Artificial intelligence (AI) has become a major force in healthcare by revolutionizing the practice of medicine and how people are treated. Recently, researchers at Penn State College of Medicine have developed an innovative AI algorithm—called EXPRESSO for EXpression PREdiction with Summary Statistics Only—that analyzes genetic data to improve autoimmune disease predictions and identify new treatments.
By integrating 3D genomic data and epigenetics, researchers reported that EXPRESSO outperformed existing methods by identifying 26% more novel gene and trait associations. When applied to genome-wide association studies (GWAS) datasets for 14 autoimmune diseases, EXPRESSO identified numerous risk genes with cell-type specific effects. This information was then used to pinpoint potential therapies and suggested repurposing of FDA-approved drugs like vitamin K for ulcerative colitis.
“With this new method, we were able to identify many more risk genes for autoimmune disease that actually have cell-type specific effects, meaning that they only have effects in a particular cell type and not others,” said Bibo Jiang, PhD. Using genetics and AI to identify early risk factors, scientists hope to develop novel therapeutics that may reverse certain genetic expressions and potentially cure or prevent autoimmune diseases.
Although the use of AI has its controversies—such as delivering misinformation, replacing human workers, and manipulating people's images and voices—when used ethically, AI can provide tremendous potential for understanding and treating autoimmune diseases.
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