Journal of Molecular Neuroscience最新文献

This work examined the causal link between palmitoylation-related genes and Parkinson’s disease (PD) by Mendelian randomization (MR). We conducted two-sample Mendelian randomization utilizing genome-wide association study (GWAS) summary statistics. Expression quantitative trait loci (eQTL) data for palmitoylation genes were sourced from eQTLGen, whilst PD data were derived from the GWAS Catalogue (15,056 cases, 12,637 controls) and FinnGen (4,681 cases, 407,500 controls). Instrumental variables (p < 5 × 10⁻⁶, r² < 0.1) were examined using inverse-variance weighted (IVW) regression, along with weighted median, MR-Egger, and Summary-data-based MR (SMR) methods. Sensitivity analyses evaluated pleiotropy and resilience. The IVW analysis revealed significant correlations with Parkinson’s disease for ZDHHC14 (OR = 1.09, P = 0.037), ZDHHC17 (OR = 1.18, P = 0.002), ZDHHC2 (OR = 1.16, P = 0.039), ZDHHC20 (OR = 0.82, P = 0.019), and ZDHHC8 (OR = 1.24, P = 0.022). SMR validation corroborated solely ZDHHC8 (OR = 1.35, P = 0.040). Replication in FinnGen corroborated ZDHHC1, ZDHHC13, ZDHHC17, and ZDHHC8. No heterogeneity or pleiotropy was observed (P > 0.05). ZDHHC8 has a strong causative relationship with PD, suggesting that palmitoylation dysregulation plays a role in disease etiology. These findings underscore synaptic dysfunction as a viable therapeutic target.

By analyzing genetic polymorphisms in the genes of patients and control subjects, it is possible to find the correlation of these factors with the phenotypic variation as mental disorders to propose hypotheses about the possible mechanisms of specific diseases. Accordingly, in the present study, the role of oxytocin receptor and dopamine D2 receptor polymorphisms in the personality traits of optimistic, pessimistic and intermediate individuals was investigated. In this study, the polymorphism of DRD2 receptors and oxytocin receptor genes in saliva samples of Iranian volunteers was investigated. Accordingly, saliva samples were prepared from 90 individuals. The mental status of these individuals (optimistic, pessimistic and intermediate) was determined by a specialist physician. Then, the DNA of the sample was extracted and the presence or absence of the rs53576 polymorphism in the OXTR gene and the rs1800497 polymorphism in the DRD2 gene was examined using PCR reaction and sequencing. The results showed a significant association between the frequency of the rs53576 polymorphism in the OXTR gene and pessimism. In fact, the A allele in this polymorphism caused a 2.4-fold increase in pessimism in the studied individuals. However, no significant association was observed between the rs1800497 polymorphism and the traits of optimism and pessimism. Such studies require more detailed assessments such as brain scans, but due to the high cost of such tests, genetic studies can be used as the first step to confirm or reject the association of the polymorphism with the aforementioned trait.

This work sought to examine the causal link between palmoyl-protein-modifying genes (ZDHHC family) and epilepsy by Mendelian randomisation (MR), utilising multi-level genomic data. A two-sample MR analysis was performed utilising publicly accessible blood and brain tissue expression quantitative trait locus (eQTL) data as exposure variables and epilepsy genome-wide association study (GWAS) data from the FinnGen as the outcome measure. The major analysis method utilised was inverse variance weighting (IVW), with robustness validation conducted by weighted median and MR-Egger procedures. Subsequently, summary-data-based MR (SMR) analysis confirmed signal colocalization, supplemented by single-cell transcriptomic data (GSE302285) to investigate target gene expression patterns at a cellular granularity. MR analysis indicated that heightened expression of ZDHHC3 (OR = 0.69, 95% CI: 0.57–0.84, p = 0.0002) and ZDHHC20 (OR = 0.88, 95% CI: 0.82–0.94, p = 0.0002) was significantly linked to a decreased risk of epilepsy, while increased expression of ZDHHC8 and ZDHHC18 was associated with an elevated risk. SMR analysis further corroborated the protective roles of ZDHHC3 and ZDHHC20. Layered MR analysis showed that the results are more significant in focal epilepsy. An eQTL study specific to brain cells revealed cell-type specificity in these correlations, with ZDHHC20 demonstrating the most significant protective impact in excitatory neurones (OR = 0.89, p = 0.0273). Single-cell transcriptomics demonstrated that ZDHHC20 was significantly expressed in astrocytes and neurones in the brain tissue of epilepsy patients, while ZDHHC3 was primarily concentrated in neurones. This work genetically confirms that certain palmitoylation genes, notably ZDHHC3 and ZDHHC20, may have causative protective effects against the risk of focal epilepsy, highlighting cell-type-specific processes. This establishes innovative theoretical frameworks for exploring the pathophysiology of epilepsy and formulating targeted treatments.

