Nature Search

Genetic and environmental determinants of diastolic heart function

O’Regan and colleagues use deep-learning cardiac motion analysis in participants of the UK Biobank to measure diastolic functional traits and perform a genome-wide association study to generate insights into the genetic and environmental factors that influence diastolic function.

Marjola Thanaj
Johanna Mielke
Declan P. O’Regan
ResearchOpen Access13 Apr 2022
Nature Cardiovascular Research

Volume: 1, P: 361-371
Genetic and functional insights into the fractal structure of the heart

A genome-wide association study shows that myocardial trabeculae are an important determinant of cardiac performance in the adult heart, identifies conserved pathways that regulate structural complexity and reveals the influence of trabeculae on the susceptibility to cardiovascular disease.

Hannah V. Meyer
Timothy J. W. Dawes
Declan P. O’Regan
Research19 Aug 2020
Nature

Volume: 584, P: 589-594
Genetic and phenotypic architecture of human myocardial trabeculation

The inner surface of the heart has a meshwork of muscles called trabeculae. McGurk et al. report the genetic regulation of these complex structures across common and rare variants, revealing pathways implicated in heart development and cell fate.

Kathryn A. McGurk
Mengyun Qiao
Declan P. O’Regan
ResearchOpen Access20 Nov 2024
Nature Cardiovascular Research

Volume: 3, P: 1503-1515
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics

MeshHeart, a conditional generative model for time-resolved 3D heart mesh generation, is proposed by Qiao et al. to unravel heart motion patterns. Their findings could advance diagnosis and treatment strategies for cardiovascular diseases.

Mengyun Qiao
Kathryn A. McGurk
Wenjia Bai
ResearchOpen Access19 May 2025
Nature Machine Intelligence

Volume: 7, P: 800-811
Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings

Polygenic scores derived from genome-wide association analyses of hypertrophic cardiomyopathy and genetically correlated left ventricular traits effectively stratify risk of disease and adverse outcomes in the general population and across clinical cohorts.

Sean L. Zheng
Sean J. Jurgens
James S. Ware
ResearchOpen Access18 Feb 2025
Nature Genetics

Volume: 57, P: 563-571
Genome-wide association analysis provides insights into the molecular etiology of dilated cardiomyopathy

Genome-wide association analyses comprising 14,256 cases and 1,199,156 controls and incorporating correlated cardiac magnetic resonance imaging traits provide insights into the molecular etiology of dilated cardiomyopathy.

Sean L. Zheng
Albert Henry
R. Thomas Lumbers
ResearchOpen Access21 Nov 2024
Nature Genetics

Volume: 56, P: 2646-2658
Environmental and genetic predictors of human cardiovascular ageing

Cardiovascular ageing is characterised by a progressive decline in function, which contributes to multi-morbidity. Here, the authors use machine learning to predict biological age and identify key genetic risk factors.

Mit Shah
Marco H. de A. Inácio
Declan P. O’Regan
ResearchOpen Access21 Aug 2023
Nature Communications

Volume: 14, P: 1-15
Deep-learning cardiac motion analysis for human survival prediction

A fully convolutional neural network is used to create time-resolved three-dimensional dense segmentations of heart images. This dense motion model forms the input to a supervised system called 4Dsurvival that can efficiently predict human survival.

Ghalib A. Bello
Timothy J. W. Dawes
Declan P. O’Regan
Research11 Feb 2019
Nature Machine Intelligence

Volume: 1, P: 95-104
A population-based phenome-wide association study of cardiac and aortic structure and function

Using magnetic resonance images of the heart and aorta from 26,893 individuals in the UK Biobank, a phenome-wide association study associates cardiovascular imaging phenotypes with a wide range of demographic, lifestyle and clinical features.

Wenjia Bai
Hideaki Suzuki
Daniel Rueckert
Research24 Aug 2020
Nature Medicine

Volume: 26, P: 1654-1662
Large-scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy

Genome-wide and multitrait analyses identify novel loci associated with hypertrophic cardiomyopathy and relevant left ventricular traits. Gene-level burden analyses show that rare truncating SVIL variants are associated with high risk of hypertrophic cardiomyopathy.

