Genetics of dyslexia: the evolving landscape (2024)

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J Med Genet. 2007 May; 44(5): 289–297.

Published online 2007 Feb 16. doi:10.1136/jmg.2006.046516

PMCID: PMC2597981

PMID: 17307837

Johannes Schumacher, Per Hoffmann, Christine Schmäl, Gerd Schulte‐Körne, and Markus M Nöthen

Author information Article notes Copyright and License information PMC Disclaimer

Abstract

Dyslexia is among the most common neurodevelopmental disorders, with a prevalence of 5–12%. At the phenotypic level, various cognitive components that enable reading and spelling and that are disturbed in affected individuals can be distinguished. Depending on the phenotype dimension investigated, inherited factors are estimated to account for up to 80%. Linkage findings in dyslexia are relatively consistent across studies in comparison to findings for other neuropsychiatric disorders. This is particularly true for chromosome regions 1p34–p36, 6p21–p22, 15q21 and 18q11. Four candidate genes have recently been identified through systematic linkage disequilibrium studies in linkage region 6p21–p22, and through cloning approaches at chromosomal breakpoints. Results indicate that a disturbance in neuronal migration is a pathological correlate of dyslexia at the functional level. This review presents a summary of the latest insights into the genetics of dyslexia and an overview of anticipated future developments.

Dyslexia is among the most common neurodevelopmental disorders, with a prevalence of 5–12%.¹^,2 The prevalence varies with the use of different diagnostic criteria and, since reading and spelling are normally distributed in the population, is influenced by the cut‐off point applied to the psychometric tests. According to the International Classification of Diseases‐10, dyslexia is “a disorder manifested by difficulty learning to read despite conventional instruction, adequate intelligence and sociocultural opportunity”.³ Longitudinal studies have shown that the disorder involves an extremely stable developmental disturbance that does not, in contrast to popular opinion, disappear with adolescence.⁴ The psychosocial consequences are correspondingly grave. Affected individuals attain a much lower educational level and have substantially higher rates of unemployment and psychosocial stress than would be expected for their level of intelligence.⁵^,6^,7 In childhood, approximately 20% of those with dyslexia also present with attention‐deficit hyperactivity disorder (ADHD),⁸^,9^,10^,11^,12 whereas in adolescence depressive disorders and disorders of social behaviour are often associated with dyslexia.¹³^,14^,15 Whether dyslexia is more common among boys than girls has been part of a controversial discussion in the past, although recent epidemiological studies indicate a twofold increase in the risk for boys compared with that in girls.²^,16 The sex ratio may be influenced by severity, IQ and assessed cognitive profiles.¹⁷

Familial clustering in dyslexia was recognised a few years after the first description of the disorder by Hinshelwood in 1895.¹⁸^,19^,20 A child with an affected parent has a risk of 40–60% of developing dyslexia. This risk is increased when other family members are also affected.¹⁹^,21^,22^,23^,24^,25 There is an estimated 3–10‐fold increase in the relative risk for a sibling (λ_s), with an increase in λ_s observed when strict criteria are applied.²⁵ Twin studies have confirmed that genetic factors are substantially responsible for the familial clustering of dyslexia.¹⁷^,26 The proportion of inherited factors involved in the development of dyslexia is between 40% and 80%, the highest estimates being reported for the phenotype dimensions word reading (up to 58%) and spelling (70%).¹⁷^,26^,27 Twin studies have allowed for the estimation of heritabilities and also the impact of shared and non‐shared environmental factors. Although shared environmental effects are low for word reading, they are substantially higher (at about 14%) for reading and spelling correlated traits—for example, phonological awareness.²⁷

Whether or not sex has an influence on heritability is controversial. Although the results of a US American twin study (Colorado Twin Study) showed similar heritability between the sexes,²⁸^,29 Harlaar et al³⁰ found a higher heritability for boys in a UK sample (London Twins Early Development Study).

Through molecular genetic linkage studies in families with dyslexia, chromosome regions have been identified in which the presence of dyslexia susceptibility genes is suspected. As with all complex disorders, linkage findings are not completely overlapping between independent studies. However, greater consistency is reported for dyslexia than for most other neuropsychiatric disorders, and the identification of the first candidate genes therefore came as no surprise.

This review presents the current state of molecular genetic research on dyslexia, including discussion of the phenotypic aspects and neuropsychological concepts of dyslexia that have received increasing consideration in genetic research over recent years. Finally, the extent to which our understanding of dyslexia is likely to be increased through the results of current and future molecular genetic research is discussed.

