Neuronal intranuclear inclusion disease misdiagnosed as Parkinson's disease: a case report.

Neuronal intranuclear inclusion disease (NIID) is a rare progressive neurodegenerative disease that mainly manifests as dementia, muscle weakness, sensory disturbances, and autonomic nervous dysfunction. Herein, we report a 68-year-old Chinese woman who was hospitalized because of resting tremor and bradykinesia that had been present for 7 years. Five years prior, bradykinesia and hypermyotonia had become apparent. She had urinary incontinence and rapid eye movement sleep behavior disorder. She was diagnosed with Parkinson's disease (PD) and received levodopa and pramipexole, which relieved her motor symptoms. During hospitalization, diffusion-weighted imaging revealed a high-intensity signal along the cortical medullary junction. Moreover, a skin biopsy revealed the presence of intranuclear inclusions in adipocytes, fibroblasts, and sweat gland cells. NIID was diagnosed by testing the Notch 2 N-terminal-like C (NOTCH2NLC) gene. We report this case to remind doctors to consider NIID when diagnosing patients with symptoms indicative of Parkinson's disease. Moreover, we note that further research is needed on the mechanism by which levodopa is effective for NIID.

Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases.

Neurodegenerative diseases (NDs) such as Alzheimer's Disease (AD) and Parkinson's Disease (PD) are devastating conditions that can develop without noticeable symptoms, causing irreversible damage to neurons before any signs become clinically evident. NDs are a major cause of disability and mortality worldwide. Currently, there are no cures or treatments to halt their progression. Therefore, the development of early detection methods is urgently needed to delay neuronal loss as soon as possible. Despite advancements in Medtech, the early diagnosis of NDs remains a challenge at the intersection of medical, IT, and regulatory fields. Thus, this review explores "digital biomarkers" (tools designed for remote neurocognitive data collection and AI analysis) as a potential solution. The review summarizes that recent studies combining AI with digital biomarkers suggest the possibility of identifying pre-symptomatic indicators of NDs. For instance, research utilizing convolutional neural networks for eye tracking has achieved significant diagnostic accuracies. ROC-AUC scores reached up to 0.88, indicating high model performance in differentiating between PD patients and healthy controls. Similarly, advancements in facial expression analysis through tools have demonstrated significant potential in detecting emotional changes in ND patients, with some models reaching an accuracy of 0.89 and a precision of 0.85. This review follows a structured approach to article selection, starting with a comprehensive database search and culminating in a rigorous quality assessment and meaning for NDs of the different methods. The process is visualized in 10 tables with 54 parameters describing different approaches and their consequences for understanding various mechanisms in ND changes. However, these methods also face challenges related to data accuracy and privacy concerns. To address these issues, this review proposes strategies that emphasize the need for rigorous validation and rapid integration into clinical practice. Such integration could transform ND diagnostics, making early detection tools more cost-effective and globally accessible. In conclusion, this review underscores the urgent need to incorporate validated digital health tools into mainstream medical practice. This integration could indicate a new era in the early diagnosis of neurodegenerative diseases, potentially altering the trajectory of these conditions for millions worldwide. Thus, by highlighting specific and statistically significant findings, this review demonstrates the current progress in this field and the potential impact of these advancements on the global management of NDs.

Identification of clinical disease trajectories in neurodegenerative disorders with natural language processing.

Neurodegenerative disorders exhibit considerable clinical heterogeneity and are frequently misdiagnosed. This heterogeneity is often neglected and difficult to study. Therefore, innovative data-driven approaches utilizing substantial autopsy cohorts are needed to address this complexity and improve diagnosis, prognosis and fundamental research. We present clinical disease trajectories from 3,042 Netherlands Brain Bank donors, encompassing 84 neuropsychiatric signs and symptoms identified through natural language processing. This unique resource provides valuable new insights into neurodegenerative disorder symptomatology. To illustrate, we identified signs and symptoms that differed between frequently misdiagnosed disorders. In addition, we performed predictive modeling and identified clinical subtypes of various brain disorders, indicative of neural substructures being differently affected. Finally, integrating clinical diagnosis information revealed a substantial proportion of inaccurately diagnosed donors that masquerade as another disorder. The unique datasets allow researchers to study the clinical manifestation of signs and symptoms across neurodegenerative disorders, and identify associated molecular and cellular features.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases.

