RNA splicing is an essential cellular process in which a series of protein-nucleic acid complexes cut and splice the products of gene transcription to generate mature RNA， and it plays an important role in maintaining the normal life activities of cells. Extensive studies have shown that proteins and nucleic acids associated with RNA splicing undergo the pathological changes such as aggregation in neurodegenerative diseases， and inadequate RNA splicing is observed in lesions. Genetic alterations within RNA splicing-related genes can cause neurodegenerative diseases. All these findings suggest that abnormalities in RNA splicing pathways may play a significant role in the pathogenesis of neurodegenerative diseases. This article reviews the research advances in the alterations of RNA splicing in common neurodegenerative diseases in terms of histopathology， biochemistry， and genetics， as well as related cell biology and animal models， in order to clarify their role in the pathogenesis of neurodegenerative diseases.
Alzheimer Disease ; Parkinson Disease

Humans ; Alzheimer Disease ; Cross-Sectional Studies ; Creatine Kinase ; Brain/metabolism*

Intermittent theta burst stimulation (iTBS), a time-saving and cost-effective repetitive transcranial magnetic stimulation regime, has been shown to improve cognition in patients with Alzheimer's disease (AD). However, the specific mechanism underlying iTBS-induced cognitive enhancement remains unknown. Previous studies suggested that mitochondrial functions are modulated by magnetic stimulation. Here, we showed that iTBS upregulates the expression of iron-sulfur cluster assembly 1 (ISCA1, an essential regulatory factor for mitochondrial respiration) in the brain of APP/PS1 mice. In vivo and in vitro studies revealed that iTBS modulates mitochondrial iron-sulfur cluster assembly to facilitate mitochondrial respiration and function, which is required for ISCA1. Moreover, iTBS rescues cognitive decline and attenuates AD-type pathologies in APP/PS1 mice. The present study uncovers a novel mechanism by which iTBS modulates mitochondrial respiration and function via ISCA1-mediated iron-sulfur cluster assembly to alleviate cognitive impairments and pathologies in AD. We provide the mechanistic target of iTBS that warrants its therapeutic potential for AD patients.
Humans ; Mice ; Animals ; Transcranial Magnetic Stimulation ; Alzheimer Disease/therapy* ; Cognitive Dysfunction/therapy* ; Cognition ; Sulfur ; Iron ; Iron-Sulfur Proteins ; Mitochondrial Proteins

The accumulation and spread of prion-like proteins is a key feature of neurodegenerative diseases (NDs) such as Alzheimer's disease, Parkinson's disease, or Amyotrophic Lateral Sclerosis. In a process known as 'seeding', prion-like proteins such as amyloid beta, microtubule-associated protein tau, α-synuclein, silence superoxide dismutase 1, or transactive response DNA-binding protein 43 kDa, propagate their misfolded conformations by transforming their respective soluble monomers into fibrils. Cellular and molecular evidence of prion-like propagation in NDs, the clinical relevance of their 'seeding' capacities, and their levels of contribution towards disease progression have been intensively studied over recent years. This review unpacks the cyclic prion-like propagation in cells including factors of aggregate internalization, endo-lysosomal leaking, aggregate degradation, and secretion. Debates on the importance of the role of prion-like protein aggregates in NDs, whether causal or consequent, are also discussed. Applications lead to a greater understanding of ND pathogenesis and increased potential for therapeutic strategies.
Humans ; Prions ; Neurodegenerative Diseases/pathology* ; Amyloid beta-Peptides ; Alzheimer Disease ; alpha-Synuclein ; tau Proteins ; Parkinson Disease

Objective To investigate the relationship between neurofilament light chain protein （NfL） and clinical features in patients with Alzheimer disease. Methods We included 58 patients with Alzheimer's disease admitted to Ningbo No. 2 Hospital from June 2020 to December 2021. NfL levels were measured for the 58 patients with Alzheimer's disease. Correlation analysis was performed to study the correlation between NfL and age， disease course， hippocampal grade， Activities of Daily Living（ADL） score， Mini-Mental State Examination （MMSE） score， and Hasegawa Dementia Scale （HDS） score. The Pearson correlation coefficient （r） represented the strength of correlation. Results Among the 58 patients， 33 were females， with a mean NfL level of（24.93±17.07）pg/mL， and 24 were males， with a mean NfL level of 28.14 ± 17.98 pg/mL， which were not significantly different. NfL levels for different educational attainments had no significant difference： illiteracy （7/58），（27.87 ± 14.75）pg/mL；primary school（7/58），（15.22±9.62）pg/mL；middle school （14/58）， （27.95±15.60）pg/mL； high school（4/58），（12.84±2.97）pg/mL； technical secondary school（7/58）， （37.35±26.63）pg/mL； junior college （5/58），（33.79±21.81）pg/mL； and university （7/58），（15.22±9.62）pg/mL. NfL was positively correlated with age （r=0.448） and hippocampal grade（r=0.345）， and not significantly correlated with the course of disease（r=0.045，P>0.05）， ADL score （r=0.242，P>0.05），MMSE score （r=‒0.099，P>0.05），and HDS score （r=‒0.096，P>0.05）. Conclusion Serum NfL levels in patients with Alzheimer disease are positively correlated with age and hippocampal grade on magnetic resonance imaging， but not associated with sex， education attainments， the course of disease，ADL score，MMSE score，and HDS score.
Alzheimer Disease

