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Notes from Beethoven’s genome

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Wesseldijk,  Laura Wendelmoet       
Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Neuroscience, Karolinska Institutet ;
Department of Psychiatry, Amsterdam UMC, University of Amsterdam;

Bignardi,  Giacomo
Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society;
Max Planck School of Cognition, Max Planck Schools, Max Planck Society;

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Mosing,  Miriam A.       
Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Neuroscience, Karolinska Institutet ;
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet;
Melbourne School of Psychological Sciences, Faculty of Medicine, Dentistry, and Health Sciences, University of Melbourne;

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Ullén,  Fredrik       
Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Neuroscience, Karolinska Institutet ;

Fisher,  Simon E.
Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, Radboud University;

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kog-24-wes-02-notes.pdf
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Citation

Wesseldijk, L. W., Henechowicz, T. L., Baker, D. J., Bignardi, G., Karlsson, R., Gordon, R. L., et al. (2024). Notes from Beethoven’s genome. Current Biology, 34(6), R233-R234. doi:10.1016/j.cub.2024.01.025.


Cite as: https://hdl.handle.net/21.11116/0000-000F-1F99-3
Abstract
Rapid advances over the last decade in DNA sequencing and statistical genetics enable us to investigate the genomic makeup of individuals throughout history. In a recent notable study, Begg et al.1 used Ludwig van Beethoven’s hair strands for genome sequencing and explored genetic predispositions for some of his documented medical issues. Given that it was arguably Beethoven’s skills as a musician and composer that made him an iconic figure in Western culture, we here extend the approach and apply it to musicality. We use this as an example to illustrate the broader challenges of individual-level genetic predictions.