While they obviously depend on environmental input, much of the variation in language and musicality-related traits within human populations is explained by genetic differences between individuals. Besides rare cases of severe disorders, such inter-individual variability mainly involves complex genetic underpinnings, involving interactions of a large number of common genetic variants, each of which has only a tiny effect on the trait. To successfully investigate the genetic architecture underlying these complex traits, we need to study large cohorts comprising thousands of participants in order to have sufficient statistical power to detect the small effects involved. Participants are assessed on behavioural and cognitive measures related to speech, language, reading, musicality and/or other communication skills. They are also characterised using DNA chips that assess hundreds of thousands of variable genetic markers across the genome. Using such datasets, we can test whether any of the genetic markers are associated with variation in the behavioural/cognitive skills of interest. In this work, we not only investigate large samples of families and cases with impairments such as developmental language disorder (DLD) or reading disability (developmental dyslexia), but also general population cohorts (cross-sectional and longitudinal designs, including twin registries and birth cohorts), in which speech-, language-, reading and musicality-related indicators have been obtained.
We are the driving force behind international efforts: the Genetics of Language (GenLang) and the Musicality Genomics (MusicGens) Consortia, to facilitate large-scale meta-analyses of multiple cohorts from around the world, to achieve sample sizes of tens of thousands of people. We are also part of the Dutch Language in Interaction Consortium, which is developing a comprehensive new test battery for the systematic evaluation of natural variation in language skills. The findings from genetic association studies are used to generate insights into the biology of human language and musicality, by integrating findings with those from other sources, including neuroimaging and evolutionary datasets.
Example publications:
Eising, E., Mirza-Schreiber, N., et al. (2022). Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people. Proceedings of the National Academy of Sciences of the United States of America, 119(35): e2202764119. doi:10.1073/pnas.2202764119 [pdf].
Doust, C., Fontanillas, P., Eising, E., Gordon, S. D., Wang, Z., Alagöz, G., Molz, B., 23andMe Research Team, Quantitative Trait Working Group of the GenLang Consortium, St Pourcain, B., Francks, C., Marioni, R. E., Zhao, J., Paracchini, S., Talcott, J. B., Monaco, A. P., Stein, J. F., Gruen, J. R., Olson, R. K., Willcutt, E. G., DeFries, J. C., Pennington, B. F., Smith, S. D., Wright, M. J., Martin, N. G., Auton, A., Bates, T. C., Fisher, S. E., & Luciano, M. (2022). Discovery of 42 genome-wide significant loci associated with dyslexia. Nature Genetics. doi:10.1038/s41588-022-01192-y [pdf].
Wesseldijk, L. W., Henechowicz, T. L., Baker, D. J., Bignardi, G., Karlsson, R., Gordon, R. L., Mosing, M. A., Ullén, F., & Fisher, S. E. (2024). Notes from Beethoven’s genome. Current Biology, 34(6), R233-R234. doi:10.1016/j.cub.2024.01.025 [pdf].
Fisher, S. E. (2025). Genomic investigations of spoken and written language abilities: A guide to advances in approaches, technologies, and discovery. Journal of Speech, Language, and Hearing Research. Advance online publication. doi:10.1044/2025_JSLHR-25-00152 [pdf].
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