-
1.
Characterization of Metabolites in Plasma, Urine and Feces of Healthy Participants after Taking Brahmi Essence for Twelve Weeks Using LC-ESI-QTOF-MS Metabolomic Approach.
Minale, G, Saesong, T, Temkitthawon, P, Waranuch, N, Nuengchamnong, N, Chootip, K, Kamkaew, N, Kongbangkerd, T, Engsuwan, J, Ingkaninan, K
Molecules (Basel, Switzerland). 2021;(10)
Abstract
Brahmi essence, developed from Bacopa monnieri (L.) Wettst. standardized extract and mulberry juice, was proven to improve the memory speed of healthy participants aged 55-80 years old, following a 12-week dietary program. However, the metabolites have not yet been reported. Our objective was to characterize the altered metabolites in the plasma, urine, and feces of healthy volunteers after consumption of Brahmi essence for 12 weeks, using the LC-MS metabolomics approach. The altered metabolites were selected from OPLS-DA S-plots; 15 metabolites in the plasma, 7 in the urine, and 17 in the feces samples were tentatively identified by comparison with an online database and literature. The metabolites in the plasma samples were in the classes of amino acids, acylcarnitine, and phospholipids. Benzeneactamide-4-O-sulphate and 3-hydroxyhippuric acid were found in urine samples. The metabolites in the class of amino acids, together with jujubogenin and pseudojujubogenin, were identified in the fecal samples. The aminoacyl-tRNA, aromatic amino acids, and branched-chain amino acid biosynthetic pathways were mainly related to the identified metabolites in all three samples. It could be implied that those metabolites and their pathways might be linked with the effect of Brahmi essence on memory speed.
-
2.
Effects of Sodium Selenite Injection on Serum Metabolic Profiles in Women Diagnosed with Breast Cancer-Related Lymphedema-Secondary Analysis of a Randomized Placebo-Controlled Trial Using Global Metabolomics.
Lee, H, Lee, B, Kim, Y, Min, S, Yang, E, Lee, S
Nutrients. 2021;(9)
Abstract
In our previous study, intravenous (IV) injection of selenium alleviated breast cancer-related lymphedema (BCRL). This secondary analysis aimed to explore the metabolic effects of selenium on patients with BCRL. Serum samples of the selenium-treated (SE, n = 15) or the placebo-controlled (CTRL, n = 14) groups were analyzed by ultra-high-performance liquid chromatography with Q-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap/MS). The SE group showed a lower ratio of extracellular water to segmental water (ECW/SW) in the affected arm to ECW/SW in the unaffected arm (arm ECW/SW ratio) than the CTRL group. Metabolomics analysis showed a valid classification at 2-weeks and 107 differential metabolites were identified. Among them, the levels of corticosterone, LTB4-DMA, and PGE3-which are known anti-inflammatory compounds-were elevated in the SE group. Pathway analysis demonstrated that lipid metabolism (glycerophospholipid metabolism, steroid hormone biosynthesis, or arachidonic acid metabolism), nucleotide metabolism (pyrimidine or purine metabolism), and vitamin metabolism (pantothenate and CoA biosynthesis, vitamin B6 metabolism, ascorbate and aldarate metabolism) were altered in the SE group compared to the CTRL group. In addition, xanthurenic acid levels were negatively associated with whole blood selenium level (WBSe) and positively associated with the arm ECW/SW. In conclusion, selenium IV injection improved the arm ECW/SW ratio and altered the serum metabolic profiles in patients with BCRL, and improved the anti-inflammatory process in lipid, nucleotide and vitamin pathways, which might alleviate the symptoms of BCRL.
-
3.
Urine and Plasma Metabolome of Healthy Adults Consuming the DASH (Dietary Approaches to Stop Hypertension) Diet: A Randomized Pilot Feeding Study.
Pourafshar, S, Nicchitta, M, Tyson, CC, Svetkey, LP, Corcoran, DL, Bain, JR, Muehlbauer, MJ, Ilkayeva, O, O'Connell, TM, Lin, PH, et al
Nutrients. 2021;(6)
Abstract
We aimed to identify plasma and urine metabolites altered by the Dietary Approaches to Stop Hypertension (DASH) diet in a post-hoc analysis of a pilot feeding trial. Twenty adult participants with un-medicated hypertension consumed a Control diet for one week followed by 2 weeks of random assignment to either Control or DASH diet. Non-missing fasting plasma (n = 56) and 24-h urine (n = 40) were used to profile metabolites using untargeted gas chromatography/mass spectrometry. Linear models were used to compare metabolite levels between the groups. In urine, 19 identifiable untargeted metabolites differed between groups at p < 0.05. These included a variety of phenolic acids and their microbial metabolites that were higher during the DASH diet, with many at false discovery rate (FDR) adjusted p < 0.2. In plasma, eight identifiable untargeted metabolites were different at p < 0.05, but only gamma-tocopherol was significantly lower on DASH at FDR adjusted p < 0.2. The results provide insights into the mechanisms of benefit of the DASH diet.
