Biologically informed genetic data transformations improve multi-omic comorbidity prediction in people with HIV
This study demonstrates that in people with HIV, biologically informed genetic data transformations—specifically polygenic risk scores and AlphaGenome-derived gene-level impact scores—significantly improve multi-omic prediction accuracy for coronary artery disease and chronic kidney disease compared to using raw SNP genotypes or principal components.