Migraine may involve neuroimmune-related mechanisms, but migraine-associated peripheral immune-cell states remain incompletely defined. We aimed to characterize peripheral blood immune remodeling in migraine at single-cell resolution. We reanalyzed PBMC single-cell RNA-sequencing dataset GSE269117, using migraine and vestibular migraine samples as the migraine group and healthy controls as controls. After quality control, we performed major immune-cell annotation, CD4 T-cell subclustering, pseudobulk differential-expression analysis, pathway enrichment, pseudotime reconstruction, CellChat-based communication analysis, transcription-factor activity inference and AL589693.1-focused state analysis. A total of 31,514 PBMCs from 15 retained biological samples were analyzed and annotated into six major immune-cell populations. Major lineage proportions showed no broad sample-level differences between groups, whereas sample-level analysis of 7,647 CD4 T cells indicated a redistribution of CD4 T-cell states. At the sample level, migraine samples showed enrichment of non-cytotoxic-like CD4 T cells and depletion of cytotoxic-like CD4 T cells compared with controls. CD4 pseudobulk and enrichment analyses highlighted inflammatory, estrogen-response, calcium-responsive and cAMP-related programs, with relative depletion of oxidative phosphorylation, MYC targets and translation-related pathways. Pseudotime analysis supported a shift toward earlier or less cytotoxic CD4 states. CellChat inferred fewer total interactions in migraine than in controls, especially cytotoxic-like CD4-related interactions. AL589693.1 emerged as a migraine-associated transcript, and its no-self signature marked a non-cytotoxic-skewed CD4 state that partially contributed to the CD4 imbalance. Peripheral CD4 T-cell state remodeling may represent an important feature of migraine-associated immune alterations, with AL589693.1-positive CD4 states as candidate markers for future validation.
Acute ischemic stroke is a major cause of death and disability, and post-stroke cognitive impairment remains a major clinical challenge. Cardioembolic stroke (CES), often associated with atrial fibrillation, is closely linked to cognitive decline. Increasing evidence suggests that vascular dysfunction contributes to both vascular cognitive impairment and Alzheimer’s disease (AD), but the shared molecular basis remains unclear. This study aimed to identify shared molecular signatures and candidate biomarkers linking CES and AD. Gene expression datasets were obtained from the Gene Expression Omnibus database. Differentially expressed genes were identified using limma, and disease-related gene modules were constructed using weighted gene co-expression network analysis. Functional enrichment analyses were performed to explore shared pathways. Three machine learning algorithms—LASSO, SVM-RFE, and random forest—were used to prioritize candidate genes. Receiver operating characteristic analysis, nomogram modeling, single-gene gene set enrichment analysis, and external validation were performed to evaluate the potential relevance of the identified gene. Seven overlapping genes were identified between CES and AD. Among them, SCRIB was consistently selected by the integrated feature-selection workflow and showed moderate diagnostic performance in both internal datasets. Supportive validation was observed in an independent AD dataset and in an atrial fibrillation-related surrogate validation cohort. SCRIB may represent a shared transcriptomic biomarker candidate linking CES and AD. These findings provide preliminary transcriptomic evidence for a potential molecular link between cerebrovascular pathology and neurodegeneration, but further mechanistic and clinical validation is required.
