Statistical power to detect genetic and environmental influences in the presence of data missing at random.

We study the situation in which a cheap measure (X) is observed in a large, representative twin sample, and a more expensive measure (Y) is observed in a selected subsample. The aim of this study is to investigate the optimal selection design in terms of the statistical power to detect genetic and environmental influences on the variance of Y and on the covariance of X and Y. Data were simulated for 4000 dizygotic and 2000 monozygotic twins. Missingness (87% vs. 97%) was then introduced in accordance with 7 selection designs: (i) concordant low + individual high design; (ii) extreme concordant design; (iii) extreme concordant and discordant design (EDAC); (iv) extreme discordant design; (v) individual score selection design; (vi) selection of an optimal number of MZ and DZ twins; and (vii) missing completely at random. The statistical power to detect the influence of additive and dominant genetic and shared environmental effects on the variance of Y and on the covariance between X and Y was investigated. The best selection design is the individual score selection design. The power to detect additive genetic effects is high irrespective of the percentage of missingness or selection design. The power to detect shared environmental effects is acceptable when the percentage of missingness is 87%, but is low when the percentage of missingness is 97%, except for the individual score selection design, in which the power remains acceptable. The power to detect D is low, irrespective of selection design or percentage of missingness. The individual score selection design is therefore the best design for detecting genetic and environmental influences on the variance of Y and on the covariance of X and Y. However, the EDAC design may be preferred when an additional purpose of a study is to detect quantitative trait loci effects

The influence of semantic top-down processing in auditory verbal hallucinations

AbstractBackgroundAuditory verbal hallucinations (AVH) are one of the most prominent symptoms of schizophrenia but have also been reported in the general population. Several cognitive models have tried to elucidate the mechanism behind auditory verbal hallucinations, among which a top-down model. According to this model, perception is biased towards top-down information (e.g., expectations), reducing the influence of bottom-up information coming from the sense organs. This bias predisposes to false perceptions, i.e., hallucinations.MethodsThe current study investigated this hypothesis in non-psychotic individuals with frequent AVH, psychotic patients with AVH and healthy control subjects by applying a semantic top-down task. In this task, top-down processes are manipulated through the semantic context of a sentence. In addition, the association between hallucination proneness and semantic top-down errors was investigated.ResultsNon-psychotic individuals with AVH made significantly more top-down errors compared to healthy controls, while overall accuracy was similar. The number of top-down errors, corrected for overall accuracy, in the patient group was in between those of the other two groups and did not differ significantly from either the non-psychotic individuals with AVH or the healthy controls. The severity of hallucination proneness correlated with the number of top-down errors.DiscussionThese findings confirm that non-psychotic individuals with AVH are stronger influenced by top-down processing (i.e., perceptual expectations) than healthy controls. In contrast, our data suggest that in psychotic patients semantic expectations do not play a role in the etiology of AVH. This finding may point towards different cognitive mechanisms for pathological and nonpathological hallucinations

Why more boys than girls with ADHD receive treatment: A study of Dutch twins.

More boys than girls with attention deficit hyperactivity disorder (ADHD) receive treatment. One explanation for this bias may be that boys score higher on disruptive behavior scales than girls. Although this was supported by findings in clinical samples, recent studies in nonreferred samples showed that boys and girls with ADHD are similar with respect to their levels of disruptive behavior as reported by their mother. In this report, we investigate whether the difference in treatment rate is associated with higher teacher problem scores in boys with ADHD than in girls with ADHD. Data were obtained from mothers and teachers in a nonreferred sample of 283 boys and 291 girls with and without ADHD. Children were selected when they scored either low (controls) or high (probands) on attention problems. Mothers completed DSM-IV interviews, Child Behavior Checklists (CBCL) and the Conners Rating Scale (CRS). Teachers filled in the Teacher Report Form (TRF), and the CRS. Boys and girls with ADHD had similar levels of psychiatric illness and school impairment (such as being held back, special class placement and learning problems) by mother report. Mothers reported similar levels of aggression and attention problems in boys and girls with ADHD. In contrast, teachers consistently rated boys with ADHD as having higher scores on reports of attention problems and aggression than girls with ADHD. Gender differences vary across settings: boys and girls with ADHD are rated as behaving differently at school, but not at home. The higher level of teacher reported problem behavior at school may explain the high male-female ratio for ADHD in clinical settings. These findings have implications for the results of genetic studies that rely on referred samples, as these studies may give a distorted view of sex differences in the population

Ethnic differences in current smoking and former smoking in the Netherlands and the contribution of socioeconomic factors: a cross-sectional analysis of the HELIUS study.

