ABSTRACT
Bayesian spatial modeling has become important in disease mapping and has also been suggested as a useful tool in genetic fine mapping. We have implemented the Potts model and applied it to the Genetic Analysis Workshop 14 (GAW14) simulated data. Because the "answers" were known we have analyzed latent phenotype P1-related observed phenotypes affection status (genetically determined) and i (random) in the Danacaa population replicate 2. Analysis of the microsatellite/single-nucleotide polymorphism-based haplotypes at chromosomes 1 and 3 failed to identify multiple clusters of haplotype effects. However, the analysis of separately simulated data with postulated differences in the effects of the two clusters has yielded clear estimated division into the two clusters, demonstrating the correctness of the algorithm. Although we could not clearly identify the disease-related and the non-associated groups of haplotypes, results of both GAW14 and our own simulation encourage us to improve the efficiency and sensitivity of the estimation algorithm and to further compare the proposed method with more traditional methods.
Subject(s)
Genetic Predisposition to Disease , Haplotypes/genetics , Models, Genetic , Computer Simulation , Ethnicity/genetics , Humans , Reproducibility of ResultsABSTRACT
Background. Increased rates of coronary heart disease (CHD) and cerebrovascular disease in later life have been repeatedly observed in subjects with low birth-weight. One possible reason for low birth-weight is prenatal stress. Little is known about the influence of prenatal stress on lifelong health outcomes. Aims. In this study we investigate the influence of prenatal stress on CHD and cerebrovascular disease incidence in adult life. Methods. We analysed data originating from the Helsinki Birth Cohort Study including hospital data from all men and women born between 1934 and 1944 (n = 13,039) in two hospitals of Helsinki. We estimated the hazard function based on Weibull distribution. We compared those exposed and unexposed to bombings while in utero in terms of lifelong CHD and cerebrovascular disease hazard. Results. In women exposed to bombings while in utero, we observed higher survival rates of both CHD and cerebrovascular disease than in those unexposed. In men, the results were ambiguous. Conclusions. Our findings suggest that prenatal exposure to severe stress may be associated with protective effects on the development of CHD in later life.
Subject(s)
Cerebrovascular Disorders/etiology , Coronary Disease/etiology , Prenatal Exposure Delayed Effects/epidemiology , Stress, Physiological , Age Factors , Aged , Aged, 80 and over , Cerebrovascular Disorders/epidemiology , Cohort Studies , Coronary Disease/epidemiology , Female , Finland , Humans , Infant, Low Birth Weight , Infant, Newborn , Male , Middle Aged , Pregnancy , Prenatal Exposure Delayed Effects/physiopathology , Proportional Hazards Models , Sex Factors , Survival Rate , WarfareABSTRACT
BACKGROUND: Previous studies have suggested that seasonal variation and weather conditions have an influence on the incidence and mortality of acute myocardial infarction (AMI). The influence of these factors on AMI: case fatality is less studied. Aims. The aim of this study was to examine the temporal variation of AMI case fatality and the effect of daily weather conditions on it. METHODS: We analysed death registry and hospital discharge data from all men and women (n=7328) with their first AMI occurrence in the seven largest cities in Finland in the years 1983, 1988, and 1993, aged 25 to 74 years. RESULTS: The mean annual 28-day case fatality was 44%. We found significant weekly and monthly variation of case fatality (P<0.001). The December holiday season had the highest case fatality throughout the year in women and men aged 65-74 years (P<0.05). The highest weekly case fatality was on Sundays; it differed significantly from the rest of the weekdays only for the oldest age-group (64-74) (P<0.01). CONCLUSIONS: There is significant weekly and monthly variation in case fatality of AMI. The highest case fatality risk for AMI is during the Christmas season and on Sundays. Weather conditions were not found to have an effect on the case fatality.