{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T19:52:13Z","timestamp":1770753133829,"version":"3.50.0"},"reference-count":65,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T00:00:00Z","timestamp":1752105600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"Electrocardiogram (ECG) recordings are affected by the heart\u2019s three-dimensional orientation within the thorax, i.e., the anatomical axis. Various cardiac conditions can cause the anatomical axis to shift and\/or alter the pattern of electrical activation, leading to changes in the electrical axis. Nevertheless, there remains a lack of a formal, population-level study of the interplay between the cardiac anatomical and electrical axes and the factors that affect them. In this context, this study aimed to: (1) propose standardised definitions for the cardiac anatomical and electrical axes, (2) characterise their population-wide interplay in healthy conditions, (3) evaluate the impact of hypertension on their distribution and (4) identify associations with\u00a0phenotypical\u00a0and disease characteristics. Using cardiac magnetic resonance images and 12-lead ECGs from ~39,000 UK Biobank participants, patient-specific, paired biventricular geometries and vectorcardiograms were constructed. Five anatomical and four electrical axis definitions were computed, with the optimal pair of definitions selected based on their mutual alignment in 3D space within 28,000 healthy subjects. Accordingly, the anatomical axis was defined as the vector from the apex to the spatial centre of the four valves, and the electrical axis as the direction of the maximum QRS dipole. Mean angular separation in 3D, \u0394<\/mml:mi>A<\/mml:mi>E<\/mml:mi>3<\/mml:mn>D<\/mml:mi><\/mml:mrow><\/mml:msub><\/mml:mrow><\/mml:math><\/jats:alternatives><\/jats:inline-formula>, was 145.0\u00b0\u2009\u00b1\u200916.8\u00b0 in the healthy cohort. The electrical axes exhibited a much larger variability, and strong evidence of anatomical-electrical coupling was identified. Increasing BMI notably affected the anatomical axis, rotating the heart more horizontally\u2014a pattern mirrored by the electrical axis. Both axes were also significantly influenced by sex and, to a lesser extent, age. The axes were then studied in the sub-cohort of ~3,500 UK BioBank participants with primary hypertension, where a similar rotational pattern as that with increasing BMI was revealed. Finally, phenome-wide association studies in the 39,000 participants reveal associations between the axes angular metrics and phenotypes signalling an increased afterload, and an association to hypertension among other clinical conditions. These findings underscore the complex anatomical-electrical interplay and highlight the potential of cardiac axes biomarkers for an improved clinical ECG interpretation and disease characterisation.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013161","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T17:22:06Z","timestamp":1752168126000},"page":"e1013161","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Anatomical-electrical coupling of cardiac axes: Definitions and population variability for advancing personalised ECG interpretation"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9830-8050","authenticated-orcid":true,"given":"Mohammad","family":"Kayyali","sequence":"first","affiliation":[]},{"given":"Ana","family":"Minchol\u00e9","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2313-0268","authenticated-orcid":true,"given":"Shuang","family":"Qian","sequence":"additional","affiliation":[]},{"given":"Alistair","family":"Young","sequence":"additional","affiliation":[]},{"given":"Devran","family":"Ugurlu","sequence":"additional","affiliation":[]},{"given":"Elliot","family":"Fairweather","sequence":"additional","affiliation":[]},{"given":"Steven","family":"Niederer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5361-5725","authenticated-orcid":true,"given":"John","family":"Whitaker","sequence":"additional","affiliation":[]},{"given":"Martin","family":"Bishop","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3097-4928","authenticated-orcid":true,"given":"Pablo","family":"Lamata","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2025,7,10]]},"reference":[{"issue":"48","key":"pcbi.1013161.ref001","doi-asserted-by":"crossref","first-page":"4556","DOI":"10.1093\/eurheartj\/ehaa159","article-title":"The \u201cDigital Twin\u201d to enable the vision of precision cardiology","volume":"41","author":"J Corral-Acero","year":"2020","journal-title":"Eur Heart J"},{"key":"pcbi.1013161.ref002","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.3389\/fphys.2019.01103","article-title":"MRI-based computational torso\/biventricular multiscale models to investigate the impact of anatomical variability on the ECG QRS complex","volume":"10","author":"A Minchol\u00e9","year":"2019","journal-title":"Front Physiol"},{"issue":"4","key":"pcbi.1013161.ref003","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/j.jelectrocard.2015.05.004","article-title":"An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects","volume":"48","author":"UC Nguy\u00ean","year":"2015","journal-title":"J Electrocardiol"},{"issue":"3","key":"pcbi.1013161.ref004","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.ahj.2004.10.041","article-title":"The relationship between electrical axis by 12-lead electrocardiogram and anatomical axis of the heart by cardiac magnetic resonance in healthy subjects","volume":"150","author":"H Engblom","year":"2005","journal-title":"Am Heart J"},{"issue":"4622","key":"pcbi.1013161.ref005","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1016\/S0140-6736(00)50560-1","article-title":"The different forms of the human electrocardiogram and their signification","volume":"179","author":"W Einthoven","year":"1912","journal-title":"Lancet"},{"key":"pcbi.1013161.ref006","doi-asserted-by":"crossref","first-page":"103895","DOI":"10.1016\/j.compbiomed.2020.103895","article-title":"A computational investigation into rate-dependant vectorcardiogram changes due to specific fibrosis patterns in non-isch\u00e6mic dilated cardiomyopathy","volume":"123","author":"PM Gemmell","year":"2020","journal-title":"Comput Biol Med"},{"issue":"6","key":"pcbi.1013161.ref007","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1016\/0002-8703(48)90284-1","article-title":"Can the longitudinal anatomical axis of the ventricles be estimated from the electrocardiogram?","volume":"36","author":"A Hyman","year":"1948","journal-title":"Am Heart J"},{"issue":"6","key":"pcbi.1013161.ref008","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1161\/01.CIR.3.6.906","article-title":"Anatomic and electrocardiographic position of the heart","volume":"3","author":"NO Fowler","year":"1951","journal-title":"Circulation"},{"issue":"4","key":"pcbi.1013161.ref009","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1016\/S0002-8703(43)90149-8","article-title":"The normal human ventricular gradient III. 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