ObjectiveThis longitudinal cohort study aimed to identify the association between baseline physiological characteristics and the risk of post-trauma depressive symptoms, characterize the heterogeneous developmental trajectories of these symptoms, and explore differences in baseline biomarkers across these trajectory groups to provide evidence for early clinical intervention. MethodsA total of 4 709 trauma patients were recruited from the China Severe Trauma Cohort (CSTC) between March 2020 and July 2025. 17 baseline biomarkers and 6 composite inflammatory index were measured, and depressive symptoms were assessed using the PHQ-9 at 1, 3, 6, and 12 months post-admission. Multivariate-adjusted Poisson regression was used to evaluate the predictive value of baseline indicators for post-trauma depressive symptoms, and Latent Class Mixed Models (LCMM) were employed to identify depression symptom developmental trajectories. ResultsElevated baseline systemic inflammation (higher leukocytes, NLR, SII, and CAR) and compromised nutritional/metabolic status (lower RBC count and albumin) significantly increased the risk of post-trauma depressive symptoms throughout the follow-up period. Trajectory analysis identified two distinct classes: "Consistently Low" and "Persistently Elevated" symptoms. Individuals in the "Persistently Elevated" group were significantly characterized by baseline profiles of low lymphocytes, albumin, red blood cells, and hematocrit. Additionally, biomarker effects exhibited some heterogeneity across gender. ConclusionSystemic inflammation activation (high white blood cell count, NLR, SII and CAR) and biological disorders driven by impaired red blood cell or nutritional status (low red blood cell count, MCHC and albumin) are significant predictors of the occurrence and persistent evolution of depressive symptoms. Baseline innate immune activation and insufficient nutritional reserves serve as early biological predictors driving the onset and chronicity of post-trauma depressive symptoms. Integrating routine hematological indicators facilitates clinical risk stratification and precision prediction of symptom trajectories.