Association of the rs3743205 variant of DYX1C1 with dyslexia in Chinese children.

BACKGROUND: Dyslexia is a learning disability that is characterized by difficulties in the acquisition of reading and spelling skills independent of intelligence, motivation or schooling. Studies of western populations have suggested that DYX1C1 is a candidate gene for dyslexia. In view of the different languages used in Caucasian and Chinese populations, it is therefore worthwhile to investigate whether there is an association of DYX1C1 in Chinese children with dyslexia. METHOD AND
RESULTS: Eight single nucleotide polymorphisms (SNPs) were genotyped from three hundred and ninety three individuals from 131 Chinese families with two which have been reported in the literature and six tag SNPs at DYX1C1. Analysis for allelic and haplotypic associations was performed with the UNPHASED program and multiple testing was corrected using false discovery rates. We replicated the previously reported association of rs3743205 in Chinese children with dyslexia (p(corrected) = 0.0072). This SNP was also associated with rapid naming, phonological memory and orthographic skills in quantitative trait analysis.
CONCLUSION: Our findings suggest that DYX1C1 is associated with dyslexia in people of Chinese ethnicity in Hong Kong.

Introduction

Developmental dyslexia (DD) is a learning disability that is characterized by difficulties in the acquisition of reading and spelling skills independent of intelligence, motivation or schooling. It is the most common form of learning disability (about 80% of learning disabilities is due to dyslexia) and affects about 5-10% of school children worldwide [1,2]. Studies delineating genetic factors in developmental dyslexia have identified several putative loci (DYX1 - DYX9) and candidate genes (KIAA0319, DYX1C1, DCDC2 and ROBO1) [3]. Recently, associations with the MRPL19/C2ORF3 genes of DYX3 locus, KIAA0319L of DYX8 locus and GRIN2B gene have also been reported [4-6].

DYX1C1 is the first candidate susceptibility gene of dyslexia to be identified. A cytogenetic study revealed that two chromosome translocations [t(2;15)(q11;q21) and t(2;15)(q13;q22)] in the DYX1 locus co-segregated with dyslexia [7]. Taipale et al. [8] confirmed these translocations in another dyslexic cohort, and further reported two functional variants -3G/A (rs3743205) and 1249G/T in DYX1C1 associated with dyslexia. Rare variant -3A was proposed to be able to alter the Elk-1 transcription factor binding site and affect translation initiation, while 1249T caused a nucleotide transversion to result in a truncated protein [8].

The association of this same variant -3A has been shown to be a quantitative trait of short-term memory but it has not been shown to be associated with categorical DD [9]. Positive findings were also found in other Caucasian population cohorts but biased transmission was shown in other polymorphisms and in the common allele of -3G/A or 1249G/T [10-12]. Wigg et al. [10] reported significant association for the common -3G allele with reading-related phenotypes in single marker analysis and biased transmission of rs11629841 and the common haplotype of 3G/1249G in categorical DD. In Scerri's study [11], a marginally significant association was shown between the common allele (1249G) and common haplotype of the two markers (-3G/1249G) and poorer performance for the phenotypic measure of orthographic coding choice (OC-choice). Dahdouh et al. [12] only showed a common haplotype (G/G/G) of three markers (rs3743205/rs3743204/rs600753) to be associated in a female subgroup and the haplotype was associated with short-term memory in quantitative trait analyses, although no associations have been found with DD. In addition, other studies have also reported negative associations [13-16].

Despite these inconsistent findings, DYX1C1 has been shown to play a molecular role in brain development. Knocking down the function of DYX1C1 using small interfering RNA (siRNA) resulted in disruption of normal neuronal migration in the developing neocortex of embryonic rat, which could be reversed by the concurrent overexpression of DYX1C1 [17]. Disruption of DYX1C1 also impaired auditory processing and spatial learning in rodent models [18]. Furthermore, targeted knock down of other dyslexia susceptibility candidate genes (such as KIAA0319 and DCDC2) resulted in similar patterns of neuronal migration [19,20].

