{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T12:57:47Z","timestamp":1768568267841,"version":"3.49.0"},"posted":{"date-parts":[[2025,8,26]]},"group-title":"Cardiovascular Medicine","reference-count":88,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T00:00:00Z","timestamp":1756166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.medrxiv.org\/about\/FAQ#license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,8,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Sphericity is a measurement of how closely an object approximates a globe. The sphericity of the blood pool of the left ventricle (LV), is an emerging measure linked to myocardial dysfunction.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    Video-based deep learning models were trained for semantic segmentation (pixel labeling) in cardiac magnetic resonance imaging in 84,327 UK Biobank participants. These labeled pixels were co-oriented in 3D and used to construct surface meshes. LV ejection fraction, mass, volume, surface area, and sphericity were calculated. Epidemiologic and genetic analyses were conducted. Polygenic score validation was performed in\n                    <jats:italic>All of Us<\/jats:italic>\n                    .\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    3D LV sphericity was found to be more strongly associated (HR 10.3 per SD, 95% CI 6.1-17.3) than LV ejection fraction (HR 2.9 per SD reduction, 95% CI 2.4-3.6) with dilated cardiomyopathy (DCM). Paired with whole genome sequencing, these measurements linked LV structure and function to 366 distinct common and low-frequency genetic loci\u2014and 17 genes with rare variant burden\u2014spanning a 25-fold range of effect size. The discoveries included 22 out of the 26 loci that were recently associated with DCM. LV genome-wide polygenic scores were equivalent to, or outperformed, dedicated hypertrophic cardiomyopathy (HCM) and DCM polygenic scores for disease prediction. In\n                    <jats:italic>All of Us<\/jats:italic>\n                    , those in the polygenic extreme 1% had an estimated 6.6% risk of DCM by age 80, compared to 33% for carriers of rare truncating variants in the gene\n                    <jats:italic>TTN<\/jats:italic>\n                    .\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>3D sphericity is a distinct, heritable LV measurement that is intricately linked to risk for HCM and DCM. The genetic findings from this study raise the possibility that the majority of common genetic loci that will be discovered in future large-scale DCM analyses are present in the current results.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2025.08.22.25334019","type":"posted-content","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T22:45:12Z","timestamp":1756248312000},"source":"Crossref","is-referenced-by-count":0,"title":["Whole-genome sequencing analysis of left ventricular structure and sphericity in 80,000 people"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6088-4037","authenticated-orcid":false,"given":"James P.","family":"Pirruccello","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2025082915350842000_2025.08.22.25334019v1.1","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1161\/01.CIR.44.4.548","article-title":"Relationship Between Changes in Left Ventricular Dimensions and the Ejection Fraction in Man","volume":"44","year":"1971","journal-title":"Circulation"},{"key":"2025082915350842000_2025.08.22.25334019v1.2","doi-asserted-by":"publisher","DOI":"10.1016\/S0002-9149(77)80187-2"},{"key":"2025082915350842000_2025.08.22.25334019v1.3","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1161\/01.CIR.48.4.786","article-title":"Dynamic Geometry of the Left Ventricle in Mitral Regurgitation","volume":"48","year":"1973","journal-title":"Circulation"},{"key":"2025082915350842000_2025.08.22.25334019v1.4","doi-asserted-by":"publisher","DOI":"10.1016\/0002-8703(92)90703-X"},{"key":"2025082915350842000_2025.08.22.25334019v1.5","doi-asserted-by":"publisher","DOI":"10.1136\/heartjnl-2016-310052"},{"key":"2025082915350842000_2025.08.22.25334019v1.6","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.medj.2023.02.009","article-title":"Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes","volume":"4","year":"2023","journal-title":"Med"},{"key":"2025082915350842000_2025.08.22.25334019v1.7","doi-asserted-by":"publisher","DOI":"10.1161\/circulationaha.119.041161"},{"key":"2025082915350842000_2025.08.22.25334019v1.8","first-page":"1","article-title":"Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy","volume":"11","year":"2020","journal-title":"Nature Communications"},{"key":"2025082915350842000_2025.08.22.25334019v1.9","doi-asserted-by":"crossref","unstructured":"Zheng SL , Henry A , Cannie D , Lee M , Miller D , McGurk KA , Bond I , Xu X , Issa H , Francis C , De Marvao A , Theotokis PI , Buchan RJ , Speed D , Abner E , Adams L , Aragam KG , \u00c4rnl\u00f6v J , Raja AA , Backman JD , Baksi J , Barton PJR , Biddinger KJ , Boersma E , Brandimarto J , Brunak S , Bundgaard H , Carey DJ , Charron P , Cook JP , Cook SA , Denaxas S , Deleuze J-F , Doney AS , Elliott P , Erikstrup C , Esko T , Farber-Eger EH , Finan C , Garnier S , Ghouse J , Giedraitis V , Gu\u00f0bjartsson DF , Haggerty CM , Halliday BP , Helgadottir A , Hemingway H , Hillege HL , Kardys I , Lind L , Lindgren CM , Lowery BD , Manisty C , Margulies KB , Moon JC , Mordi IR , Morley MP , Morris AD , Morris AP , Morton L , Noursadeghi M , Ostrowski SR , Owens AT , Palmer CNA , Pantazis A , Pedersen OBV , Prasad SK , Shekhar A , Smelser DT , Srinivasan S , Stefansson K , Sveinbj\u00f6rnsson G , Syrris P , Tammesoo M-L , Tayal U , Teder-Laving M , Thorgeirsson G , Thorsteinsdottir U , Tragante V , Tr\u00e9gou\u00ebt D-A , Treibel TA , Ullum H , Valdes AM , van Setten J , van Vugt M , Veluchamy A , Verschuren WMM , Villard E , Yang Y , Asselbergs FW , Cappola TP , Dube M-P , Dunn ME , Ellinor PT , Hingorani AD , Lang CC , Samani NJ , Shah SH , et al. 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