Edwin J. C. G. van den Oord

Internal and external validity of Attention-Deficit Hyperactivity Disorder in a population-based sample of adults

BACKGROUND Follow-up studies of childhood ADHD have shown persistence of the disorder into adulthood, but no epidemiological data are yet available. METHOD ADHD DSM-IV symptoms were obtained by self-report in an adult population-based sample of 1813 adults (aged 18-75 years), that was drawn from an automated general practitioner system used in Nijmegen, The Netherlands. The structure of ADHD symptoms was analysed by means of confirmatory factor analyses. Other data used in this report are the General Health Questionnaire (GHQ-28), information about the presence of three core symptoms of ADHD in childhood, and about current psychosocial impairment. RESULTS The three-factor model that allowed for cross-loadings provided the best fit in the entire sample. This result was replicated across gender and age subsamples. Inattentive and hyperactivity symptom scores were significantly associated with measures of impairment, even after controlling for the GHQ-28. Subjects with four or more inattentive or hyperactive-impulsive symptoms were significantly more impaired than subjects with two, one and no symptoms. The prevalence of ADHD in adults was 1.0% (95% CI 0.6-1.6) and 2.5% (1.9-3.4) using a cutoff of six and four current symptoms respectively, and requiring the presence of all three core symptoms in childhood. CONCLUSIONS These results support the internal and external validity of ADHD in adults between 18 and 75 years. ADHD is not merely a child psychiatric disorder that persists into young adulthood, but an important and unique manifestation of psychopathology across the lifespan.

Genetic and environmental influences on vocabulary IQ: parental education level as moderator.

This article examines how parental education level moderates the genetic and environmental contributions to variation in verbal IQ. Data are from 1909 non-Hispanic Whites and African American sibling pairs from the National Longitudinal Study of Adolescent Health, which obtained nationally-based samples of identical (MZ) twins, fraternal (DZ) twins, full and half siblings, cousins (in the same household), and biologically unrelated siblings. In the whole sample, the variance estimate for heritability (h2 = .57, SE = .08) was greater than that for shared environment (c2 = .13, SE = .04). Both heritability and the shared environmental estimate were moderated, however, by level of parental education. Specifically, among more highly educated families, the average h2 = .74 (SE = .10) and the average c2 = .00 (SE = .05). Conversely, among less well-educated families, heritability decreased and shared environmental influences increased, yielding similar proportions of variance explained by genetic and environmental factors, average h2 = .26 (SE = .15), and average c2 = .23 (SE = .07).

Resolving the Debate Over Birth Order, Family Size, and Intelligence

Hundreds of research articles have addressed the relationship between birth order and intelligence. Virtually all have used cross-sectional data, which are fundamentally flawed in the assessment of within-family (including birth order) processes. Although within-family models have been based on patterns in cross-sectional data, a number of equally plausible between-family explanations also exist. Within-family (preferably intact-family) data are prerequisite for separating within- and between-family causal processes. This observation reframes an old issue in a way that can be easily addressed by studying graphical patterns. Sibling data from the National Longitudinal Survey of Youth are evaluated, and the results are compared with those from other studies using within-family data. It appears that although low-IQ parents have been making large families, large families do not make low-IQ children in modern U.S. society. The apparent relation between birth order and intelligence has been a methodological illusion.

MicroRNA expression profiling in the prefrontal cortex of individuals affected with schizophrenia and bipolar disorders

MicroRNAs (miRNAs) are a large family of small non-coding RNAs which negatively control gene expression at both the mRNA and protein levels. The number of miRNAs identified is growing rapidly and approximately one-third is expressed in the brain where they have been shown to affect neuronal differentiation, synaptosomal complex localization and synapse plasticity, all functions thought to be disrupted in schizophrenia. Here we investigated the expression of 667 miRNAs (miRBase v.13) in the prefrontal cortex of individuals with schizophrenia (SZ, N = 35) and bipolar disorder (BP, N = 35) using a real-time PCR-based Taqman Low Density Array (TLDA). After extensive QC steps, 441 miRNAs were included in the final analyses. At a FDR of 10%, 22 miRNAs were identified as being differentially expressed between cases and controls, 7 dysregulated in SZ and 15 in BP. Using in silico target gene prediction programs, the 22miRNAs were found to target brain specific genes contained within networks overrepresented for neurodevelopment, behavior, and SZ and BP disease development. In an initial attempt to corroborate some of these predictions, we investigated the extent of correlation between the expressions of hsa-mir-34a, -132 and -212 and their predicted gene targets. mRNA expression of tyrosine hydroxylase (TH), phosphogluconate dehydrogenase (PGD) and metabotropic glutamate receptor 3 (GRM3) was measured in the SMRI sample. Hsa-miR-132 and -212 were negatively correlated with TH (p = 0.0001 and 0.0017) and with PGD (p = 0.0054 and 0.017, respectively).

