Thaer Barri

Effects of an isocaloric healthy Nordic diet on insulin sensitivity, lipid profile and inflammation markers in metabolic syndrome – a randomized study (SYSDIET)

Different healthy food patterns may modify cardiometabolic risk. We investigated the effects of an isocaloric healthy Nordic diet on insulin sensitivity, lipid profile, blood pressure and inflammatory markers in people with metabolic syndrome.

UPLC-QTOF/MS metabolic profiling unveils urinary changes in humans after a whole grain rye versus refined wheat bread intervention.

SCOPEnNon-targeted urine metabolite profiling has not been previously exploited in the field of whole grain (WG) products. WG products, particularly rye, are important elements in a healthy Nordic diet. The aim of this study was to identify novel urinary biomarkers of WG rye bread (RB) intake in a randomised crossover study with RB versus refined wheat bread (WB).nnnMETHODS AND RESULTSnUPLC-QTOF/MS metabolite profiling was applied to urine from a 2 × 4 wk crossover intervention with RB versus WB in 20 subjects. Sixteen metabolites were revealed as major contributing biomarkers. The most discriminative metabolite after the cereal intervention was identified as 3-(3,5-dihydroxyphenyl)-1-propanoic acid sulphate, which was excreted to a higher extent after the RB versus WB intervention. Other alkylresorcinol metabolites were identified, as well as enterolactone glucuronide, azelaic acid, 2-aminophenol sulphate and its benzoxazinoid precursor 2,4-dihydroxy-1,4-benzoxazin-3-one. Our study also suggests that nitrogen-containing metabolites are other major markers. However, other methodologies will be needed to elucidate their final structure.nnnCONCLUSIONnThe present non-targeted metabolite profiling proved to be a useful approach to identify major urine metabolites discriminating RB intake from that of white wheat bread. Once validated these markers could help evaluate compliance to healthy Nordic diets.

UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: Effect of experimental artefacts and anticoagulant

Clotting and anticoagulation of blood samples may give rise to different metabolic profiles of serum and plasma samples, respectively. The anticoagulant used for blood plasma preparation may affect the resulting metabolic profile due to different mechanisms involved in anticoagulation by various agents, e.g. heparin, EDTA and citrate. In the present study, we looked into metabolite and other differences in matched serum and plasma samples and different plasma preparations by using untargeted UPLC-ESI-QTOF/MS profiling and multivariate data analysis (PCA and OPLS-DA). Metabolite differences between serum and plasma samples were mainly related to small peptides reflecting presence or absence of coagulation. Only subtle metabolite differences between the different plasma preparations were noticed, which were primarily related to ion suppression or enhancement caused by citrate and EDTA anticoagulants. For the first time, we also report that anticoagulant counter cation (Na+ or K+) in Na-citrate and K-EDTA plasma can make some metabolites more dominant in ESI-MS. Polymeric material residues originating from blood collection tubes for serum preparation were observed only in serum samples. Hypoxanthine and xanthine were found at higher levels in serum than in plasma samples, possibly due to release from the clot. Mass spectral features of sodium formate and potassium formate ion clusters were detected in citrate and EDTA plasma samples, respectively, originating from formate in mobile phase and Na(+) (in Na-citrate tubes) and K(+) (in K-EDTA tubes). Among the anticoagulants, heparin is recommended for plasma samples used for LC-ESI/MS-based metabolomics of hydrophilic compounds because no plasma interferences or matrix effects were noticed for this polarity range. Citrate and EDTA should be avoided since interferences and serious matrix effects were encountered on some co-eluting polar metabolites. Serum is recommended as a second choice and an alternative to plasma. In conclusion, heparin plasma or serum should be the order of best choice for LC-ESI/MS-based metabolomics research.

Metabolic fingerprinting of high-fat plasma samples processed by centrifugation- and filtration-based protein precipitation delineates significant differences in metabolite information coverage.

