Now showing items 21-40 of 95

    • Opening Pandora's box in the UK: a hypothetical pharmacogenetic test for clozapine.

      Spencer, Benjamin W J; Prainsack, Barbara; Rujescu, Dan; Giegling, Ina; Collier, David A; Gaughran, Fiona; MacCabe, James H; Barr, Cathy L; Sigurdsson, Engilbert; Stovring, Henrik; et al. (FUTURE MEDICINE LTD, 2013-11)
      Clozapine is a uniquely efficacious antipsychotic drug in treatment-resistant schizophrenia. Its use is restricted due to adverse effects including a rare but dangerous reduction in neutrophils (agranulocytosis) and the mandatory hematological monitoring this entails in many countries. We review the statistical, ethical and legal issues arising from a hypothetical pharmacogenetic test for clozapine, using the UK as an exemplary case for consideration. Our key findings include: a consideration of the probabilistic results that a pharmacogenetic test may return; the impact on drug licensing; and the potential for pharmacogenetic tests for clozapine being used without consent under the UK's legal framework. We make recommendations regarding regulatory changes applicable to the special case of pharmacogenetic testing in clozapine treatment.
    • Kinetic analysis of gluconate phosphorylation by human gluconokinase using isothermal titration calorimetry.

      Rohatgi, Neha; Guðmundsson, Steinn; Rolfsson, Óttar; Univ Iceland, Ctr Syst Biol, IS-101 Reykjavik, Iceland, Univ Iceland, Biomed Ctr, IS-101 Reykjavik, Iceland (Elsevier Science BV, 2015-11-30)
      Gluconate is a commonly encountered nutrient, which is degraded by the enzyme gluconokinase to generate 6-phosphogluconate. Here we used isothermal titration calorimetry to study the properties of this reaction. ΔH, KM and kcat are reported along with substrate binding data. We propose that the reaction follows a ternary complex mechanism, with ATP binding first. The reaction is inhibited by gluconate, as it binds to an Enzyme-ADP complex forming a dead-end complex. The study exemplifies that ITC can be used to determine mechanisms of enzyme catalyzed reactions, for which it is currently not commonly applied.
    • Decoding the jargon of bottom-up metabolic systems biology.

      Rolfsson, Óttar; Palsson, Bernhard O; Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland, Univ Iceland, Biomed Ctr, Reykjavik, Iceland (Wiley-Blackwell, 2015-06)
    • Ion mobility derived collision cross sections to support metabolomics applications.

      Paglia, Giuseppe; Williams, Jonathan P; Menikarachchi, Lochana; Thompson, J Will; Tyldesley-Worster, Richard; Halldórsson, Skarphédinn; Rolfsson, Ottar; Moseley, Arthur; Grant, David; Langridge, James; et al. (Amer Chemical Soc, 2014-04-15)
      Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC-TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches.
    • Biochemical characterization of human gluconokinase and the proposed metabolic impact of gluconic acid as determined by constraint based metabolic network analysis.

      Rohatgi, Neha; Nielsen, Tine Kragh; Bjørn, Sara Petersen; Axelsson, Ivar; Paglia, Giuseppe; Voldborg, Bjørn Gunnar; Palsson, Bernhard O; Rolfsson, Óttar; Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland, Univ Iceland, Biomed Ctr, Reykjavik, Iceland, Univ Copenhagen, Fac Hlth Sci, Ctr Prot Res, Copenhagen, Denmark (Public Library Science, 2014)
      The metabolism of gluconate is well characterized in prokaryotes where it is known to be degraded following phosphorylation by gluconokinase. Less is known of gluconate metabolism in humans. Human gluconokinase activity was recently identified proposing questions about the metabolic role of gluconate in humans. Here we report the recombinant expression, purification and biochemical characterization of isoform I of human gluconokinase alongside substrate specificity and kinetic assays of the enzyme catalyzed reaction. The enzyme, shown to be a dimer, had ATP dependent phosphorylation activity and strict specificity towards gluconate out of 122 substrates tested. In order to evaluate the metabolic impact of gluconate in humans we modeled gluconate metabolism using steady state metabolic network analysis. The results indicate that significant metabolic flux changes in anabolic pathways linked to the hexose monophosphate shunt (HMS) are induced through a small increase in gluconate concentration. We argue that the enzyme takes part in a context specific carbon flux route into the HMS that, in humans, remains incompletely explored. Apart from the biochemical description of human gluconokinase, the results highlight that little is known of the mechanism of gluconate metabolism in humans despite its widespread use in medicine and consumer products.
    • Ion mobility-derived collision cross section as an additional measure for lipid fingerprinting and identification.

