Abstract
Background The complex nature of the human cognitive phenotype has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. There were two major aims of the current study: (1) conduct a large-scale GWAS meta-analysis of general cognitive function in 24 independent cohorts (N=35,298), to identify SNP-based and gene-based loci associated with cognition; and (2) determine the extent of genetic correlation between general cognitive function and published neurobehavioral phenotypes of interest. These aims were executed within the context of the Cognitive Genomics Consortium (COGENT), an international collaborative effort designed to study the molecular genetics of cognitive function. Methods To date, COGENT has acquired individual-level neuropsychological, demographic, clinical and SNP array data from 24 studies (comprised of 35 sub-cohorts) with 35,298 individuals (46.8% females, mean age of 45.3±8.6 years) of European ancestry drawn from the general population. Genotype data underwent common QC and imputation procedures, resulting in ~8M high-quality SNPs. The GWAS phenotype was general cognitive function (“g”), derived from the first principal component of a PCA performed on an average of 8±4 neuropsychological tests. Allelic association analysis was conducted with imputed allele dosages using Plink 1.9, except for 8 sub-cohorts including related individuals, which were analyzed with BOLT-LMM. GWAS results were combined for meta-analysis using the inverse-variance weighted Z-score method in METAL, with subsequebt gene-based analysis using MAGMA Additionally, we utilized individual SNP lookups and polygenic score analyses (using the LD score regression method) to identify genetic overlap with other relevant neurobehavioral phenotypes. Results Our primary GWAS meta-analysis identified two novel SNP loci associated with cognitive performance at the genomewide significance level (P Discussion These data provide new insight into the genetics of neurocognitive function that are applicable to genetic research of neuropsychiatric illness. Novel genes implicated include CENPO, TP53, ATXN7L2, ARPP21, and RPL31P12. Our results also support several loci derived from the recent CHARGE meta-analysis of general cognitive function, the UK Biobank GWAS of verbal-numerical reasoning, and the SSGAC analysis of educational attainment. Polygenic overlap analyses demonstrate the significance of understanding the genetics of general cognitive function to unraveling the etiology of numerous psychiatric illness and health-relevant conditions.
Highlights
Genome-wide association studies (GWAS) of complex quantitative phenotypes such as height[1] and body mass index[2] have successfully discovered and replicated hundreds of common variants meeting criteria for genome-wide significant association
On chromosome 1 (Figure 2, bottom), a cluster of six single-nucleotide polymorphisms (SNP) located in a large intergenic non-coding RNA (lincRNA), RP4-665J23.1, were genomewide significant
Our top GWAS hit was rs76114856, of which the minor T allele was associated with reduced cognitive performance
Summary
Genome-wide association studies (GWAS) of complex quantitative phenotypes such as height[1] and body mass index[2] have successfully discovered and replicated hundreds of common variants meeting criteria for genome-wide significant association.
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