Journal of Molecular Neuroscience最新文献

Novel therapeutic approaches, such as exosome therapy, have garnered considerable attention for the treatment of central nervous system (CNS)-related disorders. This study aimed to investigate the effect of Neural stem cell-derived exosomes(Exo-NSC) on improving behavioral, molecular, and electrophysiological symptoms. Rats were divided into: control, lesioned groups (Alz, Alz + saline), treatments (Alz + NSC, Alz + Exo-NSC). the nucleus basalis of meynert (NBM) was lesioned using electrical lesion. One week after lesion, saline, NSC, and Exo-NSC were injected into the NBM. Twenty-eight days post-injection, behavioral tests (passive avoidance memory and locomotor activity) and EEG recordings were conducted. Subsequently, hippocampal levels of brain-derived neurotrophic factor (BDNF) and acetylcholine (ACh) were measured. NBM lesioning significantly reduced the step-through latency (STL), decreased alpha and gamma wave frequencies, increased theta and delta wave frequencies, and reduced Ach and BDNF levels compared to the control group. The NSC injection resulted in decreased delta wave frequency, increased gamma wave frequency, and elevated BDNF levels. Meanwhile, Exo-NSC injection significantly increased STL, beta and gamma wave frequencies, and levels of ACh and BDNF compared to lesioned groups. Overall, the findings indicate that Exo-NSC injection may be more effective than NSCs in improving passive avoidance memory. This benefit may stem from elevated hippocampal ACh and BDNF levels in the hippocampus.

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Effects of Neural stem cells-derived exosomes on Alzheimer’s disease

A high-salt diet (HSD) not only triggers a range of adverse neurological responses but is also significantly associated with reduced lifespan. However, the link between salt-induced neurophysiological changes and lifespan shortening remains unclear. Through RNA-seq analysis of the heads of Drosophila fed a HSD, we found that the branched-chain amino acid (BCAA) metabolic pathway was activated. This study aims to investigate the role and mechanism of BCAAs in HSD-induced lifespan reduction in Drosophila. Our results show that dietary supplementation with BCAAs significantly alleviates the lifespan shortening caused by a HSD, suggesting that BCAA metabolism may contribute to lifespan maintenance under salt stress. Further experiments revealed that ubiquitous knockdown of genes related to BCAA metabolism led to increased salt sensitivity and mortality under high-salt conditions. Notably, neuron-specific disruption of BCAA metabolic genes similarly exacerbated these phenotypes, highlighting a critical role for neuronal BCAA metabolism in the response to salt stress. Interestingly, supplementation with other amino acids—such as phenylalanine, glutamate, aspartate, proline, and tyrosine—also partially rescued the lifespan shortening induced by a HSD. These findings not only underscore the central role of BCAAs in salt-mediated lifespan regulation but also suggest a potential synergistic mechanism involving multiple amino acids, offering new insights into intervention strategies for salt-related health risks.

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Insomnia is the most prevalent sleep disorder and exhibits substantial heritability. Although genome-wide association studies (GWAS) have provided broader insights, they still explain only a small proportion of the phenotypic variance, leaving critical gaps in the mechanistic understanding of insomnia. Therefore, we integrated large-scale GWAS summary statistics with single-cell expression quantitative trait loci (eQTL) data across eight major brain cell types. From 1,631 genes mapped to insomnia-associated loci, we constructed gene-cell pairs and applied rigorous filtering to derive independent, strong instrumental variables. These were analyzed using two-sample Mendelian randomization (MR) with inverse-variance weighted (IVW) estimation as the primary approach. Sensitivity analyses, including MR-Egger, Cochran’s Q test, leave-one-out, and MR-PRESSO, were employed to validate causal inferences and mitigate pleiotropy. Our analysis identified 14 genes (25 gene-cell pairs) significantly associated with insomnia risk. Notably, LINC01535 showed the strongest causal effects in astrocytes, excitatory neurons, inhibitory neurons, oligodendrocyte precursor cells, and oligodendrocytes (IVW, p < 0.001). Additionally, we identified 9 insomnia-associated genes in one specific cell type, suggesting those genes may primarily mediate insomnia in their specific cell type. Except for the outstanding genes, we identified most of the insomnia-associated genes in most of the glial cells (oligodendrocytes, OPCs, and astrocytes), suggesting its significant role in mediating insomnia risk. Our study deepens the mechanistic understanding of insomnia by revealing cell-type-specific genetic influences on insomnia, paving the way for targeted prevention and therapeutic interventions.

