Multivariate genome-wide association analysis of quantitative reading skill and dyslexia improves gene discovery

Abstract

AbstractThe ability to read is an important life skill and a major route to education. Individual differences in reading ability are influenced by genetic variation, with a heritability of 0.66 for word reading, estimated by twin studies. Until recently, genomic investigations were limited by modest sample size. Here we use a multivariate genome-wide association study (GWAS) method, MTAG, to leverage summary statistics from two independent GWAS efforts, boosting power for analyses of reading ability; GenLang meta-analysis of word reading (N = 27 180) and the 23andMe, Inc., study of dyslexia (Ncases= 51 800, Ncontrols= 1 087 070). We increase effective sample size to N = 102 082, representing the largest genetic study of reading ability, to date. We identified 35 independent genome-wide significant loci, including 7 regions not previously reported. Single-nucleotide polymorphism (SNP) based heritability was estimated at 24%. We observed clear positive genetic correlations with cognitive and educational measures. Gene-set analyses implicated neuronal synapses and proneural glioblastoma pathways, further supported by enrichment of neuronally expressed genes in the developing embryonic brain. Polygenic scores of our multivariate results predicted between 2.29-3.50% of variance in reading ability in an independent sample, the National Child Development Study cohort (N = 6 410). Polygenic adaptation was examined using a large panel of ancient genomes spanning the last ∼15k years. We did not find evidence of selection, suggesting that reading ability may not have been subject to recent selection pressure in Europeans. By combining existing datasets to improve statistical power, these results provide novel insights into the biology of reading.