Emerging data highlight oligodendrocyte dysfunction and myelin degeneration as early contributors to the pathology of Alzheimer’s disease (AD), questioning the conventional neuron-focused amyloid-tau model. This comprehensive review recapitulates both clinical and preclinical data linking oligodendrocytes (OLs) and oligodendrocyte precursor cells (OPCs) to amyloid-β secretion, accelerated cellular ageing, and loss of metabolic and trophic support. Simultaneously, microglial activation and neuroinflammation exacerbate damage to myelin and impair remyelination. High-field imaging technologies are associated with white matter pathology that is evident decades before the onset of cortical atrophy, highlighting the pathogenic importance of glial pathology. We discuss pharmacological strategies to correct OL dysfunction by drug repurposing: first-generation H₁-antihistamine clemastine, which induces OPC maturation by M₁ muscarinic antagonism and ERK/mTOR signalling; H₃-receptor antagonists/inverse agonists (e.g. pitolisant) increase neurotransmitter release and induce CREB-mediated remyelination; and serotonergic GPCR agonists (5-HT₄, 5-HT₆, 5-HT_2C) shift APP processing toward non-amyloidogenic pathways, enhance synaptic proteostasis, and protect OLs against 5-HT toxicity. We provide mechanistic details, comparative profiles, and translational considerations, including blood–brain barrier penetration, pharmacokinetics, and safety considerations, as well as patient stratification. We also cover preclinical models and early clinical trials that demonstrate cognitive benefits and advantages in myelin repair. The limitations of monotherapies imply the promise of combinatorial regimens that attack both histaminergic and serotonergic systems. We present a clinical translation roadmap featuring adaptive, biomarker-responsive trials that utilise enhanced myelin imaging; personalised and multi-omics approaches to medicine; and transdisciplinary collaboration among neuroscience, pharmacology, regulatory bodies, and patient–caregiver groups. The translation of repurposed glial-targeting therapies to clinical practice will require adaptive, biomarker-guided trials, advanced myelin imaging, and intersectoral coordination among neuroscience, pharmacology, and regulatory partners, including engagement with patients and caregivers, as well as ethical input.

As nociceptors, C-fibers play a critical role in maintaining host homeostasis under both physiological and pathological conditions. We previously demonstrated that C-fiber degeneration confers protection against respiratory syncytial virus (RSV) infection. However, a comprehensive investigation of the effects of C-fiber degeneration on the physiological state of the host remains unexplored. To address this gap, we established a C-fiber-degenerated (KCF) BALB/c mouse model and validated it by immunofluorescence staining of multiple organs. We monitored the body weight of KCF mice and performed 16S rRNA sequencing of their feces. And their brains, lungs, intestines, and spleen were subjected to section staining and RNA sequencing. Although no significant changes in body weight or tissue pathology were observed, KCF mice showed significant transcriptional alterations in the four examined organs. The lungs and intestines exhibited diminished proportions of resting mast cells, while the spleens displayed reduced proportions of monocytes. Functional enrichment analysis revealed the involvement of C-fibers in the production of immunoglobulin and changes in intestinal microbiota. Subsequent experiments confirmed a trend towards reduced globulin levels in the peripheral blood and marked alterations in the diversity and composition of intestinal microbiota. Integrated analysis of differentially expressed genes shared by all four organs identified the nucleotide-binding and oligomerization domain (NOD)-like receptor signaling pathway as a pivotal route by which C-fibers may influence these organs. In summary, this study elucidates the diverse effects of C-fibers on the host, extending our understanding in a multi-organ context. 

