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Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction

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Den Hoed,  Joery
Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society;
International Max Planck Research School for Language Sciences, MPI for Psycholinguistics, Max Planck Society;

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Snijders Blok,  Lot
Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society;

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Fisher,  Simon E.
Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society;

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Citation

Den Hoed, J., De Boer, E., Voisin, N., Dingemans, A. J. M., Guex, N., Wiel, L., et al. (2021). Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction. The American Journal of Human Genetics, 108(2), 346-356. doi:10.1016/j.ajhg.2021.01.007.


Cite as: https://hdl.handle.net/21.11116/0000-0007-623A-A
Abstract
Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression and a severe phenotype. Contrastingly, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay and encode truncated proteins, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability.