Genetic influences on thought problems in 7-year-olds: A twin-study of genetic, environmental and rater effects.

The Thought-Problem scale (TP) of the CBCL assesses symptoms such as hallucinations and strange thoughts/behaviors and has been associated with other behavioral disorders. This study uses parental reports to examine the etiology of variation in TP, about which relatively little is known, in 7-year-old twins. Parental ratings on TP were collected in 8,962 7-year-old twin pairs. Because the distribution of TP scores was highly skewed scores were categorized into 3 classes. The data were analyzed under a threshold liability model with genetic structural equation modeling. Ratings from both parents were simultaneously analyzed to determine the rater agreement phenotype (or common phenotype [TPc]) and the rater specific phenotype [TPs] that represents rater disagreement caused by rater bias, measurement error and/or a unique view of the parents on the child's behavior. Scores on the TP-scale varied as a function of rater (fathers rated fewer problems), sex (boys scored higher) and zygosity (DZ twins scored higher). The TPc explained 67% of the total variance in the parental ratings. Variation in TPc was influenced mainly by the children's genotype (76%). Variance in TPs also showed a contribution of genetic factors (maternal reports: 61%, paternal reports: 65%), indicating that TPs does not only represent rater bias. Shared environmental influences were only found in the TPs. No sex differences in genetic architecture were observed. These results indicate an important contribution of genetic factors to thought problems in children as young as 7 years

Genetic Overlap Between Schizophrenia and Developmental Psychopathology: Longitudinal and Multivariate Polygenic Risk Prediction of Common Psychiatric Traits During Development

Several nonpsychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the etiology of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by correlated genetic risk factors.Polygenic risk scores (PRS), reflecting an individual's genetic risk for schizophrenia, were constructed for 2588 children from the Netherlands Twin Register (NTR) and 6127 from the Avon Longitudinal Study of Parents And Children (ALSPAC). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13, and 15 years in the 2 cohorts. Results were then meta-analyzed, and a meta-regression analysis was performed to test differences in effects sizes over, age and disorders.Schizophrenia PRS were associated with childhood and adolescent psychopathology. Meta-regression analysis showed differences in the associations over disorders, with the strongest association with childhood and adolescent depression and a weaker association for ODD/CD at age 7. The associations increased with age and this increase was steepest for ADHD and ODD/CD. Genetic correlations varied between 0.10 and 0.25.By optimally using longitudinal data across diagnoses in a multivariate meta-analysis this study sheds light on the development of childhood disorders into severe adult psychiatric disorders. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology

Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity

BACKGROUND AND PURPOSE: The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS: We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS: We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION: The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability

DNA methylation in peripheral tissues and left-handedness

This is the final version. Available on open access from Nature Research vis the DOI in this recordData availability: The HumanMethylation450 BeadChip data from the NTR are available as part of the Biobank-based Integrative Omics Studies (BIOS) Consortium in the European Genome-phenome Archive (EGA), under the accession code EGAD00010000887 (https://ega-archive.org/datasets/EGAD00010000887). The Infinium MethylationEPIC from NTR are available from the Netherlands Twin Register on reasonable request (https://tweelingenregister.vu.nl/information_for_researchers/working-with-ntr-data). DNA methylation data from ALSPAC are available at ALSPAC and can be provided on request. The study website contains details of all the data that is available through a fully searchable data dictionary and variable search tool (http://www.bristol.ac.uk/alspac/researchers/our-data). The code used to perform the primary and secondary analyses is available at https://github.com/MRCIEU/handedness-ewas. The pipeline for the DNA methylation array analysis developed by the Biobank-based Integrative Omics Study (BIOS) consortium are available here: https://molepi.github.io/DNAmArray_workflow/. EWAS summary statistics for the top 100 CpGs are given in Supplemental Tables 6–11 and 15–29. The full EWAS summary statistics from the meta-analysis with basic and adjusted model are provided in Supplemental Tables 32 and 33. The full summary statistics for all other analyses are available upon request from the corresponding author.Handedness has low heritability and epigenetic mechanisms have been proposed as an etiological mechanism. To examine this hypothesis, we performed an epigenome-wide association study of left-handedness. In a meta-analysis of 3914 adults of whole-blood DNA methylation, we observed that CpG sites located in proximity of handedness-associated genetic variants were more strongly associated with left-handedness than other CpG sites (P = 0.04), but did not identify any differentially methylated positions. In longitudinal analyses of DNA methylation in peripheral blood and buccal cells from children (N = 1737), we observed moderately stable associations across age (correlation range [0.355-0.578]), but inconsistent across tissues (correlation range [- 0.384 to 0.318]). We conclude that DNA methylation in peripheral tissues captures little of the variance in handedness. Future investigations should consider other more targeted sources of tissue, such as the brain

Genetic and environmental influences on the stability of withdrawn behavior in children: A longitudinal, multi-informant twin study.

We examined the contribution of genetic and environmental influences on the stability of withdrawn behavior (WB) in childhood using a longitudinal multiple rater twin design. Maternal and paternal ratings on the withdrawn subscale of the Child Behavior Checklist (CBCL) were obtained from 14,889 families when the twins were 3, 7, 10 and 12 years old. A longitudinal psychometric model was fitted to the data and the fit of transmission and common factor models were evaluated for each variance component. WB showed considerable stability throughout childhood, with correlation coefficients ranging from about .30 for the 9-year time interval to .65 for shorter time intervals. Individual differences in WB as observed by the mother and the father were found to be largely influenced by genetic effects at all four time points, in both boys (50–66%) and girls (38–64%). Shared environmental influences explained a small to modest proportion (0–24%) of the variance at all ages and were slightly more pronounced in girls. Non-shared environmental influences were of moderate importance to the variance and slightly increased with age, from 22–28% at age 3 to 35–41% at age 12 years. The stability of WB was largely explained by genetic effects, accounting for 74% of stability in boys and 65% in girls. Shared environmental effects explained 7% (boys) and 17% (girls) of the behavioral stability. Most shared environmental effects were common to both raters, suggesting little influence of rater bias in the assessment of WB. The shared environmental effects common to both raters were best described by a common factor model, indicating that these effects are stable and persistent throughout childhood. Non-shared environmental effects accounted for the remaining covariance over time

A genome-wide association study of total child psychiatric problems scores.

Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EAGLE consortium. The SNP heritability of total psychiatric problems was 5.4% (SE = 0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of SBF2, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total score were shared with common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (rG > 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits

Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher

<p>Abstract</p> <p>Background</p> <p>Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and <it>complete </it>loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.</p> <p>Methods</p> <p>Data were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.</p> <p>We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.</p> <p>Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.</p> <p>Results</p> <p>The prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.</p> <p>Conclusions</p> <p>Complete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.</p