Ketamine’s possible targets and actions in combined stroke and depression studied using network and bioinformatics analysis

Stroke is the second leading cause of death worldwide and a major contributor to disability, imposing a substantial burden on families and society [1]. Post-stroke complications are common and include motor and physical impairments as well as neuropsychiatric conditions such as anhedonia, depression, mania, and other psychological disorders [2,3]. Post-stroke depression (PSD) is a frequent and debilitating sequela of acute stroke, characterized by anxiety, anhedonia, social dysfunction, and hopelessness [4]. Approximately one-third of stroke survivors are diagnosed with depression within 5 years [5,6], and symptoms often persist for at least 1 year [7]. Depression following stroke severely hampers post-stroke recovery [8], particularly of cognitive and motor functions, and negatively impacts the quality of life [9,10]. The co-occurrence of depression and stroke is thus a major clinical challenge, and early identification and intervention are essential for patient rehabilitation [11].

The pathogenesis of comorbid depression and stroke remains incompletely understood but is believed to involve a complex interplay of psychosocial factors, genetic predisposition, biological mechanisms, and neural circuitry changes [8,12]. Studies have indicated associations with alterations in the expression of brain-derived neurotrophic factor (BDNF) and its receptor TrkB, which are crucial for neuronal development and synaptic plasticity regulation. Post-stroke dysfunctions in BDNF expression may disrupt neurotransmitter balance, impair neural signal transduction, and promote depressive symptoms [13]. Additionally, binding of the BDNF precursor (proBDNF) to the p75NTR receptor can activate the RhoA–JNK signaling pathway, inducing apoptosis-related protein expression, which has been implicated in neuronal loss and impaired plasticity and may contribute to post-stroke neuropsychiatric sequelae [10]. In a hemorrhagic mouse model, structural and functional abnormalities in the frontal lobe circuitry and JAK–STAT signaling pathway dysregulation were associated with depressive-like behaviors; thus, targeting this pathway may reduce severity and provide therapeutic effects [8]. Qinlin et al. [7] suggested that hippocampal damage after stroke may involve multiple signaling pathways and increased expression of autophagy-related genes, based on differential gene analysis in a rodent model. Primary cortical ischemia may induce secondary hippocampal damage, upregulating miR34b-3p expression in neurons, suppressing eIF4E, impairing neurotransmitter-related protein synthesis, damaging neuroplasticity, and inducing neuronal apoptosis, potentially leading to depressive outcomes [11]. Collectively, these findings suggest that the pathophysiology linking stroke and depression involves neurotransmitter imbalances, neural circuit alterations, synaptic plasticity impairments, and neuroinflammation.

Current antidepressant treatments for depression in stroke survivors have limitations, including delayed onset of action and potential adverse effects on the nervous and cardiovascular systems [14,15]. Selective serotonin reuptake inhibitors (SSRIs), a common first-line treatment, typically require weeks to take effect [16,17]. Furthermore, approximately 50% of patients experience partial relief and 30% achieve symptom remission with SSRIs [2]. However, SSRIs have been associated with increased bleeding risk and, in some studies, cardiovascular events. A clinical study reported that early administration of escitalopram for post-stroke depressive symptoms did not reduce the number of patients with moderate to severe symptoms but increased that of patients with no or mild symptoms [18]. Another study reported that administering fluoxetine (20 mg/day) for 6 months after acute stroke reduced the incidence of depression but failed to improve neurological outcomes and increased fracture frequency [3,19]. These limitations underscore the need for novel therapeutic approaches with different mechanisms of action.

