American Journal of Preventive Cardiology
Use of an AI metabolomics score to predict cardiovascular risk among patients with Psoriasis in the MGB and UK Biobanks
By Christos P. Kotanidis, Art Schuermans, Priyam Choksi and 13 others.
Abstract
Background
Systemic inflammation in psoriasis accelerates atherosclerosis and confers excess cardiovascular risk that is not fully captured by traditional clinical predictors. Metabolomic profiling may identify disease-specific metabolic signatures associated with cardiovascular events and enhance risk prediction beyond conventional factors.
Objectives
To determine whether plasma metabolomic profiling improves cardiovascular risk prediction in patients with psoriasis and to develop and externally validate an artificial intelligence–driven metabolomic risk score (MetaPsoAI) for incident cardiovascular events.
Methods
We analyzed 1086 individuals with psoriasis and no prior coronary artery disease from the Mass General Brigham (MGB) Biobank who underwent nuclear magnetic resonance–based quantification of 168 circulating metabolites. Associations between metabolites and incident all-cause death or myocardial infarction were assessed. An extreme gradient boosting algorithm was used to develop MetaPsoAI for prediction of myocardial infarction or stroke. External validation was performed in the UK Biobank ( n = 274,000), stratified by psoriasis status.