Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Regulation of mass and function of pancreatic β-cells: identification of anti-apoptotic peptides and role of GLP-1

Résumé La masse de cellules β sécrétrices d'insuline est un tissu dynamique qui s'adapte aux variations de la demande métabolique pour assurer une normoglycémie. Cette adaptation se fait par un changement de sécrétion d'insuline et de la masse totale des cellules β. Une perte complète ou partielle des cellules β conduit respectivement à un diabète de type 1 et de type 2. Les mécanismes qui régulent la masse de cellules β et maintiennent leur phénotype differencié sont encore peu connus. Leur identification est nécessaire pour comprendre le développement du diabète et développer des stratégies de traitement. La greffe d'îlots est une approche thérapeutique prometteuse pour le diabète de type 1, mais est limitée par une perte précoce des cellules β due à une apoptose induite par des cytokines. Afin d'améliorer la survie des cellules β lors de la greffe d'îlots, le premier but était de trouver des peptides pouvant bloquer l'apoptose induite par FasL et TNF-α. Pour ce faire, deux librairies de phages ont été criblées pour sélectionner des peptides se liant au Fas DD ou au TNFRl DD. Nous avons identifié six peptides différents. Cependant, aucun d'entre eux n'était capable de protéger les cellules de l'apoptose induite par FasL ou TNF-α. Deuxièmement, le GLP-1 est une hormone qui stimule la sécrétion d'insuline, et est impliquée dans la prolifération des cellules β, la différentiation, et inhibe l'apoptose. Nous avons fait l'hypothèse que le GLP-1 joue un rôle crucial dans le contrôle de la masse et de la fonction des cellules β. Afin de l'évaluer, une analyse par puce à ADN a été réalisée en comparant des cellules βTC-Tet traitées avec du GLP-1 à des cellules non-traitées. 376 gènes régulés ont été identifiés, dont RGS2, CREM, ICERI et DUSP14, augmentés significativement par le GLP-1. Nous avons confirmé que le GLP-1 augmente l'expression de ces gènes, aussi bien au niveau des transcripts que des protéines. De plus, nous avons montré que le GLP-1 induit leur expression par activation de la voie cAMP/PKA, et nécessite l'entrée de calcium extracellulaire. D'après leur fonction biologique, nous avons ensuite supposé que ces gènes pourraient agir comme régulateurs négatifs de la signalisation du GLP-l, et donc freiner son effet proliférateur. Pour vérifier notre hypothèse, des siRNAs contre ces gènes ont été développés, et leurs effets sur la prolifération des cellules β seront évalués ultérieurement. Abstract The pancreatic β-cell mass is a dynamic tissue which adapts to variations in metabolic demand in order to ensure normoglycemia. This adaptation occurs through a change in both insulin secretion and the total mass of ,β-cells. An absolute or relative loss of β-cells leads to type 1 and type 2 diabetes, respectively. The mechanisms that regulate the pancreatic β-cell mass and maintain the fully differentiated phenotype of the insulin-secreting β-cells are only poorly defined. Their identification is required to understand the progression of diabetes, but also to design strategies for the treatment of diabetes. Islet transplantation is a promising therapeutic approach for type 1 diabetes, but it is still limited by an early graft loss due to cytokine-induced apoptosis. In order to improve β-cell survival during islet transplantation, our first goal was to find novel blockers of FasL- and TNF-α-mediated cell death in the form of peptides. To that end, we screened two phage display libraries to select Fas DD- or TNFR1 DD-binding peptides. We identified six different small peptides. However, none of these peptides was able to prevent cells from FasL- or TNF-α-mediated apoptosis. Secondly, GLP-1 is a hormone that has been shown to stimulate insulin secretion and to be involved in β-cell proliferation, differentiation and inhibition of apoptosis. We hypothesized that GLP-1 plays a crucial role to control mass and function of β-cells. To evaluate this hypothesis, we performed a cDNA microarray analysis with GLP-1-treated βTC-Tet cells compared to untreated cells. We found 376 regulated genes, among these, RGS2, CREM, ICERI and DUSP14, which were significantly upregulated by GLP-1. We confirmed that both their mRNA and protein levels were strongly and rapidly increased after GLP-1 treatment. Moreover, we found that GLP-1 activates their expression mainly through the activation of the cAMP/PKA signaling pathway, and requires extracellular calcium entry. According to their biological function, we then hypothesized that these genes might act as negative regulators of the GLP-1 signaling. In particular, they might brake the effects of GLP-1 on β-cell proliferation. To verify this hypothesis, siRNAs against these genes were developed. The effect of these siRNAs on GLP-1-induced β-cell proliferation will be evaluated later.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Ultra high performance supercritical fluid chromatography coupled with tandem mass spectrometry for screening of doping agents. I: Investigation of mobile phase and MS conditions.

