A systematic understanding of the aetiology of neurodevelopmental disorders (NDDs) and their co-occurrence with other conditions during childhood and adolescence remains incomplete. In the current meta-analysis, we synthesized the literature on (1) the contribution of genetic and environmental factors to NDDs, (2) the genetic and environmental overlap between different NDDs, and (3) the co-occurrence between NDDs and disruptive, impulse control and conduct disorders (DICCs). Searches were conducted across three platforms: Web of Science, Ovid Medline and Ovid Embase. Studies were included only if 75% or more of the sample consisted of children and/or adolescents and the studies had measured the aetiology of NDDs and DICCs using single-generation family designs or genomic methods. Studies that had selected participants on the basis of unrelated diagnoses or injuries were excluded. We performed multilevel, random-effects meta-analyses on 296 independent studies, including over four million (partly overlapping) individuals. We further explored developmental trajectories and the moderating roles of gender, measurement, geography and ancestry. We found all NDDs to be substantially heritable (family-based heritability, 0.66 (s.e. = 0.03); SNP heritability, 0.19 (s.e. = 0.03)). Meta-analytic genetic correlations between NDDs were moderate (grand family-based genetic correlation, 0.47 (s.e. = 0.06); grand SNP-based genetic correlation, 0.39 (s.e. = 0.19)) but differed substantially between pairs of disorders. The genetic overlap between NDDs and DICCs was strong (grand family-based genetic correlation, 0.62 (s.e. = 0.20)). While our work provides evidence to inform and potentially guide clinical and educational diagnostic procedures and practice, it also highlights the imbalance in the research effort that has characterized developmental genetics research.

Background: Individual differences in symptoms of behaviour problems in childhood and adolescence are not primarily due to nature or nurture – another substantial source of variance is non‐shared environment (NSE). However, few specific environmental factors have been found to account for these NSE estimates. This creates a ‘missing NSE' gap analogous to the ‘missing heritability’ gap, which refers to the shortfall in identifying DNA differences responsible for heritability. We assessed the extent to which variance in behaviour problem symptoms during the first two decades of life can be accounted for by measured NSE effects after controlling for genetics and shared environment. Methods: The sample included 4,039 pairs of twins in the Twins Early Development Study whose environments and symptoms of behaviour problems were assessed in preschool, childhood, adolescence and early adulthood via parent, teacher and self‐reports. Twin‐specific environments were assessed via parent‐reports, including early life adversity, parental feelings, parental discipline and classroom environment. Multivariate longitudinal twin model‐fitting was employed to estimate the variance in behaviour problem symptoms at each age that could be predicted by environmental measures at the previous age. Results: On average across childhood, adolescence and adulthood, parent‐rated NSE composite measures accounted for 3.4% of the reliable NSE variance (1.0% of the total variance) in parent‐rated, symptoms of behaviour problems, 0.5% (0.1%) in teacher‐rated symptoms and 0.9% (0.5%) in self‐rated symptoms after controlling for genetics, shared environment and error of measurement. Cumulatively across development, our parent‐rated NSE measures in preschool, childhood and adolescence predicted 4.7% of the NSE variance (2.0% of the total variance) in parent‐rated and 0.3% (0.2%) in self‐rated behaviour problem symptoms in adulthood. Conclusions: The missing NSE gap between variance explained by measured environments and total NSE variance is large. Home and classroom environments are more likely to influence behaviour problem symptoms via genetics than via NSE.

Background: One goal of the DNA revolution is to predict problems in order to prevent them. We tested here if the prediction of behaviour problems from genome‐wide polygenic scores (GPS) can be improved by creating composites across ages and across raters and by using a multi‐GPS approach that includes GPS for adult psychiatric disorders as well as for childhood behaviour problems. Method: Our sample included 3,065 genotyped unrelated individuals from the Twins Early Development Study who were assessed longitudinally for hyperactivity, conduct, emotional problems, and peer problems as rated by parents, teachers, and children themselves. GPS created from 15 genome‐wide association studies were used separately and jointly to test the prediction of behaviour problems composites (general behaviour problems, externalising, and internalising) across ages (from age 2 to 21) and across raters in penalised regression models. Based on the regression weights, we created multi‐trait GPS reflecting the best prediction of behaviour problems. We compared GPS prediction to twin heritability using the same sample and measures. Results: Multi‐GPS prediction of behaviour problems increased from <2% of the variance for observed traits to up to 6% for cross‐age and cross‐rater composites. Twin study estimates of heritability, although to a lesser extent, mirrored patterns of multi‐GPS prediction as they increased from <40% to 83%. Conclusions: The ability of GPS to predict behaviour problems can be improved by using multiple GPS, cross‐age composites and cross‐rater composites, although the effect sizes remain modest, up to 6%. Our approach can be used in any genotyped sample to create multi‐trait GPS predictors of behaviour problems that will be more predictive than polygenic scores based on a single age, rater, or GPS.