Phenotypic aspects and neurophysiological theories

In general, the cognitive processes on which reading and spelling are based are complex, and differing cognitive dimensions ease the separate skills of reading and spelling. Such processes include those of short‐term memory, phonological awareness, rapid naming, and phonological and orthographic coding (table 11).). In recent years, several theories have been developed with the aim of characterising the basic processes underlying dyslexia. These have taken into consideration the increasing body of knowledge obtained from neurophysiological and imaging research (eg, event‐related potentials, functional MRI). The phonological deficit theory,³² which assumes a disturbance in phonological processing, is currently the most salient theory. According to this theory, affected individuals have difficulties in perceiving and segmenting phonemes, leading to difficulties in establishing a connection between phonemes and graphemes. The rapid auditory processing theory is another theory³³ that proposes that phonological deficits are secondary to an auditory deficit in the perception of short or rapidly varying sounds. Many individuals with dyslexia perform poorly on auditory tasks including frequency discrimination³⁴^,35 and temporal order judgement.³⁶ Abnormal neurophysiological responses to auditory stimuli have also been reported.³⁶^,37^,38 However, individuals with dyslexia also have visual perceptual deficits which these theories cannot adequately explain. The magnocellular theory accounts for disturbances in visual processing.³⁹^,40^,41^,42 The theory proposes that in a proportion of individuals with dyslexia, the perception of visual, rapid moving stimuli and stimuli of low spatial frequency and low contrast is impaired. This deficit is associated at the central nervous system (CNS) level with impaired sensitivity of cells within the retinocortical magnocellular pathway and in the extrastriate areas in the dorsal stream to which they project. The cerebellar deficit theory suggests that the automatisation of cognitive processes and motor control in the cerebellum are disturbed in individuals with dyslexia.⁴³ The double deficit hypothesis,⁴⁴ which assumes disturbances in phonological processing and the speed of processing, should also be mentioned in this context.

Table 1 Cognitive components involved in reading and writing

Component	Remark
Visual processing	The magnocellular system responds to moving stimuli and stimuli of low spatial frequency and low contrast. Impaired perception of moving stimuli and the neurophysiological correlates of this have been found repeatedly in individuals with dyslexia. The exact nature of this deficiency and its potential relationship to dyslexia is not yet clear
Phonological awareness	The ability to perceive, segment and manipulate the sounds of spoken words.³¹ Phonemes are the smallest meaningfully distinct sounds from which an acoustic speech flow can be constructed. The word dog, for example, consists of three phonemes /d/, /o/, /g/. The capacity for phonological awareness is often tested through a phoneme deletion task
Verbal short‐term memory	Various aspects of memory are required for reading. Many known words are no longer dissected into their phonemes, but are recalled directly from memory. Processing of unknown words into their phonemes occurs in short‐term memory. Short‐term memory is often examined by a digit span task
Phonological coding	The ability to put together the phonemes and then verbally express words which have never been previously read or heard. This ability is tested through reading of pseudowords
Orthographic coding	Orthographic coding refers to the assumed process of recognising a word by its holistic form. Orthographic coding is measured by a pseudohom*ophone task where an orally presented word has to be compared with a visual presentation of two phonologically indistinguishable words, of which one may be orthographically correct
Rapid naming	Rapid naming is a measure of the speed of processing. The naming of objects, numbers, letters and colours is typically measured

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Even though evidence for one or the other of these theories is typically reported in affected individuals, there is no evidence so far for specific subgroups of dyslexia. A reason for this could be that although some of the deficits found in affected individuals are correlated with reading and spelling, they may not be causally associated with dyslexia. Findings from genetic research may have the potential to help delineate which cognitive and neurophysiological processes are causally related.⁴⁵

Linkage findings in dyslexia

To date, linkage analyses in families with dyslexia have identified nine chromosome regions (dyslexia susceptibility 1(DYX1)–dyslexia susceptibility 9 (DYX9)) listed by the HUGO Gene Nomenclature Committee in which the presence of susceptibility genes is suspected (table 22).). There was initially great hope that it would be possible to correlate the respective cognitive components of dyslexia (table 11)) with specific linkage regions. Many studies accordingly investigated individual phenotype components as categorical or quantitative (quantitative trait loci (QTL)) subdimensions, and linkages with specific chromosomal regions have been claimed; unfortunately, with little support from independent studies so far. Nevertheless, the consistency of linkage findings is impressive in comparison to those for other neuropsychiatric disorders. This is particularly true of findings in chromosome regions 1p34–p36, 6p21–p22, 15q21 and 18q11, with support for each of these regions coming from the investigation of at least two large family samples.

