Research reportThe DCDC2/intron 2 deletion and white matter disorganization: Focus on developmental dyslexia
Introduction
A disturbance in the genetically driven developmental mechanisms of early neuronal migration is at the basis of several neurodevelopment disorders, including developmental dyslexia (hereafter: dyslexia; Diaz & Gleeson, 2009). Dyslexia is an aetiologically heterogeneous condition, typically diagnosed in the first school years, characterized by an impaired reading acquisition in spite of adequate neurological and sensorial conditions, educational opportunities, and normal intelligence. Following earlier descriptions of high familial aggregation of the disorder, substantial heritability has been reported, with estimates across dyslexia and related quantitative traits (such as reading and spelling) ranging from .18 to .72 (Plomin & Kovas, 2005). A multifactorial threshold model of inheritance, whereby multiple genetic and environmental factors contribute to phenotypic variation, has been found as the most plausible mode of familial transmission of the disorder (Plomin & Kovas, 2005).
The DCDC2 gene has been recognized as one of the leading risk genes in dyslexia (Brkanac et al., 2007, Cope et al., 2012, Deffenbacher et al., 2004, Harold et al., 2006, Marino et al., 2012, Meng et al., 2005, Newbury et al., 2011, Powers et al., 2013, Schumacher et al., 2006, Wilcke et al., 2009, Zhong et al., 2013), and in reading abilities in the normal range (Lind et al., 2010, Scerri et al., 2011), even though negative results have been also reported (Becker et al., 2014, Ludwig et al., 2008, Parracchini et al., 2011). Data show that the DCDC2 gene is involved in neuronal migration and is most highly expressed in the entorhinal cortex, inferior and medial temporal cortex, hypothalamus, amygdala and hippocampus (Meng et al., 2005). The embryonic knockdown of the DCDC2 function in rodent neocortical progenitor cells results in postnatal small and scattered heterotopias within the white matter (Burbridge et al., 2008). The specific function of the Dcdc2 protein in neuronal migration has yet to be elucidated, but analyses of its protein structure provide some clues. It was found that Dcdc2 exhibits the same functional features displayed by the Dclk and Dcx proteins, which have been found to have a role in the axonal growth across the corpus callosum, and in neuronal migration within the cerebral cortex (Coquelle et al., 2006, Deuel et al., 2006, Koizumi et al., 2006). A highly polymorphic, short-tandem repeat (named BV677278) located in the intron 2 of the DCDC2 gene was reported (Meng et al., 2005), for which a role as a regulatory region has been suggested (Meng et al., 2011). Recently, Powers et al. (2013) identified the BV677278-binding protein as the transcription factor ETV6, confirmed BV677278 as a regulatory element, and proposed a new name for BV677278, i.e., regulatory element associated with dyslexia 1 (READ1). As such, READ1 could substantially influence the function of the DCDC2 gene in neuronal migration. Noteworthy, a rare DCDC2 variant, i.e., a DCDC2/intron 2 deletion embedding READ1 (DCDC2d), was found to increase the risk of dyslexia by independent studies (Brkanac et al., 2007, Cope et al., 2012, Harold et al., 2006, Marino et al., 2012, Wilcke et al., 2009) although negative findings have also been reported (Ludwig et al., 2008, Powers et al., 2013). Interestingly, in healthy adult humans DCDC2d has been found associated with altered grey matter volumes in specific cortical regions (Meda et al., 2008), several of which correspond to those found altered by post-mortem studies of dyslexia (Galaburda, Sherman, Rosen, Aboitiz, & Geschwind, 1985). Furthermore, in adult healthy humans allelic variation in the DCDC2 gene has been associated with individual differences in fibre tracts – as those connecting the left medial temporal gyrus with the angular and supramarginal gyri, the superior longitudinal fasciculus as well as the corpus callosum (Darki, Peyrard-Janvid, Matsson, Kere, & Lingberg, 2012) – which are commonly found altered in neuroimaging studies of reading and dyslexia (Vandermosten et al., 2012, Wandell and Yeatman, 2013; Fig. 1 and Table 1).
Neuroimaging studies have consistently revealed that dyslexia is linked to alterations of a left-hemispheric network, including the inferior frontal, temporo-parietal and occipito-temporal cortical regions (Brambati et al., 2004, Brambati et al., 2006, Silani et al., 2005). The first two regions constitute a dorsal phonological route, whereas the occipito-temporal region hosts a ventral orthographical route. Furthermore, some studies suggest a role of the corpus callosum that drives the left lateralization of the reading network (Linkersdorfer et al., 2012, Richlan et al., 2013, Vandermosten et al., 2012, Wandell and Yeatman, 2013). The recent computational methods that allow the study of brain structural properties via magnetic resonance imaging (MRI), such as voxel-based diffusion tensor imaging (VB-DTI) techniques, have greatly extended our knowledge of the morphology of dyslexia and consistently reported altered concentrations of white matter. Overall, DTI data on dyslexia converge in finding white matter abnormalities in multiple fibre bundles, i.e., superior longitudinal, arcuate, inferior longitudinal and inferior fronto-occipital fasciculi (mainly in the left hemisphere), and the whole corpus callosum (Vandermosten et al., 2012, Wandell and Yeatman, 2013; see Fig. 1 and Table 1 for a descriptive survey of the related literature), as anatomic correlates of the disorder.
