677 research outputs found

    Does better education mitigate risky health behavior? A mendelian randomization study

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    Education and risky health behaviors are strongly negatively correlated. Education may affect health behaviors by enabling healthier choices through higher disposable income, increasing information about the harmful effects of risky health behaviors, or altering time preferences. Alternatively, the observed negative correlation may stem from reverse causality or unobserved confounders. Based on the data from the Cardiovascular Risk in Young Finns Study linked to register-based information on educational attainment and family background, this paper identifies the causal effect of education on risky health behaviors. To examine causal effects, we used a genetic score as an instrument for years of education. We found that individuals with higher education allocated more attention to healthy habits. In terms of health behaviors, highly educated people were less likely to smoke. Some model specifications also indicated that the highly educated consumed more fruit and vegetables, but the results were imprecise in this regard. No causal effect was found between education and abusive drinking. In brief, inferences based on genetic instruments showed that higher education leads to better choices in some but not all dimensions of health behaviors

    A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module

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    A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper

    Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Gene Is a Risk Factor of Large-Vessel Atherosclerosis Stroke

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    BACKGROUND/PURPOSE: Genetic variation in proprotein convertase subtilisin/kexin type 9 (PCSK9) gene has been recently identified as an important determinant of plasma LDL-cholesterol and severity of coronary heart disease. We studied whether the PCSK9 gene is linked to the risk of ischemic stroke (IS) and with the development of intracranial atherosclerosis. METHODS/RESULTS: The pivotal E670G polymorphism, tagging an important haplotype of the PCSK9 gene, was genotyped in two independent studies. The Belgium Stroke Study included 237 middle aged (45-60) Belgian patients, with small-vessel occlusion (SVO) and large-vessel atherosclerosis stroke (LVA), and 326 gender and ethnicity matched controls (>60 yrs) without a history of stroke. In multivariate analysis the minor allele (G) carriers appeared as a significant predictor of LVA (OR = 3.52, 95% CI 1.25-9.85; p = 0.017). In a Finnish crossectional population based consecutive autopsy series of 604 males and females (mean age 62.5 years), G-allele carriers tended to have more severe allele copy number-dependent (p = 0.095) atherosclerosis in the circle of Willis and in its branches. CONCLUSION: Our findings in this unique combination of clinical and autopsy data, provide evidence that PCSK9 gene associates with the risk of LVA stroke subtype, and suggest that the risk is mediated by the severity of intracranial atherosclerosis.Journal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe

    Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase

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    Background Statins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized. Objectives This study sought to determine the molecular effects of statin therapy on multiple metabolic pathways. Methods Metabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts. Results Starting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R2 = 0.94, slope 1.00 ± 0.03). Conclusions Statin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug targets can inform indications, pleiotropic effects, and pharmacological mechanisms

    metaCCA : summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

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    Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies.Peer reviewe

    Validity of fatty liver disease indices in the presence of alcohol consumption

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    Background & aims Non-alcoholic fatty liver disease (NAFLD) and alcohol-related liver disease frequently coexist. While several blood-based indices exist for the detection of NAFLD, few studies have examined how alcohol use possibly impacts their diagnostic performance. We analysed the effects of alcohol use on the performance of indices for detecting fatty liver disease (FLD). Methods We included participants from the Cardiovascular Risk in Young Finns Study (Finnish sample) and KORA study (German sample) who underwent abdominal ultrasound or magnetic resonance imaging, respectively, for detection of FLD and had serum analyses available for calculation of Fatty Liver Index (FLI), Hepatic Steatosis Index (HSI), Lipid Accumulation Product (LAP), and Dallas Steatosis Index (DSI). Alcohol use was estimated by questionnaires as mean daily consumption and binge drinking (Finnish sample only). Predictive performance for FLD was assessed according to alcohol consumption. Results The study included 1426 (Finnish sample) and 385 (German sample) individuals, of which 234 (16%) and 168 (44%) had FLD by imaging. When alcohol consumption was 50 g/day). AUROCs decreased to 0.74-0.80 in the highest binge-drinking category (>2 times/week). Alcohol use correlated with FLI and LAP (r-range 0.09-0.16, p-rangePeer reviewe

    Genetic and observational evidence : No independent role for cholesterol efflux over static high-density lipoprotein concentration measures in coronary heart disease risk assessment

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    Background Observational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited. Objectives A large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC. Participants/methods Six independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants. Results HDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides. Conclusion HDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations.Peer reviewe

    Emergent multicellular life cycles in filamentous bacteria owing to density-dependent population dynamics

