Plasma extracellular vesicles tau and β-amyloid as biomarkers of cognitive dysfunction of Parkinson's disease

Food-derived vesicles as immunomodulatory drivers: Current knowledge, gaps, and perspectives

Extracellular vesicles (EVs) are lipid-bound membrane vesicles released from cells, containing active compounds, which can be found in different foods. In this review, the role of food-derived vesicles (FDVs) as immunomodulatory drivers is summarized, with a focus on sources, isolation techniques and yields, as well as bioavailability and potential health implications. In addition, gaps and perspectives detected in this research field have been highlighted. FDVs have been efficiently extracted from different sources, and differential ultracentrifugation seems to be the most adequate isolation technique, with yields ranging from 108 to 1014 EV particles/mL. Animal studies show promising results in how these FDVs might regulate different pathways related to inflammation. Further investigation on the production of stable components in a cost-effective way, as well as human studies demonstrating safety and health-promoting properties, since scarce information has been reported until now, in the context of modulating the immune system are needed.

Diffusion Tensor Imaging-Along the Perivascular-Space Index Is Associated with Disease Progression in Parkinson's Disease

BACKGROUND

The glymphatic clearance pathway is a waste clearance system that allows for removal of soluble proteins such as amyloid β (Aβ) from the brain. Higher Aβ levels are associated with cognitive dysfunction in Parkinson's disease (PD). Diffusion tensor imaging-along the perivascular space (DTI-ALPS) is an imaging measure proposed to indirectly measure glymphatic function.

OBJECTIVES

Evaluate differences in DTI-ALPS-index between PD and healthy controls (HC) and characterize relationships between this proposed measure of glymphatic clearance, cognition, and disease severity in PD.

METHODS

PD (n = 32) and HC (n = 23) participants underwent brain imaging to assess DTI-ALPS. PD participants were classified as PD-normal cognition (PD-NC; n = 20) or PD-mild cognitive impairment (PD-MCI; n = 12) based on a Level II comprehensive cognitive assessment. A subgroup of PD participants (n = 21) returned for annual assessments for up to 4 years after baseline. Longitudinal outcomes included changes in performance on the comprehensive cognitive assessment and changes in the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

RESULTS

PD participants had lower DTI-ALPS-index compared to HC. PD participants classified as PD-MCI had significantly lower DTI-ALPS-index compared to PD-NC. Lower DTI-ALPS-index at baseline was associated with longitudinal cognitive decline and worse longitudinal disease severity.

CONCLUSIONS

Glymphatic clearance, as measured with DTI-ALPS, has potential to serve as a marker of longitudinal disease progression. Interventions targeting glymphatic function should be explored for potential to slow cognitive decline in PD. © 2024 International Parkinson and Movement Disorder Society.

Single-molecule characterization of salivary protein aggregates from Parkinson's disease patients: a pilot study

Saliva is a convenient and accessible biofluid that has potential as a future diagnostic tool for Parkinson's disease. Candidate diagnostic tests for Parkinson's disease to date have predominantly focused on measurements of α-synuclein in CSF, but there is a need for accurate tests utilizing more easily accessible sample types. Prior studies utilizing saliva have used bulk measurements of salivary α-synuclein to provide diagnostic insight. Aggregate structure may influence the contribution of α-synuclein to disease pathology. Single-molecule approaches can characterize the structure of individual aggregates present in the biofluid and may, therefore, provide greater insight than bulk measurements. We have employed an antibody-based single-molecule pulldown assay to quantify salivary α-synuclein and amyloid-β peptide aggregate numbers and subsequently super-resolved captured aggregates using direct Stochastic Optical Reconstruction Microscopy to describe their morphological features. We show that the salivary α-synuclein aggregate/amyloid-β aggregate ratio is increased almost 2-fold in patients with Parkinson's disease (n = 20) compared with controls (n = 20, P < 0.05). Morphological information also provides insight, with saliva from patients with Parkinson's disease containing a greater proportion of larger and more fibrillar amyloid-β aggregates than control saliva (P < 0.05). Furthermore, the combination of count and morphology data provides greater diagnostic value than either measure alone, distinguishing between patients with Parkinson's disease (n = 17) and controls (n = 18) with a high degree of accuracy (area under the curve = 0.87, P < 0.001) and a larger dynamic range. We, therefore, demonstrate for the first time the application of highly sensitive single-molecule imaging techniques to saliva. In addition, we show that aggregates present within saliva retain relevant structural information, further expanding the potential utility of saliva-based diagnostic methods.

