Microbiome signature of posttraumatic stress disorder and resilience in youth.
Bibliographic record
Abstract
OBJECTIVE: Identifying biomarkers that can distinguish trauma-exposed youth at risk for developing posttraumatic pathology from resilient individuals is essential for targeted interventions. As trauma can alter the microbiome with lasting effects on the host, our longitudinal, multimeasure, cross-species study aimed to identify the microbial signature of posttraumatic stress disorder (PTSD). METHOD: = 84), repeatedly assessing posttraumatic symptomatology and maternal caregiving. In late adolescence, we collected fecal samples from mothers and youth and assessed microbiome composition, diversity, and mother-child microbial synchrony. We then transplanted adolescents' fecal samples into germ-free mice to determine if behavioral changes are observed. RESULTS: Youth with PTSD exhibited a distinct gut microbiome profile and lower diversity compared to resilient individuals, and microbiome diversity mediated the continuity of posttraumatic symptomatology throughout development. Low microbiome diversity correlated with more posttraumatic symptoms in early childhood, more emotional and behavioral problems in adolescence, and poor maternal caregiving. Youth with PTSD demonstrated less mother-child microbial synchrony, suggesting that low microbial concordance between mother and child may indicate susceptibility to posttraumatic illness. Germ-free mice transplanted with microbiomes from individuals with PTSD displayed increased anxious behavior. CONCLUSIONS: Our findings provide evidence that the trauma-associated microbiome profile is at least partially responsible for the anxiety component of the PTSD phenotype and highlight microbial underpinnings of resilience. Further, our results suggest that the microbiome may serve as additional biological memory of early life stress and underscore the potential for microbiome-related diagnosis and treatment following trauma. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".