To elucidate the role of DYX1C1 in neuronal migration, its interacting protein partners were investigated. Three transcriptional factors sTFII-I, SFPQ and PARP1 bind to the promoter region of DYX1C1 and regulate its expression [21]. The electrophoretic mobility shift assay results suggested they trans-activate the allele -3G of rs3743205 and the binding was weak in the presence of the -3A allele. In addition, two estrogen receptors (ERs), alpha (ERa) and beta (ERb) bind to the p23 domain in the N-terminus of DYX1C1 [22], while heat shock proteins Hsp70 and Hsp90 bind to the TPR domains in its C-terminus [23]. In fact, over-expression of DYX1C1 affects ERa and ERb levels in a dose-dependent manner [22]. Most importantly, the functional roles of ER and its ligand (estradiol) on brain development [24], synaptic plasticity/cognition, neuroprotection [25], and memory and learning [26] have been strongly supported by extensive reviews.

To our knowledge, all current association studies on DD were performed in Caucasian populations, with no information available for non-Caucasian dyslexic cohorts. As the prevalence rate of development dyslexia in Hong Kong Chinese school-aged children was estimated to be between 9.7% and 12.6%, similar to the rate in Caucasian populations [27], study of the genetic component of dyslexia in Chinese is necessarily important. The Chinese language is known to be substantially different from Western languages, being logographic and morphosyllabic rather than being based on an alphabet [28]. Moreover, orthographic (rather than phonological) deficits were found to be the main problem for Chinese people with dyslexia, in contrast to Caucasians [29,30]. fMRI studies of Chinese people with dyslexia also revealed different biological abnormalities in their brains [31,32]. We hypothesize that Chinese people with dyslexia may be influenced by risk alleles in DYX1C1, and we investigated this through genotyping eight genetic variants in 393 individuals from 131 Chinese families with dyslexia.

Materials and methods

Subjects

In total, 393 individuals from 131 Chinese families were recruited with informed consent. This study was approved by the ethical committee of The Chinese University of Hong Kong. Each family consisted of one dyslexic child, with a total of 95 males and 36 females, aged between 5 and 16 years (mean = 8.68 ± 2.06 years). They were diagnosed as DD using the Hong Kong Test of Specific Learning Difficulties in Reading and Writing (HKT-SpLD) [33] and referred by the local education authority, child assessment centres, and a parent association. The HKT-SpLD battery consisted of 12 subtests. The subtest are broken down into three literacy tests, which are Chinese Word Reading, One-minute Reading and Chinese Word Dictation, and one rapid naming test, where subjects were asked to name digits, colours and pictures. Two subtests are phonological awareness which tests the subjects' awareness of onset and rhymes of Chinese words, and three phonological memory subtests where subjects are asked to repeat orally the syllables presented to them from a tape recorder. The final three subtests are a test of orthographic skills. This consists of 70 simple Chinese integrated characters and Arabic numbers. Half of them were left/right reversed and the subjects were asked to cross out all items with an incorrect orientation.

These 12 subtests were combined to yield five composite scores in the domains of literacy, phonological awareness, phonological memory, rapid naming and orthographic skills. The sample characteristics of these phenotypic measures are shown in table 1. To be classified as children with dyslexia, their literacy composite score and at least one cognitive composite score had to be at least one standard deviation (SD = 3) below the means (mean = 10) of their respective ages in the HKT-SpLD (cutoff score = 7). Participants in the dyslexic group fulfilled this diagnostic criterion and all of the subjects showed a normal intelligence on Raven's Standard Progressive Matrices (with IQs of 85 or above).

Table 1

Descriptive statistics of the HKT-SpLD subtests in the samples.

Composite Tests	Sub-tests	Mean Scaled Scores (± SD)*
Literacy
	Chinese Word Reading	5.36 (2.18)
	One Minute Reading	5.52 (1.93)
	Chinese Word Dictation	4.27 (1.89)
Rapid Naming	Digit Rapid Naming	5.08 (2.98)
Phonological Awareness
	Rhyme Detection	9.18 (3.11)
	Onset Detection	9.03 (3.04)
Phonological Memory
	Word Repetition I	8.84 (3.55)
	Non-word Repetition	9.09 (3.64)
	Word repetition II	9.28 (3.28)
Orthographic Skills
	Left-Right Reversal	7.31 (3.48)
	Lexical Decision	8.19 (3.19)
	Radical Position	9.66 (2.65)

*Scaled score: Mean = 10, 1 S.D. = 3.