Background: The pathogenesis of ischemic stroke (IS) involves a starvation response (SR); however, the mechanistic link between the two remains unclear. Therefore, it is imperative to identify SR-related gene (SRRG) biomarkers involved in IS. Methods: IS datasets were obtained from the Gene Expression Omnibus, and SRRGs were acquired from the Molecular Signatures Database. Biomarkers were screened using differential expression analysis, machine learning, and expression validation. Subsequent analyses included immune infiltration, gene set enrichment analysis (GSEA), drug prediction, and single‑cell RNA sequencing (scRNA‑seq). The middle cerebral artery occlusion mouse model and oxygen-glucose deprivation/reoxygenation (OGD/R)-treated BV2 cells were used. PAK2/Iba1 co-expression was assessed using immunofluorescence double-staining. The effects of PAK2 knockdown on cell proliferation, apoptosis, and inflammation were assessed using functional assays. Results: Two biomarkers, PAK2 and lysosome-associated membrane protein 2 (LAMP2), were identified and used to construct a diagnostic model that demonstrated good performance. Immune infiltration analysis revealed changes in 33 immune cell types. GSEA revealed that biomarker‑related genes were enriched in different pathways, including NOD‑like receptor and T‑cell receptor signaling pathways. Drug prediction analysis identified 48 potential agents targeting PAK2 and 35 agents targeting LAMP2. Microglia were identified as a key cell subtype using scRNA‑seq analysis. PAK2 mRNA was significantly upregulated, and LAMP2 mRNA was downregulated in mouse ischemic penumbra; immunofluorescence confirmed PAK2/Iba1 co-localization. In vitro, PAK2 knockdown suppressed apoptosis, promoted proliferation, and reduced inflammatory cytokine levels in OGD/R-injured BV2 cells. Conclusion: In this study, two SR‑derived biomarkers were identified for IS, and a diagnostic model was established, providing new insights into IS diagnosis and therapeutic development.
Historically the development of amyloid-β plaques and tau neurofibrillary tangles have been used as the hallmarks of Alzheimer’s disease (AD). However, there is increasing evidence suggests that these pathological hallmarks are secondary to deeper metabolic defect in the brain. AD is progressively being recognized as a metabolic synaptic disorder characterized by insulin resistance, impaired cellular energy homeostasis, mitochondrial dysfunction, and synaptic degeneration. Synaptic plasticity is closely linked to the insulin-sensitive system of glucose utilization, mitochondrial activity, and local protein synthesis that render the synapses highly sensitive to the malfunction of the metabolic system. Recent discoveries highlight the important role of exosomes in mediating communication between neural cells by transferring regulatory miRNAs across neuronal networks. Exosomal miRNAs regulate insulin signaling, synaptic gene expression, mitochondrial function, and neuroinflammation. In AD, exosomal miRNA profiles are significantly altered, with enrichment of miR-29, miR-34a, miR-146a, and miR-21, alongside depletion of synapse-supporting miR-132. These changes contribute to insulin resistance, impaired glucose transporter trafficking, dendritic spine destabilization, and reduced expression of synaptic proteins such as PSD-95 and synaptophysin, ultimately leading to cognitive decline. Importantly, neuron-derived exosomes can cross the blood–brain barrier, making their miRNA cargo promising biomarkers and therapeutic targets for early AD diagnosis and precision treatment.
Graphical abstract illustrates Alzheimer’s disease as a disorder of corrupted exosome-mediated metabolic communication.
Developmental exposure to zinc/paraquat (Zn/PQ) increases susceptibility to dopaminergic neurodegeneration caused by adulthood exposure to Zn/PQ in rodents through augmented oxidative stress and inflammation. The current study delved into the consequences of developmental Zn/PQ exposure on the mechanism of neuronal apoptosis induced by Zn/PQ exposure in adult animals. Postnatal Zn/PQ exposure augmented the loss of dopaminergic neurons and mitochondrial reactive oxygen species production in animals that received Zn/PQ re-exposure at adult stage. A more pronounced decline was observed in mitochondrial complex I/III activity and membrane potential in animals that encountered both postnatal and adult stage exposures to Zn/PQ than in the animals exposed during adult stage only. Developmental Zn/PQ exposure noticeably enhanced apoptotic neuronal cell death in the animals who received adulthood re-exposure, as evident by the higher mitochondrial cytochrome c efflux into cytosol and reduction in procaspase-3 levels compared to the animals that encountered with Zn/PQ during adulthood alone. Whilst Zn exposure during adulthood pointed towards activation of Bax-mediated apoptotic cell death, exposure to PQ at adult stage suggested involvement of Bak-mediated apoptotic cell death irrespective of developmental exposure to PQ or Zn. The study indicated that early life exposure renders the dopaminergic neurons more susceptible to Zn/PQ-induced mitochondria-mediated apoptotic neuronal cell death following subsequent toxic insult in adult life. However, final apoptotic disposal pathway for dopaminergic neurons seems to be directed by the toxic insult encountered in adulthood.