Table 2 Summary of linkage findings in dyslexia

Locus	Number of families (individuals, sib pairs), country	Linkage evidence	Linkage evidence with components of the phenotype	Study design	References
DYX1	9 multiplex families (84 individuals), USA	LOD score 3.20	Reading	Categorical	Smith et al⁴⁶
	6 multiplex families (94 individuals), USA	LOD score 3.15	Single‐word reading	Categorical	Grigorenko et al⁴⁷
	7 multiplex families (67 individuals), Germany	LOD score 1.78	Spelling	Categorical	Schulte‐Körne et al⁴⁸
	90 families (611 individuals), USA	LOD score 2.34	Single‐word reading	Categorical	Chapman et al⁴⁹

DYX2	19 multiplex families (358 individuals*, 50 dizygotic twin‐pair), USA	p Values between 0.009–0.04	Dyslexia	QTL	Cardon et al⁵⁰
	82 families (181 sib pairs), UK	p Values between 0.0004–0.038	Orthographic and phonological processes	QTL	Fisher et al⁵¹
	79 families (126 sib pairs), USA	LOD scores between 2.42 and 3.10	Orthographic and phonological processes	QTL	Gayan et al⁵²
	89 families (195 sib pairs)†, UK	p Values between 0.00001–0.042	Phonological decoding	QTL	Fisher et al⁵³
	119 families (180 sib pairs)‡, USA	p Values between 0.002–0.006	Phonological decoding
	104 families (392 individuals)‡, USA	p Values between 0.0005–0.05	Orthographic and phonological processes	QTL	Kaplan et al⁵⁴
	8 multiplex families (176 individuals)§	LOD scores of 1.52 and 2.56	Single‐word reading, phoneme awareness	Categorical	Grigorenko et al⁵⁵

DYX3	1 multiplex family (36 individuals), Norway	LOD score 4.32	Dyslexia	Categorical	fagerheim et al*⁵⁶
	89 families (195 sib pairs), UK	p Value <0.001	Orthographic choice	QTL	Fisher et al⁵³
	119 families (180 sib pairs), USA	p Value of 0.001	Phonological awareness	QTL
	96 families (877 individuals), Canada	LOD scores of 1.13 and 3.82	Phonological coding,spelling	QTL and categorical	Petryshen et al⁵⁷
	11 multiplex families (97 individuals), Finland	LOD score 3.01	Dyslexia	Categarical	Kaminen et al⁵⁸

DYX4	96 families (877 individuals), Canada	LOD scores of 2.08 and 3.34	Phonological coding,spelling	QTL and categorical	Petryshen et al⁵⁹

DYX5	1 multiplex family (74 individuals), Finland	LOD score 3.84	Dyslexia	Categorical	Nopola‐Hemmi et al⁶⁰

DYX6	89 families (195 sib pairs), UK	p Value <0.001	Single‐word reading	QTL	Fisher et al⁵³
	119 families (180 sib pairs), USA	p Value <0.001	Single‐word reading	QTL
	84 families (143 sib pairs), UK	p Value <0.001	Phoneme awareness	QTL

DYX7	100 families (914 individuals), Canada	p Value <0.001	Dyslexia	Categorical	Hsiung et al⁶¹

DYX8	9 families, USA	LOD score of 1.95 and 2.33	Dyslexia	QTL	Rabin et al⁶²
	8 multiplex families (165 individuals), USA	LOD scores of 3.00 and 2.30	Single‐word reading, phonological decoding	Categorical	Grigorenko et al⁶³
	100 families (914 individuals), Canada	LOD scores of 4.01 and 1.65	Spelling, phonological coding	QTL and categorical	Tzenova et al⁶⁴

DYX9	1 multiplex family (29 individuals), Netherlands	LOD score 3.68	Dyslexia	Categorical	de Kovel et al⁶⁵
	89 families (195 sib pairs), UK	p Value of 0.001	Single‐word reading	QTL	Fisher et al⁵³

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LOD, logarithm of the odds; QTL, quantitative trait loci.

*Including 18 families with linkage evidence at DYX2 previously reported by Smith et al.⁴⁶

†Including 82 families with linkage evidence at DYX2 previously reported by Fisher et al.⁵¹

‡Including 39 families with linkage evidence at DYX2 previously reported by Cardon et al⁵⁰ and 70 families with linkage evidence at DYX2 previously reported by Gayan et al.⁵²

§Including 8 families with linkage evidence at DYX2 previously reported by Grigorenko et al.⁴⁷^,55

The largest family samples reported in the literature are from the USA (Colorado, Seattle and Yale samples), the UK (Cardiff and Oxford samples), Canada (Toronto and Vancouver samples) and Germany (German sample). For the sake of clarity, these samples will be named according to their origin in the following sections. Results from genomewide linkage studies have been reported so far from the Seattle,⁴⁹^,66^,67 Oxford and Colorado samples.⁵³ In addition, genomewide linkage studies of large multiply affected families from Holland,⁶⁵ Norway⁵⁶ and Finland⁵⁸^,60 have been reported. The following section presents results for the individual regions, and discussion is limited to positive findings only.

