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How the microbiome shapes epigenetic trained memory in neuroinflammation: Implications for neurodegenerative diseases.

Neurodegenerative diseases are increasingly recognized as disorders involving immune dysregulation. However, the mechanisms underlying this dysfunction remain poorly characterized. Trained immunity has recently emerged as a potential contributor to immune dysregulation, particularly in neuroinflammation and neurodegenerative diseases, where trained immunity is the epigenetic reprogramming of innate immune responses following an initial inflammatory stimulus, which increases responses to subsequent exposures. In parallel, although the brain has traditionally been viewed as an immune-privileged organ, growing evidence indicates that peripheral immune activity exerts significant influence on neuroinflammation in the brain. A major driver of peripheral immunity is the microbiome. Therefore, this perspective aims to present a conceptual framework for a relationship between the microbiome, trained immunity, and neurodegenerative diseases. We first summarize evidence of trained immunity in the brain and its role in neurodegeneration. Next, we highlight the role of the microbiome in peripheral immune modulation and in trained immunity. Finally, we propose potential mechanisms through which the microbiome may induce or modulate trained immunity in the brain. These include: 1) immunogenic microbial metabolites that cross the blood-brain barrier and alter host cell epigenetics; 2) migration of peripherally trained myeloid cells into the brain; 3) viral infection-induced trained immunity that may predispose to neurodegeneration. Together, this perspective suggests that microbiome-induced trained immunity offers a novel mechanism linking peripheral immune regulation with neuroinflammation and neurodegeneration with implications for therapeutic targeting of epigenetic modification as a molecular prevention strategy for progression of neurodegeneration.

Humans

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (χ), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA = 5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated χ in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific χ alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans

GPR3 in neuro-metabolic-immune-reproductive nexus - a potential therapeutic target for Multi-System diseases.

BACKGROUND: GPR3(G-protein-coupled receptor 3), an orphan G-protein-coupled receptor (GPCR) with constitutive Gs activity, is expressed in the brain, liver, ovary, and other tissues, regulating cell proliferation, differentiation, and apoptosis across the nervous, reproductive, immune, and metabolic systems. This review synthesizes evidence on its integrated signaling and physiological functions to address the lack of a comprehensive multisystem pathophysiology overview. METHODS: A systematic literature search was conducted on PubMed and Web of Science, using keywords such as "GPR3", "GPCR", "neurodegeneration", "metabolism", "immune", "reproduction", "agonist", "inhibitor", and "therapeutic target". This search identified GPR3's roles in neurodegenerative diseases, immune inflammation, reproduction, and energy metabolism. The analysis focused on signaling pathways, ligand regulation, and therapeutic potential. RESULTS: The research indicates that GPR3 is involved in neuronal survival, synaptic plasticity, and microglial activity via the cAMP/PKA, PI3K/Akt, and β - arrestin pathways. It promotes amyloid - β formation in Alzheimer's disease (AD), yet provides neuroprotection in Parkinson's disease (PD) models. It may contribute to anxiety/depression - like states, maintain oocyte meiotic arrest in the ovary, and activate thermogenic genes in adipose tissue. GPR3 modulates immune responses. Using oleic acid (OA) and diphenyleneiodonium (DPI) as activators, and AF64394 and cannabidiol (CBD) as antagonists, it shows potential in disease models. CONCLUSION: GPR3 acts as a central molecular hub integrating neural, metabolic, immune, and reproductive signaling, highlighting its potential as a therapeutic target for chronic multisystem disorders. However, its dual roles in certain pathologies and translation challenges necessitate further research.

