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Genome-wide Analyses of Individual Differences in Quantitatively Assessed Reading- and Language-related Skills in Up to 34,000 People

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Specialty Science
Date 2022 Aug 23
PMID 35998220
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Abstract

The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, = 1.098 × 10) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits.

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References
1.
Watanabe K, Taskesen E, van Bochoven A, Posthuma D . Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017; 8(1):1826. PMC: 5705698. DOI: 10.1038/s41467-017-01261-5. View

2.
Venezia J, Vaden Jr K, Rong F, Maddox D, Saberi K, Hickok G . Auditory, Visual and Audiovisual Speech Processing Streams in Superior Temporal Sulcus. Front Hum Neurosci. 2017; 11:174. PMC: 5383672. DOI: 10.3389/fnhum.2017.00174. View

3.
Turley P, Walters R, Maghzian O, Okbay A, Lee J, Fontana M . Multi-trait analysis of genome-wide association summary statistics using MTAG. Nat Genet. 2018; 50(2):229-237. PMC: 5805593. DOI: 10.1038/s41588-017-0009-4. View

4.
Soroli E, Szenkovits G, Ramus F . Exploring dyslexics' phonological deficit III: foreign speech perception and production. Dyslexia. 2010; 16(4):318-40. DOI: 10.1002/dys.415. View

5.
Le B, Stein J . Mapping causal pathways from genetics to neuropsychiatric disorders using genome-wide imaging genetics: Current status and future directions. Psychiatry Clin Neurosci. 2019; 73(7):357-369. PMC: 6625892. DOI: 10.1111/pcn.12839. View