Identifying leukocyte phenotypes by scRNA-seq to predict cardiovascular risk

Contemporary tools for predicting cardiovascular risk have limitations in accurately assessing individual patients. However, advancements in single-cell RNA sequencing offer the potential to identify specific leukocyte patterns, which could improve the precision of cardiovascular risk prediction. Cardiovascular disease is the leading cause of global deaths, with atherosclerotic cardiovascular disease being a major contributor. Traditional risk factors identified by the Framingham Study include lipid disorders, hypertension, diabetes, and smoking. Existing risk prediction algorithms like SCORE2 incorporate these factors and demographic data, but the integration of single-cell RNA sequencing data could enhance the accuracy and effectiveness of precision medicine approaches in managing cardiovascular risk.