Humans

Circular RNAs in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, with most cases lacking a clear genetic basis. Emerging evidence highlights the involvement of non-coding RNAs, particularly circular RNAs (circRNAs), in disease onset and progression. Here, we investigated circRNAs implicated in ALS and related motor neuron diseases (MNDs). Here, we provide a general overview of circular RNA metabolism and cellular functions. We then present our systematic literature review that identified ALS-associated circRNAs, followed by in silico analyses of 15 circular RNA candidates that were selected based on the most compelling data regarding ALS. Our results revealed that several circular RNAs regulate ALS-related genes, such as unfolded protein response, oxidative stress, cell cycle regulation, and apoptosis. Protein-RNA interaction analysis further showed that ALS-related circRNAs can sponge 20 RNA-binding proteins. Additionally, molecular docking analysis demonstrated that ALS-associated FUS variants significantly alter its binding affinity to circular RNAs. RNA-seq data from ALS patients confirmed significant alterations in the expression of host genes of ALS-related circRNAs and hub proteins in ALS-affected CNS tissues. Collectively, our findings identify circRNAs as potential key contributors to ALS pathogenesis.

Amyotrophic Lateral Sclerosis

How to assess different types of abstract concepts in brain disorders: A systematic review.

The clinical evaluation of semantic knowledge has predominantly relied on tools targeting concrete concepts, whereas abstract knowledge has historically received limited attention despite its importance in everyday communication. Only a few instruments have explored the internal subdivision of abstract knowledge, likely due to the intrinsic difficulty of defining specific types of concepts or dimensions, resulting in a fragmented and heterogeneous neuropsychological assessment framework that limits our understanding of this domain. This systematic review examined the tools used to assess various types of abstract concepts in clinical populations. A literature search has been performed on the electronic databases of PubMed and Google Scholar (last update: October 2025). A total of 17 tests is reviewed, differing in the test characteristics, i.e. ranging from automatic to controlled processes and varying in ecological validity, the type of stimuli employed, and the abstract dimensions explored. Most studies have focused on neurodegenerative patients, while comparatively few have examined other clinical conditions. The risk of bias of the reviewed studies was assessed using an ad hoc developed instrument. This review highlights the need for future research to extend investigations to additional abstract domains and clinical populations, while also identifying key challenges related to stimulus selection and the determination of the most appropriate assessment framework.

Humans

Nimodipine in animal models of demyelination relevant to multiple sclerosis: a systematic review.

BACKGROUND: Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease in which axonal injury, neuronal death, and demyelination occur. Treatment for MS relapses remains limited, which alleviates acute loss of function but has no impact on long-term disability. This study aimed to perform a systematic review of the effects of nimodipine on experimental demyelination models, including experimental autoimmune encephalomyelitis (EAE) and Cuprizone models in rodents. METHODS: This study was conducted following the PRISMA statement. A systematic search was performed in PubMed, Scopus, the Cochrane Library, and Google Scholar. The primary outcome was EAE clinical disease severity (peak clinical score and/or cumulative disease burden). Secondary outcomes included relapse activity (when reported), histological myelin outcomes, oligodendrocyte lineage markers, neuroaxonal injury markers, and inflammatory readouts. Risk of bias was assessed using the SYRCLE tool. RESULTS: Out of 4660 results, 5 studies were included in the systematic review (four EAE studies and one cuprizone model). Nimodipine was administered using heterogeneous regimens (oral, intravenous, intraperitoneal, subcutaneous, or osmotic pump delivery; 1-30 mg/kg/day). The included studies reported the variable effects of nimodipine on relapse-related outcomes, myelination, inflammatory processes, and neuroprotection in the EAE model of MS. Across EAE studies, nimodipine generally reduced clinical disease severity or cumulative burden, although relapse-related outcomes were inconsistent. CONCLUSIONS: Preclinical evidence suggests that nimodipine may attenuate disease severity and demyelination and may promote repair-related processes in rodent models relevant to MS. However, to evaluate the clinical applicability of nimodipine in MS patients, well-powered, transparently reported preclinical replication and early-phase clinical studies are required before clinical translation.