-
4.
Leonurine affected homocysteine-methionine metabolism based on metabolomics and gut microbiota studies of clinical trial samples.
Liao, J, Suguro, R, Zhao, X, Yu, Y, Cui, Y, Zhu, YZ
Clinical and translational medicine. 2021;(10):e535
-
5.
Ultra-Performance Liquid Chromatography-Ion Mobility Separation-Quadruple Time-of-Flight MS (UHPLC-IMS-QTOF MS) Metabolomics for Short-Term Biomarker Discovery of Orange Intake: A Randomized, Controlled Crossover Study.
Lacalle-Bergeron, L, Portolés, T, López, FJ, Sancho, JV, Ortega-Azorín, C, Asensio, EM, Coltell, O, Corella, D
Nutrients. 2020;(7)
Abstract
A major problem with dietary assessments is their subjective nature. Untargeted metabolomics and new technologies can shed light on this issue and provide a more complete picture of dietary intake by measuring the profile of metabolites in biological samples. Oranges are one of the most consumed fruits in the world, and therefore one of the most studied for their properties. The aim of this work was the application of untargeted metabolomics approach with the novel combination of ion mobility separation coupled to high resolution mass spectrometry (IMS-HRMS) and study the advantages that this technique can bring to the area of dietary biomarker discovery, with the specific case of biomarkers associated with orange consumption (Citrus reticulata) in plasma samples taken during an acute intervention study (consisting of a randomized, controlled crossover trial in healthy individuals). A total of six markers of acute orange consumption, including betonicines and conjugated flavonoids, were identified with the experimental data and previous literature, demonstrating the advantages of ion mobility in the identification of dietary biomarkers and the benefits that an additional structural descriptor, as the collision cross section value (CCS), can provide in this area.
-
6.
Metabolomic-Based Approach to Identify Biomarkers of Apple Intake.
McNamara, AE, Collins, C, Harsha, PSCS, González-Peña, D, Gibbons, H, McNulty, BA, Nugent, AP, Walton, J, Flynn, A, Brennan, L
Molecular nutrition & food research. 2020;(11):e1901158
Abstract
SCOPE There is an increased interest in developing biomarkers of food intake to address some of the limitations associated with self-reported data. The objective is to identify biomarkers of apple intake, examine dose-response relationships, and agreement with self-reported data. METHODS AND RESULTS Metabolomic data from three studies are examined: an acute intervention, a short-term intervention, and a free-living cohort study. Fasting and postprandial urine samples are collected for analysis by 1 H-NMR and liquid chromatography-mass spectrometry (LC-MS). Calibration curves are developed to determine apple intake and classify individuals into categories of intake. Multivariate analysis of data reveals that levels of multiple metabolites increase significantly post-apple consumption, compared to the control food-broccoli. In the dose-response study, urinary xylose, epicatechin sulfate, and 2,6-dimethyl-2-(2-hydroxyethyl)-3,4-dihydro-2H-1-benzopyran increase as apple intake increases. Urinary xylose concentrations in a free-living cohort perform poorly at an individual level but are capable of ranking individuals in categories of intake. CONCLUSION Urinary xylose exhibits a dose-response relationship with apple intake and performs well as a ranking biomarker in the population study. Other potential biomarkers are identified and future work will combine these with xylose in a biomarker panel which may allow for a more objective determination of individual intake.
-
7.
Different metabolism of EPA, DPA and DHA in humans: A double-blind cross-over study.
