Scientists Identify Genes Linked to Dyslexia

In the largest study of its kind, researchers pinpointed 42 genetic variations tied to the language-based learning disability

Margaret Osborne

Daily CorrespondentOctober 26, 2022

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Millions of Americans have dyslexia, a language-based learning disability that makes reading and spelling more difficult. Studies have suggested that the condition runs in families, but no research had determined which genes are linked to it. 

Now, in the largest genome-wide association study on dyslexia, scientists have pinpointed 42 genetic variants correlated with the disability. They published their findings last week in Nature Genetics.

“We can follow up the significant genes to see what their function is and how it might relate to the cognitive processes involved in reading and spelling,” lead researcher Michelle Luciano, a psychologist at the University of Edinburgh in Scotland, tells the Guardian’s Nicola Davis. “At the moment, there are no direct implications for people with dyslexia, although it helps them understand that the condition has very complex causes.”

The authors analyzed data from 51,800 adults with self-reported dyslexia and from more than one million adults without it. Most participants were of European origin, and all were involved in research with 23andMe, a DNA testing and ancestry service.

Of the genetic variations they found, 15 had previously been linked with thinking skills, academic achivement or other neurodevelopmental conditions such as language delay, per a statement from the Max Planck Institute for Psycholinguistics. But 27 were completely new; they had not been associated with any related cognitive trait. 

These genes do not necessarily cause dyslexia, but they might make it more likely to crop up if combined with certain environmental factors, such as learning styles, Luciano tells New Scientist’s Christa Lesté-Lasserre.  https://www.smithsonianmag.com/smart-news/scientists-identify-genes-linked-to-dyslexia-180980998/?utm_source=smithsoniandaily&utm_medium=email&utm_campaign=20221026daily-responsive&spMailingID=47559754&spUserID=MTA2NzA5NTYxODc4OAS2&spJobID=2326060425&spReportId=MjMyNjA2MDQyNQS2

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https://www.nature.com/articles/s41588-022-01192-y

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Discovery of 42 genome-wide significant loci associated with dyslexia

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• Open Access
• Published: 20 October 2022

Discovery of 42 genome-wide significant loci associated with dyslexia

• Catherine Doust,
• Pierre Fontanillas,
• Else Eising,
• Scott D. Gordon,
• Zhengjun Wang,
• Gökberk Alagöz,
• Barbara Molz,
• 23andMe Research Team,
• Quantitative Trait Working Group of the GenLang Consortium,
• Beate St Pourcain,
• Clyde Francks,
• Riccardo E. Marioni,
• Jingjing Zhao,
• Silvia Paracchini,
• Joel B. Talcott,
• Anthony P. Monaco,
• John F. Stein,
• Jeffrey R. Gruen,
• Richard K. Olson,
• Erik G. Willcutt,
• John C. DeFries,
• Bruce F. Pennington,
• Shelley D. Smith,
• Margaret J. Wright,
• …
• Michelle Luciano 

Nature Genetics (2022)Cite this article

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Abstract

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.

Main

The ability to read is crucial for success at school and access to employment, information and health and social services, and is related to attained socioeconomic status¹. Dyslexia is a neurodevelopmental disorder characterized by severe reading difficulties, present in 5–17.5% of the population, depending on diagnostic criteria^2,3. It often involves impaired phonological processing (the decoding of sound units, or phonemes, within words) and frequently co-occurs with psychiatric and other developmental disorders⁴, especially attention-deficit hyperactivity disorder (ADHD)^5,6 and speech and language disorders^7,8. Dyslexia may represent the low extreme of a continuum of reading ability, a complex multifactorial trait with heritability estimates ranging from 40% to 80%^9,10. Identifying genetic risk factors not only aids increased understanding of the biological mechanisms, but may also expand diagnostic capabilities, facilitating earlier identification of individuals prone to dyslexia and co-occurring disorders for specific support.

Previous genome-wide investigations of dyslexia have been limited to linkage analyses of affected families¹¹ or modest (n < 2,300 cases) association studies of diagnosed children and adolescents¹². Candidate genes from linkage studies show inconsistent replication, and genome-wide association studies (GWAS) have not found significant associations, although LOC388780 and VEPH1 were supported in gene-based tests¹². Larger cohorts are vital for increasing sensitivity to detect new genetic associations of small effect. Here, we present the largest dyslexia GWAS to date, with 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls, all of whom are research participants with the personal genetics company 23andMe, Inc. We validate our association discoveries in independent cohorts, provide functional annotations of significant variants (mainly single-nucleotide polymorphisms (SNPs)) and potential causal genes, and estimates of SNP-based heritability. Lastly, we investigate genetic correlations with reading and related skills, health, socioeconomic, and psychiatric measures, and evaluate the evidence for previously implicated dyslexia candidate genes in our well-powered results.