DYX1—chromosome 15q21

DYX1 (MIM 127700) lies in chromosome region 15q21, and a total of four research groups have reported linkage in their family samples (table 22).⁴⁶^,47^,48^,49 Evidence for linkage was found for word reading and related phenotype dimensions in three samples (Colorado, Yale and Seattle samples),⁴⁶^,47^,49 and one sample showed evidence of linkage for spelling (German sample).⁴⁸ Two linkage disequilibrium (LD) studies have been carried out in region DYX1 using short tandem repeat markers,⁶⁸^,69 and positive evidence for association was obtained for one region of approximately 4 Mb. In both studies, a three‐marker haplotype was associated in a total of three independent trio‐samples, two samples of British origin (Cardiff sample) and one of Italian origin.⁶⁸^,69 Region 15q21 has also shown evidence of linkage to ADHD. A genome scan carried out in 164 Dutch sib pairs with ADHD showed the strongest evidence for linkage in this region.⁷⁰ The risk‐conferring gene in DYX1 may contribute to the comorbidity reported between the two disorders.

DYX2— chromosome 6p21–p22

The chromosome region 6p21–p22 (DYX2, MIM 600202) is considered to be among the best‐replicated regions of linkage for dyslexia (table 22).). Evidence of linkage has been reported using a QTL approach in both a US‐American (Colorado) and a UK (Oxford) sample.⁵³^,50^,51^,52^,54 Positive evidence for linkage was also reported from a US‐American subsample (Yale sample) in which categorical phenotype dimensions had been considered.⁵⁵ A more precise containment of the phenotype subdimensions associated with DYX2 was not possible. Linkage was found with the phenotypes phonological processing ⁵¹^,52^,53^,54 and orthographic processing.⁵¹^,52^,54^,55 Meanwhile, LD mapping in DYX2 led to the identification of two strong candidate genes (DCDC2 (doublecortin domain containing protein 2) and K1AA0319).⁷¹^,72^,73^,74^,75 Interestingly, evidence for linkage has also been found in the chromosome region 6p21–p22 for ADHD.⁷⁶

DYX3—chromosome 2p15–p16

The chromosome region 2p15–p16 (DYX3, MIM 604254) has been identified through linkage analyses in five family samples (including the Oxford, Colorado and Vancouver samples; table 22).⁵³^,56^,57^,58^,77 The linkage peaks of the individual studies lie far apart from each other, however, and so it is not clear whether they indicate the same susceptibility locus. As with DYX2, no phenotype dimension has been found to be specifically linked with this locus, although not all studies have analysed subdimensions.

DYX4—chromosome 6q11–q12

The chromosome region 6q11–q12 (DYX4, MIM 127700) was identified in the context of a chromosome‐wide linkage study of a large Canadian family sample (Vancouver sample; table 22).⁵⁹ The most strongly linked phenotype dimensions were phonological coding and spelling. There has so far been no independent replication of this finding for DYX4.

DYX5—chromosome 3p12–q13

The chromosome region 3p12–q13 (DYX5, MIM 606 896) showed linkage in a large Finnish family (table 22).⁶⁰ROBO1 (roundabout Drosophila hom*olog of 1) has been identified as a possible candidate gene in this region. DYX5 also showed a positive evidence for linkage in 77 US‐American families with speech–sound disorder (SSD).⁷⁸ SSD involves impairments in phonological processing, as with dyslexia.

DYX6—chromosome 18p11

DYX6 (MIM 606616), which lies in chromosome region 18p11, was identified in two independent family samples (Oxford and Colorado samples) through a genome scan applying a QTL approach (table 22).⁵³ The strongest evidence for linkage was found for word reading. This finding was replicated in a third family sample (expanded Oxford sample), the strongest evidence for linkage being found for the phenotype subdimension phoneme awareness.⁵³ The results of a subsequent multivariate analysis in the two Oxford samples indicate that a QTL in DYX6 influences multiple aspects of reading ability and is not correlated with specific phenotype subdimensions.⁷⁹

DYX7—chromosome 11p15

Linkage with markers in the region of DYX7 (MIM 127700), which lies in chromosome region 11p15, has been described only in one family sample to date (Vancouver sample; table 22).⁶¹ The authors selected DYX7 as a candidate region on the basis that the gene for the dopamine D4 receptor (DRD4) is localised there. DRD4 is a possible risk gene for ADHD.⁸⁰

DYX8—chromosome 1p34–1p36

Three research groups in total have reported linkage between DYX8 (MIM 608995) in chromosome region 1p34–p36 and dyslexia (including the Yale and Vancouver samples; table 22).⁶²^,63^,64 Even though individual studies have shown linkage to differing phenotype subdimensions of dyslexia, linkage evidence from two studies was particularly strong when focus was placed on the phonological aspects of dyslexia.⁶³^,64

DYX9—chromosome Xq26–q27

Evidence for linkage was found in chromosome region Xq27 (DYX9, MIM 300509) in a Dutch multiplex family with dyslexia (table 22).⁶⁵ The same research group failed to replicate their result in 67 affected sib pairs. However, positive evidence for linkage was found in region DYX9 in one of the UK samples (Oxford sample; table 22).⁵³

