Reading and writing are crucial for many aspects of modern life but up to 1 in 10 children are affected by dyslexia [1, 2], which can persist into adulthood. Family studies of dyslexia suggest heritability up to 70% [3, 4], yet no convincing genetic markers have been found due to limited study power [5]. Here, we present a genome-wide association study representing a 20-fold increase in sample size from prior work, with 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls. We identified 42 independent genome-wide significant loci: 17 are in genes linked to or pleiotropic with cognitive ability/educational attainment; 25 are novel and may be more specifically associated with dyslexia. Twenty-three loci (12 novel) were validated in independent cohorts of Chinese and European ancestry. We confirmed a similar genetic aetiology of dyslexia between sexes, and found genetic covariance with many traits, including ambidexterity, but not neuroanatomical measures of language-related circuitry. Causal analyses revealed a directional effect of dyslexia on attention deficit hyperactivity disorder and bidirectional effects on socio-educational traits but these relationships require further investigation. Dyslexia polygenic scores explained up to 6% of variance in reading traits in independent cohorts, and might in future enable earlier identification and remediation of dyslexia.

Reading and writing are crucial life skills but roughly one in ten children are affected by dyslexia, which can persist into adulthood. Family studies of dyslexia suggest heritability up to 70%, yet few convincing genetic markers have been found. Here we performed a genome-wide association study of 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls and identified 42 independent genome-wide significant loci: 15 in genes linked to cognitive ability/educational attainment, and 27 new and potentially more specific to dyslexia. We validated 23 loci (13 new) in independent cohorts of Chinese and European ancestry. Genetic etiology of dyslexia was similar between sexes, and genetic covariance with many traits was found, including ambidexterity, but not neuroanatomical measures of language-related circuitry. Dyslexia polygenic scores explained up to 6% of variance in reading traits, and might in future contribute to earlier identification and remediation of dyslexia.

Reading and language abilities are critical for educational achievement and success in adulthood. Variation in these traits is highly heritable, but the underlying genetic architecture is largely undiscovered. Genetic studies of reading and language skills traditionally focus on children with developmental disorders; however, much larger unselected adult samples are available, increasing power to identify associations with specific genetic variants of small effect size. We introduce an Australian adult population cohort (41.7–73.2 years of age, N = 1505) in which we obtained data using validated measures of several aspects of reading and language abilities. We performed genetic association analysis for a reading and spelling composite score, nonword reading (assessing phonological processing: a core component in learning to read), phonetic spelling, self-reported reading impairment and nonword repetition (a marker of language ability). Given the limited power in a sample of this size (~80% power to find a minimum effect size of 0.005), we focused on analyzing candidate genes that have been associated with dyslexia and developmental speech and language disorders in prior studies. In gene-based tests, FOXP2, a gene implicated in speech/language disorders, was associated with nonword repetition (p < .001), phonetic spelling (p = .002) and the reading and spelling composite score (p < .001). Gene-set analyses of candidate dyslexia and speech/language disorder genes were not significant. These findings contribute to the assessment of genetic associations in reading and language disorders, crucial for understanding their etiology and informing intervention strategies, and validate the approach of using unselected adult samples for gene discovery in language and reading.

In the version of this article originally published, a paragraph was omitted in the Methods section, reading "Genomic control. Top SNPs are reported from the more conservative GWAS results adjusted for genomic control (Fig. 1, Extended Data Figs. 1-4, and Supplementary Tables 1, 2, 9 and 10), whereas downstream analyses (including gene-set analysis, enrichment and heritability partitioning, genetic correlations, polygenic prediction, candidate gene replication) are based on GWAS results without genomic control." The paragraph has now been included in the HTML and PDF versions of the article.

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