoic acid, and benzoic acid levels are increased in HD compared to AD, while malic acid levels are increased in AD compared with HD (p < 0.05). CONCLUSION Higher dairy products intake modifies metabolite profiles in hyperinsulinemic subjects.
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1H NMR-based fingerprinting of eleven Mexican Capsicum annuum cultivars.
Florentino-Ramos, E, Villa-Ruano, N, Hidalgo-Martínez, D, Ramírez-Meraz, M, Méndez-Aguilar, R, Velásquez-Valle, R, Zepeda-Vallejo, LG, Pérez-Hernández, N, Becerra-Martínez, E
Food research international (Ottawa, Ont.). 2019;:12-19
Abstract
Approximately 90% of the chili peppers consumed in the world are harvested in Mexico. The present article describes the untargeted 1H NMR-based metabolomic profiling of 11 cultivars of Capsicum annuum species which are routinely consumed worldwide. The metabolomic fingerprinting detected via 1H NMR contained 44 metabolites including sugars, amino acids, organic acids, polyphenolic acids and alcohols which were identified by comparison with the literature data, with Chenomx database and by 2D NMR. Statistical approaches based on principal component analysis (PCA) and linear discriminant analysis (LDA) were used to classify the Capsicum annuum cultivars according to their metabolite profile. LDA revealed metabolomic differences and similarities among Capsicum annuum cultivars, whereas hierarchical cluster analysis (HCA) significantly separated the cultivars according to the phylogenetic trees obtained. Substantial endogenous levels of free amino acids and carbohydrates were detected in all the studied cultivars but interestingly, Capsicum annuum cv. mirasol and C. annuum cv. chilaca contained almost three-fold more endogenous levels of vitamin C than the other cultivars. Considering that this antioxidant was found in crude aqueous extracts, its abundance could be directly proportional to its bioavailability for human nutrition. The results suggest that 1H NMR is an effective method to determine differences among cultivars of the Capsicum annuum species.