      Paglia, Giuseppe; Angel, Peggi; Williams, Jonathan P; Richardson, Keith; Olivos, Hernando J; Thompson, J Will; Menikarachchi, Lochana; Lai, Steven; Walsh, Callee; Moseley, Arthur; et al. (Amer Chemical Soc, 2015-01-20)
      Despite recent advances in analytical and computational chemistry, lipid identification remains a significant challenge in lipidomics. Ion-mobility spectrometry provides an accurate measure of the molecules' rotationally averaged collision cross-section (CCS) in the gas phase and is thus related to ionic shape. Here, we investigate the use of CCS as a highly specific molecular descriptor for identifying lipids in biological samples. Using traveling wave ion mobility mass spectrometry (MS), we measured the CCS values of over 200 lipids within multiple chemical classes. CCS values derived from ion mobility were not affected by instrument settings or chromatographic conditions, and they were highly reproducible on instruments located in independent laboratories (interlaboratory RSD < 3% for 98% of molecules). CCS values were used as additional molecular descriptors to identify brain lipids using a variety of traditional lipidomic approaches. The addition of CCS improved the reproducibility of analysis in a liquid chromatography-MS workflow and maximized the separation of isobaric species and the signal-to-noise ratio in direct-MS analyses (e.g., "shotgun" lipidomics and MS imaging). These results indicate that adding CCS to databases and lipidomics workflows increases the specificity and selectivity of analysis, thus improving the confidence in lipid identification compared to traditional analytical approaches. The CCS/accurate-mass database described here is made publicly available.
    • Monitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS).

      Paglia, Giuseppe; Hrafnsdóttir, Sigrún; Magnúsdóttir, Manuela; Fleming, Ronan M T; Thorlacius, Steinunn; Palsson, Bernhard Ø; Thiele, Ines; Univ Iceland, Ctr Syst Biol, Fac Ind Engn Mech Engn & Comp Sci, IS-101 Reykjavik, Iceland (Springer Heidelberg, 2012-01)
      Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by testing 86 metabolites, including amino acids, organic acids, sugars, purines, pyrimidines, vitamins, and nucleosides, that can be resolved by combining chromatographic and m/z dimensions. Subsequently, a targeted quantitative method was developed for 80 metabolites. The presented method combines a UPLC approach using hydrophilic interaction liquid chromatography (HILIC) and MS detection achieved by a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer. The optimal setup was achieved by evaluating reproducibility and repeatability of the analytical platforms using pooled quality control samples to minimize the drift in instrumental performance over time. Then, the method was validated by analyzing extracellular metabolites from acute lymphoblastic leukemia cell lines (MOLT-4 and CCRF-CEM) treated with direct (A-769662) and indirect (AICAR) AMP activated kinase (AMPK) activators, monitoring uptake and secretion of the targeted compound over time. This analysis pointed towards a perturbed purine and pyrimidine catabolism upon AICAR treatment. Our data suggest that the method presented can be used for qualitative and quantitative analysis of extracellular metabolites and it is suitable for routine applications such as in vitro drug screening.
    • Quantitative assignment of reaction directionality in a multicompartmental human metabolic reconstruction.

      Haraldsdóttir, H S; Thiele, I; Fleming, R M T; Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland, Univ Iceland, Fac Med, Reykjavik, Iceland, Univ Iceland, Fac Ind Engn Mech Engn & Comp Sci, Reykjavik, Iceland (Cell Press, 2012-04-18)
      Reaction directionality is a key constraint in the modeling of genome-scale metabolic networks. We thermodynamically constrained reaction directionality in a multicompartmental genome-scale model of human metabolism, Recon 1, by calculating, in vivo, standard transformed reaction Gibbs energy as a function of compartment-specific pH, electrical potential, and ionic strength. We show that compartmental pH is an important determinant of thermodynamically determined reaction directionality. The effects of pH on transport reaction thermodynamics are only seen to their full extent when metabolites are represented as pseudoisomer groups of multiple protonated species. We accurately predict the irreversibility of 387 reactions, with detailed propagation of uncertainty in input data, and manually curate the literature to resolve conflicting directionality assignments. In at least half of all cases, a prediction of a reversible reaction directionality is due to the paucity of compartment-specific quantitative metabolomic data, with remaining cases due to uncertainty in estimation of standard reaction Gibbs energy. This study points to the pressing need for 1), quantitative metabolomic data, and 2), experimental measurement of thermochemical properties for human metabolites.
    • Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

      Gaulton, Kyle J; Ferreira, Teresa; Lee, Yeji; Raimondo, Anne; Mägi, Reedik; Reschen, Michael E; Mahajan, Anubha; Locke, Adam; William Rayner, N; Robertson, Neil; et al. (Nature Publishing Group, 2015-12)
      We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
    • The effect of fontanel on scalp EEG potentials in the neonate.