Ketamine, an N-methyl-D-aspartate receptor (NMDAR) antagonist, has demonstrated rapid and sustained antidepressant effects in major depressive disorder [3,20,21]. It directly modulates glutamatergic and GABAergic neurotransmission [22]. Its rapid antidepressant action may involve NMDAR inhibition on GABAergic interneurons, leading to the transient disinhibition of glutamatergic pyramidal neurons and increased glutamate release in regions such as the prefrontal cortex (PFC) and hippocampus. This, in turn, activates AMPA receptors (AMPAR), triggers signaling cascades such as BDNF–TrkB–ERK and PI3–AKT–mTOR, and may enhance synaptogenesis and synaptic plasticity [23]. Concurrently, NMDAR blockade by ketamine can deactivate eEF2K, reducing eEF2 phosphorylation and increasing BDNF translation. BDNF signaling appears critical, as disruption of BDNF–TrkB signaling in the medial PFC abolishes ketamine’s antidepressant effects [24]. Furthermore, ketamine has been reported to interact with μ, κ, and δ opioid receptors, potentially contributing to its effects in treatment-resistant depression (TRD) [25]. Its sustained effects may involve the promotion of synaptic plasticity [23]. In a rat model combining middle cerebral artery occlusion and chronic unpredictable mild stress, ketamine induced rapid and persistent antidepressant-like effects, potentially by regulating the NMDAR–CaMKII signaling pathway to promote synaptic plasticity [3]. Despite this promising profile, the molecular targets and pathways through which ketamine might exert effects in the specific context of comorbid ischemic stroke and depression remain largely unexplored.

Network pharmacology, an emerging field, shifts the focus from single- to multi-target approaches by integrating systems biology and computational analysis. It encompasses drug and disease target identification, protein–protein interaction (PPI) network analysis, key gene screening, and functional enrichment studies, and has been increasingly applied to investigate the mechanisms of drug action [26]. Therefore, in this study, we aimed to employ a network pharmacology approach to hypothesize potential molecular targets and pathways of ketamine relevant to both ischemic stroke and depression. By integrating public high-throughput sequencing data with computational analyses, we sought to generate a testable framework for understanding ketamine’s putative role in this complex comorbidity, which may inform future experimental and clinical research.

Depressive symptoms following stroke represent a common neuropsychiatric complication, often manifesting as anxiety, low mood, insomnia, and even suicidal ideation, affecting approximately one-third of stroke survivors [42]. This comorbidity significantly increases disability, recurrence, and mortality rates, emerging as an independent risk factor for poor prognosis. Nonetheless, safe and effective therapeutic agents specifically tailored for this condition are lacking [43,44]. In our clinical practice, we have observed the significant challenge posed by post-stroke depressive symptoms, which underscores the urgent need to investigate the underlying mechanisms of the ischemic stroke–depression comorbidity and explore novel treatments. Ketamine has garnered attention in this context owing to its unique pharmacological profile.

Recently, ketamine has been widely studied for treating TRD and patients with suicidal ideation owing to its rapid and sustained antidepressant effects, demonstrating marked superiority over conventional antidepressants in alleviating core depressive symptoms [23]. A single administration promotes the release of BDNF, activates the mTORC1 signaling pathway, increases synaptic protein levels, and enhances the number and function of synapses in the PFC, thereby rapidly reversing deficits in neuroplasticity [45]. Ketamine also exerts neuroprotective effects [46] by mitigating excitatory amino acid neurotoxicity via NMDAR blockade and by modulating the production and release of inflammatory factors, thereby reducing neuroinflammation. Furthermore, ketamine may improve post-injury cerebral hemodynamics by modulating vascular tone, enhancing regional cerebral blood flow, optimizing cerebral oxygen metabolism, and reducing ischemic–hypoxic brain damage [47]. However, despite these promising broad mechanisms, a systematic understanding of ketamine’s molecular targets and pathways in the specific context of comorbid ischemic stroke and depression remains largely elusive. Therefore, we employed a network pharmacology approach to explore and hypothesize potential targets of ketamine relevant to both conditions, aiming to generate novel strategic insights for future therapeutic development.

