Northwestern University researchers have developed an advanced generative AI computational model, leveraging a transcriptome-wide conditional variational autoencoder (TWAVE), to identify key gene combinations driving complex polygenic diseases such as diabetes, cancer, and asthma. By enhancing limited gene expression datasets, the model reveals multigenic networks underlying genotype-phenotype relationships, addressing the analytical challenges posed by multifactorial disease traits and offering prospects for targeted therapeutic discovery.