Integrative Bioinformatics and Artificial Intelligence Approaches for Cardiovascular Health, Vascular Aging, and Arterial Stiffness

Cardiovascular health research is increasingly shaped by advances in bioinformatics, artificial intelligence (AI), machine learning, multi-omics, imaging, and digital health. Arterial stiffness is recognized as a hallmark of vascular aging and an independent predictor of cardiovascular events, cognitive decline, and mortality. At the same time, genomics, transcriptomics, proteomics, metabolomics, imaging, and wearable technologies are generating complex datasets with the potential to clarify disease mechanisms and improve risk assessment. However, the integration of these data and methods remains fragmented, with persistent challenges involving data heterogeneity, model interpretability, reproducibility, bias, validation, and clinical implementation. Although recent studies have identified promising biomarkers, predictive models, therapeutic targets, and digital phenotypes, further investigation is needed to establish robust, biologically informed, and clinically transferable approaches. Interdisciplinary research combining computational innovation with cardiovascular and vascular biology is therefore essential to advance precision cardiovascular medicine.This Research Topic aims to advance the application of integrative bioinformatics and AI to the investigation, prediction, prevention, and management of cardiovascular disease, vascular aging, and arterial stiffness. It will address how computational methods can integrate multi-omics, clinical, imaging, and longitudinal digital health data to identify mechanisms, biomarkers, risk profiles, and therapeutic opportunities. The Research Topic will also examine whether explainable, reproducible, and clinically validated models can improve early detection, personalize prevention and treatment, and support translation from computational discoveries to meaningful cardiovascular outcomes.To gather further insights into computational approaches for cardiovascular health, vascular aging, and arterial stiffness, this Research Topic welcomes contributions addressing, but not limited to, the following themes:• Biomarker discovery and validation for cardiovascular disease, vascular aging, and arterial stiffness• Multi-omics integration and omics-based cardiovascular risk stratification• Artificial intelligence, machine learning, and deep learning for vascular phenotyping• Prediction of arterial stiffness, vascular aging, cardiovascular events, and healthy longevity• Network medicine, systems biology, and computational modelling of cardiovascular mechanisms• Cardiovascular imaging analytics and automated vascular assessment• Digital phenotyping and wearable technologies for cardiovascular monitoring• Explainable, interpretable, fair, and clinically trustworthy artificial intelligence• Causal inference, target trial emulation, and computational epidemiology• Precision medicine applications in cardiovascular prevention, diagnosis, and treatment• Data harmonization, reproducibility, external validation, and clinical implementation• Translational frameworks connecting computational findings with biological and clinical evidenceThe scope includes computational and interdisciplinary studies using clinical, epidemiological, molecular, imaging, and digital health data, while emphasizing biological relevance and potential clinical translation. Contributions may address human studies, validated computational methods, or appropriate experimental and translational models.The Research Topic welcomes original research articles, systematic reviews, meta-analyses, methodological papers, brief reports, perspectives, and opinion articles. Topic editors: ALICIA DEL SAZ LARA, Ivan Cavero-Redondo, Andrea Del Saz Source: https://www.frontiersin.org/research-topics/84443/integrative-bioinformatics-and-artificial-intelligence-approaches-for-cardiovascular-health-vascular-aging-and-arterial-stiffness