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Träfflista för sökning "WFRF:(Prenni Jessica E) srt2:(2016)"

Sökning: WFRF:(Prenni Jessica E) > (2016)

  • Resultat 1-4 av 4
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1.
  • Ganna, Andrea, et al. (författare)
  • Large-scale non-targeted metabolomic profiling in three human population-based studies
  • 2016
  • Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 12
  • Tidskriftsartikel (refereegranskat)abstract
    • Non-targeted metabolomic profiling is used to simultaneously assess a large part of the metabolome in a biological sample. Here, we describe both the analytical and computational methods used to analyze a large UPLC–Q-TOF MS-based metabolomic profiling effort using plasma and serum samples from participants in three Swedish population-based studies of middle-aged and older human subjects: TwinGene, ULSAM and PIVUS. At present, more than 200 metabolites have been manually annotated in more than 3600 participants using an in-house library of standards and publically available spectral databases. Data available at the metabolights repository include individual raw unprocessed data, processed data, basic demographic variables and spectra of annotated metabolites. Additional phenotypical and genetic data is available upon request to cohort steering committees. These studies represent a unique resource to explore and evaluate how metabolic variability across individuals affects human diseases.
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2.
  • Fall, Tove, 1979-, et al. (författare)
  • Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes
  • 2016
  • Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 59:10, s. 2114-2124
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims/hypothesisIdentification of novel biomarkers for type 2 diabetes and their genetic determinants could lead to improved understanding of causal pathways and improve risk prediction.MethodsIn this study, we used data from non-targeted metabolomics performed using liquid chromatography coupled with tandem mass spectrometry in three Swedish cohorts (Uppsala Longitudinal Study of Adult Men [ULSAM], n = 1138; Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS], n = 970; TwinGene, n = 1630). Metabolites associated with impaired fasting glucose (IFG) and/or prevalent type 2 diabetes were assessed for associations with incident type 2 diabetes in the three cohorts followed by replication attempts in the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort (n = 855). Assessment of the association of metabolite-regulating genetic variants with type 2 diabetes was done using data from a meta-analysis of genome-wide association studies.ResultsOut of 5961 investigated metabolic features, 1120 were associated with prevalent type 2 diabetes and IFG and 70 were annotated to metabolites and replicated in the three cohorts. Fifteen metabolites were associated with incident type 2 diabetes in the four cohorts combined (358 events) following adjustment for age, sex, BMI, waist circumference and fasting glucose. Novel findings included associations of higher values of the bile acid deoxycholic acid and monoacylglyceride 18:2 and lower concentrations of cortisol with type 2 diabetes risk. However, adding metabolites to an existing risk score improved model fit only marginally. A genetic variant within the CYP7A1 locus, encoding the rate-limiting enzyme in bile acid synthesis, was found to be associated with lower concentrations of deoxycholic acid, higher concentrations of LDL-cholesterol and lower type 2 diabetes risk. Variants in or near SGPP1, GCKR and FADS1/2 were associated with diabetes-associated phospholipids and type 2 diabetes.Conclusions/interpretationWe found evidence that the metabolism of bile acids and phospholipids shares some common genetic origin with type 2 diabetes.Access to research materialsMetabolomics data have been deposited in the Metabolights database, with accession numbers MTBLS93 (TwinGene), MTBLS124 (ULSAM) and MTBLS90 (PIVUS).
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3.
  • Nowak, Christoph, et al. (författare)
  • Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels : A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study
  • 2016
  • Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 12:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or beta-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining "gold standard" measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.
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4.
  • Salihovic, Samira, 1985-, et al. (författare)
  • The metabolic fingerprint of p,p'-DDE and HCB exposure in humans
  • 2016
  • Ingår i: Environment International. - Oxford, United Kingdom : Elsevier. - 0160-4120 .- 1873-6750. ; 88, s. 60-66
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Dichlorodiphenyldichloroethylene (p,p'-DDE) and hexachlorobenzene (HCB) are organochlorine pesticides with well-known endocrine disrupting properties. Exposure to p,p'-DDE and HCB concerns human populations worldwide and has been linked to metabolic disorders such as obesity and type 2 diabetes, but details about these associations in humans from the general population are largely unknown.Objectives: We investigated the associations between p,p'-DDE and HCB exposure and global metabolomic profiles in serum samples from 1016 participants from the Swedish population-based Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study.Methods: HCB and p,p'-DDE levels were determined using gas chromatography coupled to high-resolution mass spectrometry (GC-HRMS). Metabolite levels were determined by using a non-targeted metabolomics approach with ultra-performance liquid chromatography coupled to time-of- flight mass spectrometry (UPLC-TOFMS). Association analyses were performed using multivariate linear regression.Results: We found circulating levels of p,p-DDE and HCB to be significantly associated with circulating levels of 16 metabolites following adjustment for age, sex, education level, exercise habits, smoking, energy intake, and alcohol intake. The majority of the 16 metabolites belong to lipid metabolism pathways and include fatty acids, glycerophospholipids, sphingolipids, and glycerolipids. Overall, p,p'-DDE and HCB levels were found to be correlated to different metabolites, which suggests that different metabolic fingerprints may be related to circulating levels of these two pesticides.Conclusions: Our findings establish a link between human exposure to organochlorine pesticides and metabolites of key metabolic processes mainly related to human lipid metabolism.
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