OBJECTIVES: Data exploring how much of the ethnic differences in smoking prevalence and former smoking are explained by socioeconomic status (SES) are lacking. We therefore assessed ethnic differences in smoking prevalence and former smoking and the contribution of both educational level and occupational-related SES to the observed ethnic differences in smoking behaviour. METHODS: Data of 22 929 participants (aged 18-70 years) from the multiethnic cross-sectional Healthy Life in an Urban Setting study in the Netherlands were analysed. Poisson regression models with a robust variance were used to estimate prevalence ratios. RESULTS: Compared with the Dutch, after adjustment for age and marital status, smoking prevalence was higher in men of Turkish (prevalence ratio 1.69, 95% CI 1.54 to 1.86), African Surinamese (1.55, 95% CI 1.41 to 1.69) and South-Asian Surinamese origin (1.53, 95% CI 1.40 to 1.68), whereas among women, smoking prevalence was higher in Turkish, similar in African Surinamese but lower in all other ethnic origin groups. All ethnic minority groups, except Ghanaians, had a significantly lower smoking cessation prevalence than the Dutch. Socioeconomic gradients in smoking (higher prevalence among those lower educated and with lower level employment) were observed in all groups except Ghanaian women (a higher prevalence was observed in the higher educated). Ethnic differences in smoking prevalence and former smoking are largely, but not completely, explained by socioeconomic factors. CONCLUSIONS: Our findings imply that antismoking policies designed to target smoking within the lower socioeconomic groups of ethnic minority populations may substantially reduce ethnic inequalities in smoking particularly among men and that certain groups may benefit from targeted smoking cessation interventions

Segment-Wise Genome-Wide Association Analysis Identifies a Candidate Region Associated with Schizophrenia in Three Independent Samples

Recent studies suggest that variation in complex disorders (e.g., schizophrenia) is explained by a large number of genetic variants with small effect size (Odds Ratio∼1.05–1.1). The statistical power to detect these genetic variants in Genome Wide Association (GWA) studies with large numbers of cases and controls (∼15,000) is still low. As it will be difficult to further increase sample size, we decided to explore an alternative method for analyzing GWA data in a study of schizophrenia, dramatically reducing the number of statistical tests. The underlying hypothesis was that at least some of the genetic variants related to a common outcome are collocated in segments of chromosomes at a wider scale than single genes. Our approach was therefore to study the association between relatively large segments of DNA and disease status. An association test was performed for each SNP and the number of nominally significant tests in a segment was counted. We then performed a permutation-based binomial test to determine whether this region contained significantly more nominally significant SNPs than expected under the null hypothesis of no association, taking linkage into account. Genome Wide Association data of three independent schizophrenia case/control cohorts with European ancestry (Dutch, German, and US) using segments of DNA with variable length (2 to 32 Mbp) was analyzed. Using this approach we identified a region at chromosome 5q23.3-q31.3 (128–160 Mbp) that was significantly enriched with nominally associated SNPs in three independent case-control samples. We conclude that considering relatively wide segments of chromosomes may reveal reliable relationships between the genome and schizophrenia, suggesting novel methodological possibilities as well as raising theoretical questions

Evaluating the role of alcohol consumption in breast and ovarian cancer susceptibility using population-based cohort studies and two-sample Mendelian randomization analyses.

Alcohol consumption is correlated positively with risk for breast cancer in observational studies, but observational studies are subject to reverse causation and confounding. The association with epithelial ovarian cancer (EOC) is unclear. We performed both observational Cox regression and two-sample Mendelian randomization (MR) analyses using data from various European cohort studies (observational) and publicly available cancer consortia (MR). These estimates were compared to World Cancer Research Fund (WCRF) findings. In our observational analyses, the multivariable-adjusted hazard ratios (HR) for a one standard drink/day increase was 1.06 (95% confidence interval [CI]; 1.04, 1.08) for breast cancer and 1.00 (0.92, 1.08) for EOC, both of which were consistent with previous WCRF findings. MR ORs per genetically predicted one standard drink/day increase estimated via 34 SNPs using MR-PRESSO were 1.00 (0.93, 1.08) for breast cancer and 0.95 (0.85, 1.06) for EOC. Stratification by EOC subtype or estrogen receptor status in breast cancers made no meaningful difference to the results. For breast cancer, the CIs for the genetically derived estimates include the point-estimate from observational studies so are not inconsistent with a small increase in risk. Our data provide additional evidence that alcohol intake is unlikely to have anything other than a very small effect on risk of EOC