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Identifying leukocyte phenotypes by scRNA-seq to predict cardiovascular risk

Nature Reviews Cardiology volume 20, pages 439–440 (2023)Cite this article

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Contemporary tools to predict cardiovascular risk lack accuracy on an individual-patient level. The use of single-cell RNA sequencing to identify specific leukocyte patterns might overcome some of these limitations, propelling us towards a precision medicine approach.

According to the WHO, 17.9 million people died from cardiovascular disease (CVD) in 2019, making it the leading cause of deaths worldwide. The majority of these deaths are caused by atherosclerotic CVD. Traditional risk factors for atherosclerotic CVD identified in the Framingham Study include lipid disorders (such as elevated plasma LDL-cholesterol levels), hypertension, diabetes mellitus and smoking. Tools such as the SCORE2 risk prediction algorithm are used to integrate these risk factors as well as basic demographic data to predict the likelihood of cardiovascular events. Increasing appreciation of the importance of controlling cardiovascular risk factors has led to lower incidences of CVD and subsequent sequelae, but a large residual risk of CVD remains. Cardiovascular outcome trials evaluating highly effective lipid-lowering therapies still show an unacceptably high residual risk even in the treatment groups (for example, in the FOURIER trial1, there was a 12.6% cumulative 3-year incidence of the primary composite end point, consisting of cardiovascular death, myocardial infarction, stroke and hospitalization for unstable angina, or coronary revascularization in patients receiving optimal medical therapy plus the PCSK9 inhibitor evolocumab).

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Fig. 1: Identifying leukocyte phenotypes by scRNA-seq to predict cardiovascular risk.

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  1. University Heart Center Graz, Department of Cardiology, Medical University Graz, Graz, Austria

    Johannes Gollmer & Andreas Zirlik

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  1. Johannes Gollmer
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  2. Andreas Zirlik
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Correspondence to Andreas Zirlik.

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Gollmer, J., Zirlik, A. Identifying leukocyte phenotypes by scRNA-seq to predict cardiovascular risk. Nat Rev Cardiol 20, 439–440 (2023). https://doi.org/10.1038/s41569-023-00891-1

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