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    Filamentous bacteria are the oldest and simplest known multicellular life forms. By using computer simulations and experiments that address cell division in a filamentous context, we investigate some of the ecological factors that can lead to the emergence of a multicellular life cycle in filamentous life forms. The model predicts that if cell division and death rates are dependent on the density of cells in a population, a predictable cycle between short and long filament lengths is produced. During exponential growth, there will be a predominance of multicellular filaments, while at carrying capacity, the population converges to a predominance of short filaments and single cells. Model predictions are experimentally tested and confirmed in cultures of heterotrophic and phototrophic bacterial species. Furthermore, by developing a formulation of generation time in bacterial populations, it is shown that changes in generation time can alter length distributions. The theory predicts that given the same population growth curve and fitness, species with longer generation times have longer filaments during comparable population growth phases. Characterization of the environmental dependence of morphological properties such as length, and the number of cells per filament, helps in understanding the pre-existing conditions for the evolution of developmental cycles in simple multicellular organisms. Moreover, the theoretical prediction that strains with the same fitness can exhibit different lengths at comparable growth phases has important implications. It demonstrates that differences in fitness attributed to morphology are not the sole explanation for the evolution of life cycles dominated by multicellularity

    Glycoprotein Acetyls : A Novel Inflammatory Biomarker of Early Cardiovascular Risk in the Young

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    Background Low-grade inflammation in the young may contribute to the early development of cardiovascular disease. We assessed whether circulating levels of glycoprotein acetyls (GlycA) were better able to predict the development of adverse cardiovascular disease risk profiles compared with the more commonly used biomarker high-sensitivity CRP (C-reactive protein). Methods and Results A total of 3306 adolescents and young adults from the Avon Longitudinal Study of Parents and Children (mean age, 15.4 +/- 0.3; n=1750) and Cardiovascular Risk in Young Finns Study (mean age, 32.1 +/- 5.0; n=1556) were included. Baseline associations between inflammatory biomarkers, body composition, cardiovascular risk factors, and subclinical measures of vascular dysfunction were assessed cross-sectionally in both cohorts. Prospective risk of developing hypertension and metabolic syndrome during 9-to-10-year follow-up were also assessed as surrogate markers for future cardiovascular risk. GlycA showed greater within-subject correlation over 9-to-10-year follow-up in both cohorts compared with CRP, particularly in the younger adolescent group (r=0.36 versus 0.07). In multivariable analyses, GlycA was found to associate with multiple lifestyle-related cardiovascular disease risk factors, cardiometabolic risk factor burden, and vascular dysfunction (eg, mean difference in flow-mediated dilation=-1.2 [-1.8, -0.7]% per z-score increase). In contrast, CRP levels appeared predominantly driven by body mass index and showed little relationship to any measured cardiovascular risk factors or phenotypes. In both cohorts, only GlycA predicted future risk of both hypertension (risk ratio [RR], approximate to 1.1 per z-score increase for both cohorts) and metabolic syndrome (RR, approximate to 1.2-1.3 per z-score increase for both cohorts) in 9-to-10-year follow-up. Conclusions Low-grade inflammation captured by the novel biomarker GlycA is associated with adverse cardiovascular risk profiles from as early as adolescence and predicts future risk of hypertension and metabolic syndrome in up to 10-year follow-up. GlycA is a stable inflammatory biomarker which may capture distinct sources of inflammation in the young and may provide a more sensitive measure than CRP for detecting early cardiovascular risk.Peer reviewe

    A Longitudinal Multilevel Study of the "Social" Genotype and Diversity of the Phenotype

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    Sociability and social domain-related behaviors have been associated with better well-being and endogenous oxytocin levels. Inspection of the literature, however, reveals that the effects between sociability and health outcomes, or between sociability and genotype, are often weak or inconsistent. In the field of personality psychology, the social phenotype is often measured by error-prone assessments based on different theoretical frameworks, which can partly explain the inconsistency of the previous findings. In this study, we evaluated the generalizability of "sociability" measures by partitioning the population variance in adulthood sociability using five indicators from three personality inventories and assessed in two to four follow-ups over a 15-year period (n = 1,573 participants, 28,323 person-observations; age range 20-50 years). Furthermore, we tested whether this variance partition would shed more light to the inconsistencies surrounding the "social" genotype, by using four genetic variants (rs1042778, rs2254298, rs53576, rs3796863) previously associated with a wide range of human social functions. Based on our results, trait (between-individual) variance explained 23% of the variance in overall sociability, differences between sociability indicators explained 41%, state (within-individual) variance explained 5% and measurement errors explained 32%. The genotype was associated only with the sociability indicator variance, suggesting it has specific effects on sentimentality and emotional sharing instead of reflecting general sociability
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