A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence

Abstract

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r g = 0.70). We used these findings as foundations for our use of a novel approach-multi-trait analysis of genome-wide association studies (MTAG;Turley et al. 2017)-to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination-as well as genes expressed in the synapse, and those involved in the regulation of the nervous systemmay explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.Intelligence, also known as general cognitive function or simply g, describes the shared variance that exists between diverse measures of cognitive ability [1]. In a population with a range of cognitive ability, intelligence accounts for around 40% of the variation between individuals in scores on diverse cognitive tests [2]. Intelligence is predictive of health states, including mortality; [3,4] a lower level of cognitive function in youth is associated with earlier death over the next several decades [5]. Intelligence is a heritable trait, with twin-and family-based estimates of heritability indicating that between 50-80% of differences in intelligence can be explained by genetic factors [6]. These genetic factors make a greater contribution to phenotypic differences as age increases from childhood to adulthood [7].C.R. Gale, G. Davies and I. J. Deary contributed equally to this work. Relatively few genetic variants have reliably been associated with intelligence differences [16]. The sparsity of genome-wide significant SNPs discovered so far, combined with the substantial heritability estimate, suggests a phenotype with a highly polygenic architecture, where the total effect of all associated variants is substantial, but in which each individual variant exerts only a small influence. This is compel...

Genome‐Wide Association Study of Latent Cognitive Measures in Adolescence: Genetic Overlap With Intelligence and Education

“…As expected, based on previous findings (e.g., Cragg et al, 2017;Hill et al, 2018;Van der Ven et al, 2012), WM was strongly positively genetically correlated with other cognitive abilities and academic attainment in independent samples. The correlations with intelligence measured in childhood (r G = .80 ± .16) and years in education (r G = .70 ± .15) were lowest, although the standard errors were large and overlapped with the estimated genetic correlation with lifespan intelligence.…”

“…Another (smaller) GWAS obtained higher estimates for WM using the N-back task (h 2 SNP = 24%-41%) (Vogler et al, 2014). As expected, large genetic correlations (r G ∼.70) have been reported between general cognitive ability and educational attainment (Hill et al, 2018), which indicates that a high proportion of the DNA sequence variants affecting g also have an effect on years spent in education (either directly or by mediation). Assessing the extent of generality and specificity of shared genetic influence between cognitive domains and educational outcomes has important implications for understanding why some children do better at school than others, and paves the way for studies centered on understanding causal relationships across development.…”

Genome‐wide association analysis of autism identified multiple loci that have been reported as strong signals for neuropsychiatric disorders

“…This locus is significant in Intelligence [Hill et al, ];Response to SSRI in MDD or openness [Amare et al, ]; Depression [Howard et al, ]; Schizophrenia [Amare et al, ; Howard et al, ];Cognitive performance [Lee et al, ]; Educational attainment (MTAG) [Lee et al, ]; General cognitive ability [Davies et al, ; Lee et al, ] in GWAS study.…”

Beyond the traditional simulation design for evaluating type 1 error control: From the “theoretical” null to “empirical” null

“…A complex trait is influenced by multiple factors. For example, intelligence has been found to be associated with more than a hundred of SNPs (Dadaev et al, ; Hill et al, ). Without loss of generality, the simple phenotype‐generating model can be extended to include SNPs, where is the main effect of SNP , is the environmental effect, and is the interaction effect of .…”