Additional linkage regions in dyslexia

In addition to the HGNC‐listed DYX1–DYX9 regions, linkage with dyslexia has also been reported for other regions, although without replication in independent samples. This includes evidence for linkage on chromosome 13q12 for word reading,⁶⁶ and on chromosome 2q22 for phonological decoding efficiency.⁶⁷ Two further studies have been conducted which aimed to identify chromosomal loci with pleiotropic effects on dyslexia and ADHD. In the Colorado sample, families with dyslexia having ADHD problems showed evidence for linkage in chromosome regions 14q32, 13q32 and 20q11.⁸¹ In families with ADHD, evidence for linkage is shown for reading ability in regions 10q11, 16p12 and 17q22.⁸²

Candidate gene findings in dyslexia

Of the newly identified candidate genes, DCDC2 and K1AA0319 seem to be of most significance for dyslexia. Both were identified through systematic investigation of LD (LD mapping) within DYX2 on chromosome 6p22. Initial findings for both genes have been replicated in independent samples, with the strongest findings being reported among severely affected individuals. By contrast, the genes DYX1C1 (dyslexia susceptibility 1 candidate 1) and ROBO1, which were identified through breakpoint mapping in Finnish patients, seem to be less involved in the development of dyslexia across different populations. Their contribution may be limited to a few families in the Finnish population.

DCDC2 (doublecortin domain containing protein 2)

Initial evidence for the involvement of DCDC2 (MIM 605755) and dyslexia was obtained through gene‐based LD mapping in a gene‐dense 680 kb section of linkage region 6p22 (DXY2; table 33).⁷² The sample was drawn from 114 US‐American nuclear families of predominantly European origin (Colorado sample). Positive evidence for association was found in two genome loci, in which a total of six genes were localised: VMP/DCDC2/KAAG1 and K1AA0319/TTRAP/THEM2. In a subsequently expanded Colorado sample (153 nuclear families), the strongest evidence for association was found in DCDC2 (table 33).⁷⁴ Additionally, a deletion of 2.4 kb in intron 2 of DCDC2, which encodes tandem repeats of putative brain‐associated transcription factor binding sites, was identified, which had an allele frequency of 8.5% in the parents.⁷⁴ The tandem repeats in the deleted region demonstrate several alleles. For the purposes of the association study, the authors combined the deletion and the rare repeat alleles into one allele, for which they reported a strong association with reading performance.

Table 3 Summary of association findings in dyslexia

Gene	Study design	Sample characteristics, country	Genotyped variants	Results	References
DYX1C1	Case–control	55 cases* vs 113 controls, Finland	8 SNPs	Significant association at the single‐marker and haplotype level	Taipale et al⁸³
	Case–control	54 cases* vs 82 controls, Finland	8 SNPs†	Significant association at the single‐marker level
	Family based	148 nuclear families, Canada	6 SNPs†	Significant association at the single‐marker and haplotype level, association in the opposite direction compared to Taipale et al⁸³	Wigg et al⁸⁴
	Family based	264 nuclear families, UK	8 SNPs†	Significant association at the single‐marker level, association in the opposite direction compared to Taipale et al⁸³	Scerri et al⁸⁵
	Family based	150 nuclear families, USA	2 SNPs†	No association	Meng et al⁸⁶
	Family based	158 nuclear families, Italy	3 SNPs†	No association	Marino et al⁸⁷
	Case–control	57 cases vs 96 controls, Italy	3 SNPs†	No association	Bellini et al⁸⁸
	Family based	247 nuclear families, UK	3 SNPs†	No association	Cope et al⁸⁹
DCDC2	Family based	114 nuclear families, USA	31 SNPs within 680 kb (including VMP, DCDC2, KAAG1, KIAA0319, TTRAP and THEM2)	Strongest association at the single‐marker and haplotype level within the VMP/DCDC2/KAAG1 locus	Deffenbacher et al⁷²
	Family based	153 nuclear families, USA	147 SNPs within 1.5 Mb (including VMP, DCDC2, KAAG1, KIAA0319, TTRAP and THEM2)	Strongest association at the single‐marker and haplotype level within DCDC2	Meng et al⁷⁴
	Case–control	240 cases vs 312 controls, UK‡	137 SNPs within VMP, DCDC2, KAAG1, KIAA0319, TTRAP and THEM2	No association within the VMP/DCDC2/KAAG1locus	Cope et al⁷¹
	Family based	137 triads, Germany	18 SNPs and 4 STRs within the VMP/DCDC2/KAAG1‐locus	Strongest association at the single‐marker and haplotype level within DCDC2, strongest results with severity selection	Schumacher et al⁷⁵
	Family based	239 triads, Germany	2 SNPs, 1 STR within DCDC2	Significant association at the haplotype level, strongest results with severity selection
KIAA0319	Family based	114 nuclear families, USA	31 SNPs within 680 kb (including VMP, DCDC2, KAAG1, KIAA0319, TTRAP and THEM2)	Significant association at the single‐marker and haplotype level within the KIAA0319/TTRAP/THEM2 locus	Deffenbacher et al⁷²
	Family based	42 nuclear families, UK§	31 SNPs within 680 kb (including the KIAA0319/TTRAP/THEM2 locus)	Strongest association at the single‐marker and haplotype level within KIAA0319 and TTRAP	Francks et al⁷³
	Family based	84 nuclear families, UK§	20 SNPs within KIAA0319 and TTRAP	Significant association at the single‐marker and haplotype level
	Family based	124 nuclear families, USA§	21 SNPs within KIAA0319 and TTRAP	Significant association at the single‐marker and haplotype level	Cope et al⁷¹
	Case– control	240 cases vs 312 controls, UK‡¶	137 SNPs within VMP, DCDC2, KAAG1, KIAA0319, TTRAP and THEM2	Strongest association at the single‐marker and haplotype level within KIAA0319
	Case–control	223 cases vs 273 controls, UK‡¶	10 SNPs within the KIAA0319/TTRAP/THEM2‐locus	Strongest association at the single‐marker and haplotype level within KIAA0319	Schumacher et al⁷⁵
	Family based	376 triads, Germany	10 SNPs within the KIAA0319/TTRAP/THEM2 locus	Nominal significant association at the single‐marker level for 1 variant within KIAA0319 in the most severely affected subsample	Harold et al⁹⁰
	Family based	126 nuclear families, UK§	16 SNPs within DCDC2, KIAA0319 and flanking region	Strongest association at the single‐marker level within 20 kB in intron1 of KIAA0319
	Case–control	350 cases vs 273 controls, UK	28 SNPs and 1 STR within DCDC2, KIAA0319 and flanking regions	Evidence for gene–gene interaction betweenKIAA0319 and DCDC2
	Case–control	419 cases vs 273 controls, UK	4 SNPs and 1 STR within DCDC2 and 5 SNPS within KIAA0319