Migraine is a complex neurological disorder showing distinct circadian rhythmicity in its onset and intensity. Attacks often follow daily patterns, suggesting that molecular clock mechanisms modulate neuronal excitability and pain signaling. Recent advances in neuroepigenetics identify RNA modifications particularly N6-methyladenosine (m6A) as rapid regulators of gene expression that respond to circadian cues. Exploring this circadian epitranscriptomic interaction may clarify time-of-day variations in migraine risk and drug response. This review integrates recent molecular and translational studies examining the interplay between m6A RNA methylation, circadian clock genes, and migraine pathophysiology. Evidence from transcriptomic, neurochemical, and pharmacological research was analyzed to understand how rhythmic RNA modifications affect calcitonin gene-related peptide (CGRP) signaling, neuroinflammation, and chronotherapeutic outcomes. Altered timing or function of m6A enzymes disrupts rhythmic transcription of core clock genes, enhancing CGRP release and inflammatory mediators such as interleukin-6, tumor necrosis factor-α, and nitric oxide. These changes heighten neuronal sensitivity and reduce the migraine threshold. Circadian variations in RNA methylation also influence drug-metabolizing enzymes and transporters, contributing to time-dependent differences in the efficacy of triptans, β-blockers, and CGRP antagonists.Integrating circadian and epitranscriptomic insights offers a pathway to precision migraine therapy. Profiling time-specific RNA modifications and tailoring drug administration to biological timing could improve efficacy, minimize side effects, and guide development of novel disease-modifying treatments targeting m6A-regulated pathways.

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Figure illustrating the interplay between circadian rhythms and epitranscriptomic regulation in migraine. The molecular clock (CLOCK, BMAL1, PER, CRY) regulates rhythmic m6A RNA methylation (METTL3, FTO, ALKBH5), which in turn modulates CGRP expression, cytokine production (IL-6, TNF-α), and neuronal excitability. These processes converge to influence time-of-day variations in migraine susceptibility and therapeutic response, highlighting the potential of chronotherapy and RNA-modification–targeted treatments for precision migraine management.

Neurodegenerative diseases (NDs) are conditions characterized by the progressive degeneration of neurons in the brain, leading to dysfunction in various aspects such as cognition, motor function, and overall quality of life. Leading causes of these disorders are various genetic factors, environmental influences, and aging. The exact pathophysiology is unclear. However, various biomarkers have been identified in NDs, including oxidative stress, neuroinflammation, neurofibrillary tangles, excitotoxicity, mitochondrial dysfunction, impaired protein homeostasis, α-synuclein, and tau hyperphosphorylation. Among them, Piezo1 is an ion channel that responds to mechanical stimuli, and it’s gaining attention for its involvement in the physiology of aging and various NDs. Additionally, it has been demonstrated to play a crucial role in modulating neurogenesis, synaptic remodeling, and cerebral blood flow. Piezo1 can also trigger neuroinflammation, oxidative stress, and neuronal damage through aberrant calcium influx and subsequent activation of pathways including MAPK, NF-κB, and YAP/ TAZ. In the present study, we have discussed molecular mechanisms and highlighted the cross-talk between oxidative stress and inflammation, focusing on Piezo1. Promising and evolving pharmacological strategies will be presented in detail with a critical consideration of current shortcomings and potential applications. Drug design and structural biology may have the potential to create more selective, brain-permeable, and safer modulators of Piezo1. Overall, Piezo1 is one of the promising mechanobiological targets, which may further broaden the scope of precision neuromodulation in complex NDs.

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Huntington’s disease (HD) is a rare, inherited neurodegenerative disorder caused by the expanded CAG repeats in the huntingtin gene. The HD domain still lacks detailed knowledge of validated drug targets, limiting the effectiveness of classical methods. To address this gap, we have applied an integrated computational approach, combining machine learning (ML) with transcriptomic analysis, to identify novel therapeutic targets. Differential expression analysis was performed on eight publicly available datasets, comprising 209 healthy control and 193 Huntington’s disease patient samples, followed by ML-based screening of differentially expressed genes (DEGs). Feature selection using mRMR and RFE, in combination with four classifiers (Linear SVC, Stochastic Gradient Descent, Logistic regression, and Ridge regression), yielded 138 DEG candidates. Subsequent literature curation, drug target analysis, and gene regulatory network (GRN) construction highlighted several key genes, including TXNIP, TNIP3, HTR1D, ADRB1, and FOXP1, which may play pivotal roles in disease progression. Furthermore, our findings highlight the contribution of non-neuronal mechanisms, such as endothelial dysfunction, vascular neurodegeneration, thermoregulation, metabolic imbalance, and impaired phagocytosis, providing a broader perspective into HD pathophysiology. This comprehensive strategy advances our HD knowledge regarding therapeutic targets, molecular pathways, transcription factors (TFs), and complex gene interactions beyond classical HD processes. In summary, the study successfully identifies a promising set of novel drug targets, indicating potential implications in HD therapy.

