A single blood sample could soon reveal an individual's likelihood of developing any of six major cardiovascular conditions as far as 15 years in the future. That is the promise of CardiOmicScore, a deep-learning framework detailed in a peer-reviewed paper published in Nature Communications.
The model, developed by researchers including corresponding author Qingpeng Zhang and first author Yan Luo at the University of Hong Kong, profiles 2,920 circulating proteins and 168 metabolites. Trained and tested on data from the UK Biobank, it generates disease-specific risk scores for coronary artery disease, stroke, heart failure, atrial fibrillation, peripheral artery disease and venous thromboembolism.
Dynamic signals versus fixed genetics
Unlike polygenic risk scores that capture a static lifetime baseline, proteomic and metabolomic profiles reflect real-time physiological processes shaped by genetics, environment and lifestyle choices. This distinction matters. Proteins and metabolites offer a window into current health status that can change with behaviour and circumstances.
Alone, the proteomic scores delivered C-index values between 0.69 and 0.82 across the six conditions, while metabolomic scores ranged from 0.64 to 0.74. When integrated with standard clinical information, the combined model lifted predictive accuracy by 0.005 to 0.102 in C-index, enabling forecasts up to 15 years before clinical onset.
Genes determine where we start—they define our baseline health risk. However, proteins and metabolites reflect our current physical health. Our AI tool is designed to decode these complex molecular signals, enabling doctors and patients to identify risks much earlier.
Qingpeng Zhang, corresponding author from the University of Hong Kong, offered that assessment. The insight aligns with a view of prevention that places responsibility in the hands of individuals and families armed with timely, actionable knowledge rather than waiting for disease to declare itself.
From reactive care to informed prevention
Cardiovascular disease remains a leading cause of illness and lost years of healthy life. Tools that move assessment upstream, before irreversible damage occurs, reduce the burden on patients, their loved ones and healthcare systems. By highlighting dynamic biological signals, CardiOmicScore encourages decisions that safeguard personal wellbeing and family stability through prevention instead of treatment after the fact.
