No description available.

No description available.

No description available.

The United States is currently experiencing an epidemic of opioid use, use disorder, and overdose-related deaths. While studies have identified several loci that are associated with opioid use disorder (OUD) risk, the genetic basis for the ability to discontinue opioid use has not been investigated. Furthermore, very few studies have investigated the non-genetic factors that are predictive of opioid cessation or their predictive ability. In this thesis, I studied a novel phenotype–opioid cessation, defined as the time since last use of illicit opioids (< 6 months ago as not cease, >1 year ago as cease) among persons meeting lifetime DSM-5 criteria for opioid use disorder (OUD). In chapter two, I identified novel genetic variants and biological pathways that potentially regulate opioid cessation success through a genome wide study, as well as genetic overlap between opioid cessation and other substance cessation traits. In chapter three, I identified multiple non-genetic risk factors specific to each racial group that are predictive of opioid cessation from the same individuals analyzed in chapter two by applying several linear and non-linear machine learning techniques to a set of more than 3,000 variables assessed by a structured psychiatric interview. Factors identified from this atheoretical approach can be grouped into opioid use activities, other drug use, health conditions, and demographics, while the predictive accuracy as high as nearly 80% was achieved. The findings from this research generated more hypotheses for future studies to reference. In chapter four, I performed differential gene expression and network analysis on mice with different oxycodone (an opioid receptor agonist)-induced behaviors and compared the significantly associated genes and network modules with top-ranked genes identified in humans. The pathway cross-talks and gene homologs identified from both species illuminate the potential molecular mechanism of opioid behaviors. In summary, this thesis utilized statistical genetics, machine learning, and a computational biology framework to address factors that are associative with opioid cessation in humans, and cross-referenced the genetic findings in a mouse model. These findings serve as references for future studies and provide a framework for personalizing the treatment of OUD.

PhD (Molecular Medicine and Haematology), Faculty of Health Sciences, University of the Witwatersrand / Background: The availability of highly active antiretroviral (ARV) treatment in the South African government sector has reduced the morbidity and mortality associated with HIV-1 infection. However, ARV drug resistance and toxicity are major obstacles to achieving and maintaining virus suppression, but there is no provision for ARV drug resistance testing in the public sector. To date, most studies of ARV drug resistance in HIV-1 reverse transcriptase (RT) and protease (PR), are based on sequence data from HIV-1 subtype B, whereas subtype C is the predominant circulating subtype in South Africa. Moreover, host genetic polymorphisms associated with ARV drug toxicity have not been investigated in South African populations. This study evaluated viral and host genetic factors associated with ARV treatment outcome in 812 ARV drug-naive South African AIDS participants enrolled on the CIPRA-SA study from Johannesburg and Cape Town. Methodology: An affordable in-house genotyping protocol (subtype C specific) was established and validated to monitor the emergence of ARV drug resistance. This assay was used to genotype all CIPRA-SA participants failing the first- and second-line ARV drug regimens. Allellic discrimination assays to identify the G1344A, A6986G, G516T and C3435T SNPs in CYP3A4, 3A5, 2B6 and MDR-1, respectively, associated with ARV metabolism and absorption were performed. Results: The in-house ARV drug resistance assay successfully genotyped 95% of patient samples, including non-C subtypes from 8 African sites. Treatment failure was experienced in 371 participants, mainly due to toxicity (n=134) or virological failure (n=83). Overall, CIPRA-SA participants with a lower CD4+ T-cell count at study onset were more likely to experience viral failure. Genotyping using the in-house assay revealed that 6 participants had ARV drug resistance mutations at study entry. Treatment failure of 58 participants was a result of ARV drug resistance mutations, whereas 19 had no known ARV drug resistance mutations. The most frequent mutations were M184V (67%) and K103N (50%). K65R was present (3%) and one participant harboured TAMs. Longitudinal genotypic analysis showed that NNRTI mutations accumulated at a rate of one per three months left on failing therapy. No PR mutations were detected amongst participants experiencing second-line failure. The four SNPs analysed occured in similar frequencies between a background and the CIPRA-SA cohort. Furthermore, no statistically significant association could be found between these four SNPs and viral failure and/or toxicity. Conclusion: Overall, HIV-1 subtype C-infected individuals receiving ARV therapy develop many of the known subtype B drug resistance mutations. However, the ARV drug resistance patterns in the closely monitored CIPRA-SA cohort were less complex compared to published data from the region, confirming that more frequent viral load monitoring, genotyping, and a virological failure cut-off value of 1000 RNA copies/ml ensure a better prognosis, and preserve future ARV treatment options.

