ArticleNature medicine2020
A population-based phenome-wide association study of cardiac and aortic structure and function.
Article in Nature medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 156 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
156 citing papers in PubMed, 4 syntheses or guidelines pooled it, 255 citations in OpenAlex.
- 2022 ACC/AHA guideline for the diagnosis and management of aortic disease: A report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines.The Journal of thoracic and cardiovascular surgery · 2023Guideline
- Guideline
- 2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines.Journal of the American College of Cardiology · 2022Guideline
- Genome-wide association analysis reveals insights into the genetic architecture of right ventricular structure and function.Nature genetics · 2022Pooled it
- Rationale and design of Dongzong CArdIovascuLar Bio-imaging RegistrY (DAILY) study: Bridging multiomics, imaging and cardiovascular disease.American journal of preventive cardiology · 2026Article
- Cardiac proteomic and phosphoproteomic profiling defines clinically relevant molecular subgroups in human heart failure.Nature cardiovascular research · 2026Article
- Inferring multi-organ genetic connections using imaging and clinical data through Mendelian randomization.Nature biomedical engineering · 2026Article
- Cerebral perfusion features linking subclinical cardiac and aortic dysfunction to vascular brain injury.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Ratio of Left Atrial and Ventricular Volume as New Marker of Atrial Cardiopathy and Stroke Risk.Stroke · 2026Article
- Digital phenotyping of aortic stenosis-related remodeling reveals complementary structural, electrical, and hemodynamic signatures.medRxiv : the preprint server for health sciences · 2026Article
- The landscape of plasma proteomic links to human organ imaging.Nature communications · 2026Article
- Genetic analysis of imaging-derived phenotypes.Nature reviews. Genetics · 2026Review
- The HFpEF-ABA score predicts adverse cardiac remodelling and incident heart failure: a UK biobank study.ESC heart failure · 2026Article
- Imaging-anchored multiomics in cardiovascular disease: integrating cardiac imaging, bulk, single-cell, and spatial transcriptomics.Briefings in bioinformatics · 2026Review
- Integrated biobanking for translational research: a surgical imperative.The British journal of surgery · 2026Article
- Quantitative ventricular trabeculation assessment in cardiac MRI: optimised blood-pool segmentation, box-counting fractal analysis and non-fractal measurements.The international journal of cardiovascular imaging · 2026Article
- Hundreds of cardiac MRI traits derived using 3D diffusion autoencoders share a common genetic architecture.Nature communications · 2026Article
- Local and global patterns support medical imaging as a biomarker of ageing.Communications medicine · 2026Article
- Four-dimensional left ventricular motion clustering reveals cardiovascular phenotypes at population scale.Scientific reports · 2026Article
- Adaptive Riemannian optimization for multi-scale diffeomorphic matching.Nature communications · 2026Article
96 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
19 authors at 10 institutions in 3 countries.
Funding
Abstract
Differences in cardiac and aortic structure and function are associated with cardiovascular diseases and a wide range of other types of disease. Here we analyzed cardiovascular magnetic resonance images from a population-based study, the UK Biobank, using an automated machine-learning-based analysis pipeline. We report a comprehensive range of structural and functional phenotypes for the heart and aorta across 26,893 participants, and explore how these phenotypes vary according to sex, age and major cardiovascular risk factors. We extended this analysis with a phenome-wide association study, in which we tested for correlations of a wide range of non-imaging phenotypes of the participants with imaging phenotypes. We further explored the associations of imaging phenotypes with early-life factors, mental health and cognitive function using both observational analysis and Mendelian randomization. Our study illustrates how population-based cardiac and aortic imaging phenotypes can be used to better define cardiovascular disease risks as well as heart-brain health interactions, highlighting new opportunities for studying disease mechanisms and developing image-based biomarkers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.