SNP markers selection

SNPs were selected from the DYX1C1 region spanning Chr15: 55,709,952 to 55,800,431 (Genome Reference Consortium Human Build 37, NC_000015.9). Six tag SNPs were selected using the TAGGER program as implemented in HaploView 4.1 [34] with parameters of minor allele frequency over 5% and pairwise r2 threshold of 0.8, based on the population of Han Chinese genotype data generated by the HapMap project (Data Rel#22/phase II Apr 07). Two previously reported SNPs, rs3743205 (-3G > A) and rs57809907 (1249G > T), were also included in this study [8].

DNA extraction and genotyping

Two milliliters of saliva was collected from each individual and genomic DNA was extracted using the Oragene™ DNA self-collection kit following the manufacturer's instructions (DNA Genotek, Inc., Ottawa, Canada). The concentration of the DNA was determined by Quant-iT™ DNA Assay Kit, Broad Range (Invitrogen Corporation, California, USA). Genotyping was performed using Sequenom® MassARRAY® iPLEX Gold assay, according to the manufacturer's instructions (Sequenom®, San Diego, CA, USA, http://www.sequenom.com). Briefly, 5 ng genomic DNA was first amplified to determine the genomic sequence containing the SNP. The unincorporated dNTPs in the PCR reaction was dephosphorylated by shrimp alkaline phosphatase treatment. This is followed by the iPLEX primer extension reaction to generate allele-specific extension products of different mass. The extension products were cleaned using SpectroClean resin and then dispensed onto SpectroCHIP bioarray. The products were detected using MALDI-TOF mass spectrometry and results were analyzed using SpectroTYPER software. Markers were checked for Mendelian inconsistencies and tests of Hardy-Weinberg equilibrium using Pedstats [35].

Statistical analyses

Family-based and haplotype association analyses were performed using UNPHASED (Version 3.1.2) which employs an allelic likelihood ratio test [36]. Haplotype analysis was performed using 2- or 3- markers sliding windows method. Initially, a global analysis was performed to test for haplotypic association and then the significant haplotypes were subsequently tested for individual haplotype analysis. Haplotypes with frequencies <1% in the whole sample were excluded. The analysis option of conditioning markers was selected for testing direct association of a single marker in the significant haplotypes. Multiple testing was corrected using Qvalue software based on false discovery rates [37]. Permutation test (1000 runs) was also used to run multiple testing corrections over all tests performed in single-marker association analyses of categorical DD. Linkage disequilibrium (LD) was calculated and LD plots were generated using Haploview version 4.1 http://www.broad.mit.edu/mpg/haploview[34].

Results

Single marker analysis

The call rate of genotyping was least 96% and Mendelian inconsistencies made up about 0.85% of the data. Genotypes of Mendelian error were eventually excluded from the analysis. Single marker association showed that SNPs rs3743205 (p = 0.0009, OR = 0.08, 95% CI = 0.01 to 0.64) and rs4774768 (p = 0.0367, OR = 1.68, 95% CI = 1.02 to 2.76) were significantly associated with categorical DD (Table 2) in a family cohort. Only rs3743205 remained significant after multiple correction with FDR (q = 0.0072) and 1000 runs of permutation tests (adjusted p = 0.002997). Given the significant association of rs3743205 with categorical DD, quantitative trait analysis of literacy and cognitive skills was also tested (Table 3). rs3743205 was associated with literacy (one minute reading: p = 0.0087, q = 0.0289), rapid naming (p = 0.0079, q = 0.0289), phonological memory (non-word repetition: p = 0.0096, q = 0.0289) and orthographic skills (left-right reversal: p = 0.0087, q = 0.0289). The allele A of rs3743205 was under-transmitted in families with a dyslexic child.