BACKGROUND: Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts. AIM OF THE REVIEW: The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies. KEY SCIENTIFIC CONCEPTS OF REVIEW: Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Highly sensitive detection of the neurodegenerative biomarker Tau by using the concentration effect of the pyro-electrohydrodynamic jetting.

It is largely documented that neurodegenerative diseases can be effectively treated only if early diagnosed. In this context, the structural changes of some biomolecules such as Tau, seem to play a key role in neurodegeneration mechanism becoming eligible targets for an early diagnosis. Post-translational modifications are responsible to drive the Tau protein towards a transition phase from a native disorder conformation into a preaggregation state, which then straight recruits the final fibrillization process. Here, we show for the first time the detection of pre-aggregated Tau in artificial urine at femto-molar level, through the concentration effect of the pyro-electrohydrodynamic jet (p-jet) technique. An excellent linear calibration curve is demonstrated at the femto-molar level with a limit of detection (LOD) of 130 fM. Moreover, for the first time we show here the structure stability of the protein after p-jet application through a deep spectroscopic investigation. Thanks to the small volumes required and the relatively compact and cost-effective characteristics, this technique represents an innovative breakthrough in monitoring the early stage associated to neurodegeneration syndromes in different scenarios of point of care (POC) and such as for example in long-term human space exploration missions.

The potential roles of salivary biomarkers in neurodegenerative diseases.

Current research efforts on neurodegenerative diseases are focused on identifying novel and reliable biomarkers for early diagnosis and insight into disease progression. Salivary analysis is gaining increasing interest as a promising source of biomarkers and matrices for measuring neurodegenerative diseases. Saliva collection offers multiple advantages over the currently detected biofluids as it is easily accessible, non-invasive, and repeatable, allowing early diagnosis and timely treatment of the diseases. Here, we review the existing findings on salivary biomarkers and address the potential value in diagnosing neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease and Amyotrophic lateral sclerosis. Based on the available research, ß-amyloid, tau protein, α-synuclein, DJ-1, Huntington protein in saliva profiles display reliability and validity as the biomarkers of neurodegenerative diseases.

Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases.

Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject's available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options.

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

Endo-lysosomal dysfunction in neurodegenerative diseases: opinion on current progress and future direction in the use of exosomes as biomarkers.

Over the past two decades, increased research has highlighted the connection between endosomal trafficking defects and neurodegeneration. The endo-lysosomal network is an important, complex cellular system specialized in the transport of proteins, lipids, and other metabolites, essential for cell homeostasis. Disruption of this pathway is linked to a wide range of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease and frontotemporal dementia. Furthermore, there is strong evidence that defects in this pathway create opportunities for diagnostic and therapeutic intervention. In this Opinion piece, we concisely address the role of endo-lysosomal dysfunction in five neurodegenerative diseases and discuss how future research can investigate this intracellular pathway, including extracellular vesicles with a specific focus on exosomes for the identification of novel disease biomarkers. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

Pangenomics: A new era in the field of neurodegenerative diseases.

A pangenome is composed of all the genetic variability of a group of individuals, and its application to the study of neurodegenerative diseases may provide valuable insights into the underlying aspects of genetic heterogenetiy for these complex ailments, including gene expression, epigenetics, and translation mechanisms. Furthermore, a reference pangenome allows for the identification of previously undetected structural commonalities and differences among individuals, which may help in the diagnosis of a disease, support the prediction of what will happen over time (prognosis) and aid in developing novel treatments in the perspective of personalized medicine. Therefore, in the present review, the application of the pangenome concept to the study of neurodegenerative diseases will be discussed and analyzed for its potential to enable an improvement in diagnosis and prognosis for these illnesses, leading to the development of tailored treatments for individual patients from the knowledge of the genomic composition of a whole population.

