Emily A. Devine, James B. Chambers, Taylorae Dunn, Ava Musarra, Sophie Porter, Christine E. Moore, Marissa Smail, Nawshaba Nawreen, Ben A. Packard, James P. Herman
The mammalian stress response relies on tightly regulated HPA axis signaling, and disruptions in glucocorticoid feedback are implicated in stress-related disorders such as PTSD. Although many individuals experience trauma, only some develop pathology, suggesting that individual differences in glucocorticoid responsivity may help predict susceptibility or resilience. Here, we examined whether corticosterone (CORT) responses to a mild stressor predict behavioral outcomes following single-prolonged stress (SPS) in male and female rats. Mild stress reactivity was quantified using area-under-the-curve (AUC) CORT responses to light-dark box exposure, after which animals underwent SPS, behavioral assays, and post-reinstatement cFos immunohistochemical analysis. Females exhibited SPS-induced reductions in basal AM CORT and displayed a robust traumatic stress-related phenotype in which high CORT responders displayed increased anxiety-like behavior, impaired fear extinction, and enhanced reinstatement. Correlational and permutation analyses revealed a consistent pattern in SPS-exposed females in which lower pre-stress basal AM CORT and higher mild stress-induced CORT (AUC) predicted increased fear expression, indicating a dissociation between resting and stress-evoked glucocorticoid signals. In males, mild stress reactivity did not predict SPS-related outcomes; however, reduced pre-stress basal AM CORT in control males predicted increased fear expression, suggesting sex-specific differences in the potential predictive value of CORT dynamics. SPS and CORT responder status also differentially modulated cFos expression across stress-related brain regions, including the PVN, infralimbic cortex, and amygdala in both males and females. These findings demonstrate that mild stress reactivity and basal glucocorticoid dynamics can predict trauma-related phenotypes in a sex-specific manner, identifying them as a potential biomarker of PTSD susceptibility in females.
Metabolic syndrome (MetS) and epilepsy are clinically associated, but how chronic peripheral metabolic stress might influence seizure susceptibility remains unclear. The potential links among CNS-interface dysfunction, glial responses, and inhibitory-circuit vulnerability require further clarification. We propose immunometabolic synaptopathy as a hypothesis-driven framework linking chronic metabolic dysfunction to impaired inhibitory-circuit resilience. MetS-associated metabolic and inflammatory signals may alter blood–brain barrier function, CNS-border immune signaling, and glial homeostasis. Evidence from peripheral myeloid training and CNS immune-memory models supports the plausibility of trained-immunity-like microglial priming, but its occurrence and persistence in MetS-associated epileptogenesis remain unestablished. We identify the parvalbumin-positive interneuron–perineuronal net (PV-PNN) unit as a candidate convergence point because of its energetic demands and dependence on ionic and extracellular-matrix homeostasis. Altered metabolic and trophic support, oxidative stress, impaired K + and glutamate handling, and PNN remodeling may jointly compromise PV-mediated inhibition. Whether these processes preferentially affect PV-PNN units or precede spontaneous seizures requires direct testing. Five candidate nodes—NLRP3, mTOR, HIF-1α, MMP-9, and Kir4.1—provide opportunities for mechanistic testing. Their therapeutic relevance to MetS-associated epilepsy remains uncertain, and available compounds differ in selectivity, CNS exposure, and safety. The framework motivates experimental evaluation of intervention timing and target dependence rather than specific clinical treatment recommendations. Immunometabolic synaptopathy integrates cross-context evidence into a testable hypothesis of metabolically associated seizure susceptibility. The complete pathway to spontaneous epilepsy has not been demonstrated end-to-end and requires longitudinal, cell- and pathway-specific validation.
Affective disorders, such as anxiety and depression, are more prevalent in individuals with inflammatory diseases than in the general population. This comorbidity suggests biological links between immune activation and affective dysregulation. Indeed, there is extensive literature on the impact of inflammation on brain function. Peripheral immune challenges activate subcortical and brainstem regions that regulate emotions and physiological homeostasis. However, cortical regions are also engaged during peripheral inflammation, and cortical dysfunction is a central feature of affective pathology. Drawing primarily on mechanistic work in rodents, we review how peripheral inflammation reaches the cortical circuits that govern emotion and how it is translated into affective changes. This communication begins with two complementary routes by which immune signals reach the brain: neural and humoral pathways. In the neural pathway, cytokine-selective vagal afferents preserve the anatomical origin of inflammation and relay it to the brainstem and downstream regions. In the humoral pathway, circulating mediators act on circumventricular organs and across the blood-brain barrier. Cortical regions, such as the prefrontal cortex, insular cortex, and primary somatosensory cortex, transform these signals into altered behavior. This occurs through shifts in excitatory/inhibitory balance, top-down control of the amygdala, and interoceptive predictions of bodily state. We integrate these studies into a circuit-level model in which inflammation biases cortical processing toward threat, driving the transition from adaptive responses to maladaptive affective dysregulation. Defining which immune signals engage which circuits, and with what specificity, remains a central open question and a promising route toward targeting the affective consequences of inflammatory disease.
Parkinson's disease (PD) is the second most common neurodegenerative disorder and is characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc), leading to dopamine deficiency and motor dysfunction. Clustered regularly interspaced palindromic repeats (CRISPR)-based technologies provide a potential approach for targeted gene modulation, although their effectiveness and safety in cellular models of PD remain to be established. This study investigated the feasibility and transcriptional effects of CRISPR activation (CRISPRa) targeting Dopa decarboxylase (DDC) and GTP cyclohydrolase 1 (GCH1) in human embryonic kidney (HEK293) cells and a 6-hydroxydopamine (6-OHDA)-induced neurotoxicity model using human neuroblastoma (SH-SY5Y) cells. Parkinsonian-like toxicity was induced in SH-SY5Y cells with 6-OHDA prior to CRISPRa transfection. A vector-free CRISPRa system was used to target DDC and GCH1, with single-guide RNAs (sgRNAs) assembled with dCas9-VP64 and MS2-p65-HSF1 (MPH) to form ribonucleoprotein (RNP) complexes and delivered using Lipofectamine 3000. CRISPRa targeting of DDC was associated with increased DDC expression in SH-SY5Y cells relative to untreated controls at 24 h (p = 0.0496) and 48 h (p = 0.0064). However, expression levels did not differ significantly from those observed in the 6-OHDA-treated PD control group. In contrast, GCH1 expression was not significantly altered following CRISPRa. CRISPRa also had no significant effect on cell viability in HEK293 cells. In SH-SY5Y cells, 6-OHDA significantly reduced cell viability compared with untreated controls (p = 0.0129). Similar reductions were observed in DDC -targeted cells at 24 h (p = 0.0026) and 48 h (p = 0.0017), and in GCH1 -targeted cells at 24 h (p = 0.0017) and 48 h (p = 0.0008); however, none of the CRISPRa-treated groups differed significantly from the 6-OHDA-treated PD control. These findings indicate that CRISPRa elicited a modest transcriptional response, characterized by upregulation of DDC without detectable modulation of GCH1, and did not exacerbate 6-OHDA-induced cytotoxicity. Further optimisation, together with protein-level, enzymatic activity, and dopamine measurements, is required to determine whether these transcriptional changes translate into functional effects on dopamine biosynthesis.
