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Article

Hundreds of cardiac MRI traits derived using 3D diffusion autoencoders share a common genetic architecture.

Nature communications - 29 Jun 2026

Ometto Sara, Chatterjee Soumick, Vergani Andrea Mario, Landini Arianna, Sharapov Sodbo, Giacopuzzi Edoardo, Visconti Alessia, Bianchi Emanuele, Santonastaso Federica, Soda Emanuel M, Cisternino Francesco, Pivato Carlo Andrea, Ieva Francesca, Angelantonio Emanuele Di, Pirastu Nicola, Glastonbury Craig A

Abstract excerpt

Biobank-scale imaging provides an unprecedented opportunity to characterise how thousands of organ phenotypes vary in populations. However, deriving specific phenotypes from imaging data requires time-consuming expert annotation, limiting scalability. In this study, we develop a 3D diffusion autoencoder to derive latent phenotypes from temporally resolved cardiac MRI data of 71,017 UK Biobank participants. These...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 42373625
DOI: 10.1038/s41467-026-74575-y
PMCID: PMC13482823

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

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