Genetic Structure of IQ, Phonemic Decoding Skill, and Academic Achievement

Project DyAdd: Non-linguistic Theories of Dyslexia Predict Intelligence

Two themes have puzzled the research on developmental and learning disorders for decades. First, some of the risk and protective factors behind developmental challenges are suggested to be shared and some are suggested to be specific for a given condition. Second, language-based learning difficulties like dyslexia are suggested to result from or correlate with non-linguistic aspects of information processing as well. In the current study, we investigated how adults with developmental dyslexia or ADHD as well as healthy controls cluster across various dimensions designed to tap the prominent non-linguistic theories of dyslexia. Participants were 18–55-year-old adults with dyslexia (n = 36), ADHD (n = 22), and controls (n = 35). Non-linguistic theories investigated with experimental designs included temporal processing impairment, abnormal cerebellar functioning, procedural learning difficulties, as well as visual processing and attention deficits. Latent profile analysis (LPA) was used to investigate the emerging groups and patterns of results across these experimental designs. LPA suggested three groups: (1) a large group with average performance in the experimental designs, (2) participants predominantly from the clinical groups but with enhanced conditioning learning, and (3) participants predominantly from the dyslexia group with temporal processing as well as visual processing and attention deficits. Despite the presence of these distinct patterns, participants did not cluster very well based on their original status, nor did the LPA groups differ in their dyslexia or ADHD-related neuropsychological profiles. Remarkably, the LPA groups did differ in their intelligence. These results highlight the continuous and overlapping nature of the observed difficulties and support the multiple deficit model of developmental disorders, which suggests shared risk factors for developmental challenges. It also appears that some of the risk factors suggested by the prominent non-linguistic theories of dyslexia relate to the general level of functioning in tests of intelligence.

Genome-wide association study of word reading: Overlap with risk genes for neurodevelopmental disorders

Reading disabilities (RD) are the most common neurocognitive disorder, affecting 5% to 17% of children in North America. These children often have comorbid neurodevelopmental/psychiatric disorders, such as attention deficit/hyperactivity disorder (ADHD). The genetics of RD and their overlap with other disorders is incompletely understood. To contribute to this, we performed a genome-wide association study (GWAS) for word reading. Then, using summary statistics from neurodevelopmental/psychiatric disorders, we computed polygenic risk scores (PRS) and used them to predict reading ability in our samples. This enabled us to test the shared aetiology between RD and other disorders. The GWAS consisted of 5.3 million single nucleotide polymorphisms (SNPs) and two samples; a family-based sample recruited for reading difficulties in Toronto (n = 624) and a population-based sample recruited in Philadelphia [Philadelphia Neurodevelopmental Cohort (PNC)] (n = 4430). The Toronto sample SNP-based analysis identified suggestive SNPs (P ~ 5 × 10^-7 ) in the ARHGAP23 gene, which is implicated in neuronal migration/axon pathfinding. The PNC gene-based analysis identified significant associations (P < 2.72 × 10^-6 ) for LINC00935 and CCNT1, located in the region of the KANSL2/CCNT1/LINC00935/SNORA2B/SNORA34/MIR4701/ADCY6 genes on chromosome 12q, with near significant SNP-based analysis. PRS identified significant overlap between word reading and intelligence (R²  = 0.18, P = 7.25  × 10^-181 ), word reading and educational attainment (R²  = 0.07, P = 4.91 × 10^-48 ) and word reading and ADHD (R²  = 0.02, P = 8.70 × 10^-6 ; threshold for significance = 7.14 × 10^-3 ). Overlap was also found between RD and autism spectrum disorder (ASD) as top-ranked genes were previously implicated in autism by rare and copy number variant analyses. These findings support shared risk between word reading, cognitive measures, educational outcomes and neurodevelopmental disorders, including ASD.