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By combining genome-sequence information and health records, Stanford scientists have developed a new algorithm that can predict the risk of abdominal aortic aneurysm, and potentially could be used for any number of diseases.
A new approach that distills deluges of genetic data and patient health records has identified a set of telltale patterns that can predict a person’s risk for a common, and often fatal, cardiovascular disease, according to a new study from the Stanford University School of Medicine.
Although the method, which uses a form of artificial intelligence called machine learning, has so far only been used to predict the likelihood of this particular condition — called abdominal aortic aneurysm, or AAA — it’s proof that such an approach could decipher the molecular nuances that put people at risk for just about any complex genetic disease.
“Right now, genome sequencing is starting to make its mark,” said Michael Snyder, PhD, professor and chair of genetics at Stanford. “It’s being used a lot in cancer, or to solve mystery diseases. But there’s still a big open question: How much can we use it for predicting disease risk?”
A new study gives Stanford researchers hope that they may have solved a big problem plaguing gene therapy: the prospect of an autoimmune attack.
Stanford University School of Medicine researchers have demonstrated that gene therapy can be effective without causing a dangerous side effect common to all gene therapy: an autoimmune reaction to the normal protein, which the patient’s immune system is encountering for the first time.
The researchers showed this in a mouse model that accurately recapitulates Duchenne muscular dystrophy. One in every 5,000 boys is born with this crippling disease, which leaves patients wheelchair-bound by mid-adolescence and is typically fatal by young adulthood. It stems from a genetic defect that deprives skeletal and cardiac muscles of a working version of a protein called dystrophin.
“Gene therapy is on the cusp of becoming a mainstream approach for treating single-gene disorders,” said Lawrence Steinman, MD, professor of neurology and neurological sciences and of pediatrics at Stanford. “But there’s a catch: If you give a gene that’s a recipe for a normal protein to someone with a faulty version of the gene, whose body never made the normal protein before, that person’s immune system will mount a reaction — in some cases, a lethal one — to the normal protein, just as it would to any foreign protein. We think we’ve solved that problem.”
The findings are described in a study published online Sept. 3 in the Proceedings of the National Academy of Sciences. Steinman, who holds the George A. Zimmermann Professorship, is the study’s senior author. The lead author is senior research scientist Peggy Ho, PhD.
Olivia Martinez, PhD
Director, Stanford Immunology and Chair, PhD Program in Immunology
Stanford Immunology is home to faculty, students, postdocs, and staff who work together to produce internationally recognized research in immunology. The long tradition of collaboration among the immunology laboratories at Stanford fosters productive interdisciplinary research, with an emphasis on the application of molecular approaches to problems in cellular, translational, and clinical immunology. Faculty research interests include both basic science research and bench-to-bedside approaches, as well as computational and systems immunology. Graduate students and postdoctoral scholars receive high caliber, state-of-the art training through their participation in research, teaching, seminars, journal clubs, and the annual Stanford Immunology Scientific Conference.