Major Cardiovascular Diseases: Multimodal and Multi-omics Prevention Strategies

Cardiovascular diseases (CVDs) remain the leading cause of global mortality, necessitating a shift from traditional reactive treatments to proactive, personalized prevention. While conventional risk factors are well-documented, they often fail to capture the intricate biological complexities of individual disease progression.The emergence of multi-omics—integrating genomics, proteomics, metabolomics, and transcriptomics—offers a granular view of the molecular landscape underlying CVDs. When combined with multimodal data, such as advanced cardiac imaging, wearable sensor metrics, and clinical phenotypes, these strategies enable the identification of novel biomarkers and therapeutic targets.This Research Topic aims to establish a more precise, data-driven paradigm for CVD management. Ultimately, the goal is to refine risk stratification and facilitate individualized preventive interventions that can be integrated into routine clinical practice. Currently, standard risk calculators often overlook the biological heterogeneity inherent in Cardiovascular Diseases. To address this, we emphasize the synthesis of Multi-omics Integration, specifically genomic and proteomic signatures with Multimodal Data Analysis of high-resolution imaging and longitudinal phenotypes. Recent breakthroughs in polygenic risk scoring and metabolic profiling provide new avenues for Precision Prevention, yet standardizing these high-dimensional models for point-of-care use remains a challenge. We seek research that validates these integrated frameworks across diverse cohorts to ensure that complex data streams translate into practical tools for detecting subclinical Risk Stratification and personalizing patient care.1.Utilizing AI for Science (AI4S) and clinical big data to integrate genomics, proteomics, and metabolomics for biomarker discovery, molecular subtyping, and exploring atherosclerotic plaque microenvironments.2.Fusing signals from wearables, digital auscultation, and ECG with clinical imaging (CT/MRI) and ultrasound data to enhance early disease prediction and population health monitoring.3.Investigating systemic aging, metabolic waste accumulation, and the progression from macro-aortic pathology to micro-circulatory dysfunction, particularly in hypertensive populations.4.Leveraging large-scale public databases and longitudinal cohorts for evidence-based risk factor analysis and personalized management.5.Investigating the brain-heart axis and neurovascular unit injury to establish recovery mechanisms and prognostic models for systemic neuro-cardiac complications. Topic editors: Kaisaierjiang Kadier, Ge Zhang, Aikeliyaer Ainiwaer, Ziyu Xu Source: https://www.frontiersin.org/research-topics/78006/major-cardiovascular-diseases-multimodal-and-multi-omics-prevention-strategies