The conditions for the analysis of selected doping substances by UHPSFC-MS/MS were optimized to ensure suitable peak shapes and maximized MS responses. A representative mixture of 31 acidic and basic doping agents was analyzed, in both ESI+ and ESI- modes. The best compromise for all compounds in terms of MS sensitivity and chromatographic performance was obtained when adding 2% water and 10mM ammonium formate in the CO2/MeOH mobile phase. Beside mobile phase, the nature of the make-up solvent added for interfacing UHPSFC with MS was also evaluated. Ethanol was found to be the best candidate as it was able to compensate for the negative effect of 2% water addition in ESI- mode and provided a suitable MS response for all doping agents. Sensitivity of the optimized UHPSFC-MS/MS method was finally assessed and compared to the results obtained in conventional UHPLC-MS/MS. Sensitivity was improved by 5-100-fold in UHPSFC-MS/MS vs. UHPLC-MS/MS for 56% of compounds, while only one compound (bumetanide) offered a significantly higher MS response (4-fold) under UHPLC-MS/MS conditions. In the second paper of this series, the optimal conditions for UHPSFC-MS/MS analysis will be employed to screen >100 doping agents in urine matrix and results will be compared to those obtained by conventional UHPLC-MS/MS.

6.2

Airborne particles can come from a variety of sources and contain variable chemical constituents. Some particles are formed by natural processes, such as volcanoes, erosion, sea spray, and forest fires, while other are formed by anthropogenic processes, such as industrial- and motor vehicle-related combustion, road-related wear, and mining. In general, larger particles (those greater than 2.5 μm) are formed by mechanical processes, while those less than 2.5 μm are formed by combustion processes. The chemical composition of particles is highly influenced by the source: for combustion-related particles, factors such as temperature of combustion, fuel type, and presence of oxygen or other gases can also have a large impact on PM composition. These differences can often be observed at a regional level, such as the greater sulphate-composition of PM in regions that burn coal for electricity production (which contains sulphur) versus regions that do not. Most countries maintain air monitoring networks, and studies based on the resulting data are the most common basis for epidemiology studies on the health effects of PM. Data from these monitoring stations can be used to evaluate the relationship between community-level exposure to ambient particles and health outcomes (i.e., morbidity or mortality from various causes). Respiratory and cardiovascular outcomes are the most commonly assessed, although studies have also considered other related specific outcomes such as diabetes and congenital heart disease. The data on particle characteristics is usually not very detailed and most often includes some combination of PM2.5, PM10, sulphate, and NO2. Other descriptors that are less commonly found include particle number (ultrafine particles), metal components of PM, local traffic intensity, and EC/OC. Measures of association are usually reported per 10 μg/m3 or interquartile range increase in pollutant concentration. As the exposure data are taken from regional monitoring stations, the measurements are not representative of an individual's exposure. Particle size is an important descriptor for understanding where in the human respiratory system the particles will deposit: as a general rule, smaller particles penetrate to deeper regions of the lungs. Initial studies on the health effects of particulate matter focused on mass of the particles, including either all particles (often termed total suspended particulate or TSP) or PM10 (all particles with an aerodynamic diameter less than 10 μm). More recently, studies have considered both PM10 and PM2.5, with the latter corresponding more directly to combustion-related processes. UFPs are a dominant source of particles in terms of PNC, yet are negligible in terms of mass. Very few epidemiology studies have measured the effect of UFPs on health; however, the numbers of studies on this topic are increasing. In addition to size, chemical composition is of importance when understanding the toxicity of particles. Some studies consider the composition of particles in addition to mass; however this is not common, in part due the cost and labour involved in such analyses.

