90 resultados para population modeling

em Helda - Digital Repository of University of Helsinki


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Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

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Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

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Cyclosporine is an immunosuppressant drug with a narrow therapeutic index and large variability in pharmacokinetics. To improve cyclosporine dose individualization in children, we used population pharmacokinetic modeling to study the effects of developmental, clinical, and genetic factors on cyclosporine pharmacokinetics in altogether 176 subjects (age range: 0.36–20.2 years) before and up to 16 years after renal transplantation. Pre-transplantation test doses of cyclosporine were given intravenously (3 mg/kg) and orally (10 mg/kg), on separate occasions, followed by blood sampling for 24 hours (n=175). After transplantation, in a total of 137 patients, cyclosporine concentration was quantified at trough, two hours post-dose, or with dose-interval curves. One-hundred-four of the studied patients were genotyped for 17 putatively functionally significant sequence variations in the ABCB1, SLCO1B1, ABCC2, CYP3A4, CYP3A5, and NR1I2 genes. Pharmacokinetic modeling was performed with the nonlinear mixed effects modeling computer program, NONMEM. A 3-compartment population pharmacokinetic model with first order absorption without lag-time was used to describe the data. The most important covariate affecting systemic clearance and distribution volume was allometrically scaled body weight i.e. body weight**3/4 for clearance and absolute body weight for volume of distribution. The clearance adjusted by absolute body weight declined with age and pre-pubertal children (< 8 years) had an approximately 25% higher clearance/body weight (L/h/kg) than did older children. Adjustment of clearance for allometric body weight removed its relationship to age after the first year of life. This finding is consistent with a gradual reduction in relative liver size towards adult values, and a relatively constant CYP3A content in the liver from about 6–12 months of age to adulthood. The other significant covariates affecting cyclosporine clearance and volume of distribution were hematocrit, plasma cholesterol, and serum creatinine, explaining up to 20%–30% of inter-individual differences before transplantation. After transplantation, their predictive role was smaller, as the variations in hematocrit, plasma cholesterol, and serum creatinine were also smaller. Before transplantation, no clinical or demographic covariates were found to affect oral bioavailability, and no systematic age-related changes in oral bioavailability were observed. After transplantation, older children receiving cyclosporine twice daily as the gelatine capsule microemulsion formulation had an about 1.25–1.3 times higher bioavailability than did the younger children receiving the liquid microemulsion formulation thrice daily. Moreover, cyclosporine oral bioavailability increased over 1.5-fold in the first month after transplantation, returning thereafter gradually to its initial value in 1–1.5 years. The largest cyclosporine doses were administered in the first 3–6 months after transplantation, and thereafter the single doses of cyclosporine were often smaller than 3 mg/kg. Thus, the results suggest that cyclosporine displays dose-dependent, saturable pre-systemic metabolism even at low single doses, whereas complete saturation of CYP3A4 and MDR1 (P-glycoprotein) renders cyclosporine pharmacokinetics dose-linear at higher doses. No significant associations were found between genetic polymorphisms and cyclosporine pharmacokinetics before transplantation in the whole population for which genetic data was available (n=104). However, in children older than eight years (n=22), heterozygous and homozygous carriers of the ABCB1 c.2677T or c.1236T alleles had an about 1.3 times or 1.6 times higher oral bioavailability, respectively, than did non-carriers. After transplantation, none of the ABCB1 SNPs or any other SNPs were found to be associated with cyclosporine clearance or oral bioavailability in the whole population, in the patients older than eight years, or in the patients younger than eight years. In the whole population, in those patients carrying the NR1I2 g.-25385C–g.-24381A–g.-205_-200GAGAAG–g.7635G–g.8055C haplotype, however, the bioavailability of cyclosporine was about one tenth lower, per allele, than in non-carriers. This effect was significant also in a subgroup of patients older than eight years. Furthermore, in patients carrying the NR1I2 g.-25385C–g.-24381A–g.-205_-200GAGAAG–g.7635G–g.8055T haplotype, the bioavailability was almost one fifth higher, per allele, than in non-carriers. It may be possible to improve individualization of cyclosporine dosing in children by accounting for the effects of developmental factors (body weight, liver size), time after transplantation, and cyclosporine dosing frequency/formulation. Further studies are required on the predictive value of genotyping for individualization of cyclosporine dosing in children.

