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Sökning: WFRF:(Prenni Jessica E)

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1.
  • Hong, Mun-Gwan, et al. (författare)
  • A genome-wide assessment of variability in human serum metabolism
  • 2013
  • Ingår i: Human Mutation. - 1059-7794 .- 1098-1004. ; 34:3, s. 515-524
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10(-13) -10(-91)). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.</p>
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2.
  • Broeckling, Corey D., et al. (författare)
  • Assigning precursor-product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies
  • 2013
  • Ingår i: Metabolomics. - 1573-3882 .- 1573-3890. ; 9:1, s. 33-43
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Tandem mass spectrometry using precursor ion selection (MS/MS) is an invaluable tool for structural elucidation of small molecules. In non-targeted metabolite profiling studies, instrument duty cycle limitations and experimental costs have driven efforts towards alternate approaches. Recently, researchers have begun to explore methods for collecting indiscriminant MS/MS (idMS/MS) data in which the fragmentation process does not involve precursor ion isolation. While this approach has many advantages, importantly speed, sensitivity and coverage, confident assignment of precursor-product ion relationships is challenging, which has inhibited broad adoption of the technique. Here, we present an approach that uses open source software to improve the assignment of precursor-product relationships in idMS/MS data by appending a dataset-wide correlational analysis to existing tools. The utility of the approach was demonstrated using a dataset of standard compounds spiked into a malt-barley background, as well as unspiked human serum. The workflow was able to recreate idMS/MS spectra which are highly similar to standard MS/MS spectra of authentic standards, even in the presence of a complex matrix background. The application of this approach has the potential to generate high quality idMS/MS spectra for each detectable molecular feature, which will streamline the identification process for non-targeted metabolite profiling studies.</p>
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3.
  • Kumar, Jitender, et al. (författare)
  • Associations of Body Mass Index and Obesity-Related Genetic Variants with Serum Metabolites
  • 2014
  • Ingår i: Current Metabolomics. - 2213-235X. ; 2:1, s. 27-36
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Objectives: Body mass index (BMI) is one of the most important risk factors for different metabolic and cardiovascular disorders. Previously, both genetic and environmental agents associated with BMI have been described. The main focus of this exploratory study was to find the circulating metabolites associated with BMI utilizing an untargeted metabolomics approach. Additionally, significant metabolites identified were studied for their relation with BMIassociated single nucleotide polymorphisms (SNPs). Materials and Methods: A total of 971 individuals from the Cancer of the Prostate in Sweden study (discovery sample- 275 prostate cancers patients and 182 controls; replication sample- 514 prostate cancer patients) were utilized. Blood samples were collected and serum metabolic profiling was obtained using ultra-performance liquid chromatography followed by mass spectrometry. Genotyping data was available for 26 out of 32 SNPs (21 genotyped and 5 proxies) previously robustly associated with BMI in individuals of European descent. Weighted genetic risk score was generated using these SNPs and studied for its association with metabolites. Results: A total of 6138 and 5209 metabolite features were detected in discovery and replication samples, respectively. Out of 6138 metabolite features in discovery sample, 201 were found to be significantly associated with BMI (p&lt;8.15*10-6) after multiple testing correction. These 201 features were further investigated in the replication samples and 16 were found to be significantly associated with BMI (p&lt;2.49*10-4). Seven of these significant features were isotopes for four of the primary metabolites. Four metabolites were putatively identified: monoacylglyceride (18:1), diacylglyrcerol (32:1) and two phosphatidylcholines (34:0 and 36:0). Weighted genetic score of BMI-associated SNPs was not associated with these four metabolites. Conclusion: Four identifiable metabolites (monoacylglyceride, diacyclglyrcerol and two phosphatidylcholines) were found to be significantly associated with BMI in both discovery and replication samples. Common variants associated with BMI did not show association with these four metabolites. - See more at: http://www.eurekaselect.com/120422/article#sthash.PgqffHqv.dpuf</p>
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4.