Table 2

Single-marker analysis between SNPs and categorical DD.

rs Number	SNP	Position	Location	Allele	F	OR (95% CI)	Nominal p-value	FDR q-value
rs8040756	A/G	26589156	Intron 1	A*	0.135	1.43 (0.88 - 2.32)	0.1445	0.2823
				G	0.865
rs3743205	G/A	26581087	5' UTR	G*	0.982	0.08 (0.01 - 0.64)	0.0009	0.0072
				A	0.018
rs4255730	C/T	26578338	Intron 3	C*	0.670	0.85 (0.59 - 1.23)	0.3969	0.6202
				T	0.330
rs692646	A/G	26557344	Intron 4	A*	0.067	2.00 (0.96 - 4.12)	0.0532	0.1385
				G	0.933
rs692691	C/T	26551132	Intron 4	C*	0.947	0.86 (0.40 - 1.85)	0.6947	0.8455
				T	0.053
rs2290981	A/G	26550245	Intron 4	A*	0.119	1.10 (0.60 - 2.02)	0.7575	0.8455
				G	0.881
rs4774768	G/T	26517062	Intron 8	G*	0.189	1.68 (1.02 - 2.76)	0.0367	0.1385
				T	0.811
rs57809907	G/T	26513439	Exon 10	T*	0.004	1.00 (0.06 - 15.99)	1.0000	0.9766
				G	0.996

F = Allele frequency

*Reference allele

Table 3

Quantitative analysis of rs3743205 in HKT-SpLD tests.

Tested area	Tests	Nominal p-value	FDR (q-value)
Literacy
	Chinese Word Reading (CWR)	0.5415	0.5445
	One Minute Reading (OMR)	0.0087	0.0289
	Chinese Word Dictation (CWD)	0.5273	0.5445
Rapid Naming	Digit Rapid Naming (DRN)	0.0079	0.0289
Phonological Awareness
	Rhyme Detection (RD)	0.1105	0.2106
	Onset Detection (OD)	0.5445	0.5445
Phonological Memory
	Word Repetition I (WRI)	0.0474	0.1138
	Non-word Repetition (NWR)	0.0096	0.0289
	Word repetition II (WRII)	0.1229	0.2106
Orthographic Skills
	Left-Right Reversal (LRR)	0.0087	0.0289
	Lexical Decision (LD)	0.3002	0.4002
	Radical Position (RP)	0.1481	0.2222

Haplotype analyses

The four haplotypes rs804075-rs3743205, rs3743205-rs4255730, rs692646-rs692691 and rs8040756-rs3743205-rs4255730 were significantly associated with categorical DD after corrections for multiple testing (Table 4). Their linkage disequilibrium (LD) structures are shown in Figure 1. Except for the rs692646-rs692691 haplotype (r2 = 0.702 between the two SNPs), all other haplotypes consisted of SNPs in low LD (r2 < 0.5). Individual haplotype analyses revealed the associated alleles in each haplotype: rs804075-rs3743205 (A-A, p = 0.0005), rs3743205-rs4255730 (A-T, p = 0.0039), rs692646-rs692691 (A-C, p = 0.0067) and rs8040756-rs3743205-rs4255730 (A-A-T, p = 0.0009). All the haplotypes which were significantly associated with categorical DD except rs692646-rs692691 were made up of the rs3743205 and had the same allele A found in single marker analysis. Direct association of the markers with the rs3743205 haplotype was tested using conditioning markers option of the software. All haplotypes consisting of the rs3743205 became insignificant associated with categorical DD after testing using conditioning markers (rs804075-rs3743205/p = 0.7814, rs3743205-rs4255730/p = 0.7593, rs8040756-rs3743205-rs4255730/p = 0.6099). With the exception of rs692646-rs692691 which was still significant whether rs692646 (p = 0.0031) or rs692691 (p = 0.0232) was set as a conditioning marker. These significant haplotypes were subsequently tested for quantitative trait analyses (Table 5). Both rs3743205-rs4255730 and rs692646-rs692691 haplotypes were associated with skills of literacy (one minute reading), rapid naming, phonological memory (non-word repetition) and orthographic skills (left-right reversal) (0.01