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Background. Evidence of cognitive dysfunction in depressive and anxiety disorders is growing. However, the neuropsychological profile of young adults has received only little systematic investigation, although depressive and anxiety disorders are major public health problems for this age group. Available studies have typically failed to account for psychiatric comorbidity, and samples derived from population-based settings have also seldom been investigated. Burnout-related cognitive functioning has previously been investigated in only few studies, again all using clinical samples and wide age groups. Aims. Based on the information gained by conducting a comprehensive review, studies on cognitive impairment in depressive and anxiety disorders among young adults are rare. The present study examined cognitive functioning in young adults with a history of unipolar depressive or anxiety disorders in comparison to healthy peers, and associations of current burnout symptoms with cognitive functioning, in a population-based setting. The aim was also to determine whether cognitive deficits vary as a function of different disorder characteristics, such as severity, psychiatric comorbidity, age at onset, or the treatments received. Methods. Verbal and visual short-term memory, verbal long-term memory and learning, attention, psychomotor processing speed, verbal intelligence, and executive functioning were measured in a population-based sample of 21-35 year olds. Performance was compared firstly between participants with pure non-psychotic depression (n=68) and healthy peers (n=70), secondly between pure (n=69) and comorbid depression (n=57), and thirdly between participants with anxiety disorders (n=76) and healthy peers (n=71). The diagnostic procedure was based on the SCID interview. Fourthly, the associations of current burnout symptoms, measured with the Maslach Burnout Inventory General Survey, and neuropsychological test performance were investigated among working young adults (n=225). Results. Young adults with depressive or anxiety disorders, with or without psychiatric comorbidity, were not found to have major cognitive impairments when compared to healthy peers. Only mildly compromised verbal learning was found among depressed participants. Pure and comorbid depression groups did not differ in cognitive functioning, either. Among depressed participants, those who had received treatment showed more impaired verbal memory and executive functioning, and earlier onset corresponded with more impaired executive functioning. In anxiety disorders, psychotropic medication and low psychosocial functioning were associated with deficits in executive functioning, psychomotor processing speed, and visual short-term memory. Current burnout symptoms were associated with better performance in verbal working memory and verbal intelligence. However, lower examiner-rated social and occupational functioning was associated with problems in verbal attention, memory, and learning. Conclusions. Depression, anxiety disorders, or burnout symptoms may not be associated with major cognitive deficits among young adults derived from the general population. Even psychiatric comorbidity may not aggravate cognitive functioning in depressive or anxiety disorders among these young adults. However, treatment-seeking in depression was found to be associated with cognitive deficits, suggesting that these deficits relate to increased distress. Additionally, early-onset depression, found to be associated with executive dysfunction, may represent a more severe form of the disorder. In anxiety disorders, those with low symptom-related psychosocial functioning may have cognitive impairment. An association with self-reported burnout symptoms and cognitive deficits was not detected, but individuals with low social and occupational functioning may have impaired cognition.