Methylome-Wide Association Study of Schizophrenia: Identifying Blood Biomarker Signatures of Environmental Insults

IMPORTANCE Epigenetic studies present unique opportunities to advance schizophrenia research because they can potentially account for many of its clinical features and suggest novel strategies to improve disease management. OBJECTIVE To identify schizophrenia DNA methylation biomarkers in blood. DESIGN, SETTING, AND PARTICIPANTS The sample consisted of 759 schizophrenia cases and 738 controls (N = 1497) collected in Sweden. We used methyl-CpG-binding domain protein-enriched genome sequencing of the methylated genomic fraction, followed by next-generation DNA sequencing. We obtained a mean (SD) number of 68 (26.8) million reads per sample. This massive data set was processed using a specifically designed data analysis pipeline. Critical top findings from our methylome-wide association study (MWAS) were replicated in independent case-control participants using targeted pyrosequencing of bisulfite-converted DNA. MAIN OUTCOMES AND MEASURES Status of schizophrenia cases and controls. RESULTS Our MWAS suggested a considerable number of effects, with 25 sites passing the highly conservative Bonferroni correction and 139 sites significant at a false discovery rate of 0.01. Our top MWAS finding, which was located in FAM63B, replicated with P = 2.3 × 10-10. It was part of the networks regulated by microRNA that can be linked to neuronal differentiation and dopaminergic gene expression. Many other top MWAS results could be linked to hypoxia and, to a lesser extent, infection, suggesting that a record of pathogenic events may be preserved in the methylome. Our findings also implicated a site in RELN, one of the most frequently studied candidates in methylation studies of schizophrenia. CONCLUSIONS AND RELEVANCE To our knowledge, the present study is one of the first MWASs of disease with a large sample size using a technology that provides good coverage of methylation sites across the genome. Our results demonstrated one of the unique features of methylation studies that can capture signatures of environmental insults in peripheral tissues. Our MWAS suggested testable hypotheses about disease mechanisms and yielded biomarkers that can potentially be used to improve disease management.

Genomewide Association Analysis Followed by a Replication Study Implicates a Novel Candidate Gene for Neuroticism

CONTEXT Neuroticism is a trait that reflects a tendency toward negative mood states. It has long been linked to internalizing psychiatric conditions, such as anxiety and depression, and it accounts for much of the substantial comorbidity seen between these disorders. OBJECTIVE To identify common genetic variants that affect neuroticism to better understand (the comorbidity between) a broad range of psychiatric disorders and to develop effective treatments. DESIGN, SETTING, AND PARTICIPANTS More than 420,000 genetic markers were tested for their association with neuroticism in a genomewide association study (GWAS). The GWAS sample consisted of 1227 healthy individuals ascertained from a US national sampling frame and available from the National Institute of Mental Health genetics repository. The most promising markers were subsequently tested in a German replication sample comprising 1880 healthy individuals. MAIN OUTCOME MEASURES A strict definition of replication (same marker, same direction of effects, and same measure) combined with a threshold we proposed previously for declaring significance in genetic studies that ensures a mean probability of producing false-positive findings of less than 10%. RESULTS The most promising results in the GWAS and replication samples were single-nucleotide polymorphisms (SNPs) in the gene MAMDC1. These SNPs all tagged the same 2 haplotypes and had P values of 10(-5) to 10(-6) in the GWAS sample and of .006 to .02 in the replication sample. Furthermore, the replication involved the same SNPs and the same direction of effects. In a combined analysis of all data, several SNPs were significant according to the threshold that allows for 10% false-positive findings. CONCLUSIONS The small effect sizes may limit the prognostic, diagnostic, and therapeutic use of SNP markers such as those in MAMDC1. However, the present study demonstrates the potential of a GWAS to discover potentially important pathogenic pathways for which clinically more powerful (bio)markers may eventually be developed.

Factor structure and external validity of the PANSS revisited

Considerable controversy exists concerning the positive and negative syndrome scale (PANSS), one of the most widely used instruments in schizophrenia research. In this article we revisited the factor structure and external validity of the PANSS in a sample of 500 participants with DSM IV diagnoses of schizophrenia. We found that a model with six latent factors provided a relatively good fit, considered adequate by two rules of thumb. Five factors corresponded closely to those typically derived in other studies: Negative, Positive, Excited/Activation, Anxious-Depressed/Dysphoric, and Disorganized/Autistic preoccupation. The sixth factor seemed to have face validity and was labeled Withdrawn. With the exception of Anxious-Depressed/Dysphoric, Cronbachs Alpha ranged from 0.70 to 0.85 suggesting an acceptable internal consistency. External validity was studied through correlations with socio-demographic variables, DSM IV (subtype) diagnoses, clinical characteristics, and drug use. The many significant correlations suggested that the six PANSS scales measure meaningful aspects of schizophrenia. Furthermore, the pattern of correlations varied, providing evidence that the scales assessed partly different aspects of the disease. Our analyses also suggested that some of the controversy about the PANSS can possibly be attributed to methodological factors where the substantial cross-loadings of some PANSS items may play an important role.