Mass and energy balance of the carbonization of babassu nutshell as affected by temperature

The objective of this work was to evaluate the carbonization yield of babassu nutshell as affected by final temperature, as well as the energy losses involved in the process. Three layers constituting the babassu nut, that is, the epicarp, mesocarp and endocarp, were used together. The material was carbonized, considering the following final temperatures: 450, 550, 650, 750, and 850ºC. The following were evaluated: energy and charcoal yields, pyroligneous liquid, non-condensable gases, and fixed carbon. The use of babassu nutshell can be highly feasible for charcoal production. The yield of charcoal from babassu nutshell carbonization was higher than that reported in the literature for Eucalyptus wood carbonization, considering the final temperature of 450ºC. Charcoal and energy yields decreased more sharply at lower temperatures, with a tendency to stabilize at higher temperatures. The energy yields obtained can be considered satisfactory, with losses between 45 and 52% (based on higher heating value) and between 43 and 49% (based on lower heating value) at temperatures ranging from 450 to 850ºC, respectively. Yields in fixed carbon and pyroligneous liquid are not affected by the final carbonization temperature.

Perception, signaling and molecular basis of oviposition-mediated plant responses.

Eggs deposited on plants by herbivorous insects represent a threat as they develop into feeding larvae. Plants are not a passive substrate and have evolved sophisticated mechanisms to detect eggs and induce direct and indirect defenses. Recent years have seen exciting development in molecular aspects of egg-induced responses. Some egg-associated elicitors have been identified, and signaling pathways and egg-induced expression profiles are being uncovered. Depending on the mode of oviposition, both the jasmonic acid and salicylic acid pathways seem to play a role in the induction of defense responses. An emerging concept is that eggs are recognized like microbial pathogens and innate immune responses are triggered. In addition, some eggs contain elicitors that induce highly specific defenses in plants. Examples of egg-induced suppression of defense or, on the contrary, egg-induced resistance highlight the complexity of plant-egg interactions in an on-going arms race between herbivores and their hosts. A major challenge is to identify plant receptors for egg-associated elicitors, to assess the specificity of these elicitors and to identify molecular components that underlie various responses to oviposition.

Hépatite B et migrants: doit-on mieux faire? [Hepatitis B and migrants: should we do better?].

More than 5% of the world's population lives with chronic hepatitis B. Migrants, particularly asylum seekers, are mostly from middle and high endemic regions. In Switzerland, however, no systematic screening of chronic hepatitis B is proposed to them. In a resolution published in 2010 the WHO encourages vaccination, but also screening of people at risk, as well as care of infected individuals. On the basis of a study conducted in asylum seekers in the canton of Vaud, prevalence of Ac antiHBc is estimated at 42% and HBsAg at 8%. Possible screening strategies and care are discussed in the light of these data. Identifying infected migrants would give them access to medical care and therefore lower the rate of complications, as well as the transmission of the virus between migrants and the local population.

