Extracellular vesicles from bodily fluids for the accurate diagnosis of Parkinson's disease and related disorders: A systematic review and diagnostic meta‐analysis
Ontology highlight
ABSTRACT:
SUBMITTER: Taha H
PROVIDER: S-EPMC11080888 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Zika virus (ZIKV) is an arbovirus that caused widespread panic beginning in 2015 in northeastern Brazil due to the threatening link between infection and fetal abnormalities such as microcephaly, spontaneous abortions, and stillbirths. Since the epidemic began, the virus has been further investigated, unveiling that the long-term dangers of ZIKV infection go beyond fetal neurological impairment. Characterization of the active infection has proven difficult as only 20% of infected individuals are symptomatic. Additionally, ZIKV is often misdiagnosed due to serological cross-reactivity with similar flaviviruses such as dengue, yellow fever, and West Nile. To date, there is no approved vaccine or therapy against ZIKV, highlighting the urgent need to accurately identify active infection to help minimize the spread of the virus. Herein, we describe a highly specific and sensitive enzyme-linked immunosorbent assay to detect early active ZIKV using neutralizing human monoclonal antibodies isolated from infected patients in Brazil that do not cross-react with dengue viruses 1-4 and bind directly to a ZIKV immunodominant epitope. The calculated limits of detection of active ZIKV fall within the physiological ranges of the virus in human bodily fluids. This selective immunoassay creates the platform required for future translation toward a point-of-care assay for ZIKV, a necessity to diagnose active ZIKV in the remote regions of which it thrives.
| S-EPMC6492231 | biostudies-literature
Project description:BackgroundWith the increasing incidence of colorectal cancer (CRC), its accurate diagnosis is critical and in high demand. However, conventional methods are not ideal due to invasiveness and low accuracy. Herein, we aimed to identify efficient CRC mRNA markers in a non-invasive manner using CRC-derived extracellular vesicles (EVs). The expression levels of EV mRNAs from cancer cell lines were compared with those of a normal cell line using quantitative polymerase chain reaction. Eight markers were evaluated in plasma EVs from CRC patients and healthy controls. The diagnostic value of each marker, individually or in combination, was then determined using recessive operating characteristics analyses and the Mann-Whitney U test.ResultsEight mRNA markers (MYC, VEGF, CDX2, CD133, CEA, CK19, EpCAM, and CD24) were found to be more abundant in EVs derived from cancer cell lines compared to control cell lines. A combination of VEGF and CD133 showed the highest sensitivity (100%), specificity (80%), and accuracy (93%) and an area under the curve of 0.96; hence, these markers were deemed to be the CRC signature. Moreover, this signature was found to be highly expressed in CRC-derived EVs compared to healthy controls.ConclusionsVEGF and CD133 mRNAs comprise a unique CRC signature in EVs that has the potential to act as a novel, non-invasive, and accurate biomarker that would improve the current diagnostic platform for CRC, while also serving to strengthen the value of EV mRNA as diagnostic markers for myriad of diseases.
| S-EPMC7001337 | biostudies-literature
Project description:Extracellular vesicles (EVs) have emerged as a rich source of biomarkers providing diagnostic and prognostic information in diseases such as cancer. Large-scale investigations into the contents of EVs in clinical cohorts are warranted, but a major obstacle is the lack of a rapid, reproducible, efficient, and low-cost methodology to enrich EVs. Here, we demonstrate the applicability of an automated acoustic-based technique to enrich EVs, termed acoustic trapping. Using this technology, we have successfully enriched EVs from cell culture conditioned media and urine and blood plasma from healthy volunteers. The acoustically trapped samples contained EVs ranging from exosomes to microvesicles in size and contained detectable levels of intravesicular microRNAs. Importantly, this method showed high reproducibility and yielded sufficient quantities of vesicles for downstream analysis. The enrichment could be obtained from a sample volume of 300 μL or less, an equivalent to 30 min of enrichment time, depending on the sensitivity of downstream analysis. Taken together, acoustic trapping provides a rapid, automated, low-volume compatible, and robust method to enrich EVs from biofluids. Thus, it may serve as a novel tool for EV enrichment from large number of samples in a clinical setting with minimum sample preparation.
| S-EPMC7556308 | biostudies-literature
Project description:tic disorders (TDs) are a series of childhood neuropsychiatric disorders characterized by invol-untary motor and/or vocal tics and commonly comorbid with several other psychopathological and/or behavioral disorders. In the present study, we aimed to identify serum small extracellular vesicles (sEVs) derived microRNAs (miRNAs) from the serum samples of children for Tic Disorders Diagnosis
2024-07-15 | GSE208318 | GEO
Project description:Background and objectiveParkinsonian 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.MethodsWe 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.ResultsDiagnostic 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.ConclusionOur 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.
| S-EPMC10973014 | biostudies-literature
Project description:BackgroundMutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson's disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.MethodsUtilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).ResultsAfter efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.ConclusionsThese findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.
