| 1. |
- Andersson, Anneli, et al.
(author)
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Continuous and simultaneous determination of venous blood metabolites
- 2017
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In: Talanta. - : Elsevier BV. - 0039-9140. ; 171, s. 270-274
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Journal article (peer-reviewed)abstract
- Metabolic syndrome is associated with cardiovascular disease, type 2 diabetes mellitus (T2DM) and prediabetes. Metabolic syndrome is a cluster of interrelated clinical disorders. Difficulties in regulating glucose levels in blood are implicated in many of these disorders. Lactate, another energy metabolite, is produced under anaerobic conditions and can be used to monitor the balance between aerobic and anaerobic metabolism. Tested together, these metabolite levels can provide pro-diagnostic information that improves patient outcomes. Glucose and lactate were determined continuously and simultaneously in whole blood using a dual-channel thermal biosensor device in which one channel employed glucose oxidase for glucose analysis in comparison with lactate oxidase for lactate analysis in the others. No detectable clogging or interference was observed using venous blood samples. The linear detection range for both the glucose and lactate assays was 0.5–45 mM. The sampling rate of up to 24 samples per hour with assay cycle time of 2.5 min was achieved. Comparative analysis between our device and the HemoCue method showed an excellent correlation. The device was stable for hundreds of injections over a period of 45 days. The broad linear range, fast response and detection sensitivity are satisfactory for the clinical requirements, e.g. for diabetic or cardiovascular patients in intensive care units or surgical operation, where the tight control of blood glucose can decrease morbidity or mortality.
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| 2. |
- Mafessoni, Fabrizio, et al.
(author)
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Turning vice into virtue : Using Batch-Effects to Detect Errors in Large Genomic Datasets
- 2018
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In: Genome Biology and Evolution. - : Oxford University Press (OUP). - 1759-6653. ; 10:10, s. 2697-2708
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Journal article (peer-reviewed)abstract
- It is often unavoidable to combine data from different sequencing centers or sequencing platforms when compiling datasets with a large number of individuals. However, the different data are likely to contain specific systematic errors that will appear as SNPs. Here, we devise a method to detect systematic errors in combined datasetIs. To measure quality differences between individual genomes, we study pairs of variants that reside on different chromosomes and co-occur in individuals. The abundance of these pairs of variants in different genomes is then used to detect systematic errors due to batch effects. Applying our method to the 1000 Genomes dataset, we find that coding regions are enriched for errors, where about 1% of the higher-frequency variants are predicted to be erroneous, whereas errors outside of coding regions are much rarer (<0.001%).As expected, predicted errors are found less often than other variants in a dataset that was generated with a different sequencing technology, indicating that many of the candidates are indeed errors. However, predicted 1000 Genomes errors are also found in other large datasets; our observation is thus not specific to the 1000 Genomes dataset. Our results show that batch effects can be turned into a virtue by using the resulting variation in large scale datasets to detect systematic errors.
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| 3. |
- Quell, Jan D., et al.
(author)
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Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies
- 2017
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In: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences. - : Elsevier BV. - 1570-0232 .- 1873-376X. ; 1071, s. 58-67
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Journal article (peer-reviewed)abstract
- Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules.Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9-tetradecenoic acid, respectively.Our data-driven approach based on measured metabolite levels and genetic associations as well as information from public resources can be used alone or together with methods utilizing spectral patterns as a complementary, automated and powerful method to characterize unknown metabolites.
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| 4. |
- Ahlzén, Maja, et al.
(author)
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Expression of the transcription factor 7-like 2 gene (TCF7L2) in human adipocytes is down regulated by insulin.
- 2008
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In: Biochemical and Biophysical Research Communications. - : Elsevier BV. - 1090-2104 .- 0006-291X. ; 370, s. 49-52
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Journal article (peer-reviewed)abstract
- Variants in the TCF7L2 gene (transcription factor 7-like 2) have shown strong association with type 2 diabetes with two defined risk haplotypes, HapA and HapB(T2D). TCF7L2 may play a role in both glucose homeostasis and adipogenesis. Our aim was to characterize the TCF7L2 mRNA expression and regulation in human adipose tissue. We quantified TCF7L2 mRNA levels in cultured human adipocytes and in biopsies from visceral (VAT) and subcutaneous (SAT) adipose tissue from 38 obese non-diabetic subjects, using real-time PCR. The influence of haplotype and clinical traits on TCF7L2 mRNA levels were investigated. In vitro, insulin decreased TCF7L2 mRNA expression. This effect was attenuated in cells incubated with the free fatty acids palmitate or oleate. In vivo, we found significantly higher expression in SAT from more insulin resistant subjects. No correlations between TCF7L2 mRNA expression and obesity measures were observed. TCF7L2 expression was higher in VAT than in SAT and when stratifying for haplotype, this difference was seen in HapA carriers but not in non-HapA carriers. In conclusion, TCF7L2 mRNA levels in adipocytes are decreased by insulin and seem to increase in insulin resistant subjects and in HapA carriers.
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| 5. |
- Leu, Monica, et al.
(author)
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NordicDB : a Nordic pool and portal for genome-wide control data
- 2010
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In: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 18:12, s. 1322-1326
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Journal article (peer-reviewed)abstract
- A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from similar to 5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW-SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries. European Journal of Human Genetics (2010) 18, 1322-1326; doi: 10.1038/ejhg.2010.112; published online 28 July 2010
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| 6. |
- Omar, Bilal, et al.
