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Genetic and environmental determinants of diastolic heart function
File | Description | Size | Format | |
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s44161-022-00048-2.pdf | Published version | 6.75 MB | Adobe PDF | View/Open |
Title: | Genetic and environmental determinants of diastolic heart function |
Authors: | Thanaj, M Mielke, J McGurk, K Bai, W Savioli, N Simoes Monteiro de Marvao, A Meyer, H Zeng, L Sohler, F Lumbers, T Wilkins, M Ware, J Bender, C Rueckert, D MacNamara, A Freitag, D O'Regan, D |
Item Type: | Journal Article |
Abstract: | Diastole is the sequence of physiological events that occur in the heart during ventricular filling and principally depends on myocardial relaxation and chamber stiffness. Abnormal diastolic function is related to many cardiovascular disease processes and is predictive of health outcomes, but its genetic architecture is largely unknown. Here, we use machine learning cardiac motion analysis to measure diastolic functional traits in 39,559 participants of the UK Biobank and perform a genome-wide association study. We identified 9 significant, independent loci near genes that are associated with maintaining sarcomeric function under biomechanical stress and genes implicated in the development of cardiomyopathy. Age, sex and diabetes were independent predictors of diastolic function and we found a causal relationship between genetically-determined ventricular stiffness and incident heart failure. Our results provide insights into the genetic and environmental factors influencing diastolic function that are relevant for identifying causal relationships and potential tractable targets. |
Issue Date: | 13-Apr-2022 |
Date of Acceptance: | 8-Mar-2022 |
URI: | http://hdl.handle.net/10044/1/95815 |
DOI: | 10.1038/s44161-022-00048-2 |
ISSN: | 2731-0590 |
Publisher: | Nature |
Start Page: | 361 |
End Page: | 371 |
Journal / Book Title: | Nature Cardiovascular Research |
Volume: | 1 |
Copyright Statement: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/. © The Author(s) 2022 |
Sponsor/Funder: | Wellcome Trust Engineering & Physical Science Research Council (EPSRC) Imperial College Healthcare NHS Trust- BRC Funding British Heart Foundation Imperial College Healthcare NHS Trust- BRC Funding Bayer Ag British Heart Foundation British Heart Foundation Engineering & Physical Science Research Council (EPSRC) Sir Jules Thorn Charitable Trust |
Funder's Grant Number: | 107469/Z/15/Z EP/P001009/1 RDC04 NH/17/1/32725 RDB02 PO2150248927 RE/18/4/34215 RG/19/6/34387 EP/K030523/1 21 JTA |
Publication Status: | Published |
Appears in Collections: | Computing National Heart and Lung Institute Institute of Clinical Sciences Faculty of Medicine Department of Brain Sciences Faculty of Engineering |
This item is licensed under a Creative Commons License