Schultebraucks K, Choi KW, Galatzer-Levy IR, et al. - Researchers aimed at examining the discriminatory accuracy of a deep neural net combining joint information from 21 psychiatric and health-related multiple polygenic scores (PGSs) for differentiating resilience vs other longitudinal symptom trajectories with use of longitudinal, genetically informed data on individuals exposed to major life stressors. This longitudinal cohort study was performed including 2,071 participants; of these, 1,638 (79.1%) were classified as resilient, 160 (7.75) were in recovery (improving), 159 (7.7%) had emerging depression, and 114 (5.5%) had preexisting/chronic depression symptoms. Per findings, accurate discrimination between resilience and symptomatic trajectories can be done using 21 polygenic scores using deep neural nets. They recorded lower polygenic scores for several psychiatry disorders as well as metabolic risk in correlation with the resilience trajectory. Polygenic scores are thus suggested to have potential utility for determining long-term risk for depression and resilience.