Researchers at Google DeepMind have used artificial intelligence to predict whether mutations in human genes are likely to be harmful, in one of the first examples of the technology helping to accelerate the diagnosis of diseases caused by genetic variants. The AI tool, called AlphaMissense, assessed all 71mn ‘‘missense” mutations, in which a single letter of the human genetic code changes. Of these, 32 per cent were classified as likely to be pathogenic, 57 per cent benign and the rest uncertain. The findings were published on Tuesday in the journal Science. Illustrating the resources being poured into AI for life sciences, Meta chief executive Mark Zuckerberg announced on Tuesday that the philanthropic group he founded with his wife Priscilla Chan, the Chan Zuckerberg Initiative, would build “one of the largest computing systems dedicated to non-profit life sciences”. It will focus on using AI to model what happens in living cells. Human experts have so far discovered the clinical effect of just 0.1 per cent of missense variants, which change the structure of proteins, the body’s main working molecules. “Experiments to uncover disease-causing mutations are expensive and laborious,” said Žiga Avsec, a researcher on the project that was based at DeepMind’s London headquarters.“Every protein is unique and each experiment has to be designed separately which can take months,” Avsec said. “By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritise resources and accelerate more complex studies.
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