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October 4, 2022Open Access

Environmental and genetic predictors of human cardiovascular ageing

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Why the study?

Cardiovascular ageing leads to progressive structural and functional decline, but its genetic architecture is not known.

Population

39,559 participants of UK Biobank

Design

Machine learning modelling study

Authors

MSMit ShahMIMarco Henrique de Almeida InácioCLChang Lu

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Overview

Genetic variants linked to CV ageing require validation before guiding risk assessment; leaves open molecular targets for interventional trials.

Structured PICO

P
Population
39,559 participants of UK Biobank
O
Outcome
Cardiovascular age quantified from image-derived traits of vascular function, cardiac motion and myocardial fibrosis, and conduction traits from electrocardiogramssurrogate

Machine learning models applied to UK Biobank data identified genetic variants and cardiometabolic risk factors associated with accelerated cardiovascular aging, revealing potential molecular targets.

Cite This Study

Shah et al. (2022) studied this question.

synapsesocial.com/papers/6a853ff0f14ace264a43d5c2https://doi.org/10.1101/2022.10.03.22280042
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Environmental and genetic predictors of human cardiovascular ageing2023 · 64 citations
  2. 2Genetics of Cardiac Aging Implicate Organ-Specific Variation2024
  3. 3Body fat and human cardiovascular ageing2024
  4. 4Transcriptomic landscape of human cardiac aging: identification of cardioselective age-associated genes and predictive modeling2026
  5. 5How to measure and model cardiovascular aging2025 · 10 citations