Metabolomics and metabolic fingerprinting are being extensively employed for improved understanding of biological changes induced by endogenous or exogenous factors. Blood serum or plasma samples are often employed for metabolomics studies. Plasma protein precipitation (PPP) is currently performed in most laboratories before LC-MS analysis. However, the impact of fat content in plasma samples on metabolite coverage has not previously been investigated. Here, we have studied whether PPP procedures influence coverage of plasma metabolites from high-fat plasma samples. An optimized UPLC-QTOF/MS metabolic fingerprinting approach and multivariate modeling (PCA and OPLS-DA) were utilized for finding characteristic metabolite changes induced by two PPP procedures; centrifugation and filtration. We used 12-h fasting samples and postprandial samples collected at 2h after a standardized high-fat protein-rich meal in obese non-diabetic subjects recruited in a dietary intervention. The two PPP procedures as well as external and internal standards (ISs) were used to track errors in response normalization and quantification. Remarkably and sometimes uniquely, the fPPP, but not the cPPP approach, recovered not only high molecular weight (HMW) lipophilic metabolites, but also small molecular weight (SMW) relatively polar metabolites. Characteristic SMW markers of postprandial samples were aromatic and branched-chain amino acids that were elevated (p<0.001) as a consequence of the protein challenge. In contrast, some HMW lipophilic species, e.g. acylcarnitines, were moderately lower (p<0.001) in postprandial samples. LysoPCs were largely unaffected. In conclusion, the fPPP procedure is recommended for processing high-fat plasma samples in metabolomics studies. While method improvements presented here were clear, use of several ISs revealed substantial challenges to untargeted metabolomics due to large and variable matrix effects.

LC-QTOF/MS metabolomic profiles in human plasma after a 5-week high dietary fiber intake.

The objective was to investigate the alterations of plasma metabolome profiles to identify exposure and effect markers of dietary fiber intake. Subjects (nu2009=u200925) aged 58.6 (1.1)u2009years (mean and SD) with a body mass index of 26.6 (0.5)u2009kg/m2 were given a high fiber (HF) and a low fiber (LF) diet, in a 5-week randomized controlled crossover intervention. The HF diet consisted of oat bran, rye bran, and sugar beet fiber incorporated into test food products, whereas the LF diet was made of equivalent food products to the HF diet, but without adding fibers. Blood plasma samples were collected at the start and end of each intervention period and analyzed by LC-QTOF/MS. In total, 6 features in positive mode and 14 features in negative mode were significantly different between the HF and the LF diet (pu2009<u20090.01, qu2009<u20090.05). Two markers, 2,6-dihydroxybenzoic acid and 2-aminophenol sulfate, were increased after HF diet, along with a tentatively identified saponin derived from oat avenacosides. The untargeted metabolomics approach enabled the identification of two new markers of dietary fiber intake in human plasma. Further studies will be needed to verify if these markers could serve as compliance markers of fiber intake.

Comparative Nontargeted Profiling of Metabolic Changes in Tissues and Biofluids in High-Fat Diet-Fed Ossabaw Pig

Typical clinical biomarker analyses on urine and plasma samples from human dietary interventions do not provide adequate information about diet-induced metabolic changes taking place in tissues. The aim of this study was to show how a large-scale nontargeted metabolomic approach can be used to reveal metabolite groups for generating new hypotheses of obesity-related metabolic disturbances produced in an animal model. A large spectrum of metabolites in the semipolar region, including small water-soluble molecules like betaine and dihydroxyindole, and a wide range of bile acids as well as various lipid species were detected. The high-fat diet influenced metabolic homeostasis of Ossabaw pigs, especially the lipid metabolome, throughout all the analyzed sample types, including plasma, urine, bile, liver, pancreas, brain cortex, intestinal jejunum and proximal colon. However, even dramatic metabolic changes in tissues were not necessarily observed in plasma and urine. Metabolite profiling involving multiple sample types was shown to be a feasible method for the examination of a wide spectrum of metabolic species extending from small water-soluble metabolites to an array of bile acids and lipids, thus pointing to the pathways of metabolism affected by the dietary treatment.