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Distinct endogenous network events, generated independently of sensory input, are a general feature of various structures of the immature central nervous system. In the immature hippocampus, these type of events are seen as "giant depolarizing potentials" (GDPs) in intracellular recordings in vitro. GABA, the major inhibitory neurotransmitter of the adult brain, has a depolarizing action in immature neurons, and GDPs have been proposed to be driven by GABAergic transmission. Moreover, GDPs have been thought to reflect an early pattern that disappears during development in parallel with the maturation of hyperpolarizing GABAergic inhibition. However, the adult hippocampus in vivo also generates endogenous network events known as sharp (positive) waves (SPWs), which reflect synchronous discharges of CA3 pyramidal neurons and are thought to be involved in cognitive functions. In this thesis, mechanisms of GDP generation were studied with intra- and extracellular recordings in the neonatal rat hippocampus in vitro and in vivo. Immature CA3 pyramidal neurons were found to generate intrinsic bursts of spikes and to act as cellular pacemakers for GDP activity whereas depolarizing GABAergic signalling was found to have a temporally non-patterned facilitatory role in the generation of the network events. Furthermore, the data indicate that the intrinsic bursts of neonatal CA3 pyramidal neurons and, consequently, GDPs are driven by a persistent Na+ current and terminated by a slow Ca2+-dependent K+ current. Gramicidin-perforated patch recordings showed that the depolarizing driving force for GABAA receptor-mediated actions is provided by Cl- uptake via the Na-K-C1 cotransporter, NKCC1, in the immature CA3 pyramids. A specific blocker of NKCC1, bumetanide, inhibited SPWs and GDPs in the neonatal rat hippocampus in vivo and in vitro, respectively. Finally, pharmacological blockade of the GABA transporter-1 prolonged the decay of the large GDP-associated GABA transients but not of single postsynaptic GABAA receptor-mediated currents. As a whole the data in this thesis indicate that the mechanism of GDP generation, based on the interconnected network of bursting CA3 pyramidal neurons, is similar to that involved in adult SPW activity. Hence, GDPs do not reflect a network pattern that disappears during development but they are the in vitro counterpart of neonatal SPWs.

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Aims: The aims of this study were 1) to identify and describe health economic studies that have used quality-adjusted life years (QALYs) based on actual measurements of patients' health-related quality of life (HRQoL); 2) to test the feasibility of routine collection of health-related quality of life (HRQoL) data as an indicator of effectiveness of secondary health care; and 3) to establish and compare the cost-utility of three large-volume surgical procedures in a real-world setting in the Helsinki University Central Hospital, a large referral hospital providing secondary and tertiary health-care services for a population of approximately 1.4 million. Patients and methods: So as to identify studies that have used QALYs as an outcome measure, a systematic search of the literature was performed using the Medline, Embase, CINAHL, SCI and Cochrane Library electronic databases. Initial screening of the identified articles involved two reviewers independently reading the abstracts; the full-text articles were also evaluated independently by two reviewers, with a third reviewer used in cases where the two reviewers could not agree a consensus on which articles should be included. The feasibility of routinely evaluating the cost-effectiveness of secondary health care was tested by setting up a system for collecting HRQoL data on approximately 4 900 patients' HRQoL before and after operative treatments performed in the hospital. The HRQoL data used as an indicator of treatment effectiveness was combined with diagnostic and financial indicators routinely collected in the hospital. To compare the cost-effectiveness of three surgical interventions, 712 patients admitted for routine operative treatment completed the 15D HRQoL questionnaire before and also 3-12 months after the operation. QALYs were calculated using the obtained utility data and expected remaining life years of the patients. Direct hospital costs were obtained from the clinical patient administration database of the hospital and a cost-utility analysis was performed from the perspective of the provider of secondary health care services. Main results: The systematic review (Study I) showed that although QALYs gained are considered an important measure of the effectiveness of health care, the number of studies in which QALYs are based on actual measurements of patients' HRQoL is still fairly limited. Of the reviewed full-text articles, only 70 reported QALYs based on actual before after measurements using a valid HRQoL instrument. Collection of simple cost-effectiveness data in secondary health care is feasible and could easily be expanded and performed on a routine basis (Study II). It allows meaningful comparisons between various treatments and provides a means for allocating limited health care resources. The cost per QALY gained was 2 770 for cervical operations and 1 740 for lumbar operations. In cases where surgery was delayed the cost per QALY was doubled (Study III). The cost per QALY ranges between subgroups in cataract surgery (Study IV). The cost per QALY gained was 5 130 for patients having both eyes operated on and 8 210 for patients with only one eye operated on during the 6-month follow-up. In patients whose first eye had been operated on previous to the study period, the mean HRQoL deteriorated after surgery, thus precluding the establishment of the cost per QALY. In arthroplasty patients (Study V) the mean cost per QALY gained in a one-year period was 6 710 for primary hip replacement, 52 270 for revision hip replacement, and 14 000 for primary knee replacement. Conclusions: Although the importance of cost-utility analyses has during recent years been stressed, there are only a limited number of studies in which the evaluation is based on patients own assessment of the treatment effectiveness. Most of the cost-effectiveness and cost-utility analyses are based on modeling that employs expert opinion regarding the outcome of treatment, not on patient-derived assessments. Routine collection of effectiveness information from patients entering treatment in secondary health care turned out to be easy enough and did not, for instance, require additional personnel on the wards in which the study was executed. The mean patient response rate was more than 70 %, suggesting that patients were happy to participate and appreciated the fact that the hospital showed an interest in their well-being even after the actual treatment episode had ended. Spinal surgery leads to a statistically significant and clinically important improvement in HRQoL. The cost per QALY gained was reasonable, at less than half of that observed for instance for hip replacement surgery. However, prolonged waiting for an operation approximately doubled the cost per QALY gained from the surgical intervention. The mean utility gain following routine cataract surgery in a real world setting was relatively small and confined mostly to patients who had had both eyes operated on. The cost of cataract surgery per QALY gained was higher than previously reported and was associated with considerable degree of uncertainty. Hip and knee replacement both improve HRQoL. The cost per QALY gained from knee replacement is two-fold compared to hip replacement. Cost-utility results from the three studied specialties showed that there is great variation in the cost-utility of surgical interventions performed in a real-world setting even when only common, widely accepted interventions are considered. However, the cost per QALY of all the studied interventions, except for revision hip arthroplasty, was well below 50 000, this figure being sometimes cited in the literature as a threshold level for the cost-effectiveness of an intervention. Based on the present study it may be concluded that routine evaluation of the cost-utility of secondary health care is feasible and produces information essential for a rational and balanced allocation of scarce health care resources.

