By using machine learning techniques to scour electronic health records, researchers have identified individuals who were likely to have binge eating disorder (BED) but had not received a formal diagnosis. Genomewide association studies including such patients enabled the investigators to identify several risk variants that were correlated with BED irrespective of body mass index (BMI), which covaries with BED and is a potential confounding factor.