Non-targeted metabolomics analyses by mass spectrometry to explore metabolic stress after six training weeks in high level swimmers.

The objective was to compare the metabolic responses of high-level national swimmers to threshold or polarised training. 22 swimmers (n = 12 males and 10 females) participated in a 28-week cross-over intervention study consisting of 2 × 6 period weeks of training. Swimmers were assigned randomly to either training group for the first period: polarised (POL) (81% in energetic zone 1: blood lactate [La]b ≤ 2 mmol.L-1; 4% in zone 2: 2 mmol.L-1 <[La]b ≤ 4 mmol.L-1; 15% in zone 3: [La]b > 4 mmol.L-1) or threshold (THR) (65%/25%/10%). Before and after each training period, urine samples were collected for non-targeted metabolomics analysis. Mixed model analysis was performed on metabolomics data including fatigue class factors and/or training and/or interaction. Ion intensities of 6-keto-decanoylcarnitine (+31%), pregnanediol-3-glucuronide (+81%), P-cresol sulphate (+18%) were higher in the threshold group (P < 0.05) indicating higher glycogenic depletion and inflammation without alteration of the neuroendocrine stress axis. 4-phenylbutanic acid sulphate was 200% higher in less fatigued swimmers (P < 0.01) linking the anti-inflammatory activity at the cell membrane level to the subjective perception of fatigue. This research suggests the importance of replenishing glycogen stores and reducing inflammation during high thresholds training loads.

Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data.

INTRODUCTION: Metabolomics is a powerful phenotyping tool in nutrition and health research, generating complex data that need dedicated treatments to enrich knowledge of biological systems. In particular, to investigate relations between environmental factors, phenotypes and metabolism, discriminant statistical analyses are generally performed separately on metabolomic datasets, complemented by associations with metadata. Another relevant strategy is to simultaneously analyse thematic data blocks by a multi-block partial least squares discriminant analysis (MBPLSDA) allowing determining the importance of variables and blocks in discriminating groups of subjects, taking into account data structure. OBJECTIVE: The present objective was to develop a full open-source standalone tool, allowing all steps of MBPLSDA for the joint analysis of metabolomic and epidemiological data. METHODS: This tool was based on the mbpls function of the ade4 R package, enriched with functionalities, including some dedicated to discriminant analysis. Provided indicators help to determine the optimal number of components, to check the MBPLSDA model validity, and to evaluate the variability of its parameters and predictions. RESULTS: To illustrate the potential of this tool, MBPLSDA was applied to a real case study involving metabolomics, nutritional and clinical data from a human cohort. The availability of different functionalities in a single R package allowed optimizing parameters for an efficient joint analysis of metabolomics and epidemiological data to obtain new insights into multidimensional phenotypes. CONCLUSION: In particular, we highlighted the impact of filtering the metabolomic variables beforehand, and the relevance of a MBPLSDA approach in comparison to a standard PLS discriminant analysis method.

Metabolomics Reveals that the Type of Protein in a High-Fat Meal Modulates Postprandial Mitochondrial Overload and Incomplete Substrate Oxidation in Healthy Overweight Men.

Background: A meal rich in saturated fatty acids induces a postprandial metabolic challenge. The type of dietary protein may modulate postprandial metabolism. Objective: We studied the effect of dietary protein type on postprandial changes in the metabolome after a high-fat meal. Methods: In a 3-period, crossover, postprandial study, 10 healthy overweight men with an elevated waist circumference (>94 cm) ingested high-fat meals made up of cream fat (70% of energy), sucrose (15% energy), and protein (15% energy) from either casein (CAS), whey protein (WHE), or α-lactalbumin-enriched whey protein (LAC). Urine collected immediately before and 2, 4, and 6 h after the meal was analyzed for metabolomics, a secondary outcome of the clinical study. We used mixed-effect models, partial least-square regression, and pathway enrichment analysis. Results: At 4 and 6 h after the meal, the postprandial metabolome was found to be fully discriminated according to protein type. We identified 17 metabolites that significantly explained the effect of protein type on postprandial metabolomic changes (protein-time interaction). Among this signature, acylcarnitines and other acylated metabolites related to fatty acid or amino acid oxidation were the main discriminant features. The difference in metabolic profiles was mainly explained by urinary acylcarnitines and some other acylated products (protein type, Ps < 0.0001), with a dramatically greater increase (100- to 1000-fold) after WHE, and to a lesser extent after LAC, as compared with CAS. Pathway enrichment analysis confirmed that the type of protein had modified fatty acid oxidation (P < 0.05). Conclusion: Taken together, our results indicate that, in healthy overweight men, the type of protein in a high-fat meal interplays with fatty acid oxidation with a differential accumulation of incomplete oxidation products. A high-fat meal containing WHE, but not CAS, resulted in this outpacing of the tricarboxylic acid cycle. This study was registered at clinicaltrials.gov as NCT00931151.

Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics.

In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of the outcome to be explained. Alternatively, this configuration can be represented with a path diagram where the input blocks are each connected by links directed to the outcome-as in multiblock supervised modeling-and are also related to each other, thus allowing one to account for block effects. On the basis of a path model, we show herein how to estimate the effect of an input block, either on its own or conditionally to other(s), on the output response, respectively called "global" and "partial" effects, by percentages of explained variance in dedicated PLS regression models. These effects have been computed in two different path diagrams in a case study relative to metabolic syndrome, involving metabolomics and clinical data from an older men's cohort (NuAge). From the two effects associated with each path, the results highlighted the complementary information provided by metabolomics to clinical data and, reciprocally, in the metabolic syndrome exploration.

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men.

BACKGROUND: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. METHODS: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. FINDINGS: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). INTERPRETATION: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS. FUNDING: The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.

ProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis.

Genes are pleiotropic and getting a better knowledge of their function requires a comprehensive characterization of their mutants. Here, we generated multi-level data combining phenomic, proteomic and metabolomic acquisitions from plasma and liver tissues of two C57BL/6 N mouse models lacking the Lat (linker for activation of T cells) and the Mx2 (MX dynamin-like GTPase 2) genes, respectively. Our dataset consists of 9 assays (1 preclinical, 2 proteomics and 6 metabolomics) generated with a fully non-targeted and standardized approach. The data and processing code are publicly available in the ProMetIS R package to ensure accessibility, interoperability, and reusability. The dataset thus provides unique molecular information about the physiological role of the Lat and Mx2 genes. Furthermore, the protocols described herein can be easily extended to a larger number of individuals and tissues. Finally, this resource will be of great interest to develop new bioinformatic and biostatistic methods for multi-omics data integration.

Inhibition of bone turnover by milk intake in postmenopausal women.

Increased postmenopausal bone turnover leads to bone loss and fragility fracture risk. In the absence of osteoporosis, risk preventive measures, particularly those modifying nutritional lifestyle, are appropriate. We tested the hypothesis that milk supplementation affects bone turnover related to biochemical markers in a direction that, in the long term, may be expected to reduce postmenopausal bone loss. Thirty healthy postmenopausal women aged 59.3 (SD 3.3) years were enrolled in a prospective crossover trial of 16 weeks. After a 4-week period of adaptation with diet providing 600 mg calcium plus 300 mg ingested as 250 ml semi-skimmed milk, participants were maintained during 6 weeks under the same 600 mg calcium diet and randomized to receive either 500 ml semi-skimmed milk, thus providing a total of 1200 mg calcium, or no milk supplement. In the next 6 weeks they were switched to the alternative regimen. At the end of the each period, i.e. after 4, 10 and 16 weeks, blood and urinary samples were collected. The changes in blood variables between the periods of 6 weeks without and with milk supplementation were: for parathyroid hormone, -3.2 pg/ml (P=0.0054); for crosslinked telopeptide of type I collagen, -624 pg/ml (P<0.0001); for propeptide of type I procollagen, -5.5 ng/ml (P=0.0092); for osteocalcin, -2.8 ng/ml (P=0.0014). In conclusion, a 6-week period of milk supplementation induced a decrease in several biochemical variables compatible with diminished bone turnover mediated by reduction in parathyroid hormone secretion. This nutritional approach to postmenopausal alteration in bone metabolism may be a valuable measure in the primary prevention of osteoporosis.

Long-term moderate zinc supplementation increases exchangeable zinc pool masses in late-middle-aged men: the Zenith Study.

