Bioinformatics for genomics purposes

Sinds enkele jaren wordt op het RIVM genomicsonderzoek uitgevoerd. Genomics omvat grootschalig onderzoek naar het erfelijk materiaal (DNA) van organismen. Dit onderzoek levert inzicht op in de manier waarop erfelijke eigenschappen zich vertalen naar het functioneren van een cel, en uiteindelijk een heel organisme. De praktische uitvoering van genomicsexperimenten is recentelijk beschreven in rapport 340200001 "Genomics: Implementatie, toepassing en toekomst", dat in december 2006 is verschenen. Dit rapport gaat in op de bioinformatica die het RIVM heeft opgezet en ontwikkeld. Bioinformatica is de wetenschap die methoden uit de informatica gebruikt om biologische data te kunnen verwerken en analyseren. Deze specifieke kennis is nodig om de grote hoeveelheden data die genomicsexperimenten genereren, te kunnen analyseren. De verschillende stappen in de data-analyse, zoals beeldverwerking, kwaliteitscontrole, normalisatie, statistische analyse, patroonherkenning, verlopen succesvol volgens algemeen geaccepteerde methoden. De bioinformatica voor de verdere biologische interpretatie van de resultaten is wereldwijd nog volop in ontwikkeling. In samenwerking met andere instituten wordt dit onderzoeksgebied gevolgd en worden nieuwe ontwikkelingen toegepast. De komende jaren zullen er via de literatuur meer data van genomicsexperimenten beschikbaar komen. Om die te kunnen vergelijken en te combineren zijn bioinformatica-methoden beschikbaar, die zich de komende jaren verder zullen ontwikkelen. Naast genomicsdata zullen ook steeds meer andere gegevens (bijvoorbeeld eiwit- en metabolietgegevens) beschikbaar komen. Dit biedt mogelijkheden om meerdere soorten data te integreren. Deze aanpak wordt "systems biology" genoemd en is vooral interessant om tot een betere risicoschatting van stoffen te komen. Ook bestaat behoefte aan bioinformatica voor grootschalig eiwitonderzoek (proteomics), dat het RIVM wil gebruiken voor bevolkingsonderzoeken en screeningsprogramma's van micro-organismen.Genomics constitutes large-scale research on hereditary material (DNA) of organisms. The genomics research that has been carried out the last few years at the National Institute for Public Health and the Environment (RIVM) has given us insight into the way hereditary information is translated into the functioning of a cell and eventually a whole organism. Practical realization of genomics experiments has recently been described in report 340200001 "Genomics: Implementation, application, and future".analysis demands specific expertise. The last few years has seen the set-up and further development of the bioinformatics required. The various steps in the data analysis, including image analysis, quality control, normalisation, statistical analysis and pattern recognition, are carried out successfully according to generally accepted methods. The bioinformatics concerned with interpretation of the results is worldwide in full development. This field will be closely followed and new developments applied in cooperation with other institutes. More genomics experimental data will become available via the literature in the coming years. Bioinformatics methods for comparing and combining these data are available and will develop further in the future. In addition, an increasing number of other kinds of data sets (like protein or metabolite data) will become available, thereby creating possibilities for integration of multidisciplinary data. This approach is called systems biology and is especially interesting for a better risk assessment for chemicals. Furthermore, there will be a need for bioinformatics for proteomics, which the RIVM aims to use for population screening programmes and screening applications on microorganisms.RIV

Genetic variation in thioredoxin interacting protein (TXNIP) is associated with hypertriglyceridaemia and blood pressure in diabetes mellitus