Predicting chick body mass by artificial intelligence-based models

The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

Managing Configurable Products in Mass Customization

Massaräätälöinti on tärkeä osa nykyaikaista tuotestrategiaa. Massaräätälöinti mahdollistaa asiakaskohtaisesti muokattujen tuotteiden valmistuksen massatuotannon tehokkuudella. Massaräätälöinti edellyttää laajamittaista tietojärjestelmien hyväksikäyttöä, niin räätälöityjen tuotteiden mallinnuksessa, tuotteistuksessa kuin ylläpidossakin. Diplomityössä käsittelen taustatekijöitä jotka ovat johtaneet massaräätälöinnin syntyyn ja yleistymiseen. Käsittelyssä ovat myös erilaiset tavat toteuttaa massaräätälöintiä ja tietojärjestelmät jota tukevat massaräätälöintiä. Diplomityön empiirisessä osassa tarkastellaan Nokia Networksin tapaa toteuttaa massaräätälöintiä sekä esitellään tärkeimmät tätä tukevat järjestelmät. Empiirisen osan painopiste on kuitenkin hyvin vahvasti keskittynyt yhteen tuoterakenteiden osaan, joka on aiheuttanut haasteita Nokia Networksin massaräätälöintikonseptille. Tämä tuoterakenteen osa on valjastettu moneen erilaiseen käyttöön, mikä aiheuttaa ongelmia tietojärjestelmissä ja prosesseissa joihin se on vaikuttamassa. Työn tarkoituksena on kartoittaa kaikki ne ongelmat joita tämä tuoterakenteen osa aiheuttaa sulavalle massaräätälöinnin toteuttamiselle, niin yleisesti kuin järjestelmä- ja prosessimielessäkin. Työ on tehty osana laajamittaista projektia. Projektin tarkoituksena on kehittää uusi ja joustavampi ratkaisu tuoterakenteisiin, mandollistaen asiakaskohtaisten räätälöityjen tuotteiden valmistamisen, niin että se sopii Nokia Networksin järjestelmä sekä prosessi ympäristöön.

The Besançon Galaxy Model renewed. I. Constraints on the Galactic thin disc evolution from Tycho data

Context. The understanding of Galaxy evolution can be facilitated by the use of population synthesis models, which allow to test hypotheses on the star formation history, star evolution, as well as chemical and dynamical evolution of the Galaxy. Aims. The new version of the Besanc¸on Galaxy Model (hereafter BGM) aims to provide a more flexible and powerful tool to investigate the Initial Mass Function (IMF) and Star Formation Rate (SFR) of the Galactic disc. Methods. We present a new strategy for the generation of thin disc stars which assumes the IMF, SFR and evolutionary tracks as free parameters. We have updated most of the ingredients for the star count production and, for the first time, binary stars are generated in a consistent way. We keep in this new scheme the local dynamical self-consistency as in Bienayme et al (1987). We then compare simulations from the new model with Tycho-2 data and the local luminosity function, as a first test to verify and constrain the new ingredients. The effects of changing thirteen different ingredients of the model are systematically studied. Results. For the first time, a full sky comparison is performed between BGM and data. This strategy allows to constrain the IMF slope at high masses which is found to be close to 3.0, excluding a shallower slope such as Salpeter"s one. The SFR is found decreasing whatever IMF is assumed. The model is compatible with a local dark matter density of 0.011 M pc−3 implying that there is no compelling evidence for significant amount of dark matter in the disc. While the model is fitted to Tycho2 data, a magnitude limited sample with V<11, we check that it is still consistent with fainter stars. Conclusions. The new model constitutes a new basis for further comparisons with large scale surveys and is being prepared to become a powerful tool for the analysis of the Gaia mission data.

Optimisation of data analysis method for a fluidized bed combustion test rig

Nowadays the used fuel variety in power boilers is widening and new boiler constructions and running models have to be developed. This research and development is done in small pilot plants where more faster analyse about the boiler mass and heat balance is needed to be able to find and do the right decisions already during the test run. The barrier on determining boiler balance during test runs is the long process of chemical analyses of collected input and outputmatter samples. The present work is concentrating on finding a way to determinethe boiler balance without chemical analyses and optimise the test rig to get the best possible accuracy for heat and mass balance of the boiler. The purpose of this work was to create an automatic boiler balance calculation method for 4 MW CFB/BFB pilot boiler of Kvaerner Pulping Oy located in Messukylä in Tampere. The calculation was created in the data management computer of pilot plants automation system. The calculation is made in Microsoft Excel environment, which gives a good base and functions for handling large databases and calculations without any delicate programming. The automation system in pilot plant was reconstructed und updated by Metso Automation Oy during year 2001 and the new system MetsoDNA has good data management properties, which is necessary for big calculations as boiler balance calculation. Two possible methods for calculating boiler balance during test run were found. Either the fuel flow is determined, which is usedto calculate the boiler's mass balance, or the unburned carbon loss is estimated and the mass balance of the boiler is calculated on the basis of boiler's heat balance. Both of the methods have their own weaknesses, so they were constructed parallel in the calculation and the decision of the used method was left to user. User also needs to define the used fuels and some solid mass flowsthat aren't measured automatically by the automation system. With sensitivity analysis was found that the most essential values for accurate boiler balance determination are flue gas oxygen content, the boiler's measured heat output and lower heating value of the fuel. The theoretical part of this work concentrates in the error management of these measurements and analyses and on measurement accuracy and boiler balance calculation in theory. The empirical part of this work concentrates on the creation of the balance calculation for the boiler in issue and on describing the work environment.