Prostate cancer is a large and increasing medical problem both in Sweden and in the rest of the developed world, with about 300.000 new cases diagnosed world wide annually. Despite the high incidence of this disease, little is known about the aetiology of prostate cancer. The aim of this study was to try to understand more about the natural history and to find possible a etiological risk factors for this tumour. In a population based study of prostate cancer cases in northern Sweden it was found that the large increase in prostate cancer during the last two decades was mainly caused by well (Gl) and moderately (G2) differentiated tumours. However, the incidence of poorly differentiated (G3) tumours remained unchanged. The introduction of new diagnostic methods is the most plausible explanation for the increase of these low grade tumours. The relative survival in prostate cancer was found to be independent of patient age at diagnosis, indicating that tumour proliferation and the aggressiveness of this disease is equal in all ages. However, due to the increasing occurrence of concurrent diseases with growing age the number of lost years caused by prostate cancer decreases dramatically in older age groups. The overall cause specific mortality for prostate cancer was found to be around 50%. In accordance with most other cancer tumours, the annual mortality rate decreased with longer survival also for prostate cancer patients. In a study from the Swedish Twin Register it was found that the proband concordance rates for prostate cancer were 4,5 time greater among monozygotic compared to dizygotic twins. In a large nation-wide cohort study of men who had a father with prostate cancer, the overall standardised incidence ratio (SIR) was 1.70 for prostate cancer. Younger age at diagnosis among the fathers were associated with an increased risk among sons. This cohort study and the twin study indicates that both inherited and familial factors are of importance in a subgroup of prostate cancer patients. In a prospective case-control study, both a high body mass index (BMI) and a high food intake were found to be independent risk factors for prostate cancer. Both BMI and a high food intake might be indicators of a high fat diet, which so far is the most consistent exogenous risk factor for prostate cancer. The use of tobacco or alcoholic beverages were not associated with prostate cancer risk. / <p>Härtill 5 uppsatser</p> / digitalisering@umu

Darbo tikslas. Įvertinti gyvensenos ir genetinių veiksnių sąsajas su dvynių antropometriniais rodikliais. Uždaviniai. 1. Nustatyti monozigotinių ir dizigotinių dvynių antropometrinius rodiklius; 2. Įvertinti antropometrinių rodiklių ir gyvensenos sąsajas su genetiniais veiksniais; 3. Nustatyti normalaus svorio ir antsvorio turinčių dvynių gyvensenos skirtumus; 4. Nustatyti gyvensenos veiksnių ryšį su antropometriniais rodikliais, atsižvelgiant į genetinius veiksnius. Tyrimo metodika. Tirti Lietuvoje gyvenantys 18–54 metų dvyniai, kurie yra įtraukti į Dvynių centro registrą ir kurių buvo žinomas elektroninio pašto adresas. Vykdyta apklausa paštu. Anketą sudarė 51 klausimas apie dvynių socialinius rodiklius, sveikatos būklę, jų ūgį ir svorį bei gyvensenos įpročius. Anketos buvo išsiųstos 146 dvynių poroms. Jas grąžino 159 asmenys (atsako dažnis 54,5 proc.). Analizuoti 70 (40 monozigotinių ir 30 dizigotinių) dvynių porų duomenys. Antsvorio paplitimas skaičiuotas pagal kūno masės indeksą (KMI>25 kg/m2). Rezultatai. Antsvorio paplitimas tarp vyrų buvo 31,3 proc., tarp moterų – 19,4 proc. Jis dažniau nustatytas 35 metų ir vyresniems bei turintiems kolegijos išsilavinimą dvyniams. Nustatyti stiprūs ryšiai tarp visų MZ dvynių porų antropometrinių rodiklių. Labiausiai susijęs buvo monozigotinių dvynių ūgis (koreliacijos koeficientas – 0,941). Monozigotiniai dvyniai dažniau turėjo vienodus fizinio aktyvumo, mitybos ir žalingus įpročius nei dizigotiniai. Antsvorio paplitimas buvo... [toliau žr. visą tekstą] / Aim of the study. To evaluate the associations of behavioural and genetic factors with anthropometrical measurements of twins. Objectives. 1. To assess the antropometric indicators of monozigotic and dizigotic twins; 2. To evaluate the relationship between genetical factors and anthropometric indicators; 3. To identify the differences in health behaviour of twins with normal weight and overweight; 4. To evaluate the aoosiations the behavioural factors with antropometric indicators, taking into account genetic factors. Methods. Study population was 18–54 years old twins living in Lithuania, which were registered in the Twin Center and have e-mail addresses. For this study, the original questionnaire was developed which included 51 questions on sociodemographic characteristics, health status, weight and height, and behavioural habits of twins. The questionnaires were sent by email to 146 twin pairs; 159 individuals returned the filled in questionnaires (response rate 54.5%). The data of 70 twin pairs (40 monozigotic ir 30 dizigotic) were analyzed. Overweight was defined when body mass index (BMI) was >25 kg/m2. The statistical analysis was performed using SPSS 13.0 software package for Windows Results. 31,3 percent of men and 19,4 percent of women had overweight. It is more common for twins over 35 years old, with college degree. A strong correlation among all monozigotic twin couples was found. The height of monozigotic twins was found to be the most related (correlation... [to full text]

No description available.