Schizophrenia Gene Networks and Pathways and Their Applications for Novel Candidate Gene Selection

Background Schizophrenia (SZ) is a heritable, complex mental disorder. We have seen limited success in finding causal genes for schizophrenia from numerous conventional studies. Protein interaction network and pathway-based analysis may provide us an alternative and effective approach to investigating the molecular mechanisms of schizophrenia. Methodology/Principal Findings We selected a list of schizophrenia candidate genes (SZGenes) using a multi-dimensional evidence-based approach. The global network properties of proteins encoded by these SZGenes were explored in the context of the human protein interactome while local network properties were investigated by comparing SZ-specific and cancer-specific networks that were extracted from the human interactome. Relative to cancer genes, we observed that SZGenes tend to have an intermediate degree and an intermediate efficiency on a perturbation spreading throughout the human interactome. This suggested that schizophrenia might have different pathological mechanisms from cancer even though both are complex diseases. We conducted pathway analysis using Ingenuity System and constructed the first schizophrenia molecular network (SMN) based on protein interaction networks, pathways and literature survey. We identified 24 pathways overrepresented in SZGenes and examined their interactions and crosstalk. We observed that these pathways were related to neurodevelopment, immune system, and retinoic X receptor (RXR). Our examination of SMN revealed that schizophrenia is a dynamic process caused by dysregulation of the multiple pathways. Finally, we applied the network/pathway approach to identify novel candidate genes, some of which could be verified by experiments. Conclusions/Significance This study provides the first comprehensive review of the network and pathway characteristics of schizophrenia candidate genes. Our preliminary results suggest that this systems biology approach might prove promising for selection of candidate genes for complex diseases. Our findings have important implications for the molecular mechanisms for schizophrenia and, potentially, other psychiatric disorders.

Structure and Stress: Trajectories of Depressive Symptoms across Adolescence and Young Adulthood

Previous research into the social distribution of early life depression has yielded inconsistent results regarding the causes and course of subgroup depression disparities. This study examines the topic by analyzing National Longitudinal Study of Adolescent Health data, modeling gender and racial/ethnic differences in early life depression trajectories and investigating the influences of stress and socioeconomic status. Results indicate females and minorities experience elevated depressive symptoms across early life compared to males and whites. SES and stressful life events explain much of the racial/ethnic disparities. Blacks, Hispanics and females show greater sensitivity to the effects of low SES, and in the case of females, SLEs. Overall, this study develops a nuanced, dynamic model of the multiplicative effects of social disadvantage on early life depression disparities.

Genomewide Association Study of Movement-Related Adverse Antipsychotic Effects

BACKGROUND Understanding individual differences in the development of extrapyramidal side effects (EPS) as a response to antipsychotic therapy is essential to individualize treatment. METHODS We performed genomewide association studies to search for genetic susceptibility to EPS. Our sample consisted of 738 schizophrenia patients, genotyped for 492K single nucleotide polymorphisms (SNPs). We studied three quantitative measures of antipsychotic adverse drug reactions-the Simpson-Angus Scale (SAS) for Parkinsonism, the Barnes Akathisia Rating Scale, and the Abnormal Involuntary Movement Scale (AIMS)-as well as a clinical diagnosis of probable tardive dyskinesia. RESULTS Two SNPs for SAS, rs17022444 and rs2126709 with p = 1.2 x 10(-10) and p = 3.8 x 10(-7), respectively, and one for AIMS, rs7669317 with p = 7.7 x 10(-8), reached genomewide significance (Q value < .1). rs17022444 and rs7669317 were located in intergenic regions and rs2126709 was located in ZNF202 on 11q24. Fourteen additional signals were potentially interesting (Q value < .5). The ZNF202 is a transcriptional repressor controlling, among other genes, PLP1, which is the major protein in myelin. Mutations in PLP1 cause Pelizaeus-Merzbacher disease, which has Parkinsonism as an occurring symptom. Altered mRNA expression of PLP1 is associated with schizophrenia. CONCLUSIONS Although our findings require replication and validation, this study demonstrates the potential of genomewide association studies to discover genes and pathways that mediate adverse effects of antipsychotics.