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The major aim of this thesis was to examine the origins and distribution of uniparental and autosomal genetic variation among the Finno-Ugric-speaking human populations living in Boreal and Arctic regions of North Eurasia. In more detail, I aimed to disentangle the underlying molecular and population genetic factors which have produced the patterns of uniparental and autosomal genetic diversity in these populations. Among Finno-Ugrics the genetic amalgamation and clinal distribution of West and East Eurasian gene pools were observed within uniparental markers. This admixture indicates that North Eurasia was colonized through Central Asia/ South Siberia by human groups already carrying both West and East Eurasian lineages. The complex combination of founder effects, gene flow and genetic drift underlying the genetic diversity of the Finno-Ugric- speaking populations were emphasized by low haplotype diversity within and among uniparental and biparental markers. A high prevalence of lactase persistence allele among the North Eurasian Finno- Ugric agriculturalist populations was also shown indicating a local adaptation to subsistence change with lactose rich diet. Moreover, the haplotype background of lactase persistence allele among the Finno- Ugric-speakers strongly suggested that the lactase persistence T-13910 mutation was introduced independently more than once to the North Eurasian gene pool. A significant difference in genetic diversity, haplotype structure and LD distribution within the cytochrome P450 CYP2C and CYP2D regions revealed the unique gene pool of the Finno-Ugric Saami created mainly by population genetic processes compared to other Europeans and sub-Saharan Mandenka population. From all studied populations the Saami showed also significantly the highest allele frequency of a CYP2C19 gene mutation causing variable drug reactions. The diversity patterns observed within CYP2C and CYP2D regions emphasize the strong effect of demographic history shaping genetic diversity and LD especially among such small and constant size populations as the Finno-Ugric-speaking Saami. Moreover, the increased LD in Saami due to genetic drift and/or admixture was shown to offer an advantage for further attempts to identify alleles associated to common complex pharmacogenetic traits.