Machine learning for the detection and diagnosis of cognitive impairment in Parkinson's Disease: A systematic review

BACKGROUND

Parkinson's Disease is the second most common neurological disease in over 60s. Cognitive impairment is a major clinical symptom, with risk of severe dysfunction up to 20 years post-diagnosis. Processes for detection and diagnosis of cognitive impairments are not sufficient to predict decline at an early stage for significant impact. Ageing populations, neurologist shortages and subjective interpretations reduce the effectiveness of decisions and diagnoses. Researchers are now utilising machine learning for detection and diagnosis of cognitive impairment based on symptom presentation and clinical investigation. This work aims to provide an overview of published studies applying machine learning to detecting and diagnosing cognitive impairment, evaluate the feasibility of implemented methods, their impacts, and provide suitable recommendations for methods, modalities and outcomes.

METHODS

To provide an overview of the machine learning techniques, data sources and modalities used for detection and diagnosis of cognitive impairment in Parkinson's Disease, we conducted a review of studies published on the PubMed, IEEE Xplore, Scopus and ScienceDirect databases. 70 studies were included in this review, with the most relevant information extracted from each. From each study, strategy, modalities, sources, methods and outcomes were extracted.

RESULTS

Literatures demonstrate that machine learning techniques have potential to provide considerable insight into investigation of cognitive impairment in Parkinson's Disease. Our review demonstrates the versatility of machine learning in analysing a wide range of different modalities for the detection and diagnosis of cognitive impairment in Parkinson's Disease, including imaging, EEG, speech and more, yielding notable diagnostic accuracy.

CONCLUSIONS

Machine learning based interventions have the potential to glean meaningful insight from data, and may offer non-invasive means of enhancing cognitive impairment assessment, providing clear and formidable potential for implementation of machine learning into clinical practice.

Potential Exosome Biomarkers for Parkinson's Disease Diagnosis: A Systematic Review and Meta-Analysis

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. Given its prevalence, reliable biomarkers for early diagnosis are required. Exosomal proteins within extracellular nanovesicles are promising candidates for diagnostic, screening, prognostic, and disease monitoring purposes in neurological diseases such as PD. This review aims to evaluate the potential of extracellular vesicle proteins or miRNAs as biomarkers for PD. A comprehensive literature search until January 2024 was conducted across multiple databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, to identify relevant studies reporting exosome biomarkers in blood samples from PD patients. Out of 417 articles screened, 47 studies were selected for analysis. Among exosomal protein biomarkers, α-synuclein, tau, Amyloid β 1-42, and C-X-C motif chemokine ligand 12 (CXCL12) were identified as significant markers for PD. Concerning miRNA biomarkers, miRNA-24, miR-23b-3p, miR-195-3p, miR-29c, and mir-331-5p are promising across studies. α-synuclein exhibited increased levels in PD patients compared to control groups in twenty-one studies, while a decrease was observed in three studies. Our meta-analysis revealed a significant difference in total exosomal α-synuclein levels between PD patients and healthy controls (standardized mean difference [SMD] = 1.369, 95% confidence interval [CI] = 0.893 to 1.846, p < 0.001), although these results are limited by data availability. Furthermore, α-synuclein levels significantly differ between PD patients and healthy controls (SMD = 1.471, 95% CI = 0.941 to 2.002, p < 0.001). In conclusion, certain exosomal proteins and multiple miRNAs could serve as potential biomarkers for diagnosis, prognosis prediction, and assessment of disease progression in PD.

The Role of Extracellular Vesicles in Metabolic Diseases

Extracellular vesicles represent a group of structures with the capacity to communicate with different cells and organs. This complex network of interactions can regulate multiple physiological processes in the organism. Very importantly, these processes can be altered during the appearance of different diseases including cancer, metabolic diseases, etc. In addition, these extracellular vesicles can transport different cargoes, altering the initiation of the disease, driving the progression, or even accelerating the pathogenesis. Then, we have explored the implication of these structures in different alterations such as pancreatic cancer, and in different metabolic alterations such as diabetes and its complications and non-alcoholic fatty liver disease. Finally, we have explored in more detail the communication between the liver and the pancreas. In summary, extracellular vesicles represent a very efficient system for the communication among different tissues and permit an efficient system as biomarkers of the disease, as well as being involved in the extracellular-vesicle-mediated transport of molecules, serving as a potential therapy for different diseases.