Animals

Diagnostic value of blood p-tau subtypes in Alzheimer's disease progression and pathology: systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease and the most likely to lead to dementia. With the availability of the latest therapies, the need for Alzheimer's disease diagnosis is now gradually increasing. Whereas blood phosphorylated-tau (p-tau) has demonstrated excellent performance in the prediction and diagnosis of disease progression and A&#x3b2; positivity in AD, there are differences between different p-tau subtypes. Therefore, a pooled analysis of different blood p-tau subtypes is of more important clinical value. METHOD: Relevant literature was screened by complete search in four databases, Pubmed, Embase, Cochrane Library and Scopus. Relevant data and AUC and their confidence intervals of the included literature were extracted and analyzed by classification according to p-tau subtypes. Quality assessment was performed using the QUADAS-2 tool. RESULT: Our results reveal that p-tau217 performs better in the diagnostic performance in most stages of AD, which is consistent with the guidelines. However, our results concluded that p-tau217 has poorer diagnostic performance in the stages of cognitive unimpaired or less cognitively impaired, especially in the A&#x3b2; positivity diagnosis of SCD and CU. Head-to-head meta-analyses formally confirmed that p-tau217 significantly outperforms p-tau181 across AD dementia, A&#x3b2; positivity, tau positivity, and biological staging (all P&#x2009;<&#x2009;0.05), whereas no significant difference was observed between p-tau231 and p-tau181. CONCLUSION: By integrating single-arm pooled AUC estimates with formal head-to-head statistical comparisons, our study provides evidence-based support for plasma p-tau217 as the subtype with the most robust diagnostic performance across AD pathology and biological staging. Head-to-head analyses formally confirmed that p-tau217 significantly outperforms p-tau181 in A&#x3b2; positivity, Tau positivity, and biological staging.

Humans

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans

A systematic review and meta-analysis of visuospatial attentional deficits in Parkinson's patients.

Parkinson's disease (PD) is a neurodegenerative condition primarily characterized by motor deficits, yet cognitive impairments are increasingly recognized. While deficits in executive functioning are well documented even in the absence of cognitive decline, evidence of attentional deficits in PD remains inconsistent, and the role of motor symptom lateralization is unclear. In this systematic review and meta-analysis, we examined visual attention in right-handed, cognitively unimpaired idiopathic PD patients, focusing on the canonical attentional domains (sustained, selective, divided) and processes (alerting, endogenous and exogenous orienting, reorienting), as well as visuospatial bias. Four databases were searched for studies comparing PD patients with healthy controls. Meta-analytic estimates were derived using Hedges' g within random-effects models, and studies that could not be quantitatively integrated were summarized narratively. In addition, studies directly comparing patients with left- and right-predominant motor symptoms (LPD vs. RPD) were reviewed qualitatively. Across 51 studies, PD patients exhibited deficits in sustained, selective, and divided attention. Among attentional processes, only exogenous orienting was impaired, whereas alerting, endogenous orienting, and reorienting were preserved. Findings from the few studies examining visuospatial bias indicated small, context-dependent shifts in spatial attention rather than a consistent directional bias. These findings indicate that PD patients show visual-attentional impairments, particularly under high-demand conditions, while basic alertness and voluntary orienting appear preserved. Exogenous orienting deficits and subtle rightward spatial tendencies in LPD suggest disruption of right-hemisphere attentional networks. These results have implications for early cognitive assessment, rehabilitation strategies, and understanding the neural bases of attentional dysfunction in PD.

Humans

Bi-compartmental CSF-serum analysis of NfL and GFAP differentiates central and peripheral pathology in neuroinfectious diseases: A monocentric real-world cohort study.

Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), established biomarkers of neuroaxonal injury and astroglial pathology, are frequently only assessed in blood, which limits conclusions regarding their origin. Bi-compartmental analyses of CSF and serum may help differentiate central or peripheral origin of biomarker elevation. Moreover, studies on NfL and GFAP in distinct neuroinfectious disease (NID) phenotypes, particularly those based on real-world cohorts, are limited. This retrospective monocentric study analyzed CSF and serum from patients with (meningo-)encephalitis/myelitis (TI+; n&#xa0;=&#xa0;48), meningitis (TI-; n&#xa0;=&#xa0;80), (cranial) nerve palsies/polyradiculitis (PND; n&#xa0;=&#xa0;61), and 113 non-neuroinflammatory/non-neurodegenerative controls. A bi-compartmental model using scatter plots and simple linear regression was applied to assess the origin of blood biomarker levels and discriminate between central and peripheral pathology. CSF and serum NfL and GFAP z-scores were significantly higher in TI+ compared with TI- (CSF-GFAP p&#xa0;<&#xa0;0.001/sGFAP p&#xa0;=&#xa0;0.0083; CSF-NfL p&#xa0;=&#xa0;0.003/sNfL p&#xa0;=&#xa0;0.0004). TI+ and PND differed only in GFAP levels, which were higher in TI+ (CSF-GFAP p&#xa0;=&#xa0;0.0049/sGFAP p&#xa0;=&#xa0;0.003). The overall group effect (p&#xa0;&#x2264;&#xa0;0.003) and principal findings remained significant after adjustment for age, sex, QAlb, and time since (symptom) onset to LP. Bi-compartmental analysis revealed simultaneous elevation of CSF and serum NfL in TI+, indicating predominantly central origin, whereas PND demonstrated a shift toward higher sNfL levels suggesting peripheral origin. Higher clinical severity (modified Rankin Scale 3-5) was associated with elevated serum and CSF GFAP and NfL (sGFAP p&#xa0;=&#xa0;0.012/sNfL p&#xa0;=&#xa0;0.002; CSF-GFAP p&#xa0;<&#xa0;0.0001/CSF-NfL p&#xa0;=&#xa0;0.0001), which also predicted unfavorable outcome at discharge (sGFAP p&#xa0;=&#xa0;0.006/sNfL p&#xa0;=&#xa0;0.004; CSF-GFAP p&#xa0;=&#xa0;0.003/CSF-NfL p&#xa0;=&#xa0;0.012). NfL and GFAP were associated with brain/myelon involvement in NID, predominantly reflecting central pathology. Despite strong CSF-serum correlations, bi-compartmental approaches provide additional insight into biomarker origin and disease compartment.

Humans

Integrated analysis uncovers exogenous induction and molecular regulation of erinacine A accumulation in Hericium erinaceus.

Erinacine A, a cyathane-type diterpenoid mainly from Hericium erinaceus mycelia, exhibits prominent neurotrophic and neuroprotective activities, making it a promising candidate for managing neurodegenerative diseases. However, its low abundance and unclear genetic regulatory mechanisms hinder its application as a nutraceutical. This study aimed to decipher its regulatory mechanisms and enhance production. Four exogenous inducers were screened, with salicylic acid (SA) and ergosterol (ERG) significantly increasing erinacine A content by 62.21% and 146.70% at 20 days, respectively. Transcriptome and WGCNA of inducer-treated sample identified darkorange and magenta modules associated with erinacine A biosynthesis, with the eri gene cluster enriched in the darkorange module and eriG and eriF as hub genes. Forward genetic analysis via QTL mapping of the HeD127 dikaryon population revealed significant phenotypic variation in erinacine A content (0.341-13.085&#x202f;mg/g) and identified two loci (erA-1 and erA-2) explaining 18.63% of phenotypic variation. Integrating these forward and reverse genetic analyses revealed that salicylic acid and ergosterol synergistically regulate core carbon metabolic pathways to augment acetyl-CoA supply for the mevalonate pathway, suppressed competitive metabolism, enhanced diterpene skeleton construction and structural modification. These results deepen our understanding of the genetic and molecular basis governing accumulation of erinacine A, and facilitate its application in neuroprotective pharmaceuticals.

Diterpenes

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (&#x3a8;) represents one of the most abundant and conserved RNA modifications. &#x3a8; provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of &#x3a8; sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel &#x3a8; site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA &#x3a8;-site prediction. The &#x3a8; modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA &#x3a8;-site prediction. Meta-PseU offers a new framework for robust &#x3a8;-site identification by using long sequences.