  • Kumar, Jitender, et al. (författare)
  • Influence of Biological and Technical Covariates on Non-targeted Metabolite Profiling in a Large-scale Epidemiological Study
  • 2013
  • Ingår i: Current Metabolomics. - 2213-235X. ; 1:3, s. 220-226
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Non-targeted metabolite profiling using ultra performance liquid chromatography-mass spectrometry (UPLCMS) was performed as part of a large-scale epidemiological study involving biobanked serum samples. The influence of both biological (age and body mass index) and technical (season of sample collection, fasting time, handling time, and storage time) covariates on the analysis was assessed. Statistical models including different sets of these covariates were compared and the results illustrate that variation in which covariates were included did not have an appreciable effect on the number or composition of biologically significant metabolite features associated with body mass index or age. Furthermore, when all covariates were included in the model, there was little overlap of metabolite features significantly associated with the different covariates. Thus, the results of this study illustrate that while some of the observed quantitative variance of metabolite features can be explained by biological and technical covariates, the use of non-targeted metabolite profiling of serum by UPLC-MS is valid for studies of biological outcomes in biobanked clinical samples from large-scale studies. - See more at: http://www.eurekaselect.com/115259/article#sthash.BOvtwWe7.dpuf</p>
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5.
  • 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. - 1553-7390 .- 1553-7404. ; 12:10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>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 β-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.</p>
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6.
  • Nowak, Christoph, et al. (författare)
  • Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance
  • 2018
  • Ingår i: Scientific Reports. - 2045-2322 .- 2045-2322. ; 8:1
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Insulin resistance (IR) predisposes to type 2 diabetes and cardiovascular disease but its causes are incompletely understood. Metabolic challenges like the oral glucose tolerance test (OGTT) can reveal pathogenic mechanisms. We aimed to discover associations of IR with metabolite trajectories during OGTT. In 470 non-diabetic men (age 70.6 ± 0.6 years), plasma samples obtained at 0, 30 and 120 minutes during an OGTT were analyzed by untargeted liquid chromatography-mass spectrometry metabolomics. IR was assessed with the hyperinsulinemic-euglycemic clamp method. We applied age-adjusted linear regression to identify metabolites whose concentration change was related to IR. Nine trajectories, including monounsaturated fatty acids, lysophosphatidylethanolamines and a bile acid, were significantly associated with IR, with the strongest associations observed for medium-chain acylcarnitines C10 and C12, and no associations with L-carnitine or C2-, C8-, C14- or C16-carnitine. Concentrations of C10- and C12-carnitine decreased during OGTT with a blunted decline in participants with worse insulin resistance. Associations persisted after adjustment for obesity, fasting insulin and fasting glucose. In mouse 3T3-L1 adipocytes exposed to different acylcarnitines, we observed blunted insulin-stimulated glucose uptake after treatment with C10- or C12-carnitine. In conclusion, our results identify medium-chain acylcarnitines as possible contributors to IR.</p>
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7.
  • Salihovic, Samira, et al. (författare)
  • Identification of metabolic profiles associated with human exposure to perfluoroalkyl substances.
  • 2019
  • Ingår i: Journal of Exposure Science and Environmental Epidemiology. - 1559-0631 .- 1559-064X. ; 29:2, s. 196-205
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Recent epidemiological studies suggest that human exposure to perfluoroalkyl substances (PFASs) may be associated with type 2 diabetes and other metabolic phenotypes. To gain further insights regarding PFASs exposure in humans, we here aimed to characterize the associations between different PFASs and the metabolome. In this cross-sectional study, we investigated 965 individuals from Sweden (all aged 70 years, 50% women) sampled in 2001-2004. PFASs were analyzed in plasma using isotope-dilution ultra-pressure liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS). Non-target metabolomics profiling was performed in plasma using UPLC coupled to time-of-flight mass spectrometry (UPLC-QTOFMS) operated in positive electrospray mode. Multivariate linear regression analysis was used to investigate associations between circulating levels of PFASs and metabolites. In total, 15 metabolites, predominantly from lipid pathways, were associated with levels of PFASs following adjustment for sex, smoking, exercise habits, education, energy, and alcohol intake, after correction for multiple testing. Perfluorononanoic acid (PFNA) and perfluoroundecanoic acid (PFUnDA) were strongly associated with multiple glycerophosphocholines and fatty acids including docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA). We also found that the different PFASs evaluated were associated with distinctive metabolic profiles, suggesting potentially different biochemical pathways in humans.</p>
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8.
