Identification of genetic susceptibility loci for migraine

Migraine is the common cause of chronic episodic headache, affecting 12%-15% of the Caucasian population (41 million Europeans and some half a million Finns), and causes considerable loss of quality of life to its sufferers, as well as being linked to increased risk for a wide range of conditions, from depression to stroke. Migraine is the 19th most severe disease in terms of disability-adjusted life years, and 9th among women. It is characterized by attacks of headache accompanied by sensitivity to external stimuli lasting 4-72 hours, and in a third of cases by neurological aura symptoms, such as loss of vision, speech or muscle function. The underlying pathophysiology, including what triggers migraine attacks and why they occur in the first place, is largely unknown. The aim of this study was to identify genetic factors associated with the hereditary susceptibility to migraine, in order to gain a better understanding of migraine mechanisms. In this thesis, we report the results of genetic linkage and association analyses on a Finnish migraine patient collection as well as migraineurs from Australia, Denmark, Germany, Iceland and the Netherlands. Altogether we studied genetic information of nearly 7,000 migraine patients and over 50,000 population-matched controls. We also developed a new migraine analysis method called the trait component analysis, which is based on individual patient responses instead of the clinical diagnosis. Using this method, we detected a number of new genetic loci for migraine, including on chromosome 17p13 (HLOD 4.65) and 10q22-q23 (female-specific HLOD 7.68) with significant evidence of linkage, along with five other loci (2p12, 8q12, 4q28-q31, 18q12-q22, and Xp22) detected with suggestive evidence of linkage. The 10q22-q23 locus was the first genetic finding in migraine to show linkage to the same locus and markers in multiple populations, with consistent detection in six different scans. Traditionally, ion channels have been thought to play a role in migraine susceptibility, but we were able to exclude any significant role for common variants in a candidate gene study of 155 ion transport genes. This was followed up by the first genome-wide association study in migraine, conducted on 2,748 migraine patients and 10,747 matched controls followed by a replication in 3,209 patients and 40,062 controls. In this study, we found interesting results with genome-wide significance, providing targets for future genetic and functional studies. Overall, we found several promising genetic loci for migraine providing a promising base for future studies in migraine.

Individual variation in in vitro efficacy of antiplatelet medication - aspirin and clopidogrel

Antiplatelet medication is known to decrease adverse effects in patients with atherothrombotic disease. However, despite ongoing antiplatelet medication considerable number of patients suffer from atherothrombotic events. The aims of the study were 1) to evaluate the individual variability in platelet functions and compare the usability of different methods in detecting it, 2) to assess variability in efficacy of antiplatelet medication with aspirin (acetylsalicylic acid) or the combination of aspirin and clopidogrel and 3) to investigate the main genetic and clinical variables as well as potential underlying mechanisms of variability in efficacy of antiplatelet medication. In comparisons of different platelet function tests in 19 healthy individuals PFA-100® correlated with traditional methods of measuring platelet function and was thus considered appropriate for testing individual variability in platelet activity. Efficacy of ongoing 100mg aspirin daily was studied in 101 patients with coronary artery disease (CAD). Aspirin response was measured with arachidonic acid (AA)-induced platelet aggregation, which reflects cyclo-oxygenase (COX)-1 dependent thromboxane (Tx) A2 formation, and PFA-100®, which evaluates platelet activation under high shear stress in the presence of collagen and epinephrine. Five percent of patients failed to show inhibition of AA-aggregation and 21% of patients had normal PFA-100® results despite aspirin and were thus considered non-responders to aspirin. Interestingly, the two methods of assessing aspirin efficacy, platelet aggregation and PFA-100®, detected different populations as being aspirin non-responders. It could be postulated that PFA-100® actually measures enhanced platelet function, which is not directly associated with TxA2 inhibition exerted by aspirin. Clopidogrel efficacy was assessed in 50 patients who received a 300mg loading dose of clopidogrel 2.5 h prior to percutaneous coronary intervention (PCI) and in 51 patients who were given a loading dose of 300mg combined with a five day treatment of 75mg clopidogrel daily mimicking ongoing treatment. Clopidogrel response was assessed with ADP-induced aggregations, due to its mechanism of action as an inhibitor of ADP-induced activation. When patients received only a loading dose of clopidogrel prior to PCI, 40% did not gain measurable inhibition of their ADP-induced platelet activity (inhibition of 10% or less). Prolongation of treatment so that all patients had reached a plateau of inhibition exerted by clopidogrel, decreased the incidence of non-responders to 20%. Polymorphisms of COX-1 and GP VI, as well as diabetes and female gender, were associated with decreased in vitro aspirin efficacy. Diabetes also impaired the in vitro efficacy of short-term clopidogrel. Decreased response to clopidogrel was associated with limited inhibition by ARMX, an antagonist of P2Y12-receptor, suggesting the reason for clopidogrel resistance to be receptor-dependent. Conclusions: Considerable numbers of CAD patients were non-responders either to aspirin, clopidogrel or both. In the future, platelet function tests may be helpful to individually select effective and safe antiplatelet medication for these patients.