Plasma extracellular vesicle synaptic proteins as biomarkers of clinical progression in patients with Parkinson's disease

Synaptic dysfunction plays a key role in Parkinson's disease (PD), and plasma extracellular vesicle (EV) synaptic proteins are emerging as biomarkers for neurodegenerative diseases. Assessment of plasma EV synaptic proteins for their efficacy as biomarkers in PD and their relationship with disease progression was conducted. In total, 144 participants were enrolled, including 101 people with PD (PwP) and 43 healthy controls (HCs). The changes in plasma EV synaptic protein levels between baseline and 1-year follow-up did not differ significantly in both PwP and HCs. In PwP, the changes in plasma EV synaptic protein levels were significantly associated with the changes in Unified Parkinson's Disease Rating Scale (UPDRS)-II and III scores. Moreover, PwP with elevated levels (first quartile) of any one plasma EV synaptic proteins (synaptosome-associated protein 25, growth-associated protein 43 or synaptotagmin-1) had significantly greater disease progression in UPDRS-II score and the postural instability and gait disturbance subscore in UPDRS-III than did the other PwP after adjustment for age, sex, and disease duration. The promising potential of plasma EV synaptic proteins as clinical biomarkers of disease progression in PD was suggested. However, a longer follow-up period is warranted to confirm their role as prognostic biomarkers.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Cerebrospinal fluid biomarkers profile in scans without evidence of dopaminergic deficits (SWEDD)

Background

A small proportion of patients with clinical parkinsonism have normal transporter-single photon emission computed tomography (DaTSPECT) which is commonly defined as scans without evidence of dopaminergic deficits (SWEDD). A better understanding of SWEDD can improve the current therapeutic options and appropriate disease monitoring.

Aim

We aimed to assess CSF biomarkers levels including α-synuclein (α-syn), amyloid βeta (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) in SWEDD and investigate the longitudinal alteration in the CSF profile.

Methods

In total, 406 early-stage PD, 58 SWEDD, and 187 healthy controls (HCs) were entered into our study from PPMI. We compared the level of CSF biomarkers at baseline, six months, one year, and two years. Furthermore, the longitudinal alteration of CSF biomarkers was explored in each group using linear mixed models.

Results

There was no significant difference in the level of CSF α-syn Aβ1-42, t-tau, and p-tau between HCs and SWEDD at different time points. Investigating the level of CSF α-syn in PD and SWEDD showed a significant difference at one (p = 0.016) and two years (p = 0.006). Also, we observed a significant difference in the level of CSF Aβ1-42 between SWEDD and PD at one year (p = 0.012). Moreover, there was a significant difference in the level of CSF t-tau between SWEDD and PD subjects at one (p = 0.013) and two years (p = 0.017). Furthermore, there was a significant difference in the level of CSF p-tau between SWEDD and PD groups at two years visits (p = 0.030). Longitudinal analysis showed a significant decrease after one (p = 0.029) and two years (p = 0.002) from baseline in the level of CSF α-syn only in the PD group. Also, we observed that the level of CSF Aβ1-42 significantly increased after one year in SWEDD (p = 0.031) and decreased after two years from baseline in PD subjects (p = 0.005). Moreover, there was a significant increase in the level of CSF t-tau after two years (p = 0.036) and CSF p-tau after six months from baseline in SWEDD subjects (p = 0.011).

Conclusion

This finding suggests a faster neurodegeneration process in PD patients compared to SWEDD at least based on these biomarkers. Future studies with longer follow-up duration and more sample sizes are necessary to validate our results.

Extracellular vesicles from bodily fluids for the accurate diagnosis of Parkinson's disease and related disorders: A systematic review and diagnostic meta-analysis

