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.
Objective
An association between bipolar disorder and cognitive impairment has repeatedly been described, even for euthymic patients. Findings are inconsistent both across primary studies and previous meta‐analyses. This study reanalysed 31 primary data sets as a single large sample (N = 2876) to provide a more definitive view.
Method
Individual patient and control data were obtained from original authors for 11 measures from four common neuropsychological tests: California or Rey Verbal Learning Task (VLT), Trail Making Test (TMT), Digit Span and/or Wisconsin Card Sorting Task.
Results
Impairments were found for all 11 test‐measures in the bipolar group after controlling for age, IQ and gender (Ps ≤ 0.001, E.S. = 0.26–0.63). Residual mood symptoms confound this result but cannot account for the effect sizes found. Impairments also seem unrelated to drug treatment. Some test‐measures were weakly correlated with illness severity measures suggesting that some impairments may track illness progression.
Conclusion
This reanalysis supports VLT, Digit Span and TMT as robust measures of cognitive impairments in bipolar disorder patients. The heterogeneity of some test results explains previous differences in meta‐analyses. Better controlling for confounds suggests deficits may be smaller than previously reported but should be tracked longitudinally across illness progression and treatment.
Our findings suggest that neurocognitive dysfunction in bipolar and schizophrenia spectrum disorders is determined more by history of psychosis than by Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) diagnostic category or subtype, supporting a more dimensional approach in future diagnostic systems.
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