  • Salihovic, Samira, et al. (författare)
  • The metabolic fingerprint of p,p'-DDE and HCB exposure in humans
  • 2016
  • Ingår i: Environment International. - 0160-4120 .- 1873-6750. ; 88, s. 60-66
  • Tidskriftsartikel (refereegranskat)abstract
    • <p><strong>BACKGROUND:</strong> 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.</p><p><strong>OBJECTIVES:</strong> 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.</p><p><strong>METHODS:</strong> 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.</p><p><strong>RESULTS:</strong> 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.</p><p><strong>CONCLUSIONS:</strong> Our findings establish a link between human exposure to organochlorine pesticides and metabolites of key metabolic processes mainly related to human lipid metabolism.</p>
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9.
  • 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
    • <p><strong>Background</strong>: 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.</p><p><strong>Objectives</strong>: 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.</p><p><strong>Methods</strong>: 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.</p><p><strong>Results</strong>: 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.</p><p><strong>Conclusions</strong>: Our findings establish a link between human exposure to organochlorine pesticides and metabolites of key metabolic processes mainly related to human lipid metabolism.</p>
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10.
  • Stenemo, Markus, et al. (författare)
  • The metabolites urobilin and sphingomyelin (30:1) are associated with incident heart failure in the general population
  • 2019
  • Ingår i: ESC Heart Failure. - 2055-5822. ; 6:4, s. 764-773
  • Tidskriftsartikel (refereegranskat)abstract
    • <p><strong>AIMS:</strong> We aimed to investigate whether metabolomic profiling of blood can lead to novel insights into heart failure pathogenesis or improved risk prediction.</p><p><strong>METHODS AND RESULTS:</strong> Mass spectrometry-based metabolomic profiling was performed in plasma or serum samples from three community-based cohorts without heart failure at baseline (total n = 3924; 341 incident heart failure events; median follow-up ranging from 4.6 to 13.9 years). Cox proportional hazard models were applied to assess the association of each of the 206 identified metabolites with incident heart failure in the discovery cohorts Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) (n = 920) and Uppsala Longitudinal Study of Adult Men (ULSAM) (n = 1121). Replication was undertaken in the independent cohort TwinGene (n = 1797). We also assessed whether metabolites could improve the prediction of heart failure beyond established risk factors (age, sex, body mass index, low-density and high-density lipoprotein cholesterol, triglycerides, lipid medication, diabetes, systolic and diastolic blood pressure, blood pressure medication, glomerular filtration rate, smoking status, and myocardial infarction prior to or during follow-up). Higher circulating urobilin and lower sphingomyelin (30:1) were associated with incident heart failure in age-adjusted and sex-adjusted models in the discovery and replication sample. The hazard ratio for urobilin in the replication cohort was estimated to 1.29 per standard deviation unit, 95% confidence interval (CI 1.03-1.63), and for sphingomyelin (30:1) to 0.72 (95% CI 0.58-0.89). Results remained similar after further adjustment for established heart failure risk factors in meta-analyses of all three cohorts. Urobilin concentrations were inversely associated with left ventricular ejection fraction at baseline in the PIVUS cohort (β = -0.70, 95% CI -1.03 to -0.38). No major improvement in risk prediction was observed when adding the top 2 metabolites (C-index 0.787, 95% CI 0.752-0.823) or nine Lasso-selected metabolites (0.790, 95% CI 0.754-0.826) to a modified Atherosclerosis Risk in Communities heart failure risk score model (0.780, 95% CI 0.745-0.816).</p><p><strong>CONCLUSIONS:</strong> Our metabolomic profiling of three community-based cohorts study identified associations of circulating levels of the haem breakdown product urobilin, and sphingomyelin (30:1), a cell membrane component involved in signal transduction and apoptosis, with incident heart failure.</p>
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