INTRODUCTION: The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE: To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS: We identified 369 nominally genome-wide significant loci ( P < 5 × 10 ⁻⁸ ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 ⁻¹⁰ ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r _G = −0.32, SE = 0.05, P = 6.5 × 10 ⁻¹² ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION: This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure.: ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

Behavioral parent training is an evidence-based intervention for children with attention-deficit/hyperactivity disorder (ADHD), but it is unknown which of its components are most effective. This meta-regression analysis investigated which specific behavioral techniques that parents learn in parent training are associated with effects on parental outcomes. We searched for randomized controlled trials on parent training for children with ADHD, with positive parenting, negative parenting, parenting sense of competence, parent-child relation quality, and/or parental mental health as outcome measures. After screening 23,026 publications, 29 studies contributing 138 effect sizes were included (N=2345). For each study, the dosage of 39 behavioral techniques was derived from intervention manuals, and meta-regression determined which techniques were related to outcomes. Parent training had robust small-to-medium-sized positive effects on all parental outcomes relative to control conditions, both for unblinded and probably blinded measures. A higher dosage of techniques focusing on the manipulation of antecedents of behavior was associated with better outcomes on parenting sense of competence and parental mental health, and a higher dosage of techniques focusing on reinforcement of desired behaviors was related to larger decreases in negative parenting. Higher dosages of psycho-education were negatively related to parental outcomes. Although techniques were not investigated in isolation, our results suggested that the manipulation of antecedents of behavior and reinforcement techniques are key components of parent training for children with ADHD in relation to parental outcomes. These exploratory findings may help to strengthen and tailor parent training interventions for children with ADHD.

Behavioral interventions are well established treatments for children with attention-deficit/hyperactivity disorder (ADHD). However, insight into moderators of treatment outcome is limited. We conducted an individual participant data meta-analysis (IPDMA), including data of randomized controlled behavioral intervention trials for individuals with ADHD <18 years of age. Outcomes were symptoms of ADHD, oppositional defiant disorder (ODD), and conduct disorder (CD) and impairment. Moderators investigated were symptoms and impairment severity, medication use, age, IQ, sex, socioeconomic status, and single parenthood. For raters most proximal to treatment, small- to medium-sized effects of behavioral interventions were found for symptoms of ADHD, inattention, hyperactivity/impulsivity (HI), ODD and CD, and impairment. Blinded outcomes were available only for small preschool subsamples and limited measures. CD symptoms and/or diagnosis moderated outcome on ADHD, HI, ODD, and CD symptoms. Single parenthood moderated ODD outcome, and ADHD severity moderated impairment outcome. Higher baseline CD or ADHD symptoms, a CD diagnosis, and single parenthood were related to worsening of symptoms in the untreated but not in the treated group, indicating a protective rather than an ameliorative effect of behavioral interventions for these children. Behavioral treatments are effective for reducing ADHD symptoms, behavioral problems, and impairment as reported by raters most proximal to treatment. Those who have severe CD or ADHD symptoms, a CD diagnosis, or are single parents should be prioritized for treatment, as they may evidence worsening of symptoms in the absence of intervention.