Pleiotropic effects of a chromosome 3 locus on speech-sound disorder and reading

Abstract

Speech-sound disorder (SSD) is a complex behavioral disorder characterized by speech-sound production errors associated with deficits in articulation, phonological processes, and cognitive linguistic processes. SSD is prevalent in childhood and is comorbid with disorders of language, spelling, and reading disability, or dyslexia. Previous research suggests that developmental problems in domains associated with speech and language acquisition place a child at risk for dyslexia. Recent genetic studies have identified several candidate regions for dyslexia, including one on chromosome 3 segregating in a large Finnish pedigree. To explore common genetic influences on SSD and reading, we examined linkage for several quantitative traits to markers in the pericentrometric region of chromosome 3 in 77 families ascertained through a child with SSD. The quantitative scores measured several processes underlying speech-sound production, including phonological memory, phonological representation, articulation, receptive and expressive vocabulary, and reading decoding and comprehension skills. Model-free linkage analysis was followed by identification of sib pairs with linkage and construction of core shared haplotypes. In our multipoint analyses, measures of phonological memory demonstrated the strongest linkage (marker D3S2465, P=5.6 x 10(-5), and marker D3S3716, P=6.8 x 10(-4)). Tests for single-word decoding also demonstrated linkage (real word reading: marker D3S2465, P=.004; nonsense word reading: marker D3S1595, P=.005). The minimum shared haplotype in sib pairs with similar trait values spans 4.9 cM and is bounded by markers D3S3049 and D3S3045. Our results suggest that domains common to SSD and dyslexia are pleiotropically influenced by a putative quantitative trait locus on chromosome 3.

Figure 1

Shared and unshared processes involved in production of speech and written text. The tasks of processing and producing speech-sound and written text share some neural processes. The processing of speech and written text begins with modality-specific sensory and perceptual analyses of the stimuli—that is, auditory and visual analyses. The analysis of speech and written text relies on shared phonological representations for the conversion of phonetic speech units to phoneme classes and on the conversion of written graphemes to the corresponding phonemes. Phonological memory is a key process in these conversions. Next, meaning is attached to the utterance or text through shared semantic and morphologic/syntactic representations. The output segment of speech production or writing again requires modality-specific processes, including the selection and retrieval of a template for the intended word, the assembly and sequencing of phonetic units or graphemes, and the execution of the motor program. There are also processes contributing to speech and written text output that bypass the phonological representation segment. These processes include repetition of words without meaning and reading by sight vocabulary rather than by reading decoding. The numbers in parentheses in the figure correspond to the measures listed in the key below. Note that a single measure may tap multiple processes. Although the figure depicts processing as linear, we recognize that many of these processes are overlapping and occur simultaneously. Key: 1 = WRMT-ID; 2 = WRMT-AT; 3 = WIAT-RC; 4 = WIAT-LC; 5 = PPVT-III; 6 = EOWPVT-R; 7 = SI; 8 = MSW; 9 = NSW; 10 = PCC; 11 = GFTA; 12 = RAN-C.

Figure 2

Results of the model-free linkage analyses for the phonology, articulation, and vocabulary factors, plotted as pP = −log₁₀(asymptotic P value) on the Y-axis against genetic distance (in cM) on the X-axis.

Figure 3

A, Decomposition of the phonology factor into its component traits, multisyllabic word repetition and nonsense-word repetition. The linkage results for the phonology factor and the two component tests, NSW and MSW, are plotted as pP = −log₁₀(asymptotic P value) on the Y-axis against genetic distance (in cM) on the X-axis. B, Comparison of linkage results for NSW and MSW after removal of sib pairs contributing to linkage based on IBD sharing for marker D3S2465.

Figure 4

Shared haplotype blocks in sibling pairs who have concordantly low values for MSW and NSW and who are linked on the basis of expression (1). “NI” refers to genotypes that were not informative for resolving phase.