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.

In the largest twin study to date, we confirmed that heritability for AD is high and that the same genetic factors are influential for both men and women. However, nongenetic risk factors also play an important role and might be the focus for interventions to reduce disease risk or delay disease onset.

Positive and negative affect, measured by the Bradburn Affect Balance Scale, were studied in a longitudinal sample spanning from 1971 to 1994. The sample (N = 2,804) represented 4 generations of families. Linear trend analyses compared generations over time for positive and negative affect and also examined the possible influences of neuroticism and extraversion on initial levels of affect and patterns of change in affect. Negative affect decreased with age for all generations, although the rate was attenuated among the oldest adults. Higher neuroticism scores also attenuated the decrease in negative affect across time. For positive affect, the younger and middle-aged adults showed marked stability, but the older group evidenced a small decrease over time. Higher levels of extraversion were related to more stability in positive affect.

While two factors are currently thought to underlie individual differences in schizotypal personality, three factors may best explain schizotypal traits. This study used confirmatory factor analysis to assess five competing models of schizotypal personality in the general population: null model, one-factor model, simple two-factor model, Kendler two-factor model, and three-factor model. The computer program LISREL was used to analyze Schizotypal Personality Questionnaire subscale scores that reflect the nine traits of schizotypal personality. The scores were obtained from (1) a sample of 822 undergraduates and (2) a replication sample of 102 subjects drawn from the community. Results indicate replicable support for a three-factor model reflecting cognitive-perceptual, interpersonal, and disorganized latent factors. Low intercorrelations between the first two factors and the lack of fit by a one-factor model are partially inconsistent with recent notions that a single vulnerability dimension underlies schizotypal personality. It is argued that future investigations should assess the correlates of all three schizotypal factors in clinical and nonclinical samples in addition to the two more traditional factors. It is hypothesized that three factors of schizophrenic symptomatology observed in recent studies may reflect an exaggeration of three analogous factors found in the general population.

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.