The genetic architecture of the human cerebral cortex

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 306 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 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 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 (rG = −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 10 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

The characteristics of psychotic features in bipolar disorder

Background In a large and comprehensively assessed sample of patients with bipolar disorder type I (BDI), we investigated the prevalence of psychotic features and their relationship with life course, demographic, clinical, and cognitive characteristics. We hypothesized that groups of psychotic symptoms (Schneiderian, mood incongruent, thought disorder, delusions, and hallucinations) have distinct relations to risk factors.Methods In a cross-sectional study of 1342 BDI patients, comprehensive demographical and clinical characteristics were assessed using the Structured Clinical Interview for DSM-IV (SCID-I) interview. In addition, levels of childhood maltreatment and intelligence quotient (IQ) were assessed. The relationships between these characteristics and psychotic symptoms were analyzed using multiple general linear models.Results A lifetime history of psychotic symptoms was present in 73.8% of BDI patients and included delusions in 68.9% of patients and hallucinations in 42.6%. Patients with psychotic symptoms showed a significant younger age of disease onset (β =-0.09, t =-3.38, p = 0.001) and a higher number of hospitalizations for manic episodes (F11 338 = 56.53, p < 0.001). Total IQ was comparable between groups. Patients with hallucinations had significant higher levels of childhood maltreatment (β = 0.09, t = 3.04, p = 0.002).Conclusions In this large cohort of BDI patients, the vast majority of patients had experienced psychotic symptoms. Psychotic symptoms in BDI were associated with an earlier disease onset and more frequent hospitalizations particularly for manic episodes. The study emphasizes the strength of the relation between childhood maltreatment and hallucinations but did not identify distinct subgroups based on psychotic features and instead reported of a large heterogeneity of psychotic symptoms in BD

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Brouwer et al. identified genetic variants that affect rates of brain growth and atrophy. The genes are linked to early brain development and neurodegeneration and suggest involvement of metabolic processes.Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.Stress-related psychiatric disorders across the life spa