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DCDC2, doublecortin domain containing protein 2gene; SNP, single‐nucleotide polymorphism.

*Some cases were extracted from the same families and are related.

†Including the two significantly associated SNPs reported by Taipale et al.⁸³

‡Cases and controls were analysed using a DNA pooling approach.

§Samples represent subsamples selected for severity of the phenotype.

¶Individual genotyping of markers that were associated in the pooled samples (most of the cases and controls are identical).

Findings from two trio‐samples also indicate the involvement of DCDC2 in the development of dyslexia (German sample; table 33).⁷⁵ Strong evidence for association was shown in both samples at the single‐marker and haplotype level. This effect seemed to be particularly substantial in severely affected individuals. In the pooled sample, severely affected individuals showed a genotypic relative risk of 4.88 on the basis of the hom*ozygous presence of the identified risk haplotype.

By contrast, investigation of the DCDC2 locus in the two UK samples (Oxford and Cardiff) had inconsistent results. In the Oxford sample, evidence of association between DCDC2 variants and various phenotype components of dyslexia were found, albeit with a weak level of significance. This association disappeared, however, when only severely affected cases were included in the analysis. Interestingly, the 2.4 kb deletion in intron 2 of DCDC2 was more common than by chance in severely affected patients. There was no association between dyslexia and DCDC2 in the Cardiff sample. Joint analysis of the two samples, however, produced evidence of a possible interaction between DCDC2 and K1AA0319.⁹⁰

In summary, these results suggest that DCDC2 is involved in the development of dyslexia. It is unlikely that KAAG1 is the susceptibility gene at this locus. KAAG1 overlaps at the genomic level with exon 1 of DCDC2, although KAAG1 does not seem to be expressed in the CNS.⁷⁴ By contrast, DCDC2 is widely expressed in the CNS, including areas of the brain in which lower activation patterns have been observed in individuals with dyslexia, such as the inferior temporal and medial temporal cortices.⁷⁴^,75^,91^,92^,93

Functionally, DCDC2 is involved in processes of cortical neuronal migration during brain development and contains a double cortin hom*ology domain which is typical of this. RNA interference studies of in utero rats have shown that downregulation of DCDC2 leads to a significant reduction in neuronal migration.⁷⁴ Determining whether the intron 2 deletion is one of the responsible variants will require further investigation in larger samples. There is no real rationale for combining the deletion with rare alleles of the STR polymorphism. Functional studies of the possible effect of the different alleles on expression or splicing are required to justify the combining of alleles.