Cerebrospinal fluid neurofilament light predicts longitudinal diagnostic change in patients with psychiatric and neurodegenerative disorders.

OBJECTIVE: People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown. METHODS: We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other. RESULTS: Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone. CONCLUSIONS: CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice.

Neuronal intranuclear inclusion disease with cortical involvement in left hemisphere: a case report.

BACKGROUND: Neuronal intranuclear inclusion disease (NIID) is a rare highly heterogeneous disease. In this paper, we present a case of NIID featured in cortical involvement in left hemisphere of brain and the imaging changes in the process of the disease. CASE PRESENTATION: A 57-year-old female was hospitalized due to recurrent attacks of headache with cognitive impairment and tremor for 2 years. The symptoms of headache episodes were reversible. The characteristic radiologic change was high intensity signal involving the grey matter-white matter junction on the brain diffusion-weighted imaging (DWI), which existed in the frontal lobe and then extended backwards. Atypical features on fluid-attenuated inversion recovery (FLAIR) sequences showing small patchy high signals in the cerebellar vermis. High signals and edema were detected on FLAIR images along the cortex of the left occipito-parieto-temporal lobes, expanding and gradually shrinking in the follow-up visit. Besides, cerebral atrophy and bilateral symmetrical leukoencephalopathy were also detected. Skin biopsy and genetic testing confirmed the diagnosis of NIID. CONCLUSION: Except for typical radiological change strongly suggesting NIID, it is also necessary to notice the insidious symptoms of NIID combining with some atypical imaging features to make an early diagnosis. Skin biopsies or genetic testing should be carried out early in patients with highly suspected NIID.

Diagnostic and therapeutic targeting of pathological tau proteins in neurodegenerative disorders.

Tauopathies, characterized by fibrillar tau accumulation in neurons and glial cells, constitute a major neuropathological category of neurodegenerative diseases. Neurofibrillary tau lesions are strongly associated with cognitive deficits in these diseases, but the causal mechanisms underlying tau-induced neuronal dysfunction remain unresolved. Recent advances in cryo-electron microscopy examination have revealed various core structures of tau filaments from different tauopathy patients, which can be used to classify tauopathies. In vivo visualization of tau pathology is now available using several tau positron emission tomography tracers. Among these radioprobes, PM-PBB3 allows high-contrast imaging of tau deposits in the brains of patients with diverse disorders and tauopathy mouse models. Selective degradation of pathological tau species by the ubiquitin-proteasome system or autophagy machinery is a potential therapeutic strategy. Alternatively, the non-cell-autonomous clearance of pathological tau species through neuron-glia networks could be reinforced as a disease-modifying treatment. In addition, the development of neuroinflammatory biomarkers is required for understanding the contribution of immunocompetent cells in the brain to preventing neurodegeneration. This review provides an overview of the current research and development of diagnostic and therapeutic agents targeting divergent tau pathologies.

Sensory disturbances in Creutzfeldt-Jakob disease.

BACKGROUND: Creutzfeldt-Jakob disease (CJD) is a fatal neurodegenerative disease characterized by rapidly progressive dementia, motor impairments, and psychiatric symptoms. Sensory disturbances were occasionally reported as well. The study aims to describe the sensory symptoms of the disease. METHODS: The CJD Israeli National Database was screened for patients who presented sensory symptoms throughout the disease course. Symptoms, characteristics, and distribution were reviewed and the demographic and clinical data (sex, etiologies of the disease, age of onset, disease duration, neurological exam finding, tau protein level, EEG and MRI findings) were compared with the demographics and clinical data of CJD without sensory symptoms. Then, the patients with sensory symptoms were divided into patients with symptom distribution consistent with peripheral nervous system (PNS) involvement and central nervous system (CNS) involvement. The demographics and clinical data of the 2 groups were compared. RESULTS: Eighty-four CJD patients with sensory symptoms and 645 CJD patients without sensory symptoms were included in the study. Sensory symptoms were more common in genetic E200K CJD patients (14.6% vs. 5.6% respectively, p = 0.0005) (chi-squared test). Numbness and neuropathic pain were the most common symptoms and distribution of symptoms of "stocking gloves" with decreased deep tendon reflexes suggesting peripheral neuropathy in 44% of the patients. In these patients, the classical EEG findings of Periodic Sharp Wave Complexes were less often found (58% vs. 22%, p = 0.02) (chi-squared test). CONCLUSIONS: Sensory symptoms are more common in E200K patients and often follow peripheral neuropathy distribution that suggests PNS involvement.

