Developmental dyslexia (DD) is a complex neurodevelopmental deficit characterized by impaired reading acquisition, in spite of adequate neurological and sensorial conditions, educational opportunities and normal intelligence. Despite the successful characterization of DD-susceptibility genes, we are far from understanding the molecular etiological pathways underlying the development of reading (dis)ability. By focusing mainly on clinical phenotypes, the molecular genetics approach has yielded mixed results. More optimally reduced measures of functioning, that is, intermediate phenotypes (IPs), represent a target for researching disease-associated genetic variants and for elucidating the underlying mechanisms. Imaging data provide a viable IP for complex neurobehavioral disorders and have been extensively used to investigate both morphological, structural and functional brain abnormalities in DD. Performing joint genetic and neuroimaging studies in humans is an emerging strategy to link DD-candidate genes to the brain structure and function. A limited number of studies has already pursued the imaging–genetics integration in DD. However, the results are still not sufficient to unravel the complexity of the reading circuit due to heterogeneous study design and data processing. Here, we propose an interdisciplinary, multilevel, imaging–genetic approach to disentangle the pathways from genes to behavior. As the presence of putative functional genetic variants has been provided and as genetic associations with specific cognitive/sensorial mechanisms have been reported, new hypothesis-driven imaging–genetic studies must gain momentum. This approach would lead to the optimization of diagnostic criteria and to the early identification of ‘biologically at-risk’ children, supporting the definition of adequate and well-timed prevention strategies and the implementation of novel, specific remediation approach.

DD genetic (DCDC2) and environmental factors (smoke and miscarriage) underlie ADHD traits supporting a potential pleiotropic effect.

Our results add further evidence in support of GRIN2B contributing toward DD and deficits in DD. More specifically, our data support the view that GRIN2B influences DD as a categorical trait and its related quantitative phenotypes, thus shedding further light on the etiologic basis and the phenotypic complexity of this disorder.

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Even if substantial heritability has been reported and candidate genes have been identified extensively, all known marker associations explain only a small proportion of the phenotypic variance of developmental dyslexia (DD) and related quantitative phenotypes. Gene-by-gene interaction (also known as "epistasis"--G × G) triggers a non-additive effect of genes at different loci and should be taken into account in explaining part of the missing heritability of this complex trait. We assessed potential G × G interactions among five DD candidate genes, i.e., DYX1C1, DCDC2, KIAA0319, ROBO1, and GRIN2B, upon DD-related neuropsychological phenotypes in 493 nuclear families with DD, by implementing two complementary regression-based approaches: (1) a general linear model equation whereby the trait is predicted by the main effect of the number of rare alleles of the two genes and by the effect of the interaction between them, and (2) a family-based association test to detect G × G interactions between two unlinked markers by splitting up the association effect into a between- and a within-family genetic orthogonal components. After applying 500,000 permutations and correcting for multiple testing, both methods show that G × G effects between markers within the DYX1C1, KIAA0319/TTRAP, and GRIN2B genes lower the memory letters composite z-score of on average 0.55 standard deviation. We provided initial evidence that the effects of familial transmission of synergistic interactions between genetic risk variants can be exploited in the study of the etiology of DD, explain part of its missing heritability, and assist in designing customized charts of individualized neurocognitive impairments in complex disorders, such as DD.