Parkinsonian disorders, including Parkinson's disease (PD), multiple system atrophy (MSA), dementia with Lewy body (DLB), corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are often misdiagnosed due to overlapping symptoms and the absence of precise biomarkers. Furthermore, there are no current methods to ascertain the progression and conversion of prodromal conditions such as REM behaviour disorder (RBD). Extracellular vesicles (EVs), containing a mixture of biomolecules, have emerged as potential sources for parkinsonian diagnostics. However, inconsistencies in previous studies have left their diagnostic potential unclear. We conducted a meta-analysis, following PRISMA guidelines, to assess the diagnostic accuracy of general EVs isolated from various bodily fluids, including cerebrospinal fluid (CSF), plasma, serum, urine or saliva, in differentiating patients with parkinsonian disorders from healthy controls (HCs). The meta-analysis included 21 studies encompassing 1285 patients with PD, 24 with MSA, 105 with DLB, 99 with PSP, 101 with RBD and 783 HCs. Further analyses were conducted only for patients with PD versus HCs, given the limited number for other comparisons. Using bivariate and hierarchal receiver operating characteristics (HSROC) models, the meta-analysis revealed moderate diagnostic accuracy in distinguishing patients with PD from HCs, with substantial heterogeneity and publication bias. The trim-and-fill method revealed at least two missing studies with null or low diagnostic accuracy. CSF-EVs showed better overall diagnostic accuracy, while plasma-EVs had the lowest performance. General EVs demonstrated higher diagnostic accuracy compared to CNS-originating EVs, which are more time-consuming, labour- and cost-intensive to isolate. In conclusion, while holding promise, utilizing biomarkers in general EVs for PD diagnosis remains unfeasible due to existing challenges. The focus should shift toward harmonizing the field through standardization, collaboration, and rigorous validation. Current efforts by the International Society For Extracellular Vesicles (ISEV) aim to enhance the accuracy and reproducibility of EV-related research through rigor and standardization, aiming to bridge the gap between theory and practical clinical application.

Tau: a biomarker of Huntington's disease

Developing effective treatments for patients with Huntington's disease (HD)-a neurodegenerative disorder characterized by severe cognitive, motor and psychiatric impairments-is proving extremely challenging. While the monogenic nature of this condition enables to identify individuals at risk, robust biomarkers would still be extremely valuable to help diagnose disease onset and progression, and especially to confirm treatment efficacy. If measurements of cerebrospinal fluid neurofilament levels, for example, have demonstrated use in recent clinical trials, other proteins may prove equal, if not greater, relevance as biomarkers. In fact, proteins such as tau could specifically be used to detect/predict cognitive affectations. We have herein reviewed the literature pertaining to the association between tau levels and cognitive states, zooming in on Alzheimer's disease, Parkinson's disease and traumatic brain injury in which imaging, cerebrospinal fluid, and blood samples have been interrogated or used to unveil a strong association between tau and cognition. Collectively, these areas of research have accrued compelling evidence to suggest tau-related measurements as both diagnostic and prognostic tools for clinical practice. The abundance of information retrieved in this niche of study has laid the groundwork for further understanding whether tau-related biomarkers may be applied to HD and guide future investigations to better understand and treat this disease.

High resolution imaging and analysis of extracellular vesicles using mass spectral imaging and machine learning

Extracellular vesicles (EVs) are potentially useful biomarkers for disease detection and monitoring. Development of a label-free technique for imaging and distinguishing small volumes of EVs from different cell types and cell states would be of great value. Here, we have designed a method to explore the chemical changes in EVs associated with neuroinflammation using Time-of-Flight Secondary Ion Mass spectrometry (ToF-SIMS) and machine learning (ML). Mass spectral imaging was able to identify and differentiate EVs released by microglia following lipopolysaccharide (LPS) stimulation compared to a control group. This process requires a much smaller sample size (1 µL) than other molecular analysis methods (up to 50 µL). Conspicuously, we saw a reduction in free cysteine thiols (a marker of cellular oxidative stress associated with neuroinflammation) in EVs from microglial cells treated with LPS, consistent with the reduced cellular free thiol levels measured experimentally. This validates the synergistic combination of ToF-SIMS and ML as a sensitive and valuable technique for collecting and analysing molecular data from EVs at high resolution.

Extracellular Vesicles for the Diagnosis of Parkinson's Disease: Systematic Review and Meta-Analysis