Guo, XF, Tong, WF, Ruan, Y, Sinclair, AJ, Li, D
Prostaglandins, leukotrienes, and essential fatty acids. 2020;:102033
Abstract
This study aimed to compare eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) incorporated into red blood cells (RBC) phospholipids (PL), plasma PL, plasma triglyceride (TAG), and plasma cholesteryl ester (CE) fractions, and the metabolomics profiles in a double-blind cross-over study. Twelve female healthy subjects randomly consumed 1 g per day for 6 days of pure EPA, DPA, or DHA. The placebo treatment was olive oil. The fasting venous blood was taken at days 0, 3 and 6, and the RBC PL and plasma lipid fractions were separated for fatty acid determination using thin layer chromatography followed by gas chromatography. Plasma metabolites were analyzed by UHPLC-Q-Exactive Orbitrap/MS. Supplemental EPA significantly increased the concentrations of EPA in RBC PL (days 3 and 6). For subjects consuming the DPA supplement, the concentrations of both DPA and EPA were significantly increased in RBC PL over a 6-day period, respectively. For plasma PL fraction, EPA and DPA supplementation significantly increased the concentrations of EPA and DPA at both days 3 and 6, respectively. Supplemental DHA significantly increased the concentrations of DHA in plasma PL at day 6. For plasma TAG fraction, supplementation with EPA and DPA significantly increased the concentrations of EPA and DPA at both days 3 and 6, respectively. After DHA supplementation, significant increases in the concentrations of DHA were found relative to baseline at both days 3 and 6. For plasma CE fraction, EPA supplementation significantly increased the concentrations of EPA (days 3 and 6) and DPA (days 6), respectively. Supplemental DPA significantly increased the concentrations of EPA at day 6. Meanwhile, the concentrations of DHA were significantly increased over a 6-day period of intervention after subjects consuming the DHA supplements. There were a total of 922 plasma metabolites identified using metabolomics analyses. Supplementation with DPA and DHA significantly increased the levels of sphingosine 1-phosphate (P for DPA = 0.025, P for DHA = 0.029) and 15-deoxy-Δ12,14-prostaglandin A1 (P for DPA = 0.034; P for DHA = 0.021) in comparison with olive oil group. Additionally, supplementation with EPA (P = 0.007) and DHA (P = 0.005) significantly reduced the levels of linoleyl carnitine, compared with olive oil group. This study shows that DPA might act as a reservoir of n-3 LCP incorporated into blood lipid fractions, metabolized into DHA, and retro-converted back to EPA. Metabolomics analyses indicate that supplemental EPA, DPA and DHA have shared and differentiated metabolites. The differences of these metabolic biomarkers should be investigated in additional studies.
-
8.
Randomized nutrient bar supplementation improves exercise-associated changes in plasma metabolome in adolescents and adult family members at cardiometabolic risk.
Mietus-Snyder, M, Narayanan, N, Krauss, RM, Laine-Graves, K, McCann, JC, Shigenaga, MK, McHugh, TH, Ames, BN, Suh, JH
PloS one. 2020;(10):e0240437
Abstract
BACKGROUND Poor diets contribute to metabolic complications of obesity, insulin resistance and dyslipidemia. Metabolomic biomarkers may serve as early nutrition-sensitive health indicators. This family-based lifestyle change program compared metabolic outcomes in an intervention group (INT) that consumed 2 nutrient bars daily for 2-months and a control group (CONT). METHODS Overweight, predominantly minority and female adolescent (Teen)/parent adult caretaker (PAC) family units were recruited from a pediatric obesity clinic. CONT (8 Teen, 8 PAC) and INT (10 Teen, 10 PAC) groups randomized to nutrient bar supplementation attended weekly classes that included group nutrition counseling and supervised exercise. Pre-post physical and behavioral parameters, fasting traditional biomarkers, plasma sphingolipids and amino acid metabolites were measured. RESULTS In the full cohort, a baseline sphingolipid ceramide principal component composite score correlated with adiponectin, triglycerides, triglyceride-rich very low density lipoproteins, and atherogenic small low density lipoprotein (LDL) sublasses. Inverse associations were seen between a sphingomyelin composite score and C-reactive protein, a dihydroceramide composite score and diastolic blood pressure, and the final principal component that included glutathionone with fasting insulin and the homeostatic model of insulin resistance. In CONT, plasma ceramides, sphinganine, sphingosine and amino acid metabolites increased, presumably due to increased physical activity. Nutrient bar supplementation (INT) blunted this rise and significantly decreased ureagenic, aromatic and gluconeogenic amino acid metabolites. Metabolomic changes were positively correlated with improvements in clinical biomarkers of dyslipidemia. CONCLUSION Nutrient bar supplementation with increased physical activity in obese Teens and PAC elicits favorable metabolomic changes that correlate with improved dyslipidemia. The trial from which the analyses reported upon herein was part of a series of nutrient bar clinical trials registered at clinicaltrials.gov as NCT02239198.
-
9.
Serum Metabolomic Response to Low- and High-Dose Vitamin E Supplementation in Two Randomized Controlled Trials.
