Every human has tens of thousands of tiny genetic alterations in their DNA, also known as variants, that affect how cells build proteins.
- By CATHERINE CARUSO
Yet in a given human genome, only a few of these changes are likely to modify proteins in ways that cause disease, which raises a key question: How can scientists find the disease-causing needles in the vast haystack of genetic variants?
For years, scientists have been working on genome-wide association studies and artificial intelligence tools to tackle this question. Now, a new AI model developed by Harvard Medical School researchers and colleagues has pushed forward these efforts. The model, called popEVE, produces a score for each variant in a patient's genome indicating its likelihood of causing disease and places variants on a continuous spectrum.
In a paper published Nov. 24 in Nature Genetics, the scientists show that popEVE can predict whether variants are benign or pathogenic (disease-causing) and which variants lead to death in childhood versus adulthood.
The model was able to identify more than 100 novel alterations responsible for undiagnosed, rare genetic diseases.