Parkinson's disease (PD) biomarkers are needed by both clinicians and researchers (for diagnosis, identifying study populations, and monitoring therapeutic response). Imaging, genetic, and biochemical biomarkers have been widely studied. In recent years, extracellular vesicles (EVs) have become a promising material for biomarker development. Proteins and molecular material from any organ, including the central nervous system, can be packed into EVs and transported to the periphery into easily obtainable biological specimens like blood, urine, and saliva. We performed a systematic review and meta-analysis of articles (published before November 15, 2022) reporting biomarker assessment in EVs in PD patients and healthy controls (HCs). Biomarkers were analyzed using random effects meta-analysis and the calculated standardized mean difference (Std.MD). Several proteins and ribonucleic acids have been identified in EVs in PD patients, but only α-synuclein (aSyn) and leucine-rich repeat kinase 2 (LRRK2) were reported in sufficient studies (n = 24 and 6, respectively) to perform a meta-analysis. EV aSyn was significantly increased in neuronal L1 cell adhesion molecule (L1CAM)-positive blood EVs in PD patients compared to HCs (Std.MD = 1.84, 95% confidence interval = 0.76-2.93, P = 0.0009). Further analysis of the biological sample and EV isolation method indicated that L1CAM-IP (immunoprecipitation) directly from plasma was the best isolation method for assessing aSyn in PD patients. Upcoming neuroprotective clinical trials immediately need peripheral biomarkers for identifying individuals at risk of developing PD. Overall, the improved sensitivity of assays means they can identify biomarkers in blood that reflect changes in the brain. CNS-derived EVs in blood will likely play a major role in biomarker development in the coming years. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Observing Extracellular Vesicles Originating from Endothelial Cells in Vivo Demonstrates Improved Astrocyte Function Following Ischemic Stroke via Aggregation-Induced Emission Luminogens

Extracellular vesicles (EVs) obtained from endothelial cells (ECs) have significant therapeutic potential in the clinical management of individuals with ischemic stroke (IS) because they effectively treat ischemic stroke in animal models. However, because molecular probes with both high labeling efficiency and tracer stability are lacking, monitoring the actions of EC-EVs in the brain remains difficult. The specific intracellular targets in the brain that EC-EVs act on to produce their protective effects are still unknown, greatly impeding their use in clinical settings. For this research, we created a probe that possessed aggregation-induced emission (AIE) traits (namely, TTCP), enabling the effective labeling of EC-EVs while preserving their physiological properties. In vitro, TTCP simultaneously had a higher EC-EV labeling efficiency and better tracer stability than the commercial EV tags PKH-67 and DiI. In vivo, TTCP precisely tracked the actions of EC-EVs in a mouse IS model without influencing their protective effects. Furthermore, through the utilization of TTCP, it was determined that astrocytes were the specific cells affected by EC-EVs and that EC-EVs exhibited a safeguarding impact on astrocytes following cerebral ischemia-reperfusion (I/R) injury. These protective effects encompassed the reduction of the inflammatory reaction and apoptosis as well as the enhancement of cell proliferation. Further analysis showed that miRNA-155-5p carried by EC-EVs is responsible for these protective effects via regulation of the c-Fos/AP-1 pathway; this information provided a strategy for IS therapy. In conclusion, TTCP has a high EC-EV labeling efficiency and favorable in vivo tracer stability during IS therapy. Moreover, EC-EVs are absorbed by astrocytes during cerebral I/R injury and promote the restoration of neurological function through the regulation of the c-Fos/AP-1 signaling pathway.

Clinical Potential of Mesenchymal Stem Cell-Derived Exosomes in Bone Regeneration

Bone metabolism is regulated by osteoblasts, osteoclasts, osteocytes, and stem cells. Pathologies such as osteoporosis, osteoarthritis, osteonecrosis, and traumatic fractures require effective treatments that favor bone formation and regeneration. Among these, cell therapy based on mesenchymal stem cells (MSC) has been proposed. MSC are osteoprogenitors, but their regenerative activity depends in part on their paracrine properties. These are mainly mediated by extracellular vesicle (EV) secretion. EV modulates regenerative processes such as inflammation, angiogenesis, cell proliferation, migration, and differentiation. Thus, MSC-EV are currently an important tool for the development of cell-free therapies in regenerative medicine. This review describes the current knowledge of the effects of MSC-EV in the different phases of bone regeneration. MSC-EV has been used by intravenous injection, directly or in combination with different types of biomaterials, in preclinical models of bone diseases. They have shown great clinical potential in regenerative medicine applied to bone. These findings should be confirmed through standardization of protocols, a better understanding of the mechanisms of action, and appropriate clinical trials. All that will allow the translation of such cell-free therapy to human clinic applications.