Promotion of a cancer-like phenotype, through chronic exposure to inflammatory cytokines and hypoxia in a bronchial epithelial cell line model

Globally, lung cancer accounts for approximately 20% of all cancer related deaths. Five-year survival is poor and rates have remained unchanged for the past four decades. There is an urgent need to identify markers of lung carcinogenesis and new targets for therapy. Given the recent successes of immune modulators in cancer therapy and the improved understanding of immune evasion by tumours, we sought to determine the carcinogenic impact of chronic TNF-α and IL-1β exposure in a normal bronchial epithelial cell line model. Following three months of culture in a chronic inflammatory environment under conditions of normoxia and hypoxia (0.5% oxygen), normal cells developed a number of key genotypic and phenotypic alterations. Important cellular features such as the proliferative, adhesive and invasive capacity of the normal cells were significantly amplified. In addition, gene expression profiles were altered in pathways associated with apoptosis, angiogenesis and invasion. The data generated in this study provides support that TNF-α, IL-1β and hypoxia promotes a neoplastic phenotype in normal bronchial epithelial cells. In turn these mediators may be of benefit for biomarker and/or immune-therapy target studies. This project provides an important inflammatory in vitro model for further immuno-oncology studies in the lung cancer setting.

Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins

Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.

Role of γ1 Laminin and Its KDI Peptide in the Central Nervous System

Since the 1980 s, laminin-1 has been linked to regeneration of the central nervous system (CNS) and promotion of neuronal migration and axon guidance during CNS development. In this thesis, we clarify the role of γ1 laminin and its KDI tripeptide in development of human embryonic spinal cord, in regeneration of adult rat spinal cord injury (SCI), in kainic acid-induced neuronal death, and in the spinal cord tissue of amyotrophic lateral sclerosis (ALS). We demonstrated that γ1 laminin together with α1, β1, and β3 laminins localize at the floor plate region in human embryonic spinal cord. This localization of γ1 laminin is in spatial and temporal correlation with development of the spinal cord and indicates that γ1 laminin may participate in commissural axon guidance during the embryonic development of the human CNS. With in vitro studies using the Matrigel culture system, we demonstrated that the KDI tripeptide of γ1 laminin provides a chemotrophic guidance cue for neurites of the human embryonic dorsal spinal cord, verifying the functional ability of γ1 laminin to guide commissural axons. Results from our experimental SCI model demonstrate that the KDI tripeptide enhanced functional recovery and promoted neurite outgrowth across the mechanically injured area in the adult rat spinal cord. Furthermore, our findings indicate that the KDI tripeptide as a non-competitive inhibitor of the ionotropic glutamate receptors can provide when administered in adequate concentrations an effective method to protect neurons against glutamate-induced excitotoxic cell death. Human postmortem samples were used to study motor neuron disease, ALS (IV), and the study revealed that in human ALS spinal cord, γ1 laminin was selectively over-expressed by reactive astrocytes, and that this over-expression may correlate with disease severity. The multiple ways by which γ1 laminin and its KDI tripeptide provide neurotrophic protection and enhance neuronal viability suggest that the over-expression of γ1 laminin may be a glial attempt to provide protection for neurons against ALS pathology. The KDI tripeptide is effective therapeutically thus far in animal models only. However, because KDI containing γ1 laminin exists naturally in the human CNS, KDI therapies are unlikely to be toxic or allergenic. Results from our animal models are encouraging, with no toxic side-effects detected even at high concentrations, but the ultimate confirmation can be achieved only after clinical trials. More research is still needed until the KDI tripeptide is refined into a clinically applicable method to treat various neurological disorders.

