Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16–102) and find 148 genome-wide significant independent loci (P < 5 × 10−8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Evolutionarily significant selective sweeps may result in long stretches of homozygous polymorphisms in individuals from outbred populations. We developed whole-genome homozygosity association (WGHA) methodology to characterize this phenomenon in healthy individuals and to use this genomic feature to identify genetic risk loci for schizophrenia (SCZ). Applying WGHA to 178 SCZ cases and 144 healthy controls genotyped at 500,000 markers, we found that runs of homozygosity (ROHs), ranging in size from 200 kb to 15 mb, were common in unrelated Caucasians. Properties of common ROHs in healthy subjects, including chromosomal location and presence of nonancestral haplotypes, converged with prior reports identifying regions under selective pressure. This interpretation was further supported by analysis of multiethnic HapMap samples genotyped with the same markers. ROHs were significantly more common in SCZ cases, and a set of nine ROHs significantly differentiated cases from controls. Four of these 9 ''risk ROHs'' contained or neighbored genes associated with SCZ (NOS1AP, ATF2, NSF, and PIK3C3). Several of these risk ROHs were very rare in healthy subjects, suggesting that recessive effects of relatively high penetrance may explain a proportion of the genetic liability for SCZ. Other risk ROHs feature haplotypes that are also common in healthy individuals, possibly indicating a source of balancing selection.genomewide ͉ selection ͉ haplotype ͉ HapMap ͉ susceptibility

Background Recent data suggest trait-like neurocognitive impairments in bipolar disorder (BPD), with deficits about 1 s.D. below average, less severe than deficits noted in schizophrenia. The frequency of significant impairment in BPD is approximately 60%, with 40% of patients characterized as cognitively spared. This contrasts with a more homogeneous presentation in schizophrenia. It is not understood why some BPD patients develop deficits while others do not. Method A total of 136 patients with BPD completed the MATRICS Consensus Cognitive Battery and data were entered into hierarchical cluster analyses to: (1) determine the optimal number of clusters (subgroups) that fit the sample; and (2) assign subjects to a specific cluster based on individual profiles. We then compared subgroups on several clinical factors and real-world community functioning. Results Three distinct neurocognitive subgroups were found: (1) an intact group with performance comparable with healthy controls on all domains but with superior social cognition; (2) a selective impairment group with moderate deficits on processing speed, attention, verbal learning and social cognition and normal functioning in other domains; and (3) a global impairment group with severe deficits across all cognitive domains comparable with deficits in schizophrenia. Conclusions These results suggest the presence of multiple cognitive subgroups in BPD with unique profiles and begin to address the relationships between these subgroups, several clinical factors and functional outcome. Next steps will include using these data to help guide future efforts to target these disabling symptoms with treatment.

While it is known that rare copy-number variants (CNVs) contribute to risk for some neuropsychiatric disorders, the role of CNVs in bipolar disorder is unclear. Here, we reasoned that a contribution of CNVs to mood disorders might be most evident for de novo mutations. We performed a genome-wide analysis of de novo CNVs in a cohort of 788 trios. Diagnoses of offspring included bipolar disorder (n = 185), schizophrenia (n= 177), and healthy controls (n= 426). Frequencies of de novo CNVs were significantly higher in bipolar disorder as compared with controls (OR= 4.8 [1.4,16.0], p= 0.009). De novo CNVs were particularly enriched among cases with an age at onset younger than 18 (OR= 6.3 [1.7,22.6], p= 0.006). We also confirmed a significant enrichment of de novo CNVs in schizophrenia (OR= 5.0 [1.5,16.8], p= 0.007). Our results suggest that rare spontaneous mutations are an important contributor to risk for bipolar disorder and other major neuropsychiatric diseases.

The cognitive improvements observed in the trial were consistent in magnitude with practice effects observed in healthy controls, suggesting that some of the improvements in cognition in the first-episode schizophrenia group may have been due to practice effects (ie, exposure, familiarity, and/or procedural learning). Our results also indicated that differential medication effects on cognition were small. We believe that these findings have important implications for drug discovery and the design of registration trials that attempt to demonstrate cognitive enhancement.

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia, evident prior to full illness onset and independent of medication. The possibility of genetic overlap between risk for schizophrenia and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with schizophrenia; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of schizophrenia have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common SNPs of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for schizophrenia. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from 9 non-clinical cohorts comprising the COGENT consortium) to four schizophrenia case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for schizophrenia were associated with lower general cognitive ability. Additionally, using our large cognitive meta-analytic dataset, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with schizophrenia susceptibility. Results provide molecular confirmation of the genetic overlap between schizophrenia and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.