| 1. |
- Broeckling, Corey D., et al.
(författare)
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Assigning precursor-product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies
- 2013
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Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 9:1, s. 33-43
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Fall, Tove, 1979-, et al.
(författare)
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Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes
- 2016
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 59:10, s. 2114-2124
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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. |
- Ganna, Andrea, et al.
(författare)
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Large-scale Metabolomic Profiling Identifies Novel Biomarkers for Incident Coronary Heart Disease
- 2014
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 10:12, s. e1004801-
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Tidskriftsartikel (refereegranskat)abstract
- Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease (CHD). We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1,028 individuals (131 events; 10 y. median follow-up) with validation in 1,670 individuals (282 events; 3.9 y. median follow-up). Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18∶1 (hazard ratio [HR] per standard deviation [SD] increment = 0.77, P-value<0.001), lysophosphatidylcholine 18∶2 (HR = 0.81, P-value<0.001), monoglyceride 18∶2 (MG 18∶2; HR = 1.18, P-value = 0.011) and sphingomyelin 28∶1 (HR = 0.85, P-value = 0.015)]. Together they contributed to moderate improvements in discrimination and re-classification in addition to traditional risk factors (C-statistic: 0.76 vs. 0.75; NRI: 9.2%). MG 18∶2 was associated with CHD independently of triglycerides. Lysophosphatidylcholines were negatively associated with body mass index, C-reactive protein and with less evidence of subclinical cardiovascular disease in additional 970 participants; a reverse pattern was observed for MG 18∶2. MG 18∶2 showed an enrichment (P-value = 0.002) of significant associations with CHD-associated SNPs (P-value = 1.2×10-7 for association with rs964184 in the ZNF259/APOA5 region) and a weak, but positive causal effect (odds ratio = 1.05 per SD increment in MG 18∶2, P-value = 0.05) on CHD, as suggested by Mendelian randomization analysis. In conclusion, we identified four lipid-related metabolites with evidence for clinical utility, as well as a causal role in CHD development.
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| 4. |
- Ganna, Andrea, et al.
(författare)
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Large-scale non-targeted metabolomic profiling in three human population-based studies
- 2016
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Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 12
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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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| 5. |
- Hong, Mun-Gwan, et al.
(författare)
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A genome-wide assessment of variability in human serum metabolism
- 2013
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 34:3, s. 515-524
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 6. |
- Kumar, Jitender, et al.
(författare)
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Associations of Body Mass Index and Obesity-Related Genetic Variants with Serum Metabolites
- 2014
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Ingår i: Current Metabolomics. - 2213-235X. ; 2:1, s. 27-36-
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Tidskriftsartikel (refereegranskat)abstract
- 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<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<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
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| 7. |
- Kumar, Jitender, et al.
(författare)
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Influence of Biological and Technical Covariates on Non-targeted Metabolite Profiling in a Large-scale Epidemiological Study
- 2013
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Ingår i: Current Metabolomics. - 2213-235X. ; 1:3, s. 220-226-
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Tidskriftsartikel (refereegranskat)abstract
- 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
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| 8. |
- Lind, Lars, et al.
(författare)
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A Multi-Cohort Metabolomics Analysis Discloses Sphingomyelin (32:1) Levels to be Inversely Related to Incident Ischemic Stroke
- 2020
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Ingår i: Journal of Stroke & Cerebrovascular Diseases. - : Elsevier BV. - 1052-3057 .- 1532-8511. ; 29:2
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose:To search for novel pathophysiological pathways related to ischemic stroke using a metabolomics approach.Methods: We identified 204 metabolites in plasma by liquid chromatography mass spectrometry in 3 independent population-based samples (TwinGene, Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) and Uppsala Longitudinal Study of Adult Men). TwinGene was used for discovery and the other 2 samples were meta-analyzed as replication. In PIVUS, traditional cardiovascular (CV) risk factors, multiple markers of subclinical CV disease, markers of coagulation/fibrinolysis were measured and analyzed in relation to top metabolites.Results:In TwinGene (177 incident cases, median follow-up 4.3 years), levels of 28 metabolites were associated with incident ischemic stroke at a false discover rate (FDR) of 5%. In the replication (together 194 incident cases, follow-up 10 and 12 years, respectively), only sphingomyelin (32:1) was significantly associated (HR.69 per SD change, 95% CI.57-0.83, P value = .00014; FDR <5%) when adjusted for systolic blood pressure, diabetes, smoking, low density lipoportein (LDL)- and high density lipoprotein (HDL), body mass index (BMI) and atrial fibrillation. In PIVUS, sphingomyelin (32:1) levels were significantly related to both LDL- and HDL-cholesterol in a positive fashion, and to serum triglycerides, BMI and diabetes in a negative fashion. Furthermore, sphingomyelin (32:1) levels were related to vasodilation in the forearm resistance vessels, and inversely to leukocyte count (P < .0069 and .0026, respectively).Conclusions:An inverse relationship between sphingomyelin (32:1) and incident ischemic stroke was identified, replicated, and characterized. A possible protective role for sphingomyelins in stroke development has to be further investigated in additional experimental and clinical studies.
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| 9. |
- Lind, Lars, et al.
(författare)
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Multicohort Metabolomics Analysis Discloses 9-Decenoylcarnitine to Be Associated With Incident Atrial Fibrillation
- 2021
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Ingår i: Journal of the American Heart Association. - : Wiley-Blackwell Publishing Inc.. - 2047-9980 .- 2047-9980. ; 10:2
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Tidskriftsartikel (refereegranskat)abstract
- Background: The molecular mechanisms involved in atrial fibrillation are not well known. We used plasma metabolomics to investigate if we could identify novel biomarkers and pathophysiological pathways of incident atrial fibrillation.Methods and Results: We identified 200 endogenous metabolites in plasma/serum by nontargeted ultra‐performance liquid chromatography coupled to time‐of‐flight mass spectrometry in 3 independent population‐based samples (TwinGene, n=1935, mean age 68, 43% females; PIVUS [Prospective Investigation of the Vasculature in Uppsala Seniors], n=897, mean age 70, 51% females; and ULSAM [Uppsala Longitudinal Study of Adult Men], n=1118, mean age 71, all males), with available data on incident atrial fibrillation during 10 to 12 years of follow‐up. A meta‐analysis of ULSAM and PIVUS was used as a discovery sample and TwinGene was used for validation. In PIVUS, we also investigated associations between metabolites of interest and echocardiographic indices of myocardial geometry and function. Genome‐wide association studies were performed in all 3 cohorts for metabolites of interest. In the meta‐analysis of PIVUS and ULSAM with 430 incident cases, 4 metabolites were associated with incident atrial fibrillation at a false discovery rate <5%. Of those, only 9‐decenoylcarnitine was associated with incident atrial fibrillation and replicated in the TwinGene sample (288 cases) following adjustment for traditional risk factors (hazard ratio, 1.24 per unit; 95% CI, 1.06–1.45, P=0.0061). A meta‐analysis of all 3 cohorts disclosed another 4 significant metabolites. In PIVUS, 9‐decenoylcarnitine was related to left atrium size and left ventricular mass. A Mendelian randomization analysis did not suggest a causal role of 9‐decenoylcarnitine in atrial fibrillation.Conclusions: A nontargeted metabolomics analysis disclosed 1 novel replicated biomarker for atrial fibrillation, 9‐Decenoylcarnitine, but this acetylcarnitine is likely not causally related to atrial fibrillation.
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| 10. |
- Nowak, Christoph, et al.
(författare)
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Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels : A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study
- 2016
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 12:10
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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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