Quench dynamics and defect production in the Kitaev and extended Kitaev models

We study quench dynamics and defect production in the Kitaev and the extended Kitaev models. For the Kitaev model in one dimension, we show that in the limit of slow quench rate, the defect density n∼1/√τ, where 1/τ is the quench rate. We also compute the defect correlation function by providing an exact calculation of all independent nonzero spin correlation functions of the model. In two dimensions, where the quench dynamics takes the system across a critical line, we elaborate on the results of earlier work [K. Sengupta, D. Sen, and S. Mondal, Phys. Rev. Lett. 100, 077204 (2008)] to discuss the unconventional scaling of the defect density with the quench rate. In this context, we outline a general proof that for a d-dimensional quantum model, where the quench takes the system through a d−m dimensional gapless (critical) surface characterized by correlation length exponent ν and dynamical critical exponent z, the defect density n∼1/τmν/(zν+1). We also discuss the variation of the shape and spatial extent of the defect correlation function with both the rate of quench and the model parameters and compute the entropy generated during such a quenching process. Finally, we study the defect scaling law, entropy generation and defect correlation function of the two-dimensional extended Kitaev model.

Identification of genetic susceptibility loci for migraine

Migraine is the common cause of chronic episodic headache, affecting 12%-15% of the Caucasian population (41 million Europeans and some half a million Finns), and causes considerable loss of quality of life to its sufferers, as well as being linked to increased risk for a wide range of conditions, from depression to stroke. Migraine is the 19th most severe disease in terms of disability-adjusted life years, and 9th among women. It is characterized by attacks of headache accompanied by sensitivity to external stimuli lasting 4-72 hours, and in a third of cases by neurological aura symptoms, such as loss of vision, speech or muscle function. The underlying pathophysiology, including what triggers migraine attacks and why they occur in the first place, is largely unknown. The aim of this study was to identify genetic factors associated with the hereditary susceptibility to migraine, in order to gain a better understanding of migraine mechanisms. In this thesis, we report the results of genetic linkage and association analyses on a Finnish migraine patient collection as well as migraineurs from Australia, Denmark, Germany, Iceland and the Netherlands. Altogether we studied genetic information of nearly 7,000 migraine patients and over 50,000 population-matched controls. We also developed a new migraine analysis method called the trait component analysis, which is based on individual patient responses instead of the clinical diagnosis. Using this method, we detected a number of new genetic loci for migraine, including on chromosome 17p13 (HLOD 4.65) and 10q22-q23 (female-specific HLOD 7.68) with significant evidence of linkage, along with five other loci (2p12, 8q12, 4q28-q31, 18q12-q22, and Xp22) detected with suggestive evidence of linkage. The 10q22-q23 locus was the first genetic finding in migraine to show linkage to the same locus and markers in multiple populations, with consistent detection in six different scans. Traditionally, ion channels have been thought to play a role in migraine susceptibility, but we were able to exclude any significant role for common variants in a candidate gene study of 155 ion transport genes. This was followed up by the first genome-wide association study in migraine, conducted on 2,748 migraine patients and 10,747 matched controls followed by a replication in 3,209 patients and 40,062 controls. In this study, we found interesting results with genome-wide significance, providing targets for future genetic and functional studies. Overall, we found several promising genetic loci for migraine providing a promising base for future studies in migraine.

Evolution of polyembryony: Consequences to the fitness of mother and offspring

Polyembryony, referring here to situations where a nucellar embryo is formed along with the zygotic embryo, has different consequences for the fitness of the maternal parent and offspring. We have developed genetic and inclusive fitness models to derive the conditions that permit the evolution of polyembryony under maternal and offspring control. We have also derived expressions for the optimal allocation (evolutionarily stable strategy, ESS) of resources between zygotic and nucellar embryos. It is seen that (i) Polyembryony can evolve more easily under maternal control than under that of either the offspring or the ‘selfish’ endosperm. Under maternal regulation, evolution of polyembryony can occur for any clutch size. Under offspring control polyembryony is more likely to evolve for high clutch sizes, and is unlikely for low clutch sizes (<3). This conflict between mother and offspring decreases with increase in clutch size and favours the evolution of polyembryony at high clutch sizes, (ii) Polyembryony can evolve for values of “x” (the power of the function relating fitness to seed resource) greater than 0.5758; the possibility of its occurrence increases with “x”, indicating that a more efficient conversion of resource into fitness favours polyembryony. (iii) Under both maternal parent and offspring control, the evolution of polyembryony becomes increasingly unlikely as the level of inbreeding increases, (iv) The proportion of resources allocated to the nucellar embryo at ESS is always higher than that which maximizes the rate of spread of the allele against a non-polyembryonic allele.Finally we argue that polyembryony is a maternal counter strategy to compensate for the loss in her fitness due to brood reduction caused by sibling rivalry. We support this assertion by two empirical evidences: (a) the extent of polyembryony is positively correlated with brood reduction inCitrus, and (b) species exhibiting polyembryony are more often those that frequently exhibit brood reduction.

Categorical Meteorological Products: Evaluation and Analysis

In meteorology, observations and forecasts of a wide range of phenomena for example, snow, clouds, hail, fog, and tornados can be categorical, that is, they can only have discrete values (e.g., "snow" and "no snow"). Concentrating on satellite-based snow and cloud analyses, this thesis explores methods that have been developed for evaluation of categorical products and analyses. Different algorithms for satellite products generate different results; sometimes the differences are subtle, sometimes all too visible. In addition to differences between algorithms, the satellite products are influenced by physical processes and conditions, such as diurnal and seasonal variation in solar radiation, topography, and land use. The analysis of satellite-based snow cover analyses from NOAA, NASA, and EUMETSAT, and snow analyses for numerical weather prediction models from FMI and ECMWF was complicated by the fact that we did not have the true knowledge of snow extent, and we were forced simply to measure the agreement between different products. The Sammon mapping, a multidimensional scaling method, was then used to visualize the differences between different products. The trustworthiness of the results for cloud analyses [EUMETSAT Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Météo-France (SAFNWC/MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS)] compared with ceilometers of the Helsinki Testbed was estimated by constructing confidence intervals (CIs). Bootstrapping, a statistical resampling method, was used to construct CIs, especially in the presence of spatial and temporal correlation. The reference data for validation are constantly in short supply. In general, the needs of a particular project drive the requirements for evaluation, for example, for the accuracy and the timeliness of the particular data and methods. In this vein, we discuss tentatively how data provided by general public, e.g., photos shared on the Internet photo-sharing service Flickr, can be used as a new source for validation. Results show that they are of reasonable quality and their use for case studies can be warmly recommended. Last, the use of cluster analysis on meteorological in-situ measurements was explored. The Autoclass algorithm was used to construct compact representations of synoptic conditions of fog at Finnish airports.

Smoking patterns and lung function : A longitudinal twin study

In many countries, the prevalence of smoking and smokers average cigarette consumption have decreased, with occasional smoking and daily light smoking (1-4 cigarettes per day, CPD) becoming more common. Despite these changes in smoking patterns, the prevalence of chronic obstructive pulmonary disease (COPD), a disorder characterized by a progressive decline in lung function, continues to rise globally. Smoking is the most important factor causing COPD, however, not all smokers develop the disease. Genetic factors partly explain the inter-individual differences in lung function and susceptibility of some smokers to COPD. No earlier research on the genetic and environmental determinants of lung function or on the phenomenon of light smoking exists in the Finnish population. Further, the association between low-rate smoking patterns and COPD remains partly unknown. This thesis aimed to study the prevalence and consistency of light smoking longitudinally in the Finnish population, to assess the characteristics of light smokers, and to examine the risks of chronic bronchitis and COPD associated with changing smoking patterns over time. A further aim was to estimate longitudinally the proportions of genetic and environmental factors that explain the inter-individual variances in lung function. Data from the Older Finnish Twin Cohort, including same-sex twin pairs born in Finland before 1958, were used. Smoking patterns and chronic bronchitis symptoms were consistently assessed in surveys conducted in 1975, 1981, and 1990. National registry data on reimbursement eligibilities and medication purchases were used to define COPD. Lung function data were obtained from a subsample of the cohort, 217 female twin pairs, who attended spirometry in 2000 and 2003 as part of the Finnish Twin Study on Ageing. The genetic and environmental influences on lung function were estimated by using genetic modeling. This thesis found that light smokers are more often female, well-educated, and exhibit a healthier lifestyle than heavy smokers. At individual level, light smoking is rarely a constant pattern. Light smoking, reducing from heavier smoking to light smoking, and relapsing to light smoking after quitting, are among patterns associated with an increased risk of chronic bronchitis and COPD. Constant light smoking is associated with an increased use of inhaled anticholinergics, a medication for CODP. In addition to smoking, other environmental factors influence lung function in the older age. During a three-year follow-up, new environmental effects influencing spirometry values were observed, whereas the genes affecting lung function remained mostly the same. In conclusion, no safe level of daily smoking exists with regard to pulmonary diseases. Even daily light smoking in middle-age is associated with increased respiratory morbidity later in life. Smoking reduction does not decrease the risk of COPD, and should not be recommended as an alternative to quitting smoking. In elderly people, attention should also be drawn to other factors that can prevent poor lung function.