Alzheimer’s disease (AD), a progressive neurodegenerative disorder, is marked by memory loss, cognitive decline, and characteristic pathological features including β-amyloid (Aβ) plaques, tau tangles, and neuroinflammation. Despite extensive research, effective therapies remain elusive. Exosome/EVs-based therapeutics have emerged as a promising avenue for AD treatment. Neuron-derived exosomes/extracellular vesicles (EVs) (NDEs) and stem cell-derived exosomes/EVs exhibit neuroprotective effects by promoting Aβ degradation, modulating tau pathology, and reducing inflammation. Notably, NDEs carry insulin-degrading enzyme (IDE) and cellular prion proteins (PrPC), aiding Aβ clearance. However, exosomes also present challenges, such as the potential propagation of pathogenic tau and complement-mediated neurotoxicity. Neural and mesenchymal stem cell-derived exosomes further demonstrate therapeutic efficacy by altering amyloid precursor protein processing and activating PI3K/Akt/mTOR signaling to reduce AD pathology. Despite these advancements, clinical translation requires a deeper understanding of exosome/EVs biology, improved isolation techniques, and personalized strategies. Continued research may establish exosomes as a transformative approach in AD therapy.

De novo variants in the Activity-Dependent Neuroprotective Protein (ADNP) gene cause the autistic Helsmoortel-Van der Aa syndrome with patients showing mild to disastrous phenotypes impacting brain functioning, behavior, and organ functions. In this respect, two treatment strategies have been proposed to alleviate symptoms in patients with this syndrome: (1) the ADNP-derived octapeptide investigational drug NAP (davunetide), which enhances ADNP’s ability to target cytoskeletal deficits, and (2) subnarcotic levels of ketamine, which are suggested to increase endogenous ADNP mRNA levels. Here, we focus on the perspective of ketamine and investigated the transcriptomic response of low-dose and high-dose ketamine applications at different time points, experimentally controlled by the non-toxic drug NAP, in lymphoblastoid cell lines obtained from individuals with Helsmoortel-Van der Aa syndrome. Transcriptome profiling was performed at baseline conditions, followed by dose (low or high) and time (40 min or 4 h)-dependent ketamine application in patient and control lymphoblastoid cell lines. We showed that ketamine affected ADNP expression levels in a dose- and time-dependent manner with only toxic ketamine concentrations increasing ADNP protein levels. Ketamine application also triggered a transcriptomic response with profound gene expression alterations centered around processes such as immune response-regulating signaling pathways and cell fate commitment at low-dose ketamine, together with organelle assembly and cytoskeletal dysregulation at high doses. A parallel control experiment with NAP under the same experimental conditions did not induce detectable gene expression differences in patient-derived cell lines. The ketamine-induced cytoskeletal alterations were functionally studied using immunoblotting, showing a disturbed expression of α-tubulin, β-actin, and to a minor extent microtubule-associated protein EB3 in patient-derived lymphoblastoid cells. Ketamine upregulates wild-type ADNP transcript and protein levels in a dose- and time-dependent manner in patient-derived lymphoblastoid cell lines from individuals with Helsmoortel-Van der Aa syndrome, while inducing a transcriptomic response that affects key processes including immune system signaling and cytoskeletal organization.

Objectives: Many children with neurodevelopmental disorders (NDD) show complex, multidimensional impairments meeting criteria for multiple NDD, yet remain “diagnostically homeless” as DSM-5 lacks a Multidimensional Impairment (MDI) category. We investigated the prevalence of genetic abnormalities in such complex NDD cases. Methods:Between 2017 and 2019, we diagnosed MDI in 666 patients. Among them, 122 (18%) underwent genetic assessment (DNA microarrays, karyotype, gene panels, FISH, FMR1 testing, exome/genome sequencing). We used univariate analyses and clustering to explore associations between clinical dimensions and genetic findings. Results: Genetic abnormalities were identified in 78 patients. Of these:

1. (1)

   41 had known abnormalities usually linked to complex NDD (e.g., del22q11.2);

2. (2)

   16 had mutations associated with severe ASD/ID (e.g., GRIA3 on Xq25);

3. (3)

   11 showed novel abnormalities not previously linked to NDD (e.g., duplication Xq21.1 including POU3F4);

4. (4)

   10 had variants of uncertain significance.

Depending on classification, prevalence ranged from 47% (57/122, definite or predisposition) to 64% (78/122, including uncertain/possible pathogenic variants). Neither clinical dimensions nor severity clusters were associated with the presence of genetic abnormalities. Conclusion:Despite a referral bias toward severe cases, the high rate of genetic findings in this cohort underscores the need for more systematic genetic testing in complex NDD with multidimensional impairment.

This study investigated oxidative stress biomarkers in differentiating trichotillomania (TTM), obsessive–compulsive disorder (OCD), and healthy controls (HC), focusing on thiol-disulfide homeostasis, total oxidant status (TOS), total antioxidant status (TAS), and ischemia-modified albumin (IMA). A total of 68 adolescent females aged 10–18 were recruited and divided into three groups: TTM (n = 24), OCD (n = 21), and HC (n = 23). Oxidative stress biomarkers were assessed through blood analyses, including measurements of thiol-disulfide homeostasis, TOS, TAS, and IMA. Blood analyses revealed that TTM patients had significantly lower native and total thiol levels, a reduced native/total thiol ratio, and elevated disulfide levels compared to OCD and HC (p < 0.01). ROC analysis indicated that the native thiol/total thiol ratio effectively distinguished TTM from both HC and OCD with high accuracy. These findings reveal distinct oxidative stress patterns in TTM and OCD, with disrupted thiol-disulfide homeostasis in TTM and elevated oxidative burden in OCD. The discriminative power of the native thiol/total thiol ratio suggests molecular-level differences, which may inform the etiopathogenesis of TTM and support the development of targeted treatment strategies.

This study aims to develop and evaluate deep neural network (DNN) models for accurately predicting the recurrence risk of glioblastoma multiforme (GBM) to enhance individualized treatment strategies and improve patient outcomes. This study implemented DNN architectures optimized using a hybrid differential evolution neural network (HDE-NN) framework to forecast GBM recurrence risk, particularly in patients at advanced disease stages. The models were trained and validated on a multimodal dataset comprising genomic profiles, imaging-derived metrics, and longitudinal clinical records from 780 GBM patients. Data were sourced from The Cancer Genome Atlas (TCGA) and institutional repositories. Performance was benchmarked against conventional machine learning models, including support vector machines (SVM), random forests (RF), and standard DNNs. The models were implemented in Python. The proposed HDE-optimized DNN achieved an accuracy of 94%, precision of 92%, recall of 90%, F1 score of 91%, and an AUC-ROC of 0.96. These metrics significantly outperformed baseline models, with improvements of 6–12% across evaluation criteria. Confidence intervals (95%) were computed via tenfold cross-validation, confirming statistical robustness. This research introduces a high-performance and generalizable deep learning framework for GBM recurrence prediction. By incorporating multi-source clinical and genomic data, the model demonstrates superior predictive capacity over traditional methods. These findings support the integration of AI-driven tools into GBM care workflows to improve prognosis assessment and personalize therapeutic interventions.