Intersecting predicted ketamine target genes with DEGs from ischemic stroke and major depressive disorder datasets yielded 42 intersection genes. KEGG and GO enrichment analyses suggested that these genes are potentially involved in pathways such as “Lipid and Atherosclerosis,” “IL-17 Signaling Pathway,” “Apoptosis,” “Response to Ketone,” “Response to Starvation,” and “Response to Oxygen Levels.” This implies that ketamine’s putative therapeutic effects might involve modulating lipid metabolism, inhibiting apoptosis, enhancing neuronal tolerance to ischemia and hypoxia, and maintaining immune homeostasis via suppression of the IL-17 signaling pathway. Subsequently, to interpret and rank the relative importance of these hub genes, SHAP-based interpretability analysis was performed. This approach does not aim to build diagnostic classifiers but to quantify each gene’s contribution to the model’s output, thereby identifying the most influential features. IL1RN and DDIT3 were prioritized as the top candidate biomarkers based on their consistently dysregulated expression patterns and robust discriminatory capacity in independent validation cohorts. To elucidate their potential functional roles, single-gene GSEA was performed. In the context of ischemic stroke, DDIT3 may be associated with immunity and inflammation via the Toll-like receptor signaling pathway, whereas both DDIT3 and IL1RN might be linked to neuronal survival and synaptic plasticity through the neurotrophin signaling pathway. In the depression dataset, DDIT3 may influence apoptosis and inflammation through ubiquitin-mediated proteolysis, oxidative phosphorylation, and ribosome pathway, whereas IL1RN could be involved in immune regulation via Fc gamma R-mediated phagocytosis.

IL1RN is an immunomodulatory molecule [48] that acts as an endogenous IL-1 receptor antagonist (IL-1Ra) [49], competitively binds IL-1R to inhibit signaling by IL-1α and IL-1β, thereby exerting anti-inflammatory effects. IL-1Ra suppresses proinflammatory cytokine production, potentially reducing tissue damage and maintaining immune balance [50]. Studies have reported increased IL1RN expression in post-stroke plasma [51], with plasma IL-1Ra serving as an independent predictor of post-stroke infection and conferring neuroprotection; administration of IL-1Ra has been shown to improve stroke outcomes in models [52]. Given that post-stroke depressive symptoms are frequently accompanied by neuroinflammation, our analysis leads us to hypothesize that ketamine might modulate IL1RN expression or its pathway, thereby suppressing IL-1β-mediated inflammation, mitigating neuroinflammation, and contributing to neural protection.

DDIT3 (CHOP) is a key regulator of endoplasmic reticulum (ER) stress, activated by DNA damage, hypoxia, and nutrient deprivation, and it modulates cell fate decisions including apoptosis. During ER stress, DDIT3 can promote apoptosis via the PERK–eIF2α–ATF4–DDIT3 pathway [53], activating BH3-only protein B-cell lymphoma 2 (BCL-2) interacting mediator of cell death (BCL2L11/BIM) and suppressing activity of anti-apoptotic protein BCL-2 [54]. Located in the nucleus and mitochondria, nuclear DDIT3 enhances glycolysis by inhibiting the negative regulator TIGAR, whereas mitochondrial DDIT3 downregulates COQ9 and COX4 to attenuate mitochondrial aerobic respiration. Thus, under hypoxic and nutrient-deficient conditions, DDIT3 maintains the energy balance by promoting glycolysis and suppressing mitochondrial oxidative phosphorylation, preventing the accumulation of harmful reactive oxygen species [55]. Additionally, ER stress mediates mitochondrial autophagy via the ATF4–DDIT3–TRIB3–AKT–mTOR pathway [56]. Therefore, we speculate that ketamine might influence DDIT3 expression or activity, potentially inhibiting apoptosis, maintaining metabolic balance, and modulating mitochondrial autophagy, collectively contributing to nervous system protection in the comorbid condition.