Statistical inference from molecular population genetic data is currently a very active area of research for two main reasons. First, in the past two decades an enormous amount of molecular genetic data have been produced and the amount of data is expected to grow even more in the future. Second, drawing inferences about complex population genetics problems, for example understanding the demographic and genetic factors that shaped modern populations, poses a serious statistical challenge. Amongst the many different kinds of genetic data that have appeared in the past two decades, the highly polymorphic microsatellites have played an important role. Microsatellites revolutionized the population genetics of natural populations, and were the initial tool for linkage mapping in humans and other model organisms. Despite their important role, and extensive use, the evolutionary dynamics of microsatellites are still not fully understood, and their statistical methods are often underdeveloped and do not adequately model microsatellite evolution. In this thesis, I address some aspects of this problem by assessing the performance of existing statistical tools, and developing some new ones. My work encompasses a range of statistical methods from simple hypothesis testing to more recent, complex computational statistical tools. This thesis consists of four main topics. First, I review the statistical methods that have been developed for microsatellites in population genetics applications. I review the different models of the microsatellite mutation process, and ask which models are the most supported by data, and how models were incorporated into statistical methods. I also present estimates of mutation parameters for several species based on published data. Second, I evaluate the performance of estimators of genetic relatedness using real data from five vertebrate populations. I demonstrate that the overall performance of marker-based pairwise relatedness estimators mainly depends on the population relatedness composition and may only be improved by the marker data quality within the limits of the population relatedness composition. Third, I investigate the different null hypotheses that may be used to test for independence between loci. Using simulations I show that testing for statistical independence (i.e. zero linkage disequilibrium, LD) is difficult to interpret in most cases, and instead a null hypothesis should be tested, which accounts for the “background LD” due to finite population size. I investigate the utility of a novel approximate testing procedure to circumvent this problem, and illustrate its use on a real data set from red deer. Fourth, I explore the utility of Approximate Bayesian Computation, inference based on summary statistics, to estimate demographic parameters from admixed populations. Assuming a simple demographic model, I show that the choice of summary statistics greatly influences the quality of the estimation, and that different parameters are better estimated with different summary statistics. Most importantly, I show how the estimation of most admixture parameters can be considerably improved via the use of linkage disequilibrium statistics from microsatellite data.

<p>This study investigated the associations between IL-4 -590 C/T and IL-10 -1087 A/G polymorphisms and malariometric indexes in the Fulani and the Dogon ethnic groups living in sympatry in Mali and differing in susceptibility to malaria. The correlations between antibodies level and parasitological data as well as splenomegaly were assessed. The impact of IL-4 -590 variants on the levels of the studied antibodies was also studied. </p><p>The allele and genotype frequencies of both studied SNPs differed significantly between the two groups. The Fulani IL-4 T allele carriers had a significantly higher infection prevalence compared with those carrying the CC genotype. No correlation between anti-malarial antibody levels and parasite prevalence was seen in any of the communities. In the Fulani, the increase in total IgE levels was related to the presence of infection. Malaria-specific IgG4 levels were negatively correlated to the number of clones within the Fulani. The Fulani IL-4 T allele carriers had higher total and malaria-specific IgE levels, compared to the CC genotype carriers. These results suggest that the amount of antibodies may not be the key element in the protection against malaria. IgG4 might be involved in protection against malaria. The impact of IL-4 -590 variants on the antibody levels may be affected by other genetic/epigenetic/epistatic or environmental factors. </p><p>In the study in Senegal, multiplicity of infection (MOI) increased after the transmission season in all subjects, except in α-thalassaemic and in G6PD-mutated children, suggesting that α-thalassaemia may protect against infection by certain parasite strains. G6PD-mutated individuals may resist against increase in MOI after the transmission season due to rapid clearance of infection at an early stage. HbAs and the ABO system do not affect MOI in asymptomatic individuals. MOI was positively correlated to parasitemia, and did not vary over age (in the range of 2 to 10 years). No relation between MOI and clinical attack was noted. </p>