Extracellular vesicles: Critical bilateral communicators in periphery-brain crosstalk in central nervous system disorders

Growing evidence shows that there is a comorbid mechanism between the central nervous system (CNS) and the peripheral organs. The bilateral transmission of signal molecules in periphery-brain crosstalk plays an important role in the underlying mechanism, which result from complex networks of neurohumoral circuits. Secreted by almost all cells and considered innovative information transport systems, extracellular vesicles (EVs) encapsulate and deliver nucleic acids, proteins, lipids, and various other bioactive regulators. Moreover, EVs can cross the blood-brain barrier (BBB), they are also identified primarily as essential communicators between the periphery and the CNS. In addition to transporting molecules under physiological or pathological conditions, EVs also show novel potential in targeted drug delivery. In this review, we discuss the mechanisms implicated in the transport of EVs in crosstalk between the peripheral and the central immune systems as well as in crosstalk between the peripheral organs and the brain in CNS disorders, especially in neurodegenerative diseases, stroke, and trauma. This work will help in elucidating the contributions of EVs to brain health and disorders, and promote the development of new strategies for minimally invasive treatment.

Cytokine profiles of plasma extracellular vesicles as progression biomarkers in Parkinson's disease

BACKGROUND

Inflammation contributes substantially to the pathogenesis of Parkinson's disease (PD). Plasma extracellular vesicle (EV)-derived cytokines are emerging biomarkers of inflammation. We conducted a longitudinal study of the plasma EV-derived cytokine profiles of people with PD (PwP).

METHODS

A total of 101 people with mild to moderate PD and 45 healthy controls (HCs) were recruited, and they completed motor assessments (Unified Parkinson Disease Rating Scale [UPDRS]) and cognitive tests at baseline and 1-year follow-up. We isolated the participants' plasma EVs and analyzed their levels of cytokines, including interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, and transforming growth factor (TGF)-β.

RESULTS

We noted no significant changes in the plasma EV-derived cytokine profiles of the PwPs and HCs between baseline and the 1-year follow-up. Among the PwP, changes in plasma EV-derived IL-1β, TNF-α and IL-6 levels were significantly associated with changes in the severity of postural instability and gait disturbance (PIGD) and cognition. Baseline plasma EV-derived IL-1β, TNF-α, IL-6, and IL-10 levels were significantly associated with the severity of PIGD and cognitive symptoms at follow-up, and PwP with elevated IL-1β and IL-6 levels exhibited significant progression of PIGD over the study period.

CONCLUSION

These results suggested the role of inflammation in PD progression. In addition, baseline levels of plasma EV-derived proinflammatory cytokines can be used to predict the progression of PIGD, the most severe motor symptom of PD. Additional studies with longer follow-up periods are necessary, and plasma EV-derived cytokines may serve as effective biomarkers of PD progression.

Plasma extracellular vesicle tau, β-amyloid, and α-synuclein and the progression of Parkinson's disease: a follow-up study

Background

Plasma extracellular vesicle (EV) contents are promising biomarkers of Parkinson's disease (PD). The pathognomonic proteins of PD, including α-synuclein, tau, and β-amyloid, are altered in people with PD (PwP) and are associated with clinical presentation in previous cross-sectional studies. However, the dynamic changes in these plasma EV proteins in PwP and their correlation with clinical progression remain unclear.

Objective

We investigated the dynamic changes in plasma EV α-synuclein, tau, and β-amyloid and their correlation with/prediction of clinical progression in PwP.

Design

A cohort study.

Methods

In total, 103 PwP and 37 healthy controls (HCs) completed baseline assessment and 1-year follow-up. Clinical assessments included Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III, Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). Plasma EVs were isolated, and immunomagnetic reduction-based immunoassay was used to assess α-synuclein, tau, and β-amyloid 1-42 (Aβ1-42) levels within the EVs.

Results

Compared with HCs, significant differences were noted in the annual changes in all three EV pathognomonic proteins in PwP. Although the absolute changes in plasma EV pathognomonic proteins did not significantly correlate with clinical changes, PwP with elevated baseline plasma EV tau (upper-half) levels demonstrated significantly greater decline in motor and cognition, and increased plasma EV α-synuclein levels were associated with postural instability and the gait disturbance motor subtype. For PwP with elevated levels of all three biomarkers, clinical deterioration was significant, as indicated by UPDRS-II scores, postural instability and gait disturbance subscores of UPDRS-III, and MMSE score.

Conclusion

The combination of plasma EV α-synuclein, tau, and Aβ1-42 may identify PwP with a high risk of deterioration. Our findings can elucidate the interaction between these pathognomonic proteins, and they may serve as treatment response markers and can be applied in treatment approaches for disease modification.