Pseudouridine

A systematic review and meta-analysis of OCT-based ophthalmic changes in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease marked by motor decline and respiratory failure. Optical coherence tomography (OCT), a non-invasive imaging technique, has been explored for detecting retinal structural changes that may reflect neurodegeneration in ALS. While some studies report thinning of retinal layers, findings remain inconsistent. Therefore, a meta-analysis is needed to clarify the extent of retinal involvement and the potential of OCT as a biomarker in ALS. METHODS: A systematic literature search was conducted across PubMed, EMBASE, and Cochrane databases for studies published between 2010 and May 2025. Study quality was assessed using the Newcastle-Ottawa Scale (NOS), and publication bias was evaluated through funnel plot asymmetry and Egger's test. Pooled effect sizes were calculated using random-effects models to account for between-study heterogeneity, and differences in OCT parameters between ALS patients and healthy controls were expressed as standardized mean differences (SMD) with 95% confidence intervals (CI). Statistical heterogeneity was quantified using the I2 statistic. RESULTS: A total of 17 studies were included in the present meta-analysis. The primary unadjusted global model demonstrated significant reduction of retinal nerve fibre layer (RNFL) thickness in ALS patients compared to controls (unadjusted SMD&#xa0;=&#xa0;-0.295, 95% CI: -0.522, -0.068). Upon applying a Design Effect variance inflation model to address fellow-eye non-independence, the pooled estimate remained robustly significant across a conservative range of intraclass correlations (SMD ranged from -0.256 to -0.249). Subgroup analyses revealed that RNFL thinning was particularly pronounced in spinal-onset ALS (SMD&#xa0;=&#xa0;-0.54, 95% CI: (-0.98, -0.10). When studies were stratified by the region of conduct, RNFL and macular thinning reached statistical significance only within the non-Asian subgroup, though the formal test for subgroup differences was not significant. CONCLUSION: This meta-analysis demonstrates significant bilateral RNFL thinning in ALS, with relative preservation of the Inner Nuclear Layer and Ganglion Cell Layer - Inner Plexiform Layer, supporting retinal neurodegeneration as a feature of this multisystem disorder. SYSTEMATIC REVIEW REGISTRATION: PROSPERO identifier CRD420251076035.

Humans

Mitophagy-mediated ferroptosis involved in 2,5-hexanedione-induced neurotoxicity in rats.

n-Hexane, a widespread environmental and industrial pollutant, poses serious health risks, particularly neurotoxicity. Chronic exposure primarily induces sensorimotor neuropathy via its metabolite 2,5-hexanedione (HD), yet the mechanisms underlying HD-induced neuronal injury remain unclear. Recent evidence implicates ferroptosis, an iron-dependent form of regulated cell death, in neurodegenerative processes. In this study, Sprague-Dawley (SD) rats were exposed to HD to establish a neuropathy model. Ferroptosis involvement was assessed using the iron chelator deferoxamine (DFO) and the ferroptosis inhibitor Ferrostatin-1. The potential role of mitophagy in HD-induced ferroptosis was evaluated by monitoring mitophagy markers and by autophagy inhibition with chloroquine (CQ). In vitro, SH-SY5Y cells were transfected with PINK-1 siRNA to explore mitophagy-mediated regulation of ferroptosis. HD exposure led to iron accumulation, lipid peroxidation, mitochondrial abnormalities, and decreased GPX4 in rat spinal neurons. DFO or ferrostatin-1 treatment ameliorated these changes and preserved mitochondrial integrity. Mechanistic analyses revealed HD-induced activation of mitophagy, as shown by upregulation of Beclin-1, LC3II, Drp-1, and PINK-1, with concomitant downregulation of P62 in spinal mitochondria. CQ suppressed mitophagy, reduced iron deposition and lipid peroxidation, and improved motor function. Similarly, PINK-1 knockdown in SH-SY5Y cells mitigated HD-induced mitophagy and ferroptosis. These findings demonstrate that HD induces neuronal ferroptosis via mitophagy activation. Inhibition of ferroptosis or mitophagy effectively attenuates HD-induced neurotoxicity, suggesting potential therapeutic strategies to reduce neural damage from environmental n-hexane exposure.

