Post-traumatic stress disorder (PTSD) faces a translational crisis in psychopharmacology, evidenced by the limited efficacy of approved selective serotonin reuptake inhibitors (SSRIs) and the recent failure of novel monoaminergic strategies. Classical neurobiological models, centered on the amygdala, prefrontal cortex, and hippocampus, have proven insufficient for therapeutic development. A primary bottleneck remains the failure of preclinical animal models to capture core human symptoms, such as spontaneous intrusive memories. This review argues for a paradigm shift, integrating three key domains to elucidate PTSD pathophysiology. First, we examine neuroinflammation, moving beyond general immune activation to a specific mechanism of C1q-independent, C3-mediated pathological synaptic pruning in the medial prefrontal cortex (mPFC). Second, we analyze epigenetic scaffolds, highlighting the role of the long non-coding RNA (lncRNA) as a synaptic coordinator essential for fear extinction memory consolidation. We propose a feedforward loop where inflammation drives pathological lncRNA expression, which in turn suppresses neuroprotection and promotes synaptic erosion. Third, we evaluate human induced pluripotent stem cell (iPSC) models, not as platforms for modeling acquired trauma, but as crucial tools for identifying inherent cellular susceptibility, such as glucocorticoid hypersensitivity. By integrating these domains, this review proposes a multi-scale model where trauma-induced molecular and cellular dysfunction underlies the persistent circuit-level impairment observed in PTSD. This integrated framework provides a novel, mechanistically-driven roadmap for identifying and validating the next generation of therapeutic targets. • Current animal models may fail to capture intrusive traumatic memories. • lncRNAs might link inflammation to persistent fear extinction deficits. • Human iPSC models may reveal inherent cellular vulnerabilities to stress. • We explore if specific immune molecules drive synaptic loss in PTSD circuits.
Zhang et al. (Wed,) studied this question.
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