Current Updates on the Role of MicroRNA in the Diagnosis and Treatment of Neurodegenerative Diseases.

BACKGROUND: MicroRNAs (miRNA) are small noncoding RNAs that play a significant role in the regulation of gene expression. The literature has explored the key involvement of miRNAs in the diagnosis, prognosis, and treatment of various neurodegenerative diseases (NDD), such as Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). The miRNA regulates various signalling pathways; its dysregulation is involved in the pathogenesis of NDD. OBJECTIVE: The present review is focused on the involvement of miRNAs in the pathogenesis of NDD and their role in the treatment or management of NDD. The literature provides comprehensive and cutting-edge knowledge for students studying neurology, researchers, clinical psychologists, practitioners, pathologists, and drug development agencies to comprehend the role of miRNAs in the NDD's pathogenesis, regulation of various genes/signalling pathways, such as α-synuclein, P53, amyloid-ß, high mobility group protein (HMGB1), and IL-1ß, NMDA receptor signalling, cholinergic signalling, etc. Methods: The issues associated with using anti-miRNA therapy are also summarized in this review. The data for this literature were extracted and summarized using various search engines, such as Google Scholar, Pubmed, Scopus, and NCBI using different terms, such as NDD, PD, AD, HD, nanoformulations of mRNA, and role of miRNA in diagnosis and treatment. RESULTS: The miRNAs control various biological actions, such as neuronal differentiation, synaptic plasticity, cytoprotection, neuroinflammation, oxidative stress, apoptosis and chaperone-mediated autophagy, and neurite growth in the central nervous system and diagnosis. Various miRNAs are involved in the regulation of protein aggregation in PD and modulating ß-secretase activity in AD. In HD, mutation in the huntingtin (Htt) protein interferes with Ago1 and Ago2, thus affecting the miRNA biogenesis. Currently, many anti-sense technologies are in the research phase for either inhibiting or promoting the activity of miRNA. CONCLUSION: This review provides new therapeutic approaches and novel biomarkers for the diagnosis and prognosis of NDDs by using miRNA.

Identifying and Diagnosing TDP-43 Neurodegenerative Diseases in Psychiatry.

Neuropsychiatric symptoms (NPS) are common manifestations of neurodegenerative disorders and are often early signs of those diseases. Among those neurodegenerative diseases, TDP-43 proteinopathies are an increasingly recognized cause of early neuropsychiatric manifestations. TDP-43-related diseases include frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and Limbic-Predominant Age-Related TDP-43 Encephalopathy (LATE). The majority of TDP-43-related diseases are sporadic, but a significant proportion is hereditary, with progranulin (GRN) mutations and C9orf72 repeat expansions as the most common genetic etiologies. Studies reveal that NPS can be the initial manifestation of those diseases or can complicate disease course, but there is a lack of awareness among clinicians about TDP-43-related diseases, which leads to common diagnostic mistakes or delays. There is also emerging evidence that TDP-43 accumulations could play a role in late-onset primary psychiatric disorders. In the absence of robust biomarkers for TDP-43, the diagnosis remains primarily based on clinical assessment and neuroimaging. Given the association with psychiatric symptoms, clinical psychiatrists have a key role in the early identification of patients with TDP-43-related diseases. This narrative review provides a comprehensive overview of the pathobiology of TDP-43, resulting clinical presentations, and associated neuropsychiatric manifestations to help guide clinical practice.