Molecular biology of progressive myoclonus epilepsy of Unverricht-Lundborg type (EPM1)

Progressive myoclonus epilepsy of Unverricht-Lundborg type (EPM1) is an autosomal recessively inherited disorder characterized by age of onset at 6-15 years, stimulus-sensitive myoclonus, tonic-clonic epileptic seizures and a progressive course. Mutations in the cystatin B (CSTB) gene underlie EPM1. The most common mutation underlying EPM1 is a dodecamer repeat expansion in the promoter region of CSTB. In addition, nine other mutations have been identified. CSTB, a cysteine protease inhibitor, is a ubiquitously expressed inhibitor of cathepsins, but its physiological function is unknown. The purpose of this study was to investigate CSTB gene expression and CSTB protein function in normal and pathological conditions. The basal CSTB promoter was mapped and characterized using different promoter-luciferase gene constructs. The binding activity of transcription factors to one ARE half, five Sp1 and four AP1 sites in the CSTB promoter was demonstrated. The CSTB promoter activity was clearly decreased using a CSTB promoter with "premutation" repeat expansions and in individuals with alike expansions. The expression of CSTB mRNA and protein was markedly reduced in patient cells. The endogenous CSTB protein localized to the nucleus, cytoplasm and lysosomes, and in differentiated cells merely to the cytoplasm. This suggests that the subcellular distribution of CSTB is dependent on the differentation status of the cells. The proteins representing patient missense mutations failed to associate with lysosomes, implying the importance of the lysosomal association for the proper physiological function of CSTB. Several alternatively spliced CSTB isoforms were identified. Of these CSTB2 was widely expressed with very low levels whereas the other alternatively spliced forms seemed to have limited tissue expression. In patients CSTB2 expression was reduced similarly to that of CSTB. The physiological relevance of CSTB alternative splicing remains unknown. The mouse Cstb transcript was shown to be present in all embryonic stages and adult tissues examined. The expression was highest at embryonic day 7 and in thymus, as well as in postnatal brain in the cortex, caudate putamen, thalamus, hippocampus, and in the Purkinje cell layer of the cerebellum. Our data implies that CSTB expression is tightly temporally and spatially regulated. The data presented in my thesis lay the basis for further understanding of the role of CSTB in health and disease.

Fatty acids, fibre, carotenoids and tocopherols in relation to glucose metabolism in subjects at high risk for type 2 diabetes : a cross-sectional analysis

Fatty acids, fibre, carotenoids and tocopherols in relation to glucose metabolism in subjects at high risk for type 2 diabetes a cross-sectional analysis Type 2 diabetes (T2D) is a heterogeneous disorder of carbohydrate, lipid and protein metabolism, resulting from genetics, environmental influences and interactions between these. The disease is characterized by insulin resistance, β-cell dysfunction, hepatic glucose overproduction and disordered fat mobilization and storage. The literature on associations between dietary factors and glucose metabolism is inconsistent. One factor behind the discrepant results may be genetic heterogeneity of study populations. Data on nutrient-gene interactions in relation to glucose metabolism are scarce. Thus, investigating high-risk populations and exploring nutrient-gene interactions are essential for improving the understanding of T2D aetiology. Ideally, this information could help to develop prevention programmes that take into account the genetic predisposition to the disease. In this study, associations between measures of glucose metabolism predicting T2D and fatty acids, antioxidative nutrients and fibre were examined in a high-risk population, i.e., in non-diabetic relatives of affected patients. Interactions between the PPARG Pro12Ala polymorphism and fatty acids on glucose metabolism were taken into consideration. This common polymorphism plays an important role in the regulation of glucose metabolism. The inverse associations observed between dietary fibre and insulin resistance are consistent with the prevailing recommendations urging increased intake of fibre to prevent T2D. Beneficial associations observed between the intake of carotenoids and glucose levels stress that a high consumption of vegetables, fruits and berries rich in carotenoids might also play a role in the prevention of T2D. Whether tocopherols have an independent association with glucose metabolism remains questionable. Observed interactions between fatty acids and glucose metabolism suggest that a high intake of palmitic acid is associated with high fasting glucose levels mainly in female Ala allele carriers. Furthermore, the PPARG Pro12Ala polymorphism may modify the metabolic response to dietary marine fat. The beneficial associations of high intake of marine n 3 fatty acids with insulin resistance and glucose levels may be restricted to carriers of the Ala allele. The findings pertain to subjects with a family history of T2D, and the cross-sectional nature of the study precludes inferences about causality. Results nevertheless show that associations of dietary factors with glucose metabolism may be modulated by the genetic makeup of an individual. Additional research is warranted to elucidate the role of probably numerous nutrient-gene interactions, some of which may be sex-specific, in the aetiology of T2D.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Boundedness and convergence of singular integrals on fractal type sets

The topic of this dissertation lies in the intersection of harmonic analysis and fractal geometry. We particulary consider singular integrals in Euclidean spaces with respect to general measures, and we study how the geometric structure of the measures affects certain analytic properties of the operators. The thesis consists of three research articles and an overview. In the first article we construct singular integral operators on lower dimensional Sierpinski gaskets associated with homogeneous Calderón-Zygmund kernels. While these operators are bounded their principal values fail to exist almost everywhere. Conformal iterated function systems generate a broad range of fractal sets. In the second article we prove that many of these limit sets are porous in a very strong sense, by showing that they contain holes spread in every direction. In the following we connect these results with singular integrals. We exploit the fractal structure of these limit sets, in order to establish that singular integrals associated with very general kernels converge weakly. Boundedness questions consist a central topic of investigation in the theory of singular integrals. In the third article we study singular integrals of different measures. We prove a very general boundedness result in the case where the two underlying measures are separated by a Lipshitz graph. As a consequence we show that a certain weak convergence holds for a large class of singular integrals.

Bayesian fisheries stock assessment: integrating and updating knowledge

In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.