Given the above evidence, we hypothesized that DCDC2d could: (1) be associated with disorganization of the white matter structure in general; (2) be associated with disorganization of the white matter structure in the dyslexic brain; (3) influence the correlation between reading performance and white matter structure.
To address these hypotheses we measured the fractional anisotropy (FA) – a parameter linked to axon packing and myelination (Beaulieu, 2002) – of four groups, namely, subjects with dyslexia with/without DCDC2d (hereafter: DYS+ and DYS−, respectively), and normal readers with/without DCDC2d (hereafter: NR+ and NR−, respectively). A 3 T MRI scanner was employed together with VB-DTI analyses. Furthermore, we tested DCDC2d effects upon the correlation patterns between FA and average reading. This was the first study to investigate subjects with dyslexia with an identified element of genetic susceptibility (DCDC2d) at a neuroanatomical level by means of FA analyses.
Section snippets
Ethics
The protocol was approved by the Scientific Review Board and the Ethical Committee of the “Eugenio Medea” and “San Raffaele” Scientific Institutes.
Subjects
Subjects with dyslexia were recruited from a sample of an ongoing genetic study cohort, which has been genotyped for DCDC2d gene for genetic association tests (n = 303; Marino et al., 2012). Inclusion criteria at the time of recruitment for the genetic study were: (1) either accuracy or speed z-scores ≤−2.0 standard deviations (SDs) on timed
Demographic assessment, genotypes and neuropsychological characteristics of participants
Table 2a summarizes descriptives and related statistics for the socio-demographic measures and Adult Dyslexia Checklist score in the four groups. At the Bonferroni-corrected level of significance, there were significant group differences in education, IQ and Adult Dyslexia Checklist scores. All measures displayed acceptable distribution as tested by the Shapiro–Wilk test of normality, except for education (p = .008 and p = .004, respectively, in NR− and NR+) and socio-economic status (p < .001
Discussion
The major contribution of our study was to provide clear, in vivo evidence of white matter disorganization related to the DCDC2-mediated genetic vulnerability. There is a relative paucity of studies relating genes, brain and behaviour in the developmental cognitive neurosciences, and in dyslexia specifically. Since genes are distal contributors whereas the brain is the proximal driver of human behaviour, we believe that data on the anatomical pathways from genes to behaviour are essential to
Acknowledgements
We thank all the young adults who took part in this study. We also want to express our gratitude towards A. Citterio for helping in neuropsychological data collection, G. Menozzi for technical assistance on databases and C. Saccuman and A. Iadanza for assistance in MRI scan acquisition.
References (70)
- et al.
Neuropsychological deficits and neural dysfunction in familial dyslexia
Brain Research
(2006) - et al.
Patterns of hand preference in a student population
Cortex
(1975) - et al.
Postnatal analysis of the effect of embryonic knockdown and overexpression of candidate dyslexia susceptibility gene homolog DCDC2 in the rat
Neuroscience
(2008) - et al.
White matter fiber tracts of the human brain: three-dimensional mapping at microscopic resolution, topography and intersubject variability
NeuroImage
(2006) - et al.
A diffusion tensor imaging tractography atlas for virtual in vivo dissections
Cortex
(2008) - et al.
Variants in the DYX2 locus are associated with altered brain activation in reading-related brain regions in subjects with reading disability
NeuroImage
(2012) - et al.
Association of attention-deficit/hyperactivity disorder with a candidate region for reading disabilities on chromosome 6p
Biological Psychiatry
(2009) - et al.
Three dyslexia susceptibility genes, DYX1C1, DCDC2, and KIAA0319, affect temporo-parietal white matter structure
Biological Psychiatry
(2012) - et al.
Genetic interactions between doublecortin and doublecortin-like kinase in neuronal migration and axon outgrowth
Neuron
(2006) - et al.
Children's reading performance is correlated with white matter structure measured by diffusion tensor imaging
Cortex
(2005)
The molecular and genetic mechanisms of neocortex development
Clinics in Perinatology
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data
NeuroImage
A temporal sampling framework for developmental dyslexia
Trends in Cognitive Sciences
Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification
NeuroImage
Altering cortical connectivity: remediation-induced changes in the white matter of poor readers
Neuron
Microstructure of temporo-parietal white matter as a basis for reading ability: evidence from diffusion tensor magnetic resonance imaging
Neuron
Doublecortin-like kinase functions with doublecortin to mediate fiber tract decussation and neuronal migration
Neuron
Different underlying neurocognitive deficits in developmental dyslexia: a comparative study
Neuropsychologia
Modifying the brain activation of poor readers during sentence comprehension with extended remedial instruction: a longitudinal study of neuroplasticity
Neuropsychologia
Left lateralized white matter microstructure accounts for individual differences in reading ability and disability
Neuropsychologia
Alleles of a polymorphic ETV6 binding site in DCDC2 confer risk of reading and language impairment
American Journal of Human Genetics
Developmental dyslexia: specific phonological deficit or general sensorimotor dysfunction?
