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<p>Static blood-based biomarkers provide limited insight into psychiatric illness and recovery, largely because they capture only a single, unperturbed snapshot of inherently dynamic biological systems. In this study, we applied a dynamic, longitudinal dual-state approach to characterize peripheral blood mononuclear cell (PBMC) transcriptional trajectories associated with psychotherapy outcomes in post-traumatic stress disorder (PTSD). PBMC transcriptional profiles were generated for veterans with PTSD (<i>n</i> = 46, 21, and 17, respectively) and controls (<i>n</i> = 26, 26, and 23) at pre-treatment, post-treatment, and follow-up. The PTSD cohort with profiles across all three timepoints was divided into responders (<i>n</i> = 6) and non-responders (<i>n</i> = 11) based on their Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) trajectories. All subjects were profiled in both unstimulated and dexamethasone-stimulated states. At pre-treatment, unstimulated responders and non-responders exhibited pronounced transcriptional differences exceeding those observed between PTSD and controls. Longitudinally, unstimulated responders showed a marked shift toward control-like profiles, whereas non-responders retained persistent divergence. Pathway analyses identified a prominent temporal signal within Class C/3 G-protein-coupled receptor pathways driven largely by bitter taste receptors (TAS2Rs), along with subgroup-specific regulation of GABAB, opioid, and NMDA receptor signaling. Dexamethasone-induced responses further differentiated subgroups and showed opposing associations with recovery trajectories, implicating glucocorticoid sensitivity as a potential predictor of treatment outcomes. These findings indicate that biological responsiveness itself constitutes a measurable phenotype of recovery, and that dynamic functional profiling of living immune cells can reveal clinically relevant trajectories and candidate mechanisms not accessible through static biomarkers.</p>

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Dynamic gene expression signatures predict psychotherapy response in PTSD

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月23日

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  • Changxin Xu,
  • Heather N. Bader,
  • Janine D. Flory,
  • Linda M. Bierer,
  • Mitali Chattopadhyay,
  • Frank Desarnaud,
  • Ruoting Yang,
  • Amy Lehrner,
  • Iouri Makotkine,
  • Rachel Yehuda

摘要

Static blood-based biomarkers provide limited insight into psychiatric illness and recovery, largely because they capture only a single, unperturbed snapshot of inherently dynamic biological systems. In this study, we applied a dynamic, longitudinal dual-state approach to characterize peripheral blood mononuclear cell (PBMC) transcriptional trajectories associated with psychotherapy outcomes in post-traumatic stress disorder (PTSD). PBMC transcriptional profiles were generated for veterans with PTSD (n = 46, 21, and 17, respectively) and controls (n = 26, 26, and 23) at pre-treatment, post-treatment, and follow-up. The PTSD cohort with profiles across all three timepoints was divided into responders (n = 6) and non-responders (n = 11) based on their Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) trajectories. All subjects were profiled in both unstimulated and dexamethasone-stimulated states. At pre-treatment, unstimulated responders and non-responders exhibited pronounced transcriptional differences exceeding those observed between PTSD and controls. Longitudinally, unstimulated responders showed a marked shift toward control-like profiles, whereas non-responders retained persistent divergence. Pathway analyses identified a prominent temporal signal within Class C/3 G-protein-coupled receptor pathways driven largely by bitter taste receptors (TAS2Rs), along with subgroup-specific regulation of GABAB, opioid, and NMDA receptor signaling. Dexamethasone-induced responses further differentiated subgroups and showed opposing associations with recovery trajectories, implicating glucocorticoid sensitivity as a potential predictor of treatment outcomes. These findings indicate that biological responsiveness itself constitutes a measurable phenotype of recovery, and that dynamic functional profiling of living immune cells can reveal clinically relevant trajectories and candidate mechanisms not accessible through static biomarkers.