Major depressive disorder (MDD) constitutes a substantial global health burden; however, the causal genes and cell-type-specific mechanisms underlying its pathogenesis remain incompletely understood. We conducted an integrative transcriptomic and proteomic Mendelian randomization (MR) study incorporating expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets to prioritize genes associated with MDD. Candidate genes were further evaluated using neuron-specific single-cell eQTL analyses across multiple brain cell types, and brain imaging–derived phenotypes were assessed as exploratory structural mediators through two-step MR mediation analysis. Integrative eQTL-MR and pQTL-MR analyses identified 20 genes associated with MDD at both transcriptomic and proteomic levels. Notably, CKAP2 showed directionally discordant associations across molecular layers: genetically predicted CNS-related CKAP2 expression was inversely associated with MDD risk, whereas genetically predicted plasma CKAP2 protein levels showed an association in the opposite direction. Rather than establishing a unified causal mechanism across transcriptomic and proteomic layers, this discordance suggests that CKAP2-related genetic signals may differ across tissues, molecular layers, or instrument constructions. Single-cell eQTL analyses provided supportive evidence for a protective-direction association of CKAP2 expression in excitatory neurons (OR = 0.986, p = 0.007), inhibitory neurons (OR = 0.990, p = 0.007), and oligodendrocyte precursor cells (OR = 0.987, p = 0.009). Mediation analysis suggested that right thalamic ventral anterior nucleus volume may represent an exploratory imaging phenotype related to the CKAP2–MDD association, accounting for 17.0% of the total effect, although this finding requires independent replication. Sensitivity analyses provided no evidence of heterogeneity or horizontal pleiotropy, and reverse MR analyses showed no evidence of reverse causation, although these analyses were limited in statistical power. Collectively, these findings prioritize CKAP2 as a candidate gene with convergent but non-confirmatory genetic evidence for involvement in MDD, warranting further validation in independent causal and experimental frameworks.
Extracellular ATP is a central danger signal linking cellular stress to neuroinflammation, yet the mechanisms governing the transition from physiological purinergic signaling to pathological neuroimmune activation remain incompletely understood. In this review, we integrate current evidence into a conceptual framework describing how ATP-dependent purinergic signaling may contribute to the shift from adaptive neuron–glia communication to maladaptive glial crosstalk and inflammatory amplification. Under physiological conditions, controlled ATP turnover primarily engages lower-threshold purinergic pathways, including P2X4-mediated signaling that supports microglial surveillance, synaptic remodeling, and tissue homeostasis. In contrast, sustained extracellular ATP accumulation during injury, oxidative stress, or impaired ATP clearance preferentially recruits the low-affinity P2X7 receptor, triggering ionic dysregulation, Ca²⁺ influx, and redox-sensitive signaling pathways that promote NF-κB activation and NLRP3 inflammasome assembly. We further examine how receptor crosstalk, particularly with TLR4 and emerging redox regulatory mechanisms involving protein disulfide isomerase (PDI), may influence P2X7 signaling across different neuroinflammatory contexts. Finally, we discuss current evidence for therapeutic targeting of P2X7, highlighting translational challenges related to blood–brain barrier penetration, receptor occupancy, disease stage, and patient selection. By integrating recent advances in purinergic, redox, and neuroimmune signaling, this review provides a heuristic framework for understanding context-dependent P2X7 activation while distinguishing established mechanisms from emerging concepts that require further experimental validation.
