Some people’s faces — or even just a photo of them — hint at the genes they carry. And now, an algorithm can predict not only whether they carry a genetic mutation, but which genes were mutated.
The study, published [January 7] in Nature Medicine, is the latest from a Boston-based company called FDNA, one of a few organizations creating software that can help physicians diagnose genetic syndromes based just on a face.
The study itself is a collection of experiments testing how the results of algorithms — FDNA refers to them as DeepGestalt — stack up against clinicians’ diagnoses. In one of the experiments, DeepGestalt’s performance was better than random chance when picking which of five genetic mutations might be causing a condition called Noonan syndrome. It was correct 64 percent of the time.
…[FDNA chief technology officer Yaron] Gurovich is quick to say that the tool isn’t specifically or only for Noonan syndrome. His team chose the condition because there are already published studies about how well humans can distinguish between the various faces associated with it.
Understanding how a child with Noonan syndrome will develop can help health care providers figure out what medical problems they may face, [Noonan syndrome expert Bruce] Gelb said. But the algorithm isn’t likely to replace a genetic test, he said.