(author)
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Regulation of the pro-inflammatory cytokine osteopontin by GIP in adipocytes - A role for the transcription factor NFAT and phosphodiesterase 3B.
- 2012
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In: Biochemical and Biophysical Research Communications. - : Elsevier BV. - 1090-2104 .- 0006-291X. ; 425:4, s. 812-817
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Journal article (peer-reviewed)abstract
- The incretin - glucose-dependent insulinotropic polypeptide (GIP) - and the pro-inflammatory cytokine osteopontin are known to have important roles in the regulation of adipose tissue functions. In this work we show that GIP stimulates lipogenesis and osteopontin expression in primary adipocytes. The GIP-induced increase in osteopontin expression was inhibited by the NFAT (the transcription factor nuclear factor of activated T-cells) inhibitor A285222. Also, the NFAT kinase glycogen synthase kinase (GSK) 3 was upregulated by GIP. To test whether cAMP might be involved in GIP mediated effects on osteopontin a number of strategies were used. Thus, the β3-adrenergic receptor aganist CL316,243 stimulated osteopontin expression, an effects which was mimicked by OPC3911, a specific inhibitor of phosphodiesterase 3. Furthermore, treatment of phosphodiesterase 3B knock-out mice with CL316,243 resulted in a dramatic upregulation of osteopontin in adipose tissue which was not the case in wild-type mice. In summary, we delineate mechanisms by which GIP stimulate osteopontin in adipocytes. Given the established link between osteopontin and insulin resistance, our data suggest that GIP by stimulating osteopontin expression, also could promote insulin resistance in adipocytes.
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| 7. |
- Ahlqvist, Emma, et al.
(author)
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Genetics of type 2 diabetes
- 2011
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In: Clinical Chemistry. - : Oxford University Press (OUP). - 0009-9147 .- 1530-8561. ; 57:2, s. 241-254
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Research review (peer-reviewed)abstract
- Background: Type 2 diabetes (T2D) is a complex disorder that is affected by multiple genetic and environmental factors. Extensive efforts have been made to identify the disease-affecting genes to better understand the disease pathogenesis, find new targets for clinical therapy, and allow prediction of disease.Content: Our knowledge about the genes involved in disease pathogenesis has increased substantially in recent years, thanks to genomewide association studies and international collaborations joining efforts to collect the huge numbers of individuals needed to study complex diseases on a population level. We have summarized what we have learned so far about the genes that affect T2D risk and their functions. Although more than 40 loci associated with T2D or glycemic traits have been reported and reproduced, only a minor part of the genetic component of the disease has been explained, and the causative variants and affected genes are unknown for many of the loci.Summary: Great advances have recently occurred in our understanding of the genetics of T2D, but much remains to be learned about the disease etiology. The genetics of T2D has so far been driven by technology, and we now hope that next-generation sequencing will provide important information on rare variants with stronger effects. Even when variants are known, however, great effort will be required to discover how they affect disease risk.
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| 8. |
- Asplund, Olof, et al.
(author)
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MuscleAtlasExplorer : a web service for studying gene expression in human skeletal muscle
- 2020
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In: Database: the journal of biological databases and curation. - : Oxford University Press (OUP). - 1758-0463. ; 2020
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Journal article (peer-reviewed)abstract
- MuscleAtlasExplorer is a freely available web application that allows for the exploration of gene expression data from human skeletal muscle. It draws from an extensive publicly available dataset of 1654 skeletal muscle expression microarray samples. Detailed, manually curated, patient phenotype data, with information such as age, sex, BMI and disease status, are combined with skeletal muscle gene expression to provide insights into gene function in skeletal muscle. It aims to facilitate easy exploration of the data using powerful data visualization functions, while allowing for sample selection, in-depth inspection and further analysis using external tools. Availability: MuscleAtlasExplorer is available at https://mae.crc.med.lu.se/mae2 (username 'muscle' and password 'explorer' pre-publication).
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| 9. |
- Bengtsson-Ellmark, S. H, 1900, et al.
(author)
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Association between a polymorphism in the carboxyl ester lipase gene and serum cholesterol profile
- 2004
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In: European journal of human genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 12:8, s. 627-632
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Journal article (peer-reviewed)abstract
- Carboxyl ester lipase (CEL) is involved in the hydrolysis and absorption of dietary lipids, but it is largely unknown to what extent CEL could be involved in determining the serum lipid levels. The C-terminal part of CEL consists of a unique structure with proline-rich O-glycosylated repeats of 11 amino-acid residues each. The common variant of the human CEL gene contains 16 proline-rich repeats, but there is a high degree of polymorphism in the repeated region. While the biological function of the polymorphic repeat region is unknown, it has been suggested that it may be important for protein stability and/or secretion of the enzyme. Given that the polymorphism in the repeated region may affect the functionality of the protein, this study aimed to investigate whether the number of repeated units is correlated to serum lipid phenotype. Comparison of CEL repeat genotype and serum lipid phenotype revealed an association between the number of repeats and serum cholesterol profile. Individuals carrying at least one allele with fewer than the common 16 repeats had significantly lower total and low-density lipoprotein (LDL) cholesterol levels compared to individuals carrying two common alleles. This gives support to the notion that CEL may be involved in determining the plasma lipid composition.
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| 10. |
- Berndt, Sonja I., et al.
(author)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Journal article (peer-reviewed)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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