Results

Genome-wide associations

The full dataset included 51,800 (21,513 males, 30,287 females) participants responding ‘yes’ to the question ‘Have you been diagnosed with dyslexia?’ (cases) and 1,087,070 (446,054 males, 641,016 females) participants responding ‘no’ (controls). Participants were aged 18 years or over (mean ages of cases and controls were 49.6 years (s.d. 16.2) and 51.7 years (s.d. 16.6), respectively). We identified 42 independent genome-wide significant associated loci (P < 5 × 10⁻⁸) and 64 loci with suggestive significance (P < 1 × 10⁻⁶) (Fig. 1 and Supplementary Table 1). Genomic inflation was moderate (λ_GC = 1.18) and consistent with polygenicity (see Q–Q plot, Extended Data Fig. 1). We also performed sex-specific GWAS and age-specific GWAS (younger or older than 55 years) because dyslexia prevalence was higher in our younger (5.34% in 20- to 30-year-olds) than older (3.23% in 80- to 90-year-olds) participants. These subsample analyses showed high consistency with the main GWAS (of the full sample). Genetic correlation estimated by linkage disequilibrium (LD) score regression (LDSC) was 0.91 (95% confidence intervals (CI): 0.86–0.96; P = 8.26 × 10⁻²⁵³) in males and females, and 0.97 (95% CI: 0.91–1.02; P = 2.32 × 10⁻²⁶⁸) between younger and older adults.

Of the 17 genome-wide significant variants in the female GWAS (Extended Data Fig. 2), all but four (rs61190714, rs4387605, rs12031924 and rs57892111) were significant in the main GWAS and, of these four, three were in LD with an SNP that approached significance (P < 3.3 × 10⁻⁷ or smaller) in the main analysis. Intergenic SNP rs57892111 (located between TFAP2B and PKHD1 on chromosome 6p) was not among the significant or suggestive SNPs of the main analysis, and so may represent a female-specific variant. There is no evidence from existing GWAS that this SNP is associated with any other human trait. Of the six genome-wide significant variants in the male GWAS (Extended Data Fig. 3), all were significant in the main GWAS.

In the main GWAS, all significant variants were autosomal, except rs5904158 at Xq27.3 (for regional association plots, see Supplementary Fig. 1). A total of 17 index variants were in high LD with published (genome-wide significant) associated SNPs in the NHGRI GWAS Catalog¹³ (15 were associated with cognitive/educational traits; Supplementary Tables 1 and 2). Thus, a total of 27 associated loci showed no evidence of published genome-wide associations with traits expected to overlap with dyslexia (for example, educational attainment, cognitive ability) and were considered new (Table 1).Table 1 New SNP associations with dyslexia, including gene-based results, eQTL status, expression in brain and validation in three independent cohorts (GenLang Consortium, CRS and NeuroDys)

Full size table

Of 38 associated loci (the 4 remaining were tagged by indels unavailable in validation cohorts), 3 (rs13082684, rs34349354 and rs11393101) were significant at a Bonferroni-corrected level (P < 0.05/38) in the GenLang consortium GWAS meta-analysis of reading (n = 33,959) and spelling (n = 18,514) ability¹⁴. At P < 0.05, 18 were associated in GenLang, 3 in the NeuroDys case-control GWAS¹² (n = 2,274 cases), and 5 in the Chinese Reading Study (CRS) of reading accuracy and fluency (n = 2,270; Supplementary Note) (Table 1 and Supplementary Tables 3–6).

Gene-based tests identified 173 significantly associated genes (Supplementary Table 7) but no significantly enriched biological pathways (Supplementary Table 8). We estimated the LDSC liability-scale SNP-based heritability of dyslexia to be h²_SNP = 0.152 (standard error = 0.006) using the 23andMe sample prevalence of 5%, and h²_SNP = 0.189 (standard error = 0.008) using a 10% prevalence of dyslexia, which is more typical of the general population^2,3.

Fine-mapping and functional annotations

Within the credible variant set (Supplementary Table 1), missense variants were the most common (55%) of the coding variants; Extended Data Figure 4 summarizes all predicted variant effects. Predicted deleterious variants by SIFT (Sorting Intolerant From Tolerant) score were identified in R3HCC1L, SH2B3, CCDC171, C1orf87, LOXL4, DLAT, ALG9 and SORT1. Within the credible variant set, no genes were especially intolerant to functional variation (smallest LoFtool (Loss-of-Function) percentile was 0.39). For the 42 associated loci, the most probable gene targets of each were estimated by the Overall V2G (Variant-to-Gene) score from OpenTargets (Supplementary Table 9). Two index variants (missense variant rs12737449 (C1orf87) and rs3735260 (AUTS2)) could be causal because they had combined annotation dependent depletion (CADD) scores suggestive of deleteriousness to gene function according to Kircher et al.¹⁵ (Supplementary Table 10). The AUTS2 variant RegulomeDB rank of 2b indicated a regulatory role; its chromatin state supported location at an active transcription start site^16,17.

Of the 173 significant genes from genome-wide gene-based tests in MAGMA (see Supplementary Table 11 for their functions), 129 could be functionally annotated (Supplementary Table 12). Protein-coding and noncoding sequences are actively conserved in approximately three-quarters of these genes, 63% are more intolerant to variation than average and 33% are intolerant to loss-of-function mutations. Gene property analysis for general tissues and 13 brain tissues confirmed the importance of the brain and specific brain regions (Supplementary Tables 13 and 14). Levels of brain expression for 125 of the 173 significant genes from gene-based tests could be mapped in FUMA and are shown in Supplementary Table 15. A total of 20 genes showed high general brain expression levels and, of these, 3 (PPP1R1B, NPM1 and WASF3) were located near significant SNP associations. Of the 12 brain regions assessed, gene expression was generally highest in the cerebellar hemisphere, cerebellum, and cerebral cortex, consistent with the results of gene property analysis…CONT…

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