Modulation of pancreatic β-cell mass and insulin secretion by PPARβ/δ

SUMMARY : Peroxisome proliferator-activated receptor ß/δ protects against obesity by reducing dyslipidemia and insulin resistance via effects in various organs, including muscle, adipose tissue and liver. However, nothing is known about the function of PPARß in pancreas, a prime organ in the control of glucose homeostasis. To gain insight into so far hypothetical functions of this PPAR isotype in ß-cell function, we specifically ablated Pparß in the whole epithelial compartment of the pancreas. The mutated mice presented expanded ß-cell mass, possibly, this is due to increased burst of ß-cell proliferation at 2 weeks of age. These PPARß null pancreas mice exhibit hyperinsulinemia-hypoglycaemia starting at 4 weeks of age, due to hyperfunctionality of ß-cell. Gene expression profiling indicated a broad repressive function of PPARß impacting the vesicular and granular compartment, actin cytoskeleton, and metabolism of glucose and fatty acids. Analyses of insulin release from isolated islets revealed accelerated second-phase of glucose-stimulated insulin secretion. Higher levels of PKD and PKCS in mutated animals, in concert with F-actin disassembly, lead to an increased insulin secretion and its associated systemic effects. Enhanced palmitate potentiation of glucose-stimulated insulin secretion in PPARß mutant islets, suggests an important role of this receptor in lipid/glucose metabolism in ß-cell. Taken together, these results provide evidence for PPARß playing a repressive role on ß-cell growth and insulin exocytosis, and shed new light on its metabolic .action. RESUME : Le récepteur nucléaire PPARß (Peroxisome proliferator-activated receptor ß/δ) protège contre l'obésité en réduisant la dyslipidémie et la résistance à l'insuline dans différents organes, comme le muscle, le tissue adipeux et le foie. Cependant, il y a, à ce jour, très peu de connaissance par rapport au rôle de PPARß dans le pancréas, qui est un organe très important dans le contrôle homéostatique du glucose. Afin de comprendre le rôle de cet isotype de PPAR dans le fonctionnement des cellules beta du pancréas, nous avons invalidé le gène Pparß dans tout le compartiment pancréatique de la souris. Ces souris mutantes présentent une augmentation de la masse totale de cellules beta; Cela serait dû à une intense prolifération des cellules beta à 2 semaines après la naissance. Également, ces souris présentent une hyperinsulinémie et une hypoglycémie qui commencent à l'âge de 4 semaines; la raison de ce phénotype serait une hyperactivité des cellules beta. Le profil d'expression génique indique une fonction répressive globale de PPARß en se référant aux compartiments vésiculaire et granulaire, au cytosquelette d'actine, et au métabolisme du glucose et des acides gras. L'analyse de la sécrétion d'insuline par les cellules beta a démontré que la deuxième phase de sécrétion d'insuline après stimulation au glucose est augmentée. Les niveaux élevés de PKD et PKCS dans les îlots pancréatiques de souris mutantes, ainsi qu'une augmentation de la dépolymérisation des filaments d'active génèrent un surplus de sécrétion d'insuline après stimulation au glucose. Les îlots pancréatiques des souris mutantes secrètent plus d'insuline après stimulation au glucose et au palmitate que les îlots de souris contrôles. Ceci suggère un rôle important de PPARß dans le métabolisme des lipides et du glucose des cellules beta. En résumé, ces résultats mettent en évidence un rôle répressif de PPARß dans la croissance des cellules beta et dans l'exocytose d'insuline.