Transcriptomic decoding of surface-based imaging phenotypes and its application to pharmacotranscriptomics

Christine Ecker (), Charlotte M. Pretzsch, Johanna Leyhausen, Lisa M. Berg, Caroline Gurr, Hanna Seelemeyer, Grainne McAlonan, Nicolaas A. Puts, Eva Loth, Flavio Dell’Aqua, Luke Mason, Tony Charman, Bethany Oakley, Thomas Bourgeron, Christian Beckmann, Jan K. Buitelaar, Celso Arango, Tobias Banaschewski, Andreas G. Chiocchetti, Christine M. Freitag, Elke Hattingen, Dilja Krueger-Burg, Michael J. Schmeisser, Jonathan Repple, Andreas Reif and Declan G. Murphy
Additional contact information
Christine Ecker: University Hospital of the Goethe University
Charlotte M. Pretzsch: King’s College London
Johanna Leyhausen: University Hospital of the Goethe University
Lisa M. Berg: University Hospital of the Goethe University
Caroline Gurr: University Hospital of the Goethe University
Hanna Seelemeyer: University Hospital of the Goethe University
Grainne McAlonan: King’s College London
Nicolaas A. Puts: King’s College London
Eva Loth: King’s College London
Flavio Dell’Aqua: King’s College London
Luke Mason: King’s College London
Tony Charman: King’s College London
Bethany Oakley: King’s College London
Thomas Bourgeron: University de Paris
Christian Beckmann: Radboud University Medical Centre
Jan K. Buitelaar: Radboud University Medical Centre
Celso Arango: CIBERSAM
Tobias Banaschewski: partner site Mannheim-Heidelberg-Ulm
Andreas G. Chiocchetti: University Hospital of the Goethe University
Christine M. Freitag: University Hospital of the Goethe University
Elke Hattingen: University Hospital of the Goethe University
Dilja Krueger-Burg: University Medical Center of the Johannes Gutenberg-University
Michael J. Schmeisser: University Medical Center of the Johannes Gutenberg-University
Jonathan Repple: Goethe University Frankfurt
Andreas Reif: University Hospital of the Goethe University Frankfurt
Declan G. Murphy: King’s College London

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Imaging transcriptomics has become a power tool for linking imaging-derived phenotypes (IDPs) to genomic mechanisms. Yet, its potential for guiding CNS drug discovery remains underexplored. Here, utilizing spatially-dense representations of the human brain transcriptome, we present an analytical framework for the transcriptomic decoding of high-resolution surface-based neuroimaging patterns, and for linking IDPs to the transcriptomic landscape of complex neurotransmission systems in vivo. Leveraging publicly available Positron Emission Tomography (PET) data, we initially validated our approach against molecular targets with a high correspondence between gene expression and protein binding. Subsequently, we used the cortical gene expression profiles of candidate genes to dissect two discrete classes of GABAA-receptor subunits, each characterized by a distinct cortical expression pattern, and to link these to specific behavioural symptoms and traits. Our approach thus represents a future avenue for in vivo pharmacotranscriptomics that may guide the development of targeted pharmacotherapies and personalized interventions.

Date: 2025
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DOI: 10.1038/s41467-025-61927-3

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