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Objectives of this study were to determine secular trends of diabetes prevalence in China and develop simple risk assessment algorithms for screening individuals with high-risk for diabetes or with undiagnosed diabetes in Chinese and Indian adults. Two consecutive population based surveys in Chinese and a prospective study in Mauritian Indians were involved in this study. The Chinese surveys were conducted in randomly selected populations aged 20-74 years in 2001-2002 (n=14 592) and 35-74 years in 2006 (n=4416). A two-step screening strategy using fasting capillary plasma glucose (FCG) as first-line screening test followed by standard 2-hour 75g oral glucose tolerance tests (OGTTs) was applied to 12 436 individuals in 2001, while OGTTs were administrated to all participants together with FCG in 2006 and to 2156 subjects in 2002. In Mauritius, two consecutive population based surveys were conducted in Mauritian Indians aged 20-65 years in 1987 and 1992; 3094 Indians (1141 men), who were not diagnosed as diabetes at baseline, were reexamined with OGTTs in 1992 and/or 1998. Diabetes and pre-diabetes was defined following 2006 World Health Organization/ International Diabetes Federation Criteria. Age-standardized, as well as age- and sex-specific, prevalence of diabetes and pre-diabetes in adult Chinese was significantly increased from 12.2% and 15.4% in 2001 to 16.0% and 21.2% in 2006, respectively. A simple Chinese diabetes risk score was developed based on the data of Chinese survey 2001-2002 and validated in the population of survey 2006. The risk scores based on β coefficients derived from the final Logistic regression model ranged from 3 – 32. When the score was applied to the population of survey 2006, the area under operating characteristic curve (AUC) of the score for screening undiagnosed diabetes was 0.67 (95% CI, 0.65-0.70), which was lower than the AUC of FCG (0.76 [0.74-0.79]), but similar to that of HbA1c (0.68 [0.65-0.71]). At a cut-off point of 14, the sensitivity and specificity of the risk score in screening undiagnosed diabetes was 0.84 (0.81-0.88) and 0.40 (0.38-0.41). In Mauritian Indian, body mass index (BMI), waist girth, family history of diabetes (FH), and glucose was confirmed to be independent risk predictors for developing diabetes. Predicted probabilities for developing diabetes derived from a simple Cox regression model fitted with sex, FH, BMI and waist girth ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, the AUC of the predicted probabilities was 0.62 (95% CI, 0.56-0.68) in men and 0.64(0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity was 0.72(0.71-0.74) and 0.47(0.45-0.49) in men; and 0.77(0.75-0.78) and 0.50(0.48-0.52) in women, respectively. In conclusion, there was a rapid increase in prevalence of diabetes in Chinese adults from 2001 to 2006. The simple risk assessment algorithms based on age, obesity and family history of diabetes showed a moderate discrimination of diabetes from non-diabetes, which may be used as first line screening tool for diabetes and pre-diabetes, and for health promotion purpose in Chinese and Indians.