Animals

Definition and prevalence of residual disease in inflammatory arthritis: a systematic literature review and meta-analysis.

OBJECTIVE: To assess how residual disease (i.e., clinically relevant signs/symptoms despite achieving treatment targets) is defined in rheumatoid arthritis (RA), psoriatic arthritis (PsA) or axial spondyloarthritis (axSpA), and estimate the prevalence/severity of residual disease in these diseases. METHODS: Systematic review of original research in RA/PsA/axSpA. Two key residual disease components were extracted: (1) the patient's disease state (often remission/low disease activity) and (2) which residual signs/symptoms were measured, e.g. swollen joints or fatigue (indicators of residual disease). Frequencies of the disease states and indicators were described (Objective 1). Prevalence (%) and severity (absolute score on instrument, e.g. fatigue NRS) of residual disease was analysed by indicator, using random effects meta-analysis (&#x2265;4 studies) or descriptively (<4 studies) (Objective 2). RESULTS: Regarding residual disease definitions (59 studies), disease states were almost exclusively disease activity-based (>99%), but with much variation in specific instruments/thresholds. Across diseases, physician-reported (66%) and patient-reported (73%) indicators were used more often than laboratory indicators to define residual disease (46%). Especially peripheral joint counts, pain, physical function and CRP were frequently used (42-56% of studies). The prevalence of residual disease (84 studies) was notable. For example, 5-25% of RA and PsA patients in remission still had swollen joints, and up to one-third reported relevant pain or fatigue. For axSpA, evidence was limited. CONCLUSION: Residual disease definitions in RA/PsA/axSpA are based on various disease activity instruments/thresholds and indicators (signs/symptoms). Residual disease affects up to half of patients. Future research should aim for a consensus-based definition of residual disease.

Humans

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans

Dual-tasking reveals severity-dependent reorganization of cortical beta energy landscapes in Parkinson's disease.

Dual-task impairment is a hallmark of Parkinson's disease (PD), yet the large-scale neural mechanisms underlying postural-motor interference remain poorly understood. In particular, it is unclear how cortical network dynamics reorganize across disease severity when postural control competes with concurrent task demands. This study investigated EEG-derived beta-band cortical energy landscapes in healthy older adults, early-stage PD, and mid-stage PD during single- and dual-task conditions. Dual-task behavioral cost increased with disease severity for concurrent manual performance (p&#xa0;<&#xa0;0.001), whereas a quadratic pattern was observed for postural performance. Energy landscape analysis revealed severity-dependent reconfiguration of cortical beta dynamics. Dual-task-related landscape changes in effective network flexibility (&#x394;Neff), landscape geometry (&#x394;Evar and &#x394;Gmag), and dominant low-energy attractor organization (&#x394;Low mass and &#x394;Low area) showed significant monotonic trends (p&#xa0;<&#xa0;0.05), reflecting progressive constrained cortical network dynamics with advancing PD severity. In addition, dual-task-related landscape alterations were associated with clinical severity, as indexed by Hoehn and Yahr stage (|r|&#xa0;=&#xa0;0.353-0.423, p&#xa0;=&#xa0;0.016-0.048), and showed associations with motor impairment, as measured by MDS-UPDRS part III scores (|r|&#xa0;=&#xa0;0.333-0.455, p&#xa0;=&#xa0;0.009-0.063). These findings demonstrate that dual-task demands induce severity-dependent reconfiguration of cortical beta energy landscapes in PD. Energy landscape geometry may capture systems-level neural constraints associated with dual-task susceptibility in PD, providing a physiologically grounded framework to characterize disease-related functional vulnerability.

Humans

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans