298-scPRS: Risk Scores Dissect Complex Disease Heterogeneity
The paper introduces a novel computational approach called the single-cell Polygenic Risk Score (scPRS), which is designed to overcome the limitations of conventional risk prediction by accounting for cellular and molecular heterogeneity in complex human diseases. This methodology integrates single-cell epigenome profiling, specifically scATAC-seq data, with a Graph Neural Network (GNN) to calculate genetic risk scores at the individual cell level. Researchers applied scPRS to four major conditions, including Type 2 Diabetes, Alzheimer Disease, and Hypertrophic Cardiomyopathy, consistently…
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