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Pharmacogenetics deals with genetically determined variation in drug response. In this context, three phase I drug-metabolizing enzymes, CYP2D6, CYP2C9, and CYP2C19, have a central role, affecting the metabolism of about 20-30% of clinically used drugs. Since genes coding for these enzymes in human populations exhibit high genetic polymorphism, they are of major pharmacogenetic importance. The aims of this study were to develop new genotyping methods for CYP2D6, CYP2C9, and CYP2C19 that would cover the most important genetic variants altering the enzyme activity, and, for the first time, to describe the distribution of genetic variation at these loci on global and microgeographic scales. In addition, pharmacogenetics was applied to a postmortem forensic setting to elucidate the role of genetic variation in drug intoxications, focusing mainly on cases related to tricyclic antidepressants, which are commonly involved in fatal drug poisonings in Finland. Genetic variability data were obtained by genotyping new population samples by the methods developed based on PCR and multiplex single-nucleotide primer extension reaction, as well as by collecting data from the literature. Data consisted of 138, 129, and 146 population samples for CYP2D6, CYP2C9, and CYP2C19, respectively. In addition, over 200 postmortem forensic cases were examined with respect to drug and metabolite concentrations and genotypic variation at CYP2D6 and CYP2C19. The distribution of genetic variation within and among human populations was analyzed by descriptive statistics and variance analysis and by correlating the genetic and geographic distances using Mantel tests and spatial autocorrelation. The correlation between phenotypic and genotypic variation in drug metabolism observed in postmortem cases was also analyzed statistically. The genotyping methods developed proved to be informative, technically feasible, and cost-effective. Detailed molecular analysis of CYP2D6 genetic variation in a global survey of human populations revealed that the pattern of variation was similar to those of neutral genomic markers. Most of the CYP2D6 diversity was observed within populations, and the spatial pattern of variation was best described as clinal. On the other hand, genetic variants of CYP2D6, CYP2C9, and CYP2C19 associated with altered enzymatic activity could reach extremely high frequencies in certain geographic regions. Pharmacogenetic variation may also be significantly affected by population-specific demographic histories, as seen within the Finnish population. When pharmacogenetics was applied to a postmortem forensic setting, a correlation between amitriptyline metabolic ratios and genetic variation at CYP2D6 and CYP2C19 was observed in the sample material, even in the presence of confounding factors typical for these cases. In addition, a case of doxepin-related fatal poisoning was shown to be associated with a genetic defect at CYP2D6. Each of the genes studied showed a distinct variation pattern in human populations and high frequencies of altered activity variants, which may reflect the neutral evolution and/or selective pressures caused by dietary or environmental exposure. The results are relevant also from the clinical point of view since the genetic variation at CYP2D6, CYP2C9, and CYP2C19 already has a range of clinical applications, e.g. in cancer treatment and oral anticoagulation therapy. This study revealed that pharmacogenetics may also contribute valuable information to the medicolegal investigation of sudden, unexpected deaths.

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A population-based early detection program for breast cancer has been in progress in Finland since 1987. According to regulations during the study period 1987-2001, free of charge mammography screening was offered every second year to women aged 50-59 years. Recently, the screening service was decided to be extended to age group 50-69. However, the scope of the program is still frequently discussed in public and information about potential impacts of mass-screening practice changes on future breast cancer burden is required. The aim of this doctoral thesis is to present methodologies for taking into account the mass-screening invitation information in breast cancer burden predictions, and to present alternative breast cancer incidence and mortality predictions up to 2012 based on scenarios of the future screening policy. The focus of this work is not on assessing the absolute efficacy but the effectiveness of mass-screening, and, by utilizing the data on invitations, on showing the estimated impacts of changes in an existing screening program on the short-term predictions. The breast cancer mortality predictions are calculated using a model that combines incidence, cause-specific and other cause survival on individual level. The screening invitation data are incorporated into modeling of breast cancer incidence and survival by dividing the program into separate components (first and subsequent rounds and years within them, breaks, and post screening period) and defining a variable that gives the component of the screening program. The incidence is modeled using a Poisson regression approach and the breast cancer survival by applying a parametric mixture cure model, where the patient population is allowed to be a combination of cured and uncured patients. The patients risk to die from other causes than breast cancer is allowed to differ from that of a corresponding general population group and to depend on age and follow-up time. As a result, the effects of separate components of the screening program on incidence, proportion of cured and the survival of the uncured are quantified. According to the predictions, the impacts of policy changes, like extending the program from age group 50-59 to 50-69, are clearly visible on incidence while the effects on mortality in age group 40-74 are minor. Extending the screening service would increase the incidence of localized breast cancers but decrease the rates of non-localized breast cancer. There were no major differences between mortality predictions yielded by alternative future scenarios of the screening policy: Any policy change would have at the most a 3.0% reduction on overall breast cancer mortality compared to continuing the current practice in the near future.

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In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.