      Gargiulo, P; Belfiore, P; Friðgeirsson, E A; Vanhatalo, S; Ramon, C; [ 1 ] Reykjavik Univ, Inst Biomed & Neural Engn, Reykjavik, Iceland [ 2 ] Landspitali Univ Hosp, Dept Sci, Reykjavik, Iceland [ 3 ] Univ Naples Federico II, Dept Biomed Elect & Telecommun Engn, Naples, Italy [ 4 ] Landspitali Univ Hosp, Dept Dev CE & IT, Reykjavik, Iceland [ 5 ] Univ Helsinki, Cent Hosp, HUS Med Imaging Ctr, Dept Childrens Clin Neurophysiol, Helsinki, Finland [ 6 ] Univ Helsinki, Cent Hosp, Childrens Hosp, Helsinki, Finland [ 7 ] Univ Helsinki, Helsinki, Finland [ 8 ] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA (Elsevier, 2015-09)
      To define how fontanels affect scalp EEG potentials in neonates.
    • Development of a hypoallergenic recombinant parvalbumin for first-in-man subcutaneous immunotherapy of fish allergy.

      Zuidmeer-Jongejan, Laurian; Huber, Hans; Swoboda, Ines; Rigby, Neil; Versteeg, Serge A; Jensen, Bettina M; Quaak, Suzanne; Akkerdaas, Jaap H; Blom, Lars; Asturias, Juan; et al. (Karger, 2015)
      The FAST (food allergy-specific immunotherapy) project aims at developing safe and effective subcutaneous immunotherapy for fish allergy, using recombinant hypoallergenic carp parvalbumin, Cyp c 1.
    • Metabolomic analysis of platelets during storage: a comparison between apheresis- and buffy coat-derived platelet concentrates.

      Paglia, Giuseppe; Sigurjónsson, Ólafur E; Rolfsson, Óttar; Hansen, Morten Bagge; Brynjólfsson, Sigurður; Gudmundsson, Sveinn; Palsson, Bernhard O; [ 1 ] Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland [ 2 ] Landspitali Univ Hosp, Blood Bank, IS-105 Reykjavik, Iceland [ 3 ] Reykjavik Univ, Sch Sci & Engn, Reykjavik, Iceland [ 4 ] Copenhagen Univ Hosp, Rigshosp, Dept Clin Immunol, Copenhagen, Denmark (Wiley-Blackwell, 2015-02)
      Platelet concentrates (PCs) can be prepared using three methods: platelet (PLT)-rich plasma, apheresis, and buffy coat. The aim of this study was to obtain a comprehensive data set that describes metabolism of buffy coat-derived PLTs during storage and to compare it with a previously published parallel data set obtained for apheresis-derived PLTs.
    • An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers.

      Blein, Sophie; Bardel, Claire; Danjean, Vincent; McGuffog, Lesley; Healey, Sue; Barrowdale, Daniel; Lee, Andrew; Dennis, Joe; Kuchenbaecker, Karoline B; Soucy, Penny; et al. (BioMed Central, 2015)
      Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers.
    • Polygenic risk scores for schizophrenia and bipolar disorder predict creativity.

      Power, Robert A; Steinberg, Stacy; Bjornsdottir, Gyda; Rietveld, Cornelius A; Abdellaoui, Abdel; Nivard, Michel M; Johannesson, Magnus; Galesloot, Tessel E; Hottenga, Jouke J; Willemsen, Gonneke; et al. (Nature Publishing Group, 2015-07)
      We tested whether polygenic risk scores for schizophrenia and bipolar disorder would predict creativity. Higher scores were associated with artistic society membership or creative profession in both Icelandic (P = 5.2 × 10(-6) and 3.8 × 10(-6) for schizophrenia and bipolar disorder scores, respectively) and replication cohorts (P = 0.0021 and 0.00086). This could not be accounted for by increased relatedness between creative individuals and those with psychoses, indicating that creativity and psychosis share genetic roots.
    • Hazelnut allergy across Europe dissected molecularly: A EuroPrevall outpatient clinic survey.