Huang, J, Hodis, HN, Weinstein, SJ, Mack, WJ, Sampson, JN, Mondul, AM, Albanes, D
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2020;(7):1329-1334
-
-
Free full text
-
Abstract
BACKGROUND Vitamin E is an essential micronutrient and critical human antioxidant previously tested for cancer preventative effects with conflicting clinical trial results that have yet to be explained biologically. METHODS We examined baseline and on-trial serum samples for 154 men randomly assigned to receive 400 IU vitamin E (as alpha-tocopheryl acetate; ATA) or placebo daily in the Vitamin E Atherosclerosis Prevention Study (VEAPS), and for 100 men administered 50 IU ATA or placebo daily in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC). Over 970 metabolites were identified using ultrahigh-performance LC/MS-MS. Linear regression models estimated the change in serum metabolites of men supplemented with vitamin E versus those receiving placebo in VEAPS as compared with ATBC. RESULTS Serum alpha-carboxyethyl hydrochroman (CEHC) sulfate, alpha-tocopherol, and beta/gamma-tocopherol were significantly altered by ATA supplementation in both trials (all P values ≤5.1 × 10-5, the Bonferroni multiple comparisons corrected statistical threshold). Serum C22 lactone sulfate was significantly decreased in response to the high-dose vitamin E in VEAPS (β = -0.70, P = 8.1 × 10-6), but not altered by the low dose in ATBC (β = -0.17, P = 0.4). In addition, changes in androgenic steroid metabolites were strongly correlated with the vitamin E supplement-associated change in C22 lactone sulfate only in the VEAPS trial. CONCLUSIONS We found evidence of a dose-dependent vitamin E supplementation effect on a novel C22 lactone sulfate compound that was correlated with several androgenic steroids. IMPACT Our data add information on a differential hormonal response based on vitamin E dose that could have direct relevance to opposing prostate cancer incidence results from previous large controlled trials.
-
10.
Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation.
McBride, N, Yousefi, P, White, SL, Poston, L, Farrar, D, Sattar, N, Nelson, SM, Wright, J, Mason, D, Suderman, M, et al
BMC medicine. 2020;(1):366
Abstract
BACKGROUND Prediction of pregnancy-related disorders is usually done based on established and easily measured risk factors. Recent advances in metabolomics may provide earlier and more accurate prediction of women at risk of pregnancy-related disorders. METHODS We used data collected from women in the Born in Bradford (BiB; n = 8212) and UK Pregnancies Better Eating and Activity Trial (UPBEAT; n = 859) studies to create and validate prediction models for pregnancy-related disorders. These were gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), small for gestational age (SGA), large for gestational age (LGA) and preterm birth (PTB). We used ten-fold cross-validation and penalised regression to create prediction models. We compared the predictive performance of (1) risk factors (maternal age, pregnancy smoking, body mass index (BMI), ethnicity and parity) to (2) nuclear magnetic resonance-derived metabolites (N = 156 quantified metabolites, collected at 24-28 weeks gestation) and (3) combined risk factors and metabolites. The multi-ethnic BiB cohort was used for training and testing the models, with independent validation conducted in UPBEAT, a multi-ethnic study of obese pregnant women. RESULTS Maternal age, pregnancy smoking, BMI, ethnicity and parity were retained in the combined risk factor and metabolite models for all outcomes apart from PTB, which did not include maternal age. In addition, 147, 33, 96, 51 and 14 of the 156 metabolite traits were retained in the combined risk factor and metabolite model for GDM, HDP, SGA, LGA and PTB, respectively. These include cholesterol and triglycerides in very low-density lipoproteins (VLDL) in the models predicting GDM, HDP, SGA and LGA, and monounsaturated fatty acids (MUFA), ratios of MUFA to omega 3 fatty acids and total fatty acids, and a ratio of apolipoprotein B to apolipoprotein A-1 (APOA:APOB1) were retained predictors for GDM and LGA. In BiB, discrimination for GDM, HDP, LGA and SGA was improved in the combined risk factors and metabolites models. Risk factor area under the curve (AUC 95% confidence interval (CI)): GDM (0.69 (0.64, 0.73)), HDP (0.74 (0.70, 0.78)) and LGA (0.71 (0.66, 0.75)), and SGA (0.59 (0.56, 0.63)). Combined risk factor and metabolite models AUC 95% (CI): GDM (0.78 (0.74, 0.81)), HDP (0.76 (0.73, 0.79)) and LGA (0.75 (0.70, 0.79)), and SGA (0.66 (0.63, 0.70)). For GDM, HDP and LGA, but not SGA, calibration was good for a combined risk factor and metabolite model. Prediction of PTB was poor for all models. Independent validation in UPBEAT at 24-28 weeks and 15-18 weeks gestation confirmed similar patterns of results, but AUCs were attenuated. CONCLUSIONS Our results suggest a combined risk factor and metabolite model improves prediction of GDM, HDP and LGA, and SGA, when compared to risk factors alone. They also highlight the difficulty of predicting PTB, with all models performing poorly.