KIAA0319

Besides evidence for association in the region of DCDC2, positive association with variants in the region of the K1AA0319/TTRAP/THEM2 gene cluster (MIM 609269) was reported in the Colorado sample.⁷² Association for the same gene cluster was reported by Francks et al in two independent samples (Oxford samples), which was particularly notable in severely affected individuals (table 33).⁷³ Association in this region was replicated in a third UK sample (Cardiff sample; table 33).⁷¹ There was an association with SNPs in the region of KIAA0319 through the use of a DNA pooling screening step and subsequent replication through individual genotyping.

Meanwhile, further analyses of the two samples (Oxford and Cardiff) have shown that the responsible gene variant(s) is (are) probably localised near exon 1 of K1AA0319. Investigation of both UK samples has resulted in evidence of a gene–gene interaction between K1AA0319 and DCDC2.⁹⁰

One sample (German sample), which had reported strong association with DCDC2, has so far produced no convincing evidence for association with the KIAA0319/TTRAP/THEM2 gene cluster.⁷⁵ There was no further evidence of association at the K1AA0319 locus from the extended Colorado sample (153 nuclear families),⁷⁴ although the genomic segment that had shown the strongest association findings in the two UK samples was insufficiently analysed.

The evidence of association for K1AA0319 obtained from independent samples is convincing. As with DCDC2, involvement of the KIAA0319 locus seems to be particularly marked in severely affected cases. Association findings, which were strongest around KIAA0319, and results from gene expression and functional studies suggest that KIAA0319 is the most likely susceptibility gene for dyslexia in this gene cluster. Allele‐specific expression analyses in lymphoblastoid cells have shown that carriers of the risk‐associated haplotype have a 40% reduction in the expression of KIAA0319, whereas the expression of other genes in this region remains unaffected.⁹⁴ The expression of KIAA0319 is particularly strong in the cerebral neocortex of developing mouse and human brain tissue, and, similar to DCDC2, reduced expression of KIAA0319 through RNA interference leads to disturbed neuronal migration in rats in utero.⁹⁴

DYX1C1

DYX1C1 (MIM 608706) was cloned in a two‐generation Finnish family with a translocation t(2;15)(q11;q21).⁸³DYX1C1, which lies in chromosome region 15q21, is interrupted through the translocation breakpoint. All four family members in whom the translocation was detected showed reading‐associated problems.⁹⁵ To determine whether DYX1C1 is of significance for affected cases outside of this family, a polymorphism discovery approach was used in 20 Finnish individuals with dyslexia. A total of eight SNPs were identified, which were then investigated in affected individuals and controls of Finnish origin. In an initial sample, two SNPs were found to be associated in the single‐marker and haplotype analysis. Replication was then achieved for one of the two variants in a second sample (table 33).). However, the sample sizes were limited, and a proportion of the affected individuals in the initial sample were related to each other.⁸³

DYX1C1 is expressed in many tissues, including those of the CNS, where it is found in cortical neurones and white matter glial cells.⁸³ Interestingly, it has recently been shown that DYX1C1, similar to KIAA0319 and DCDC2, functions in neuronal migration in rodent neocortex.⁹⁶

Six other association analyses using independent samples of predominantly European origin have been carried out to date (including the Oxford, Cardiff, Colorado and Toronto samples).⁸⁴^,85^,86^,87^,88^,89 Overall, the results must be viewed as being negative, since the initial findings have not been replicated. Positive findings have been reported from two of these studies, although the association was with the opposite two‐marker haplotype (Oxford and Toronto samples; table 33).⁸⁴^,85 Given this failure to replicate, it is unlikely that DYX1C1 makes a significant contribution to the development of dyslexia in non‐Finnish European populations.

It is highly probable that the linkage findings in chromosome region 15q21 (DYX1) cannot be traced back to DYX1C1, since DYX1C1 lies outside of the linkage peaks. Whether or not DYX1C1 contributes to dyslexia in the Finnish population requires clarification through larger association studies.

ROBO1

As with DYX1C1, the identification of ROBO1 (MIM 602430) was achieved through breakpoint mapping of a translocation. A translocation, which had probably occurred de novo, was diagnosed in an affected individual from Finland t(3;8)(p12:q11).⁹⁷ROBO1 was interrupted through the translocation breakpoint, localised in linkage region 3p12 (DYX5). A rare ROBO1 haplotype was identified in the Finnish family, in which the original linkage finding for DYX5 had been found, and cosegregation of this haplotype with dyslexia was reported. Lymphocyte investigation of four affected family members showed that expression of the risk haploytpe was reduced.⁹⁷ Investigation of the orthologous gene in Drosophila (robo) and mice (Robo1) suggests that ROBO1 functions as a neuronal axon guidance gene involved in brain development.⁹⁸^,99^,100

Whether or not ROBO1 actually contributes to the development of dyslexia is currently not clear. A critical point is that the connection between the translocation and dyslexia in the original translocation patient was not imperative: A sibling of the translocation carrier also had dyslexia without carrying the translocation. Should the dyslexia of the Finnish multiplex family be based on a rare and highly penetrant mutation, the causal variant will not be easy to identify, given its size (990 kb of genomic DNA) and the difficulties involved in separating the effects of individual variants from the background variation characterising the haplotype.

