| Application: | 16406, Causes of individual differences in cognitive and mental health |
| Title: | Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence |
| Size: | 3867 B |
| Archived: | 26 Nov 2020 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 2886
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Notes
Intelligence is highly heritable and a major determinant of human health and well-being, being linked to numerous aspects of physical and mental functioning. Recent studies have identified 24 genomic loci linked to variation in intelligence, but the vast majority of its underlying genetic influences remains undiscovered. In this study, we conducted a meta-analysis of data from UK Biobank and other large samples in which cognitive testing had been performed to assess general fluid intelligence (total sample of 269,867 individuals). In each sample, we conducted a genome-wide association analysis to find regions of the genome linked to variation in cognitive test performance, and then we meta-analysed the results across samples. By pooling together this data, 205 associated genomic loci (190 novel) and 1,016 genes were found to be related to variation in intelligence, confirming prior studies and dramatically increasing the previously known catalogue. However, these loci still explain only a small portion of the heritability of intelligence, indicating that it is an extremely genetically complex trait with much remaining to be discovered.The associated genetic variants were spread throughout the whole genome, but especially concentrated in regions related to protein-coding functions and regulation of gene expression, as well as regions that have been conserved between species across evolution. The associated genes are strongly expressed in the brain, specifically in neuronal regions related to memory and decision-making. The results also highlighted strong genetic correlations between intelligence and multiple health-related outcomes, especially psychiatric disorders, and suggested that there are protective effects of intelligence (or the genetic factors related to intelligence) on risk of Alzheimer s disease and ADHD. This study moves forward our understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
Application 16406
Causes of individual differences in cognitive and mental health
The main goal of our study is to quantify and understand the role of genetic variants, the environment (including lifestyle), and their interaction on outcomes related to cognitive health. In doing so we will combine expertise of statistical genetics, medical genetics, bioinformatics and functional genomics. We are specifically interested in the following health-relevant outcomes from the U.K. Biobank data: cognitive function (incl. normal function and dementia), mental health (incl. depression, neuroticism, personality, smoking, and alcohol drinking), and brain MRI. Our research will contribute to quantifying and understanding how several risk factors (e.g. lifestyle, environment, genes), both separately and in combination, influence cognitive health as well as the comorbidities between different cognitive health outcomes. Our study will consist of a combination of methods, including: - Genome-wide association studies (GWAS) that aim to identify individual genetic variants associated with a particular outcome. - Comorbidity analyses, using e.g. meta-analytic techniques, LD score regression or BOLD-GREML methods to quantify the extent of genetic overlap between particular outcomes - Gene-set analyses (e.g. using MAGMA and INRICH tools) and bioinformatic secondary analyses to understand genetic findings in terms of their biological function - Heterogeneity analyses to determine genetic subgroups of individuals - Annotation of genetic findings using external information from e.g. expression or quantitative proteomics data - Gene-by-environment correlation and interaction analyses to quantify the relevance of the interplay between genes and environment (including lifestyle) on outcomes related to cognitive health We aim to use all available observations in the UKB that are currently released and will be released in the future, and that have been successfully genotyped and have measures of relevant outcomes. ?
| Lead investigator: | Professor Danielle Posthuma |
| Lead institution: | VU University Amsterdam |
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1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 2887 | Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence | Jeanne E. Savage (+116) | 2018 | Nature Genetics |
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