| 1. |
- 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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| 2. |
- Brandmaier, Stefan, et al.
(författare)
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An evaluation of experimental design in QSAR modelling utilizing the k-medoid clustering
- 2012
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Ingår i: Journal of Chemometrics. - : Wiley. - 0886-9383 .- 1099-128X. ; 26:10, s. 509-517
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Tidskriftsartikel (refereegranskat)abstract
- A reliable selection of a representative subset of chemical compounds has been reported to be crucial for numeroustasks in computational chemistry and chemoinformatics. We investigated the usability of an approach on the basisof the k-medoid algorithm for this task and in particular for experimental design and the split between training andvalidation set. We therefore compared the performance of models derived from such a selection to that of modelsderived using several other approaches, such as space-filling design and D-optimal design. We validated the performance on four datasets with different endpoints, representing toxicity, physicochemical properties and others.Compared with the models derived from the compounds selected by the other examined approaches, those derivedwith the k-medoid selection show a high reliability for experimental design, as their performance was constantlyamong the best for all examined datasets. Of all the models derived with all examined approaches, those derivedwith the k-medoid approach were the only ones that showed a significantly improved performance compared witha random selection, for all datasets, the whole examined range of selected compounds and for each dimensionalityof the search space.
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| 3. |
- Brandmaier, Stefan, et al.
(författare)
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PLS-Optimal: A stepwise D-Optimal design based on latent variables
- 2012
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 52:4, s. 975-983
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Tidskriftsartikel (refereegranskat)abstract
- Several applications, such as risk assessment within REACH or drug discovery, require reliable methods for the design of experiments and efficient testing strategies. Keeping the number of experiments as low as possible is important from both a financial and an ethical point of view, as exhaustive testing of compounds requires significant financial resources and animal lives. With a large initial set of compounds, experimental design techniques can be used to select a representative subset for testing. Once measured, these compounds can be used to develop quantitative structure–activity relationship models to predict properties of the remaining compounds. This reduces the required resources and time. D-Optimal design is frequently used to select an optimal set of compounds by analyzing data variance. We developed a new sequential approach to apply a D-Optimal design to latent variables derived from a partial least squares (PLS) model instead of principal components. The stepwise procedure selects a new set of molecules to be measured after each previous measurement cycle. We show that application of the D-Optimal selection generates models with a significantly improved performance on four different data sets with end points relevant for REACH. Compared to those derived from principal components, PLS models derived from the selection on latent variables had a lower root-mean-square error and a higher Q2 and R2. This improvement is statistically significant, especially for the small number of compounds selected.
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| 4. |
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| 5. |
- Brandmaier, Stefan, et al.
(författare)
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The QSPR-THESAURUS : The Online Platform of the CADASTER Project
- 2014
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Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 42:1, s. 13-24
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Tidskriftsartikel (refereegranskat)abstract
- The aim of the CADASTER project (CAse Studies on the Development and Application of in Silico Techniques for Environmental Hazard and Risk Assessment) was to exemplify REACH-related hazard assessments for four classes of chemical compound, namely, polybrominated diphenylethers, per and polyfluorinated compounds, (benzo)triazoles, and musks and fragrances. The QSPR-THESAURUS website (http: / /qspr-thesaurus.eu) was established as the project's online platform to upload, store, apply, and also create, models within the project. We overview the main features of the website, such as model upload, experimental design and hazard assessment to support risk assessment, and integration with other web tools, all of which are essential parts of the QSPR-THESAURUS.
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| 6. |
- Cassani, Stefano, et al.
(författare)
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Evaluation of CADASTER QSAR Models for the Aquatic Toxicity of (Benzo)triazoles and Prioritisation by Consensus Prediction
- 2013
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Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929. ; 41:1, s. 49-64
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Tidskriftsartikel (refereegranskat)abstract
- QSAR regression models of the toxicity of triazoles and benzotriazoles ([B] TAZs) to an alga (Pseudokirchneriella subcapitata), Daphnia magna and a fish (Onchorhynchus mykiss), were developed by five partners in the FP7-EU Project, CADASTER. The models were developed by different methods - Ordinary Least Squares (OLS), Partial Least Squares (PLS), Bayesian regularised regression and Associative Neural Network (ASNN) - by using various molecular descriptors (DRAGON, PaDEL-Descriptor and QSPR-THESAURUS web). In addition, different procedures were used for variable selection, validation and applicability domain inspection. The predictions of the models developed, as well as those obtained in a consensus approach by averaging the data predicted from each model, were compared with the results of experimental tests that were performed by two CADASTER partners. The individual and consensus models were able to correctly predict the toxicity classes of the chemicals tested in the CADASTER project, confirming the utility of the QSAR approach. The models were also used for the prediction of aquatic toxicity of over 300 (B)TAZs, many of which are included in the REACH pre-registration list, and were without experimental data. This highlights the importance of QSAR models for the screening and prioritisation of untested chemicals, in order to reduce and focus experimental testing.
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| 7. |
- 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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