Conclusions

Of the candidate genes discussed to date, the evidence for DCDC2 and KIAA0319 is the most convincing. Their identification represents an important step in our understanding of the molecular processes that lead to dyslexia. However, many outstanding questions will need to be addressed by future studies. It is necessary to clarify whether population‐specific genetic heterogeneity and/or phenotypic differences between samples have led to differing findings for the respective loci. Identifying which of the genetic changes in these candidate genes are causal is also important. The lack of associated variants in the coding regions suggests that it is variants influencing generegulation and expression which are responsible.

The nature of the genes identified to date suggests that a disturbance in cortical neurone migration and reduced activity in left‐hemispheric brain regions are pathophysiological correlates of dyslexia. With DCDC2, as with KIAA0319, inhibition leads to poorer neuronal migration in the neocortex of fetal rats through specific small interfering RNAs.⁷⁴^,94 This concept of disturbed neuronal migration is also supported by the few results available from postmortem brain studies of affected individuals, which report cortical malformations in the region of the perisylvian cortex.¹⁰¹^,102^,103 The concept of disturbed neuronal migration in dyslexia is intriguing and will stimulate further research in this area. In view of the fact that DCDC2 and K1AA0319 only contribute a limited part to the development of dyslexia and that most susceptibility genes are still unknown, it may be possible in the future to identify completely new pathophysiological mechanisms.

To date, no specific cognitive processes are known to be influenced by the proposed susceptibility genes. Some studies have already started to include neurophysiological (eg, event‐related potential) and imaging (eg, functional MRI) procedures in their phenotype characterisation of patients. Such samples are an important prerequisite for the identification of those processes that are most proximal to the effects of particular genes and their associated biological pathways.

Through the availability of detailed clinical data, it should be possible to associate special phenotype dimensions of dyslexia with specific risk genes (genotype–phenotype association). Phenotype subdimensions are, of course, correlated with each other, and the effects will not affect isolated subdimensions. Nor is it to be expected that specific genes will affect the whole spectrum of phenotype dimensions equally. Studies have not yet managed to establish genotype–phenotype relations convincingly, although samples may have been too small to demonstrate these effects. However, proof of genotype–phenotype associations could be facilitated through the joint analysis of larger samples and the identification of causative variants.

The molecular genetic studies conducted so far have not considered sex‐specific genetic effects. Differing prevalence rates between males and females could be suggestive of a sex‐specific geneeffect. A satisfactory power to detect such effects can be provided only when sex is taken into account during the analysis of results, ⁶⁶ and this should be a feature of future studies.

Identification of susceptibility genes will allow research into the molecular background of clinically observed comorbidity. Eight loci have already been proposed as having pleiotropic effects on dyslexia and ADHD at a linkage level.⁴⁶^,47^,48^,49^,50^,51^,52^,53^,54^,70^,76^,81^,82 The identification of susceptibility genes also allows examination of the extent to which dyslexia‐associated disorders, such as SSD and language impairment, are influenced by the same susceptibility genes. For SSD, overlapping linkage evidence in DYX5 already provides the first concrete evidence of such common gene effects.⁶⁰^,78

The identification of susceptibility genes will enable the analysis of gene–gene interactions, through which epistatic effects can be discovered. A first example of this might be the proposed interaction between DCDC2 and KIAA0319.⁹⁰ A further aim of future research will be to establish a better understanding of gene–environment interactions in order to identify relevant exogenous risk factors. It has long been recognised that environmental factors are of great relevance to the development of dyslexia, but only some of these factors have been identified so far.¹⁰⁴ If such factors can be modulated, future dyslexia prevention and individual genetic risk profiling could be envisaged.

The genes that accompany the development of dyslexia are naturally of great interest from an evolutionary perspective.¹⁰⁵ Through the identification of the gene at the DNA level, comparison with species that are closely related to us but that do not have the same speech capacity could be carried out, as well as examination of sequence variability between humans. Speech‐associated genes may have been under a selection pressure, which proved advantageous for the development of modern man.

As is generally the case with research on complex genetic disorders, it can be assumed that the speed by which susceptibility genes are identified will be increased through increasing knowledge and huge technological advances (eg, genomewide association studies). Future research efforts will be of a collaborative nature, drawing on complementary expertise from various scientific disciplines and involving the combining of large samples, an approach exemplified by the large multidisciplinary European research consortium (www.neurodys.com) which integrates the work of research groups from nine countries.

Abbreviations

ADHD - attention‐deficit hyperactivity disorder

Footnotes

Funding: This work was supported by the Deutsche Forschungsgemeinschaft.

Competing interests: None.

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