Posttraumatic stress disorder (PTSD) and depression are highly co-morbid among individuals with childhood abuse history, while the mechanism of the co-morbidity is highly debated. This study sought to extent the work among college students with network analysis, which is a novel method that sees the co-morbidity from a symptom interacting perspective.Methods:Data was collected from 476 college students who were assessed to have childhood abuse history, PTSD and depression at the same time, using Childhood Trauma Questionnaire- Short Form, PTSD Checklist for DSM-5 and The Center for Epidemiological Studies Depression. We created a Graphical Gaussian Model (GGM) network to show associations between symptom pairs and a Directed Acyclic Graph (DAG) to estimate potential casual relationships among symptoms.Results:The GGM network was reliably stable, feeling sad (Depression) and trouble experiencing positive feelings (PTSD) were the most central nodes. Trouble experiencing positive feelings and several negative affect symptoms, sleep problems and difficulty in concentrating were acting as important bridging nodes. The DAG network suggested the key triggering roles of exaggerated startle (PTSD) and several re-experiencing symptoms.Limitations:The study used cross-sectional data and self-reported measures. Results from network analysis could be affected by scale factors and contain spurious correlations.Conclusions:In the childhood-abuse-related co-morbid structure, several negative affect symptoms both in PTSD and depression have pivotal roles, hyper-arousal symptoms and re-experiencing symptoms could trigger the co-morbid structure. Illustrating the strength and limitations of network analysis, this study help target the potentially influential symptoms for better clinical intervention.