Aims Thioredoxin interacting protein (TXNIP) is an attractive candidate gene for diabetes or diabetic dyslipidaemia, since TXNIP is the strongest glucose-responsive gene in pancreatic B-cells, TXNIP deficiency in a mouse model is associated with hyperlipidaemia and TXNIP is located in the 1q21-1q23 chromosomal Type 2 diabetes mellitus (DM) locus. We set out to investigate whether metabolic effects of TXNIP that were previously reported in a murine model are also relevant in human Type 2 DM. Methods The frequency distribution of a 3' UTR single nucleotide polymorphism (SNP) in TXNIP was investigated in subjects with normal glucose tolerance (NGT; n = 379), impaired glucose tolerance (IGT; n = 228) and Type 2 DM (n = 230). Metabolic data were used to determine the effect of this SNP on parameters associated with lipid and glucose metabolism. Results The frequency of the TXNIP variation did not differ between groups, but within the group of diabetic subjects, carriers of the TXNIP-T variant had 1.6-fold higher triglyceride concentrations (P = 0.015; n = 136) and a 5.5-mmHg higher diastolic blood pressure (P = 0.02; n = 212) than homozygous carriers of the common C-allele, whereas in non-diabetic subjects fasting glucose was 0.26 mmol/l lower (P = 0.002; n = 478) in carriers of the T-allele. Moreover, a significant interaction between plasma glucose concentrations and TXNIP polymorphism on plasma triglycerides was observed (P = 0.012; n = 544). Conclusion This is the first report to implicate TXNIP in a human disorder of energy metabolism, Type 2 diabetes. The effect of TXNIP on triglycerides is influenced by plasma glucose concentrations, suggesting that the biological relevance of TXNIP variations may be particularly relevant in recurrent episodes of hyperglycaemia

Influence of beta(2)-adrenoceptor gene polymorphisms on diet-induced thermogenesis

The sympathetic nervous system is involved in the control of energy metabolism and expenditure. Diet-induced thermogenesis is mediated partly by the ß-adrenergic component of this system. The aim of the present study was to investigate the role of genetic variation in the ß2-adrenoceptor in diet-induced thermogenesis. Data from twenty-four subjects (fourteen men and ten women; BMI 26·7(SEM 0·8) kg/m2; age 45·2(SEM1·4) years) with different polymorph-isms of the ß2-adrenoceptor at codon 16 (Gly16Gly, Gly16Arg or Arg16Arg) were recruited for this study. Subjects were given a high-carbohydrate liquid meal, and the energy expenditure, respiratory exchange ratio, and plasma concentrations of NEFA, glycerol, glucose, insulin and catecholamines were measured before and over 4 h after the meal. The AUC of energy expenditure (diet-induced thermogenesis) was not significantly different between poly-morphism groups, nor was the response of any of the other measured variables to the meal. In a multiple regression model, the only variable that explained a significant proportion (32 %) of the variation in diet-induced thermogenesis was the increase in plasma adrenaline in response to the meal (P,0·05). The ß2-adrenoceptor codon16 polymorphisms did not contribute significantly. In conclusion, an independent contribution of the codon 16 polymorphism of the ß2-adrenoceptor gene to the variation in thermogenic response to a high-carbohydrate meal could not be demonstrated. The interindividual variation in thermo-genic response to the meal was correlated with variations in the plasma adrenaline response to the meal. ß2-Adrenoceptor polymorphisms: Diet-induced thermogenesis: Catecholamines Energy expenditure (EE) is an important factor in body-weight regulation. Diet-induced thermogenesis (DIT) is the EE associ-ated with ingestion, absorption and storage of food and account

Novel concepts in virally induced asthma

Viruses are the predominant infectious cause of asthma exacerbations in the developed world. In addition, recent evidence strongly suggests that viral infections may also have a causal role in the development of childhood asthma. In this article, we will briefly describe the general perception of how the link between infections and asthma has changed over the last century, and then focus on very recent developments that have provided new insights into the contribution of viruses to asthma pathogenesis. Highlighted areas include the contribution of severe early life viral infections to asthma inception, genetic determinants of severe viral infections in infancy, the differences in innate and adaptive immune system cytokine responses to viral infection between asthmatic and nonasthmatic subjects, and a potential vaccine strategy to prevent severe early life virally-induced illness