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TWAVE AI Model Identifies Multigene Drivers of Diabetes, Cancer and Asthma

By using expression profiles, the tool sidesteps privacy barriers to capture environmental influences on gene networks.

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Overview

  • Northwestern University researchers created the Transcriptome-Wide conditional Variational auto-Encoder (TWAVE), a generative AI framework that amplifies sparse gene expression data to reveal causal gene sets.
  • TWAVE simulates both healthy and diseased cellular states to pinpoint expression changes that trigger complex traits.
  • Validation across diabetes, cancer and asthma showed TWAVE uncovered genes missed by conventional genome-wide association studies.
  • Analysis revealed that different combinations of genes can underlie the same disease in different patients, suggesting opportunities for personalized therapies.
  • The study appeared in the Proceedings of the National Academy of Sciences with support from the National Cancer Institute, National Science Foundation and Simons Foundation.