BACKGROUND: Zinc supplementation may be beneficial for health. Assessing exchangeable zinc pools may be a useful approach to evaluate zinc status. OBJECTIVE: We evaluated the effects of long-term supplementation with 2 moderate doses of zinc on the mass of exchangeable zinc pools. DESIGN: Three groups of healthy, late-middle-aged men (n = 16 per group) participated in a stable-isotope zinc kinetic study after 6 mo of daily supplementation with 0 (placebo), 15, or 30 mg Zn. At the end of the supplementation period, each subject received an intravenous injection of 0.89 mg (70)Zn, and the plasma zinc disappearance curve was monitored for the next 10 d. Two approaches were used to determine the characteristics of the exchangeable zinc pools: 1) formal 3-compartmental modeling and 2) a simplified determination of the total mass of the rapidly exchangeable zinc pool (EZP). RESULTS: In the placebo group, the exchangeable zinc pool masses for the 3 considered pools were as follows: 2.15, 12.7, and 100.5 mg Zn. The rapidly exchangeable zinc pool mass in the placebo group was 143 mg Zn. Zinc supplementation significantly increased the exchangeable zinc pool masses regardless of the approach used to determine these pools. In addition, these data confirm that exchangeable zinc pool masses correlate positively with total zinc intake and negatively with subject age and do not correlate with plasma zinc concentrations. CONCLUSION: Our data show that long-term supplementation with 2 moderate doses of zinc is an efficient way to increase exchangeable zinc pool masses in late-middle-aged men.

Therapeutic paracetamol treatment in older persons induces dietary and metabolic modifications related to sulfur amino acids.

Sulfur amino acids are determinant for the detoxification of paracetamol (N-acetyl-p-aminophenol) through sulfate and glutathione conjugations. Long-term paracetamol treatment is common in the elderly, despite a potential cysteine/glutathione deficiency. Detoxification could occur at the expense of anti-oxidative defenses and whole body protein stores in elderly. We tested how older persons satisfy the extra demand in sulfur amino acids induced by long-term paracetamol treatment, focusing on metabolic and nutritional aspects. Effects of 3 g/day paracetamol for 14 days on fasting blood glutathione, plasma amino acids and sulfate, urinary paracetamol metabolites, and urinary metabolomic were studied in independently living older persons (five women, five men, mean (±SEM) age 74 ± 1 years). Dietary intakes were recorded before and at the end of the treatment and ingested sulfur amino acids were evaluated. Fasting blood glutathione, plasma amino acids, and sulfate were unchanged. Urinary nitrogen excretion supported a preservation of whole body proteins, but large-scale urinary metabolomic analysis revealed an oxidation of some sulfur-containing compounds. Dietary protein intake was 13% higher at the end than before paracetamol treatment. Final sulfur amino acid intake reached 37 mg/kg/day. The increase in sulfur amino acid intake corresponded to half of the sulfur excreted in urinary paracetamol conjugates. In conclusion, older persons accommodated to long-term paracetamol treatment by increasing dietary protein intake without any mobilization of body proteins, but with decreased anti-oxidative defenses. The extra demand in sulfur amino acids led to a consumption far above the corresponding population-safe recommendation.

Effect of zinc supplementation on in vitro copper-induced oxidation of low-density lipoproteins in healthy French subjects aged 55-70 years: the Zenith Study.

Zn has been shown to possess antioxidant properties in vitro and in vivo. As inadequate dietary Zn intake has been reported in these populations, Zn supplementation may protect against oxidative stress and thereby limit the progression of degenerative diseases in such populations. We conducted the present study to evaluate the long-term supplementation effects of two moderate doses of Zn on in vitro Cu-induced LDL oxidation in French men and women. Three groups of sixteen healthy subjects aged 55-70 years from each sex participated in this randomized double-blind, placebo-controlled study. Each group received for six months either 0, 15 or 30 mg supplemental Zn per d. At the beginning and at the end of the supplementation periods, dietary intakes of Zn, Cu, Fe and vitamin E were estimated using 4 d food-intake records (including the weekend) and the GENI program. Zn, Cu, Fe and vitamin E status were also determined. In vitro LDL oxidizability (basal conjugated diene level, maximal conjugated diene formation and lag time) and lipid parameters were also determined. Dietary intakes of Zn, Cu, Fe and vitamin E were adequate in this population. Zn supplementation significantly increased serum Zn levels but did not significantly modify Cu, Fe or vitamin E status. However, Zn supplementation had no effect on in vitro LDL oxidation parameters, nor were there any sex-related differences in in vitro LDL oxidizability. The present study showed that long-term Zn supplementation of healthy subjects aged 55-70 years had no effect on in vitro Cu-induced LDL oxidation under the study conditions.