Objectives: The aim of this study was to indicate which variables are the most important determinants of swimming results in the 50 m front crawl among non-elite pre-pubertal female swimmers. Methods: The study group consisted of 14 female swimmers (at the time of the research commencement—biological age: 10.52 ± 0.37 years; body mass: 34.99 ± 2.77 kg; height: 146.00 ± 3.05 cm). The study was conducted over three years. The swimmers performed capacity training recommended by the British Swimming Federation. Every 6 months, in the participants the following parameters were measured: percentage of body fat; anthropometric measurements; aerobic and anaerobic capacity; and respiratory parameters: vital capacity—VC, forced expiratory volume—FEV1, and forced vital capacity—FVC. Additionally, a 50 m front crawl swim test was performed. Results: After adjusting for multicollinearity, the most influential determinants of swimming performance were anthropometric measures: shoulder width was the most influential predictor, with a regression coefficient of −0.66, followed by foot length (with a beta of −0.15) and chest depth (with a beta of 0.008). The remaining anthropometric and physical predictors did not contribute to the prediction of 50 m freestyle performance. Conclusions: These research results suggest to coaches and trainers that sports performance in sprint distances in pre-pubertal girls is not determined by aerobic and anaerobic capacity or body fat but is based on the somatic build of the swimmer.

Background One goal of the DNA revolution is to predict problems in order to prevent them. We tested here if the prediction of behaviour problems from genome-wide polygenic scores (GPS) can be improved by creating composites across ages and across raters and by using a multi-GPS approach that includes GPS for adult psychiatric disorders as well as for childhood behaviour problems. Method Our sample included 3,065 genotyped unrelated individuals from the Twins Early Development Study who were assessed longitudinally for hyperactivity, conduct, emotional problems and peer problems as rated by parents, teachers and children themselves. GPS created from 15 genome-wide association studies were used separately and jointly to test the prediction of behaviour problems composites (general behaviour problems, externalizing and internalizing) across ages (from age 2 to age 21) and across raters in penalized regression models. Based on the regression weights, we created multi-trait GPS reflecting the best prediction of behaviour problems. We compared GPS prediction to twin heritability using the same sample and measures. Results Multi-GPS prediction of behaviour problems increased from less than 2% of the variance for observed traits to up to 6% for cross-age and cross-rater composites. Twin study estimates of heritability mirrored patterns of multi-GPS prediction as they increased from less than 40% to up to 83%. Conclusions The ability of GPS to predict behaviour problems can be improved by using multiple GPS, cross-age composites and cross-rater composites, although the effect sizes remain modest, up to 6%. Our results can be used in any genotyped sample to create multi-trait GPS predictors of behaviour problems that will be more predictive than polygenic scores based on a single age, rater or GPS. Key points Genome-wide polygenic scores (GPS) can be used to predict behaviour problems in childhood, but the effect sizes are generally less than 3.5%. DNA-based prediction models of achieve greater accuracy if holistic approaches are employed, that is cross-trait, longitudinal and trans-situational approaches. The prediction of childhood behaviour problems can be improved by using multiple GPS to predict composites that aggregate behaviour problems across ages and across raters. Our results yield weights that can be applied to GPS in any study to create multi-trait GPS predictors of behaviour problems based on cross-age and cross-rater composites. As compared to individuals in the lowest multi-trait GPS decile, nearly three times as many individuals in the highest internalizing multi-trait GPS decile were diagnosed with anxiety disorder and 25% more individuals in the highest general behaviour problems and externalizing multi-trait GPS deciles have taken medication for mental health.