Aβ1-42-containing platelet-derived extracellular vesicle is associated with cognitive decline in Parkinson's disease

Background

Cortical amyloid deposition is a common observation in Parkinson's disease dementia (PDD) patients. Aβ1-42 is linked to a more rapid progression of dementia. Platelets, which degranulate upon activation, are a primary source of Aβ. It has been repeatedly reported that peripheral extracellular vesicles (EVs) can partially reach the central nervous system. Thus, we speculate that activated platelet-derived Aβ1-42-containing EVs (PEV-Aβ1-42) play a crucial role in the cognitive decline of PD patients.

Methods

The study included 189 participants: 66 with non-dementia PD, 73 with PDD, and 50 healthy controls. All participants underwent blood collection and clinical assessments. Twenty PD patients underwent re-examination and repeated blood collection 14 months later. A nano-scale flow cytometry assay was used to detect PEVs and PEV-Aβ1-42 using fluorescence-labeled CD62P and Aβ1-42 antibodies.

Results

Parkinson's disease dementia patients had higher PEV-Aβ1-42 concentrations than healthy controls (p = 0.028). The ratio of PEV-Aβ1-42 to PEV was significantly higher in PDD patients compared to those in non-dementia PD and healthy controls (p _PD-ND < 0.001, p _HC = 0.041). The PEV-Aβ1-42/PEV ratio appears to influence the odds of developing dementia (OR = 1.76, p < 0.001). The change in the PEV-Aβ1-42/PEV ratio was also correlated with cognitive decline over 14 months (r = -0.447, p < 0.05).

Conclusion

The plasma PEV-Aβ1-42/PEV ratio may serve as a diagnostic and prognostic biomarker for PDD patients.

Early Diagnosis of Brain Diseases Using Artificial Intelligence and EV Molecular Data: A Proposed Noninvasive Repeated Diagnosis Approach

Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invasive and enable repeatable measurements based on body fluids. However, EVs from various cells and organs are mixed in the blood, acting as potential obstacles for brain diagnostic systems using BDEVs. Therefore, it is important to screen appropriate brain EV markers to isolate BDEVs in blood. Here, we established a strategy for screening potential BDEV biomarkers. To collect various molecular data from the BDEVs, we propose that the sensitivity and specificity of the diagnostic system could be enhanced using machine learning and AI analysis. This BDEV-based diagnostic strategy could be used to diagnose various brain diseases and will help prevent disease through early diagnosis and early treatment.

Identification of exosomal biomarkers and its optimal isolation and detection method for the diagnosis of Parkinson's disease: A systematic review and meta-analysis

Recently, there has been growing interest in exosomal biomarkers for their active targeting and specificity for delivering their cargos (proteins, lipids, nucleic acids) from the parent cell to the recipient cell. Currently, the clinical diagnosis of Parkinson's disease (PD) is mainly based on a clinician's neuropsychological examination and motor symptoms (e.g., bradykinesia, rigidity, postural instability, and resting tremor). However, this diagnosis method is not accurate due to overlapping criteria of other neurodegenerative diseases. Exosomes are differentially expressed in PD and a combination of types and contents of exosomes might be used as a biomarker in PD. Here, we systematically reviewed and meta-analyzed exosomal contents, types and sources of exosomes, method of isolation, and protein quantification tools to determine the optimum exosome-related attributes for PD diagnosis. Pubmed, Embase, and ISI Web of Science were searched for relevant studies. 25 studies were included in the meta-analysis. The Ratio of Mean (RoM) with 95% confidence intervals (CI) was calculated to estimate the effect size. Biomarker performances were rated by random-effects meta-analysis with the Restricted Maximum Likelihood (REML) method. The study protocol is available at PROSPERO (CRD42022331885). Exosomal α-synuclein (α-Syn) was significantly altered in PD patients from healthy controls [RoM = 1.67, 95% CI (0.99 to 2.35); p = 0.00] followed by tau [RoM = 1.33, 95% CI (0.79 to 1.87); p = 0.00], PS-129 [RoM = 0.97, 95% CI (0.54 to 1.40); p = 0.00], and DJ-1/PARK7 [RoM = 0.93, 95% CI (0.64 to 1.21); p = 0.00]. Central nervous system derived L1CAM exosome [RoM = 1.24, 95% CI (1.04 to 1.45); p = 0.00] from either plasma [RoM = 1.35, 95% CI (1.09 to 1.61); p = 0.00]; or serum [RoM = 1.47, 95% CI (1.05 to 1.90); p = 0.00] has been found the optimum type of exosome. The exosome isolation by ExoQuick [RoM = 1.16, 95% CI (0.89 to 1.43); p = 0.00] and protein quantification method by ELISA [RoM = 1.28, 95% CI (1.15 to 1.41); p = 0.00] has been found the optimum isolation and quantification method, respectively for PD diagnosis. This meta-analysis suggests that α-Syn in L1CAM exosome derived from blood, isolated by ExoQuick kit, and quantified by ELISA can be used for PD diagnosis.

