Failure of Biomarkers in Extracellular Vesicles for Parkinson's disease and Related Disorders Diagnosis

Parkinsonian disorders, a puzzle of movement and coordination, go beyond Parkinson's disease. Diagnosing them is complex. Intriguingly, extracellular vesicles, once overlooked, are now under scrutiny. Could they hold clues, or are they misleading us in understanding these baffling conditions?

Published in Neuroscience

Failure of Biomarkers in Extracellular Vesicles for Parkinson's disease and Related Disorders Diagnosis
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Analysis of biomarkers in speculative CNS-enriched extracellular vesicles for parkinsonian disorders: a comprehensive systematic review and diagnostic meta-analysis - Journal of Neurology

Background and objective Parkinsonian disorders, including Parkinson’s disease (PD), multiple system atrophy (MSA), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS), exhibit overlapping early-stage symptoms, complicating definitive diagnosis despite heterogeneous cellular and regional pathophysiology. Additionally, the progression and the eventual conversion of prodromal conditions such as REM behavior disorder (RBD) to PD, MSA, or DLB remain challenging to predict. Extracellular vesicles (EVs) are small, membrane-enclosed structures released by cells, playing a vital role in communicating cell-state-specific messages. Due to their ability to cross the blood–brain barrier into the peripheral circulation, measuring biomarkers in blood-isolated speculative CNS enriched EVs has become a popular diagnostic approach. However, replication and independent validation remain challenging in this field. Here, we aimed to evaluate the diagnostic accuracy of speculative CNS-enriched EVs for parkinsonian disorders. Methods We conducted a PRISMA-guided systematic review and meta-analysis, covering 18 studies with a total of 1695 patients with PD, 253 with MSA, 21 with DLB, 172 with PSP, 152 with CBS, 189 with RBD, and 1288 HCs, employing either hierarchical bivariate models or univariate models based on study size. Results Diagnostic accuracy was moderate for differentiating patients with PD from HCs, but revealed high heterogeneity and significant publication bias, suggesting an inflation of the perceived diagnostic effectiveness. The bias observed indicates that studies with non-significant or lower effect sizes were less likely to be published. Although results for differentiating patients with PD from those with MSA or PSP and CBS appeared promising, their validity is limited due to the small number of involved studies coming from the same research group. Despite initial reports, our analyses suggest that using speculative CNS-enriched EV biomarkers may not reliably differentiate patients with MSA from HCs or patients with RBD from HCs, due to their lesser accuracy and substantial variability among the studies, further complicated by substantial publication bias. Conclusion Our findings underscore the moderate, yet unreliable diagnostic accuracy of biomarkers in speculative CNS-enriched EVs in differentiating parkinsonian disorders, highlighting the presence of substantial heterogeneity and significant publication bias. These observations reinforce the need for larger, more standardized, and unbiased studies to validate the utility of these biomarkers but also call for the development of better biomarkers for parkinsonian disorders.

Parkinsonian disorders are a group of neurological conditions that primarily affect a person’s movement, causing symptoms like tremors, stiffness, and slowness of movement. The most well-known of these is Parkinson's disease, which is caused by the loss of nerve cells in a part of the brain called the substantia nigra. These cells produce dopamine, a chemical that helps control body movement. The same condition that affected Muhammad Ali, one of the greatest boxers of all the time.  However, Parkinsonian disorders encompass more than just Parkinson's disease. They include multiple system atrophy, dementia with Lewy body, progressive supranuclear palsy, and corticobasal degeneration. Each of these disorders has unique characteristics, but they share the common challenge of disrupted motor functions and often overlap in symptoms, making diagnosis and treatment a complex task.

Extracellular vesicles (EVs) have emerged as a potential source of biomarkers, carrying cell-state-specific messages that reflect the status of their parent cells. These tiny vesicles can traverse the blood-brain barrier (BBB), offering a glimpse into the cellular activities within the central nervous system (CNS). This unique ability positions them as promising candidates for diagnosing Parkinsonian disorders. Researchers are intrigued by the possibility that EVs might contain specific markers indicative of these disorders, potentially revolutionizing early detection and monitoring.

However, this hypothesis faces significant challenges. EVs can be uptaken and recycled by other cells, complicating their interpretation. Even if they originate from the CNS, their content might not accurately reflect the current state of the brain due to this recycling and uptake by different cell types. This raises critical questions about the reliability of EVs as mirrors of CNS conditions. Can they truly be used for biomarker discovery in Parkinsonian disorders, or do they present a misleading picture? To address these uncertainties, a comprehensive meta-analysis was conducted. The findings from this study provide essential insights, potentially reshaping our understanding of the role of EVs in diagnosing these complex neurological conditions

The meta-analysis embarked on an extensive evaluation of what are often referred to as speculative CNS-enriched extracellular vesicles, in the context of Parkinsonian disorders. By encompassing all studies available to date, it aimed to determine if these vesicles could reliably distinguish between various Parkinsonian conditions and healthy controls. However, the outcome of this analysis indicated that these CNS-enriched markers found within extracellular vesicles fell short of expectations. They did not consistently differentiate between the disorders or in comparison with healthy individuals, casting doubt on their touted potential as diagnostic tools. This finding is critical, especially considering the challenges of publication bias, where results favoring positive outcomes are more likely to be reported. Furthermore, the analysis uncovered a significant degree of heterogeneity across the studies, with variances in experimental approaches and patient populations. These factors collectively contribute to the skepticism surrounding the speculative CNS-enriched extracellular vesicles as effective biomarkers for Parkinsonian disorders, prompting a reevaluation of their role and utility in diagnosis.

The findings from the comprehensive meta-analysis send a clear message to the scientific community and public funding bodies: it's time to redirect efforts and resources. The pursuit of speculative CNS-enriched extracellular vesicles as biomarkers for Parkinsonian disorders, despite initial promise, has not yielded the expected breakthroughs. Continued investment in this area seems less likely to benefit patients with these disorders. Therefore, researchers and funding agencies should consider pivoting towards more promising avenues of investigation. Exploring alternative biomarkers or novel therapeutic strategies could offer more tangible hope and assistance to those affected by Parkinsonian disorders. This strategic shift in focus and allocation of resources is not just a scientific imperative but a moral one, ensuring that the primary goal remains the improved understanding, diagnosis, and treatment of these complex and debilitating conditions.

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Go to the profile of Hash Brown
almost 2 years ago

Check out the other part of the meta-analysis here!  

https://doi.org/10.1002/jex2.121

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Neurodegenerative diseases
Life Sciences > Biological Sciences > Neuroscience > Neurological Disorders > Neurodegenerative diseases
Neurological Disorders
Life Sciences > Biological Sciences > Neuroscience > Neurological Disorders