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Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\\CHRNA3\\CHRNB4, CHRNB3\\CHRNA6 and EGLN2\\CYP2A6. Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations. We employed targeted capture of the CHRNA5\\CHRNA3\\CHRNB4, CHRNB3\\CHRNA6, and EGLN2\\CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations. In total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3\\CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6. Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2. We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up.

We examine the role that an exogenous increase in household income due to a government transfer unrelated to household characteristics plays in children's long run outcomes. Children in affected households have higher levels of education in their young adulthood and a lower incidence of criminality for minor offenses. Effects differ by initial household poverty status. An additional $4000 per year for the poorest households increases educational attainment by one year at age 21 and reduces having ever committed a minor crime by 22% at ages 16-17. Our evidence suggests that improved parental quality is a likely mechanism for the change.

We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12–70 years, Australia: 16–73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a ‘rolling weights’ model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41–70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.

OBJECTIVES: Pediatric chronic physical illness and adult psychiatric disorders are substantial sources of burden for family care-takers, but little attention has been paid to parental burden resulting from children's or adolescents' psychiatric disorders. This paper describes the predictors of perceived parental burden and its impact on the use of specialty mental health and school services. METHODS: A representative general population sample of 1015 9-, 11-, and 13-year-olds and their parents completed structured psychiatric diagnostic interviews and the Child and Adolescent Burden Assessment. RESULTS: Weighted estimates indicated that 10.7% of parents in the general population perceived burden resulting from their children's symptomatology. Significant predictors of perceived burden were levels of child symptomatology and impairment and parental mental health problems. Children's depressive and anxiety disorders were associated with less burden than other diagnoses. The effects of child disorder severity on specialty mental health service use appeared to be mediated by the level of burden induced. CONCLUSIONS: Substantial levels of parental burden resulted from child psychiatric disorders and were a major reason for specialist mental health service use.

The NIMH Diagnostic Interview Schedule for Children (DISC) was used to evaluate 40 psychiatric referrals aged 7-11 and 40 pediatric referrals matched for age, sex, race, and socioeconomic status. Each parent and child was interviewed separately using parallel versions of the interview, DISC-P and DISC-C, and parents completed the Child Behavior Checklist (CBCL). The psychiatric referrals had more psychiatric diagnoses and higher symptom scores than the pediatric referrals. Parent reports discriminated better between the criterion groups than child reports. In both groups, mild oppositional behavior and fears were commonly reported by parents, whereas mild separation anxiety, fears, and dysthymia were commonly reported by children. Attention deficit disorder, conduct disorder, and affective disorders were much more common among psychiatrically referred children. There was an association (chi 2 = 37.1, p less than .001) between abnormally high CBCL scores and diagnoses derived from the interview with the parent, but the association between the CBCL and the child interview was not significant. Over all, the results support the validity of the DISC-P, and to a lesser extent that of the DISC-C, in discriminating psychiatric from pediatric referrals, at the level of both symptoms and severe diagnoses, but not at the mild/moderate level of diagnosis.

We consider Bayesian inference and model selection for prevalence estimation using a longitudinal two‐phase design in which subjects initially receive a low‐cost screening test followed by an expensive diagnostic test conducted on several occasions. The change in the subject's diagnostic probability over time is described using four mixed‐effects probit models in which the subject‐specific effects are captured by latent variables. The computations are performed using Markov chain Monte Carlo methods. These models are then compared using the deviance information criterion. The methodology is illustrated with an analysis of alcohol and drug use in adolescents using data from the Great Smoky Mountains Study.