Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization
Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) are personalized physics-constrained and physiology-constrained in silico representations, uncovering multi-scale insights tied to these mechanisms. In this study, we constructed 3,461 CDTs from the UK Biobank and another 359 from an ischemic heart disease (IHD) cohort, using cardiac magnetic resonance images and electrocardiograms. We show here that sex-specific differences in QRS duration were fully explained by myocardial anatomy while their myocardial conduction velocity (CV) remains similar across sexes but changes with age and obesity, indicating myocardial tissue remodeling. Longer QTc intervals in obese females were attributed to larger delayed rectifier potassium conductance <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub><mml:mrow><mml:mi>G</mml:mi></mml:mrow> <mml:mrow><mml:mi>KrKs</mml:mi></mml:mrow> </mml:msub> </mml:math> . These findings were validated in the IHD cohort. Moreover, CV and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub><mml:mrow><mml:mi>G</mml:mi></mml:mrow> <mml:mrow><mml:mi>KrKs</mml:mi></mml:mrow> </mml:msub> </mml:math> were associated with cardiac function, lifestyle and mental health phenotypes, and CV was also linked with adverse clinical outcomes. Our study demonstrates how CDT development at scale reveals biological insights across populations.
Authors
- Steven Niederer (ORCID: https://orcid.org/0000-0002-4612-6982)
- Devran Uğurlu (ORCID: https://orcid.org/0009-0009-0158-5040)
- Reza Razavi (ORCID: https://orcid.org/0000-0003-1065-3008)
- Hassan Zaidi (ORCID: https://orcid.org/0000-0003-2806-9483)
- Ludovica Cicci (ORCID: https://orcid.org/0000-0002-2544-9889)
- Daniel Hammersley (ORCID: https://orcid.org/0000-0002-1164-5993)
- Gernot Plank (ORCID: https://orcid.org/0000-0002-7380-6908)
- Yu Deng (ORCID: https://orcid.org/0000-0003-4158-8966)
- Elliot Fairweather (ORCID: https://orcid.org/0000-0003-0880-0785)
- Shuang Qian (ORCID: https://orcid.org/0000-0002-2313-0268)
- Brian P. Halliday (ORCID: https://orcid.org/0000-0002-5876-1748)
- Martin J. Bishop (ORCID: https://orcid.org/0000-0002-6237-1902)
- Alistair A. Young (ORCID: https://orcid.org/0000-0001-5702-4220)
- Edward J. Vigmond (ORCID: https://orcid.org/0000-0003-1388-3589)
- Laura Dal Toso
- X Liu
- Richard E. Jones (ORCID: https://orcid.org/0000-0002-7869-8061)
- Pablo Lamata (ORCID: https://orcid.org/0000-0002-3097-4928)
- Marina Strocchi (ORCID: https://orcid.org/0000-0003-1312-251X)
- Sanjay Prasad
Institutions
- Turing Institute (GB)
- Centre National de la Recherche Scientifique (FR)
- Université de Bordeaux (FR)
- Science and Technology Facilities Council (GB)
- King's College London (GB)
- Medical University of Graz (AT)
- British Library (GB)
- Harefield Hospital (GB)
- ETH Zurich (CH)
- Electrophysiology and Heart Modeling Institute (FR)
- Institute for Biomedical Engineering (CH)
- Lung Institute (US)
- King's College Hospital NHS Foundation Trust (GB)
- BioTechMed-Graz (AT)
- Imperial College London (GB)
- Anglia Ruskin University (GB)
Publication Details
- Journal
- Nature Cardiovascular Research
- Published
- 2025-05-16
- DOI
- https://doi.org/10.1038/s44161-025-00650-0
- Citations
- 23
- Primary Topic
- Cardiac electrophysiology and arrhythmias
- Type
- article
- Field-Weighted Citation Impact
- 31.93