      Datema, Mareen R; Zuidmeer-Jongejan, Laurian; Asero, Riccardo; Barreales, Laura; Belohlavkova, Simona; de Blay, Frédéric; Bures, Peter; Clausen, Michael; Dubakiene, Ruta; Gislason, David; et al. (Elsevier, 2015-03-13)
      Hazelnut allergy is birch pollen-driven in Northern/Western Europe and lipid transfer protein-driven in Spain and Italy. Little is known about other regions and other allergens.
    • Identification of six new susceptibility loci for invasive epithelial ovarian cancer.

      Kuchenbaecker, Karoline B; Ramus, Susan J; Tyrer, Jonathan; Lee, Andrew; Shen, Howard C; Beesley, Jonathan; Lawrenson, Kate; McGuffog, Lesley; Healey, Sue; Lee, Janet M; et al. (Nature Publishing Group, 2015-02)
      Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
    • Prediction of intracellular metabolic states from extracellular metabolomic data.

      Aurich, Maike K; Paglia, Giuseppe; Rolfsson, Óttar; Hrafnsdóttir, Sigrún; Magnúsdóttir, Manuela; Stefaniak, Magdalena M; Palsson, Bernhard Ø; Fleming, Ronan M T; Thiele, Ines; Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland, Univ Luxembourg, Luxembourg Ctr Syst Biomed, Esch Sur Alzette, Luxembourg, Univ Iceland, Sch Hlth Sci, Fac Food Sci & Nutr, Reykjavik, Iceland, Univ Calif San Diego, Dept Bioengn, La Jolla, CA 92093 USA (Springer, 2015-06)
      Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well-suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context.
    • A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

      Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; et al. (BioMed Central Ltd, 2011)
      Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem.
    • The human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions.

      Rolfsson, Ottar; Palsson, Bernhard Ø; Thiele, Ines; Addresses: [Show the Organization-Enhanced name(s)] [ 1 ] Univ Iceland, Ctr Syst Biol, IS-101 Reykjavik, Iceland [Show the Organization-Enhanced name(s)] [ 2 ] Univ Iceland, Fac Ind Engn Mech Engn & Comp Sci, IS-101 Reykjavik, Iceland (BioMed Central Ltd, 2011)
      Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the same time, a major challenge in the post genomic era involves characterisation of missing biological components to complete genome annotation.
    • A systems biology approach to drug targets in Pseudomonas aeruginosa biofilm.

      Sigurdsson, Gunnar; Fleming, Ronan M T; Heinken, Almut; Thiele, Ines; [ 1 ] Univ Iceland, Ctr Syst Biol, Reykajavik, Iceland [ 2 ] Univ Iceland, Fac Ind Engn Mech Engn & Comp Sci, Reykajavik, Iceland (Public Library Science, 2012)
      Antibiotic resistance is an increasing problem in the health care system and we are in a constant race with evolving bacteria. Biofilm-associated growth is thought to play a key role in bacterial adaptability and antibiotic resistance. We employed a systems biology approach to identify candidate drug targets for biofilm-associated bacteria by imitating specific microenvironments found in microbial communities associated with biofilm formation. A previously reconstructed metabolic model of Pseudomonas aeruginosa (PA) was used to study the effect of gene deletion on bacterial growth in planktonic and biofilm-like environmental conditions. A set of 26 genes essential in both conditions was identified. Moreover, these genes have no homology with any human gene. While none of these genes were essential in only one of the conditions, we found condition-dependent genes, which could be used to slow growth specifically in biofilm-associated PA. Furthermore, we performed a double gene deletion study and obtained 17 combinations consisting of 21 different genes, which were conditionally essential. While most of the difference in double essential gene sets could be explained by different medium composition found in biofilm-like and planktonic conditions, we observed a clear effect of changes in oxygen availability on the growth performance. Eight gene pairs were found to be synthetic lethal in oxygen-limited conditions. These gene sets may serve as novel metabolic drug targets to combat particularly biofilm-associated PA. Taken together, this study demonstrates that metabolic modeling of human pathogens can be used to identify oxygen-sensitive drug targets and thus, that this systems biology approach represents a powerful tool to identify novel candidate antibiotic targets.