Blood-based biomarker in Parkinson's disease: potential for future applications in clinical research and practice

The clinical presentation of Parkinson's disease (PD) is both complex and heterogeneous, and its precise classification often requires an intensive work-up. The differential diagnosis, assessment of disease progression, evaluation of therapeutic responses, or identification of PD subtypes frequently remains uncertain from a clinical point of view. Various tissue- and fluid-based biomarkers are currently being investigated to improve the description of PD. From a clinician's perspective, signatures from blood that are relatively easy to obtain would have great potential for use in clinical practice if they fulfill the necessary requirements as PD biomarker. In this review article, we summarize the knowledge on blood-based PD biomarkers and present both a researcher's and a clinician's perspective on recent developments and potential future applications.

Plasma MIA, CRP, and Albumin Predict Cognitive Decline in Parkinson's Disease

OBJECTIVE

Using a multi-cohort, discovery-replication-validation design, we sought new plasma biomarkers that predict which individuals with Parkinson's disease (PD) will experience cognitive decline.

METHODS

In 108 discovery cohort PD individuals and 83 replication cohort PD individuals, we measured 940 plasma proteins on an aptamer-based platform. Using proteins associated with subsequent cognitive decline in both cohorts, we trained a logistic regression model to predict which patients with PD showed fast (> = 1 point drop/year on Montreal Cognitive Assessment [MoCA]) versus slow (< 1 point drop/year on MoCA) cognitive decline in the discovery cohort, testing it in the replication cohort. We developed alternate assays for the top 3 proteins and confirmed their ability to predict cognitive decline - defined by change in MoCA or development of incident mild cognitive impairment (MCI) or dementia - in a validation cohort of 118 individuals with PD. We investigated the top plasma biomarker for causal influence by Mendelian randomization (MR).

RESULTS

A model with only 3 proteins (melanoma inhibitory activity protein [MIA], C-reactive protein [CRP], and albumin) separated fast versus slow cognitive decline subgroups with an area under the curve (AUC) of 0.80 in the validation cohort. The individuals with PD in the validation cohort in the top quartile of risk for cognitive decline based on this model were 4.4 times more likely to develop incident MCI or dementia than those in the lowest quartile. Genotypes at MIA single nucleotide polymorphism (SNP) rs2233154 associated with MIA levels and cognitive decline, providing evidence for MIA's causal influence.

CONCLUSIONS

An easily obtained plasma-based predictor identifies individuals with PD at risk for cognitive decline. MIA may participate causally in development of cognitive decline. ANN NEUROL 2022.

Huntingtin Co-Isolates with Small Extracellular Vesicles from Blood Plasma of TgHD and KI-HD Pig Models of Huntington's Disease and Human Blood Plasma

(1) Background: Huntington’s disease (HD) is rare incurable hereditary neurodegenerative disorder caused by CAG repeat expansion in the gene coding for the protein huntingtin (HTT). Mutated huntingtin (mHTT) undergoes fragmentation and accumulation, affecting cellular functions and leading to neuronal cell death. Porcine models of HD are used in preclinical testing of currently emerging disease modifying therapies. Such therapies are aimed at reducing mHTT expression, postpone the disease onset, slow down the progression, and point out the need of biomarkers to monitor disease development and therapy efficacy. Recently, extracellular vesicles (EVs), particularly exosomes, gained attention as possible carriers of disease biomarkers. We aimed to characterize HTT and mHTT forms/fragments in blood plasma derived EVs in transgenic (TgHD) and knock-in (KI-HD) porcine models, as well as in HD patients’ plasma. (2) Methods: Small EVs were isolated by ultracentrifugation and HTT forms were visualized by western blotting. (3) Results: The full length 360 kDa HTT co-isolated with EVs from both the pig model and HD patient plasma. In addition, a ~70 kDa mutant HTT fragment was specific for TgHD pigs. Elevated total huntingtin levels in EVs from plasma of HD groups compared to controls were observed in both pig models and HD patients, however only in TgHD were they significant (p = 0.02). (4) Conclusions: Our study represents a valuable initial step towards the characterization of EV content in the search for HD biomarkers.