Molecular Dynamics Investigation of Structure and Transport in the K2O-2SiO2 System Using a Partial Charge Based Model Potential

Potassium disilicate glass and melt have been investigated by using a new partial charge based potential model in which nonbridging oxygens are differentiated from bridging oxygens by their charges. The model reproduces the structural data pertaining to the coordination polyhedra around potassium and the various bond angle distributions excellently. The dynamics of the glass has been studied by using space and time correlation functions. It is found that K ions migrate by a diffusive mechanism in the melt and by hops below the glass transition temperature. They are also found to migrate largely through nonbridging oxygenrich sites in the silicate matrix, thus providing support to the predictions of the modified random network model.

Molecular dynamics Investigation of structure and transport in the K2O-2SiO2 system using a partial charge based model potential

Potassium disilicate glass and melt have been investigated by using anew partial charge based potential model in which nonbridging oxygens are differentiated from bridging oxygens by their charges. The model reproduces the structural data pertaining to the coordination polyhedra around potassium and the various bond angle distributions excellently. The dynamics of the glass has been studied by using space and time correlation functions. It is found that K ions migrate by a diffusive mechanism in the melt and by hops below the glass transition temperature. They are also found to migrate largely through nonbridging oxygen-rich sites in the silicate matrix, thus providing support to the predictions of the modified random network model.

Brownian dynamics simulation of dense binary colloidal mixtures. II. Translational and bond-orientational order

We report the Brownian dynamics simulation results on the translational and bond-angle-orientational correlations for charged colloidal binary suspensions as the interparticle interactions are increased to form a crystalline (for a volume fraction phi = 0.2) or a glassy (phi = 0.3) state. The translational order is quantified in terms of the two- and four-point density autocorrelation functions whose comparisons show that there is no growing correlation length near the glass transition. The nearest-neighbor orientational order is determined in terms of the quadratic rotational invariant Q(l) and the bond-orientational correlation functions g(l)(t). The l dependence of Q(l) indicates that icosahedral (l = 6) order predominates at the cost of the cubic order (l = 4) near the glass as well as the crystal transition. The density and orientational correlation functions for a supercooled liquid freezing towards a glass fit well to the streched-exponential form exp[-(t/tau)(beta)]. The average relaxation times extracted from the fitted stretched-exponential functions as a function of effective temperatures T* obey the Arrhenius law for liquids freezing to a crystal whereas these obey the Vogel-Tamman-Fulcher law exp[AT(0)*/(T* - T-0*)] for supercooled Liquids tending towards a glassy state. The value of the parameter A suggests that the colloidal suspensions are ''fragile'' glass formers like the organic and molecular liquids.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Relation between Local Structure and Glass Forming Ability of Liquid Alloys

An attempt has been made to describe the glass forming ability (GFA) of liquid alloys, using the concepts of the short range order (SRO) and middle range order (MRO) characterizing the liquid structure.A new approach to obtain good GFA of liquid alloys is based on the following four main factors: (1) formation of new SRO and competitive correlation with two or more kinds of SROs for crystallization, (2) stabilization of dense random packing by interaction between different types of SRO, (3) formation of stable cluster (SC) or middle range order (MRO) by harmonious coupling of SROs, and (4) difference between SRO characterizing the liquid structure and the near-neighbor environment in the corresponding equilibrium crystalline phases. The atomic volume mismatch estimated from the cube of the atomic radius was found to be a close relation with the minimum solute concentration for glass formation. This empirical guideline enables us to provide the optimum solute concentration for good GFA in some ternary alloys. Model structures, denoted by Bernal type and the Chemical Order type, were again tested in the novel description for the glass structure as a function of solute concentration. We illustrated the related energetics of the completion between crystal embryo and different types of SRO. Recent systematic measurements also provide that thermal diffusivity of alloys in the liquid state may be a good indicator of their GFA.