Freezing of gait (FOG) is a disabling complication of Parkinson’s disease (PD), but peripheral associations remain poorly defined. C-terminal agrin fragment-22 (CAF22) is a circulating biomarker of neuromuscular junction degradation. We investigated whether baseline plasma CAF22 predicts the development of FOG in PD patients. In this prospective cohort study, 233 patients with idiopathic PD and no baseline FOG were followed for 24 months with assessments at 6-month intervals. Incident FOG was identified using the New Freezing of Gait Questionnaire. Cox proportional hazards models assessed associations between CAF22 and time to first FOG, adjusting for age, sex, disease duration, motor severity, gait speed, muscle strength, cognitive performance, and levodopa-equivalent daily dose. During follow-up, 55 participants (23.6%) developed incident FOG. Higher baseline plasma CAF22 was associated with an increased risk of FOG per standard deviation increase (HR 1.4, 95% CI 1.09–1.81). This association remained significant after multivariate adjustment (adjusted HR 1.37, 95% CI 1.03–1.82). Baseline CAF22 concentrations were higher in participants with greater motor severity and slower gait speed, but showed weaker associations with global cognitive performance. Faster gait speed was independently protective against FOG (HR 0.64, 95% CI 0.52–0.78). Kaplan–Meier analyses demonstrated progressively lower FOG-free survival across increasing CAF22 tertiles (log-rank p = 0.046). Elevated baseline plasma CAF22 independently predicts incident FOG in PD. CAF22 may reflect peripheral neuromuscular dysfunction and could serve as a biomarker of FOG risk.
Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by widespread dysregulation of gene expression and regulatory pathways. MicroRNAs (miRNAs) act as key post-transcriptional regulators by modulating messenger RNAs (mRNAs), and their disruption can influence synaptic function, neuroinflammation, and neuronal survival. In this study, we present a transcriptomic-driven framework in which differentially expressed genes (DEGs) are identified from gene expression data and integrated with curated miRNA–target interaction databases to infer putative AD-associated miRNA–mRNA regulatory signatures and potential candidate biomarkers. Transcriptomic and clinical data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and the GEO dataset GSE48552 was used as supplementary support to assess the consistency of observed transcriptomic patterns. Using an exploratory differential expression threshold with Welch’s t-test and FDR correction, 123 candidate dysregulated genes (34 up-regulated, 89 down-regulated) were identified between AD and cognitively normal controls. To further assess robustness, threshold-sensitivity and cross-method concordance analyses were conducted, supporting the presence of a reproducible core transcriptional signal within the broader discovery-level DEG set. Experimentally validated and predicted miRNA–target interactions were integrated using miRTarBase, yielding 1,669,089 miRNA–gene interactions involving 3,055 unique miRNAs, with strong enrichment toward down-regulated gene targeting. Functional enrichment analysis revealed convergence of miRNA-regulated genes on synaptic signaling, neuronal communication, intracellular transport, apoptosis, oxidative stress, and PI3K–Akt/MAPK-related pathways. A bipartite putative miRNA–mRNA regulatory network (2,207 nodes connected by 11,437 edges, including 2,104 miRNAs and 103 significant genes) was constructed and analyzed using centrality metrics, prioritizing candidate hub genes, including PBX1 and KREMEN1, which were subsequently interpreted in the context of neuronal transcriptional regulation, Wnt-related signalling, synaptic vulnerability, and AD-associated pathway enrichment. Finally, supervised machine learning models trained on selected molecular features showed discriminative performance in the held-out test set, with Random Forest, Gradient Boosting, and LightGBM achieving the highest ROC–AUC values, indicating strong capability in distinguishing AD from control samples. Overall, the framework provides a biologically interpretable strategy for biomarker discovery, prioritizing AD-associated candidate biomarkers and putative regulatory interactions while highlighting targets for future experimental and clinical validation.
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