Immune dysregulation is implicated in both ischemic stroke and depression [57]. Our exploratory immune infiltration analysis revealed differences in immune cell proportions between disease and control samples. In ischemic stroke samples, increased infiltration of M0 macrophages, neutrophils, memory activated CD4⁺ T cells, and gamma delta T cells was observed. In depression samples, increased proportions of M2 macrophages and neutrophils were noted. Correlations were found between IL1RN and DDIT3 expression and specific immune cell types. After ischemic stroke, activated M0 macrophages effectively clear necrotic neurons from infarcted regions, reducing neuroinflammation and aiding neural recovery [58]. Post-stroke neutrophils exacerbate neuroinflammation through multiple mechanisms, including disruption of the blood–brain barrier, activation of the complement system, and release of inflammatory mediators, further inducing neuronal apoptosis or necrosis [59]. Memory activated CD4⁺ T cells migrate to brain injury sites, regulating immune responses via cytokine secretion [60]. Gamma delta T cells exhibit a dual nature in the nervous system by secreting cytokines that promote neuronal survival, growth, and differentiation, mitigate neuroinflammation, regulate the activity of other immune cells, and enhance blood–brain barrier stability to protect neural function. However, under certain pathological conditions, their excessive activation may provoke intense inflammation and autoimmune responses, aggravating secondary damage [61]. Post-stroke, activated dendritic cells rapidly migrate to the injured brain, participating in local inflammatory responses [62]. Moreover, type 2 dendritic cells induce IL-17 production by gamma delta T cells, further promoting neutrophil infiltration [60]. Meanwhile, in depression, M2 macrophages exert anti-inflammatory and neuroprotective effects by secreting cytokines such as IL-10, facilitating neural repair [63]. Neutrophils may contribute to depression onset by enhancing neuroinflammation, with studies reporting increased numbers and increased neutrophil activity in the peripheral blood and cerebrospinal fluid of patients with depression, correlating with chronic inflammation [64].

Molecular docking simulations suggested potential binding interactions between ketamine and the proteins IL1RN and DDIT3, with varying affinities. IL1RN exhibited the highest affinity, suggesting it may play a critical role in the efficacy of ketamine in PSD treatment. Collectively, our integrated network pharmacology analysis provides a hypothetical framework suggesting that the putative effects of ketamine in the context of ischemic stroke–depression comorbidity may involve modulating immune responses, reducing oxidative stress, inhibiting neuronal apoptosis, and regulating cellular metabolism.

Despite these insights, this study has some limitations that must be acknowledged. First, the analysis relies on public databases and computational predictions, which may not fully capture the complexity and dynamics of the disease state or drug action. The integrated set of ‘ketamine targets’ in this study was derived from public databases and encompasses associations ranging from direct binding targets to downstream regulatory genes. Although this broad strategy facilitates exploratory network analysis, the intersecting core genes should be interpreted as putative ketamine targets rather than definitive direct binding targets. Future experimental validation, including studies in relevant preclinical models and ultimately in clinical cohorts, is essential to confirm the roles of IL1RN, DDIT3, and the associated pathways. Second, the absence of in vitro or in vivo experimental data in this study confines it to the theoretical and hypothesis-generating level. Our hospital-based clinical setting provides a foundation for future translational research aimed at validating these candidate biomarkers in well-characterized patient cohorts. Finally, network pharmacology approaches are currently ill-equipped to assess critical pharmacological parameters such as dose–response relationships or long-term safety. Prolonged ketamine use may carry risks such as transient psychiatric symptoms, cognitive side effects, hemodynamic fluctuations, and dependency/abuse potential, necessitating careful clinical evaluation. The ultimate translation of these findings into clinical practice will require rigorous safety and efficacy trials in the target patient population.

In conclusion, this study employed an integrated network pharmacology approach to explore the potential molecular mechanisms and candidate targets through which ketamine might exert effects in the context of comorbid ischemic stroke and depression. Our in silico analyses highlight IL1RN and DDIT3 as central candidate genes worthy of further investigation. We hypothesize that ketamine’s putative therapeutic actions may involve the modulation of multiple pathways—including IL-17 signaling, apoptosis, and cellular stress responses—potentially contributing to the suppression of neuroinflammation and apoptosis, enhancement of neuronal resilience, and maintenance of immune and metabolic homeostasis. These computational findings offer a novel, hypothesis-generating perspective on the pharmacological mechanisms of ketamine relevant to post-stroke neuropsychiatric sequelae. However, it is crucial to emphasize that these insights are derived from bioinformatic predictions and require rigorous validation. Future research should focus on experimental confirmation of these targets and pathways in relevant biological models, followed by clinical translation studies to assess their therapeutic relevance and safety in patient populations. This work provides a foundational framework for guiding such future investigations towards the development of more targeted therapeutic strategies.