Current Opinion in Neurobiology
White matter microstructural differences linked to left perisylvian language network in children with dyslexia
Cortex
DCDC2, KIAA0319 and CMIP are associated with reading-related traits
Biological Psychiatry
Strong genetic evidence of DCDC2 as a susceptibility gene for dyslexia
American Journal of Human Genetics
The contribution of white and gray matter differences to developmental dyslexia: insights from DTI and VBM at 3.0 T
Neuropsychologia
A qualitative and quantitative review of diffusion tensor imaging studies in reading and dyslexia
Neuroscience and Biobehavioral Reviews
Do differences in brain activation challenge universal theories of dyslexia?
Brain Language
The basis of anisotropic water diffusion in the nervous system – a technical review
NMR in Biomedicine
Genetic analysis of dyslexia candidate genes in the European cross-linguistic NeuroDys cohort
European Journal of Human Genetics
Regional reductions of gray matter volume in familial dyslexia
Neurology
Evaluation of candidate genes for DYX1 and DYX2 in families with dyslexia
American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics
Culture Fair: una piccola batteria di test per la misura del fattore “g”
Common and divergent roles for members of the mouse DCX superfamily
Cell Cycle
Gruppo MT Nuove prove di lettura MT per la scuola media inferiore
Cited by (37)
A large-scale investigation of white matter microstructural associations with reading ability
2022, NeuroImageCitation Excerpt :Two fiber bundles that run under the SLF, the inferior longitudinal fasciculus (ILF) and inferior fronto-occipital fasciculus (IFO), serve to connect occipital and temporal-occipital areas to anterior temporal and frontal regions, respectively (Martino et al., 2010; Herbet et al., 2018), and have been identified as candidate reading tracts (Vandermosten et al., 2012a; Yeatman et al., 2013). The left ILF has exhibited increased FA in typically developing readers compared to dyslexic readers (Steinbrink et al., 2008; Marino et al., 2014; Su et al., 2018), and bilateral ILF FA has been positively related to reading performance (Steinbrink et al., 2008; Odegard et al., 2009; Feldman et al., 2012; Yeatman et al., 2012a; Lebel et al., 2013; Horowitz-Kraus et al., 2014; Zhang et al., 2014; Horowitz-Kraus et al., 2015). However, a few studies have found negative associations between FA and reading scores in the left ILF (Yeatman et al., 2012a; Huber et al., 2018), and one study has found increased left ILF FA in dyslexic individuals compared to their typically reading counterparts (Banfi et al., 2019).
Animal models of developmental dyslexia: Where we are and what we are missing
2021, Neuroscience and Biobehavioral ReviewsThe effects of the functional interplay between the Default Mode and Executive Control Resting State Networks on cognitive outcome in preterm born infants at 6 months of age
2021, Brain and CognitionCitation Excerpt :Coherently similar patterns of functional tuning underlying normotypical behavioral performance have been also observed in subjects with developmental dyslexia (Shaywitz et al., 2003), attention deficit hyperactivity disorder (Cortese et al., 2012; Fassbender & Schweitzer, 2006) and dyscalculia (Kaufmann et al., 2009). This is not surprising when taking into consideration that developmental disorders can stem from dysfunctional migratory trajectories similar to those that may occur in very preterm born brains (Kuzniecky, 1994; Marino et al., 2014; McManus & Golden, 2004), potentially resulting in a ‘preterm cognitive syndrome’. Thus, sub-threshold difficulties may potentially arise in different cognitive domains which necessitate to be supported (or surrogated) by alternate processing strategies in order to boost and adjust functional homeostatic configurations to the degree of cognitive processing load.
Sensory auditory interval perception errors in developmental dyslexia
2020, NeuropsychologiaNeurobiological systems in dyslexia
2019, Trends in Neuroscience and EducationCitation Excerpt :Finally, ongoing genetic studies are beginning to identify variants of DCDC2 which are protective as well as deleterious [34]. In a diffusion tensor imaging study of four groups of 16–21 year-old subjects (dyslexia with/without the DCDC2 variant, and normal readers with/without the variant), Marino et al. [140] found that irrespective of dyslexia, individuals with the DCDC2 gene had reduced FA in the left arcuate fasciculus and left hemisphere region of the splenium of the corpus callosum. Moreover, the individuals with dyslexia who also possessed the DCDC2 variant had reduced splenium FA which favored better reading ability.
Neural Noise Hypothesis of Developmental Dyslexia
2017, Trends in Cognitive SciencesCitation Excerpt :In addition, there is evidence that the interference technique used to produce knockdown phenotypes (used by Centanni et al. [3,10]) can have phenotypic effects unrelated to the target gene [69,70]. Finally, we note that these genes have also been associated with neurobiological phenotypes other than those discussed, such as corpus callosum area in rats (Kiaa0319 [13]) and white matter integrity in humans in both corpus callosum and left arcuate fasciculus (DCDC2[25]). Collectively, evidence from animal models, along with convergent findings in humans, suggests a link between RD risk genes and abnormal cortical microcircuits.
- 1
These authors equally contributed to the work.