Previous studies mainly used β-amyloid and α-synuclein as the biomarkers for the diagnosis of neurodegenerative diseases. In recent years，studies have shown that telomeres at the end of chromosome can be used as an index to measure the degree of biological aging，and telomere length and telomerase activity may also be used as the blood markers to evaluate the risk，progression，and poor prognosis of neurodegenerative diseases in the elderly；however，there is still a lack of consistency between the research findings in China and globally. Understanding the role of telomere-related biomarkers in age-related diseases can help clinicians learn more about the mechanism of disease development and progression. This article reviews the latest research advances in the telomere-telomerase system in neurodegenerative diseases，in order to introduce the influence of telomere length and telomerase activity on neurodegenerative diseases and their potential mechanisms of action.
Telomere ; Telomerase ; Neurodegenerative Diseases ; Alzheimer Disease ; Parkinson Disease

Enlarged perivascular spaces（EPVSs）are one of the imaging biomarkers of cerebral small vessel disease（CSVD），and associated with other pathological changes of CSVD，worse cognitive function，and aging. This review describes the imaging characteristics and visual rating of EPVSs using magnetic resonance imaging and summarizes the research progress of EPVSs in Alzheimer disease in recent years in order to promote the understanding of this field.
Alzheimer Disease

Alzheimer disease（AD）， a degenerative disease of the central nervous system characterized by progressive cognitive dysfunction and behavioral impairment， has gradually become one of the most burdensome diseases in this century. At present， the amyloid cascade hypothesis is a widely recognized theory on the pathogenesis of AD. However， recent studies have shown that the immune system can play an important role in the occurrence of AD. This article summarizes the relationship between the immune system and the development and progression of AD from the existing literature， with an emphasis on the role of peripheral immunity in both the innate and adaptive immune systems， aiming to provide novel ideas for future research on AD in the immunological direction.
Alzheimer Disease

Objective: To understand the distribution characteristics of age of Alzheimer's disease (AD) onset and influencing factors. Methods: Based on the follow-up data of Alzheimer's Disease Neuroimaging Initiative from 2005 to 2022, participants with normal cognition (CN) or mild cognitive impairment (MCI) at baseline survey, and those with progression to AD during follow-up period were selected as study subjects. Univariate analysis and multiple linear regression analysis were performed to explore the associations of gender, race, number of ApoE ε4 genes carried, family history, years of education and marital status with the age of AD onset. Results: A total of 405 participants, with an average age of (74.0±6.9) years at baseline survey, progressed to AD during follow up period. The age of AD onset was (76.6±7.5) years, and age of onset in men was about 1.9 years later than women. Multiple linear regression analysis showed that for each increase in ApoE ε4 gene number, the age of AD onset was about 0.344 years earlier. The age of AD onset was 4.007 years earlier for those with MCI at baseline survey compared with those with CN. Years of education were not significantly associated with the age of onset of AD (P>0.05). Conclusion: Those who carry ApoE ε4 gene, and have MCI at baseline survey might have earlier age of AD onset.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Alzheimer Disease/genetics* ; Apolipoprotein E4/genetics* ; Cognition ; Cognition Disorders ; Cognitive Dysfunction/genetics*

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Neuroimaging based on magnetic resonance imaging (MRI) is one of the most intuitive and reliable methods to perform AD screening and diagnosis. Clinical head MRI detection generates multimodal image data, and to solve the problem of multimodal MRI processing and information fusion, this paper proposes a structural and functional MRI feature extraction and fusion method based on generalized convolutional neural networks (gCNN). The method includes a three-dimensional residual U-shaped network based on hybrid attention mechanism (3D HA-ResUNet) for feature representation and classification for structural MRI, and a U-shaped graph convolutional neural network (U-GCN) for node feature representation and classification of brain functional networks for functional MRI. Based on the fusion of the two types of image features, the optimal feature subset is selected based on discrete binary particle swarm optimization, and the prediction results are output by a machine learning classifier. The validation results of multimodal dataset from the AD Neuroimaging Initiative (ADNI) open-source database show that the proposed models have superior performance in their respective data domains. The gCNN framework combines the advantages of these two models and further improves the performance of the methods using single-modal MRI, improving the classification accuracy and sensitivity by 5.56% and 11.11%, respectively. In conclusion, the gCNN-based multimodal MRI classification method proposed in this paper can provide a technical basis for the auxiliary diagnosis of Alzheimer's disease.
Humans ; Alzheimer Disease/diagnostic imaging* ; Neurodegenerative Diseases ; Magnetic Resonance Imaging/methods* ; Neural Networks, Computer ; Neuroimaging/methods* ; Cognitive Dysfunction/diagnosis*