Alzheimer’s disease (AD) is a neurodegenerative disorder that progressively deteriorates a person’s memory, as well as their ability to think and move. It has been reported to be the most common cause of dementia. Alterations in gene expression have been increasingly recognised as key contributors to the onset and progression of AD, driving interest in transcriptomic approaches to better understand the disease at a molecular level. The development of machine learning (ML) approaches in transcriptomics have been rapid in the past decade, and this advancement can be applied to the study of AD transcriptomes. An ML program that enhances the alignment data through filtering out low confidence splice junction reads, Splam, has been developed by Chao et al. (2023). However, this program has not been utilised and assessed in the transcriptomic study of a complex neurological disease such as AD. This study investigates both the transcriptome of AD brain and the potential of an ML program to enhance alignment-stage data quality and influence downstream analyses. Using the Integrative Genomics Viewer, a selection of filtered reads was visualised, uncovering the types of splice junction reads Splam discards to refine the alignment data. From the differential expression (DE) analysis, we found a higher number of DE transcripts using ML-filtered data compared to unfiltered data, potentially unmasking aspects of AD brain DE profile obscured by alignment noise. The gene loci expressing those transcripts were also determined to be more AD-relevant by comparing these findings with external studies, and contribute to more related gene ontology enrichment terms. We identified gene loci expressing transcripts of interest shared between ML-filtered and unfiltered data, as this consistency in detection suggests that these genes are robust candidates for downstream analyses and biomarkers in AD.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease leading to disability and death. Genetic animal models, like transgenic mice, are critical for studying disease mechanisms and developing therapies. Model validity, experimental standardization, and predictability are key to successful research. This retrospective study analyzed physiological parameters of the S-FUS (1-359) transgenic mouse model over 10 years, focusing on lifespan, body weight dynamics, symptomatic stages, and molecular changes. Hemizygous mice had a mean lifespan of 137.8 days (males) and 125.1 days (females), longer than homozygous counterparts. The symptomatic stage, marked by motor deficits, began at ~ 123 days and lasted 10–15 days. Body weight loss correlated with disease progression, reaching 28.93% of baseline at death. Molecular analysis revealed regional FUS expression differences (midbrain > spinal cord), alongside proinflammatory cytokine activation (Il6, Tnf alpha) and oxidative stress. Dopaminergic dysregulation was evident, with striatal dopamine/metabolite levels rising 40–60%, linked to Maob downregulation and impaired GABAergic inhibition. Midbrain-selective caspase-3 suppression suggested a shift from apoptosis to necroptosis, while spinal cord astrogliosis indicated compensatory mechanisms. Heterogeneity in lifespan, symptom onset timing, and disease duration was observed, underscoring the need for rigorous experimental design, particularly for therapies aiming to delay symptoms or extend survival. Dopamine oxidation emerged as a novel neurotoxicity contributor, highlighting potential therapeutic targets: modulating dopaminergic signaling and reducing oxidative stress.

Background: Isolated REM sleep behavior disorder (iRBD) is among the strongest clinical markers of prodromal α-synucleinopathies. Pinpointing causal proteins may open the door to early diagnosis and disease-modifying therapies.

Methods: We performed a proteome-wide Mendelian randomization (MR) using protein QTLs from brain, cerebrospinal fluid, and plasma, with GWAS data from 1,061 iRBD cases and 8,386 controls. The findings were validated in an independent cohort of 35,559 individuals from Iceland, utilizing plasma proteome data. To assess the directionality and robustness of the association, we additionally performed Steiger filtering and Bayesian colocalization analyses. PheWAS was applied to explore pleiotropy and safety.

Results: Among hundreds of proteins screened, only plasma SPOCK3 (SPARC/Osteonectin, Cwcv and Kazal-like Domains Proteoglycan 3) showed a significant causal link to iRBD (OR = 2.07, 95% CI = 1.50–2.84, P = 7.45 × 10⁻⁶). No brain or CSF proteins met significance. In the independent cohort, MR confirmed the association between SPOCK3 and iRBD risk (OR = 1.39, 95% CI: 1.03–1.88, P = 0.029). Steiger filtering supported the inferred causal direction (P < 0.05), and colocalization analysis revealed a high posterior probability of a shared causal variant between SPOCK3 levels and iRBD risk (PPH4 = 0.96). PheWAS revealed no major off-target associations.

Conclusions: Plasma SPOCK3 emerges as a candidate peripheral biomarker for iRBD. While Mendelian randomization supports a potential causal association, the underlying mechanisms—such as extracellular matrix involvement—require further experimental validation.