Rafik Tadros
Sean L. Zheng
Hugh Watkins
ResearchOpen Access18 Feb 2025
Nature Genetics

Volume: 57, P: 530-538
Titin-truncating variants affect heart function in disease cohorts and the general population

Stuart Cook and colleagues study the role of TTN (titin)-truncating variants using a combination of heart physiology experiments in rats and genomic analysis in humans. Their data show that TTN variants are associated with a range of cardiac phenotypes in healthy individuals and in patients with dilated cardiomyopathy.

Sebastian Schafer
Antonio de Marvao
Stuart A Cook
Research21 Nov 2016
Nature Genetics

Volume: 49, P: 46-53
Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect

Genome-wide analyses identify multiple loci associated with hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM) and left ventricular (LV) traits. Cardiomyopathies exhibit strong genetic correlations with LV traits, with opposing effects in HCM and DCM.

Rafik Tadros
Catherine Francis
Connie R. Bezzina
Research25 Jan 2021
Nature Genetics

Volume: 53, P: 128-134
Current understanding and management of cardiovascular involvement in rheumatic immune-mediated inflammatory diseases

Cardiovascular involvement is one of the many manifestations of rheumatic immune-mediated inflammatory diseases (IMIDs) that increase mortality. The pathogenesis of atherosclerosis and inflammatory cardiomyopathies involves inflammatory pathways common with those operating and targeted in rheumatic IMIDs. Here, Maya Buch and colleagues discuss implications of these shared pathways for the prevention, detection and management of cardiovascular involvement in patients with rheumatic IMIDs, while highlighting complexities and open questions.

Maya H. Buch
Ziad Mallat
Sven Plein
Reviews02 Sept 2024
Nature Reviews Rheumatology

Volume: 20, P: 614-634
Cardiac structure and function in patients with schizophrenia taking antipsychotic drugs: an MRI study

Toby Pillinger
Emanuele F. Osimo
Oliver D. Howes
ResearchOpen Access07 Jun 2019
Translational Psychiatry

Volume: 9, P: 1-10
Adipose tissue dysfunction, inflammation, and insulin resistance: alternative pathways to cardiac remodelling in schizophrenia. A multimodal, case–control study

Emanuele F. Osimo
Mark Sweeney
Oliver D. Howes
ResearchOpen Access06 Dec 2021
Translational Psychiatry

Volume: 11, P: 1-9
Systematic large-scale assessment of the genetic architecture of left ventricular noncompaction reveals diverse etiologies

Francesco Mazzarotto
Megan H. Hawley
Roddy Walsh
ResearchOpen Access26 Jan 2021
Genetics in Medicine

Volume: 23, P: 856-864
Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Xiaolei Zhang
Roddy Walsh
James S. Ware
ResearchOpen Access13 Oct 2020
Genetics in Medicine

Volume: 23, P: 69-79
The relationship between synaptic density marker SV2A, glutamate and N-acetyl aspartate levels in healthy volunteers and schizophrenia: a multimodal PET and magnetic resonance spectroscopy brain imaging study

Ellis Chika Onwordi
Thomas Whitehurst
Oliver D. Howes
ResearchOpen Access17 Jul 2021
Translational Psychiatry

Volume: 11, P: 1-9
CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation

Nicola Whiffin
Roddy Walsh
Stuart A Cook
ResearchOpen Access25 Jan 2018
Genetics in Medicine

Volume: 20, P: 1246-1254
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

The DECIDE-AI checklist, resulting from a multi-stakeholder group of experts in a Delphi process and following the EQUATOR Network’s recommendations, includes key items that should be reported in early-stage clinical studies of AI-based decision support systems, to ensure a responsible and transparent deployment of AI systems in healthcare.

Baptiste Vasey
Myura Nagendran
Zane B. Perkins
Reviews18 May 2022
Nature Medicine

Volume: 28, P: 924-933
Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Baptiste Vasey
Myura Nagendran
Zane B. Perkins
Amendments and Corrections12 Aug 2022
Nature Medicine

Volume: 28, P: 2218
The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: defining a healthy volunteer cohort

Yasmine Aguib
Mona Allouba
Magdi Yacoub
ResearchOpen Access23 Oct 2020
npj Genomic Medicine

Volume: 5, P: 1-8

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