Attempted suicide in mental disorders in young adulthood

Background  

Nationwide general population study establishes the prevalence of suicide attempts in different mental disorders among young adults and their sociodemographic correlates. Current psychiatric symptoms are also examined.     

Determinants of Changes in Bone Density: A 5-Year Follow-Up Study of Adult Male Monozygotic Twins

The relative importance of determinants in bone mineral density (BMD) in adult men is partly unclear. Our goals were to investigate the effects of familial aggregation and behavioral factors on the change in BMD during a 5-yr follow-up. Subjects (n = 140) were 70 exposure-discordant monozygotic twin pairs (age 35–69 yr). BMD was measured with the same dual-energy X-ray absorptiometry scanner at baseline and at the 5-yr follow-up. A variety of covariates were used including physical examination and interview data. Multivariate linear regression was used. The mean annual decrease in femoral BMD was 0.2%. The mean lumbar BMD was unchanged, although 8–17% of subjects had a decrease of more than 5%. Familial aggregation explained 14% of the changes in femoral BMD and 19% in lumbar BMD. The stability of BMD in the follow-up was high, both for individuals (intraclass correlation coefficient [ICC] = 0.90–0.94) and for co-twins in a pair (ICC = 0.77–0.84). In femoral BMD, use of alcohol (p = 0.006), coffee (p = 0.046), and beta-blockers (p = 0.043) led to increases, whereas smoking led to a decrease (p < 0.01). We concluded that frequent increases in BMD, influenced by beta-blockers, partly explain the minor mean changes during follow-up; however, about every 10th subject had a significant decrease. Overall, familial effects played a dominant role in BMD changes in adult men.     

Deterioration of initially accepted radiological alignment of conservatively treated AO type-C distal radius fractures: mid-term outcome

European Journal of Orthopaedic Surgery & Traumatology - It still remains controversial how often the once-accepted radiological alignment of an AO type-C distal radius fracture deteriorates...     

Hierarchical Bayesian Model for Rare Variant Association Analysis Integrating Genotype Uncertainty in Human Sequence Data

Next‐generation sequencing (NGS) has led to the study of rare genetic variants, which possibly explain the missing heritability for complex diseases. Most existing methods for rare variant (RV) association detection do not account for the common presence of sequencing errors in NGS data. The errors can largely affect the power and perturb the accuracy of association tests due to rare observations of minor alleles. We developed a hierarchical Bayesian approach to estimate the association between RVs and complex diseases. Our integrated framework combines the misclassification probability with shrinkage‐based Bayesian variable selection. It allows for flexibility in handling neutral and protective RVs with measurement error, and is robust enough for detecting causal RVs with a wide spectrum of minor allele frequency (MAF). Imputation uncertainty and MAF are incorporated into the integrated framework to achieve the optimal statistical power. We demonstrate that sequencing error does significantly affect the findings, and our proposed model can take advantage of it to improve statistical power in both simulated and real data. We further show that our model outperforms existing methods, such as sequence kernel association test (SKAT). Finally, we illustrate the behavior of the proposed method using a Finnish low‐density lipoprotein cholesterol study, and show that it identifies an RV known as FH North Karelia in LDLR gene with three carriers in 1,155 individuals, which is missed by both SKAT and Granvil.