Discovery of exposure markers in urine for Brassica-containing meals served with different protein sources by UPLC-qTOF-MS untargeted metabolomics

An untargeted metabolomics approach has been applied to discover and identify exposure markers in urine for nine Nordic meals. A cross-over meal study was carried out in 17 subjects. The meals included a Pie, a Soup and a Barleyotto (pearl barley based risotto), each prepared with three protein sources; meat, fish or vegetarian. Urine samples were collected in different time intervals before and after intake of the test meals, covering a total of 24xa0h. The samples were analyzed by UPLC-qTOF-MS. Discriminating features for meals and protein sources were selected by use of double cross-validated partial least squares discriminant analysis and two additional validation steps: (1) time-course of excretion and (2) analysis of sensitivity and specificity. In addition, eight meal studies with single foods were carried out to investigate the food sources of the markers. In total 31 potential exposure markers (PEMs) of foods were found for the meals and protein sources. Fifteen of the 31 PEMs were also found in studies with single foods. Ten PEMs were identified or putatively annotated. Among the PEMs were a range of conjugated isothiocyanates from the Brassica oleracea species. Trimethylamine N-oxide was found as a fish marker. Additional unknown PEMs were found for chicory salad, parsley and fava beans, while other PEMs were dependent on the meal matrix rather than individual foods. The study demonstrates that it is possible to find PEMs in 24xa0h urine samples even when foods are given as part of a complex meal.

Effects of an onion by-product on bioactivity and safety markers in healthy rats

Onions are excellent sources of bioactive compounds including fructo-oligosaccharides (FOS) and polyphenols. An onion by-product was characterised in order to be developed as a potentially bioactive food ingredient. Our main aim was to investigate whether the potential health and safety effects of this onion by-product were shared by either of two derived fractions, an extract containing the onion FOS and polyphenols and a residue fraction containing mainly cell wall materials. We report here on the effects of feeding these products on markers of potential toxicity, protective enzymes and gut environment in healthy rats. Rats were fed during 4 weeks with a diet containing the products or a control feed balanced in carbohydrate. The onion by-product and the extract caused anaemia as expected in rodents for Allium products. No other toxicity was observed, including genotoxicity. Glutathione reductase (GR) and glutathione peroxidase (GPx1) activities in erythrocytes increased when rats were fed with the onion extract. Hepatic gene expression of Gr, Gpx1, catalase, 5-aminolevulinate synthase and NAD(P)H:quinone oxidoreductase was not altered in any group of the onion fed rats. By contrast, gamma-glutamate cysteine ligase catalytic subunit gene expression was upregulated but only in rats given the onion residue. The onion by-products as well as the soluble and insoluble fractions had prebiotic effects as evidenced by decreased pH, increased butyrate production and altered gut microbiota enzyme activities. In conclusion, the onion by-products have no in vivo genotoxicity, may support in vivo antioxidative defence and alter the functionality of the rat gut microbiota.

Patterns of time since last meal revealed by sparse PCA in an observational LC–MS based metabolomics study

In metabolomics studies, liquid chromatography mass spectrometry (LC–MS) provides comprehensive information on biological samples. However, extraction of few relevant metabolites from this large and complex data is cumbersome. To resolve this issue, we have employed sparse principal component analysis (SPCA) to capture the underlying patterns and select relevant metabolites from LC–MS plasma profiles. The study involves a small pilot cohort with 270 subjects where each subject’s time since last meal (TSLM) has been recorded prior to plasma sampling. Our results have demonstrated that both PCA and SPCA can capture the TSLM patterns. Nevertheless, SPCA provides more easily interpretable loadings in terms of selection of relevant metabolites, which are identified as amino acids and lyso-lipids. This study demonstrates the utility of SPCA as a pattern recognition and variable selection tool in metabolomics. Furthermore, amino acids and lyso-lipids are determined as dominating compounds in response to TSLM.