| S-EPMC10172329 | biostudies-literature
Project description:BackgroundParkinson's disease is generally asymptomatic at earlier stages. At an early stage, there is an extensive progression in the neuropathological hallmarks, although, at this stage, diagnosis is not possible with currently available diagnostic methods. Therefore, the pressing need is for susceptibility risk biomarkers that can aid in better diagnosis and therapeutics as well can objectively serve to measure the endpoint of disease progression. The role of small extracellular vesicles (sEV) in the progression of neurodegenerative diseases could be potent in playing a revolutionary role in biomarker discovery.MethodsIn our study, the salivary sEV were efficiently isolated by chemical precipitation combined with ultrafiltration from subjects (PD = 70, healthy controls = 26, and prodromal PD = 08), followed by antibody-based validation with CD63, CD9, GAPDH, Flotillin-1, and L1CAM. Morphological characterization of the isolated sEV through transmission electron microscopy. The quantification of sEV was achieved by fluorescence (lipid-binding dye-labeled) nanoparticle tracking analysis and antibody-based (CD63 Alexa fluor 488 tagged sEV) nanoparticle tracking analysis. The total alpha-synuclein (α-synTotal) in salivary sEVs cargo was quantified by ELISA. The disease severity staging confirmation for n = 18 clinically diagnosed Parkinson's disease patients was done by 99mTc-TRODAT-single-photon emission computed tomography.ResultsWe observed a significant increase in total sEVs concentration in PD patients than in the healthy control (HC), where fluorescence lipid-binding dye-tagged sEV were observed to be higher in PD (p = 0.0001) than in the HC using NTA with a sensitivity of 94.34%. In the prodromal PD cases, the fluorescence lipid-binding dye-tagged sEV concentration was found to be higher (p = 0.008) than in HC. This result was validated through anti-CD63 tagged sEV (p = 0.0006) with similar sensitivity of 94.12%. We further validated our findings with the ELISA based on α-synTotal concentration in sEV, where it was observed to be higher in PD (p = 0.004) with a sensitivity of 88.24%. The caudate binding ratios in 99mTc-TRODAT-SPECT represent a positive correlation with sEV concentration (r = 0.8117 with p = 0.0112).ConclusionsIn this study, for the first time, we have found that the fluorescence-tagged sEV has the potential to screen the progression of disease with clinically acceptable sensitivity and can be a potent early detection method for PD.
| S-EPMC10478478 | biostudies-literature
Project description:The classic model of blood pressure regulation by Guyton et al. (Annu Rev Physiol 34:13-46, 1972a; Ann Biomed Eng 1:254-281, 1972b) set a new standard for quantitative exploration of physiological function and led to important new insights, some of which still remain the focus of debate, such as whether the kidney plays the primary role in the genesis of hypertension (Montani et al. in Exp Physiol 24:41-54, 2009a; Exp Physiol 94:382-388, 2009b; Osborn et al. in Exp Physiol 94:389-396, 2009a; Exp Physiol 94:388-389, 2009b). Key to the success of this model was the fact that the authors made the computer code (in FORTRAN) freely available and eventually provided a convivial user interface for exploration of model behavior on early microcomputers (Montani et al. in Int J Bio-med Comput 24:41-54, 1989). Ikeda et al. (Ann Biomed Eng 7:135-166, 1979) developed an offshoot of the Guyton model targeting especially the regulation of body fluids and acid-base balance; their model provides extended renal and respiratory functions and would be a good basis for further extensions. In the interest of providing a simple, useable version of Ikeda et al.'s model and to facilitate further such extensions, we present a practical implementation of the model of Ikeda et al. (Ann Biomed Eng 7:135-166, 1979), using the ODE solver Berkeley Madonna.
| S-EPMC4531145 | biostudies-literature
Project description:Brain disorders are the leading cause of disability worldwide, affecting people's quality of life and causing economic burdens. The current clinical diagnosis of brain disorders relies solely on individual phenotypes and lacks accurate molecular biomarkers. An emerging field of research centers around extracellular vesicles (EVs), nanoscale membrane vesicles which can easily cross the blood-brain barrier. EVs in the blood are derived from various tissues, including the brain. Therefore, purifying central nervous system (CNS)-derived EVs from the blood and analyzing their contents may be a relatively non-invasive way to analyze brain molecular alterations and identify biomarkers in brain disorders. Recently, methods for capturing neuron-derived EVs (NDEs), astrocyte-derived EVs (ADEs), and oligodendrocyte-derived EVs (ODEs) in peripheral blood were reported. In this article, we provide an overview of the research history of EVs in the blood, specifically focusing on biomarker findings in six major brain disorders (Alzheimer's disease, Parkinson's disease, schizophrenia, bipolar disorder, depression, and autism spectrum disorder). Additionally, we discuss the methodology employed for testing CNS-derived EVs. Among brain disorders, Alzheimer's disease has received the most extensive attention in EV research to date. Most studies focus on specific molecules, candidate proteins, or miRNAs. Notably, the most studied molecules implicated in the pathology of these diseases, such as Aβ, tau, and α-synuclein, exhibit good reproducibility. These findings suggest that CNS-derived EVs can serve as valuable tools for observing brain molecular changes minimally invasively. However, further analysis is necessary to understand the cargo composition of these EVs and improve isolation methods. Therefore, research efforts should prioritize the analysis of CNS-derived EVs' origin and genome-wide biomarker discovery studies.
| S-EPMC10445044 | biostudies-literature
Project description:Extracellular vesicles (EVs) play a central role in intercellular communication, which is relevant for inflammatory and immune processes implicated in neurodegenerative disorders, such as Parkinson's Disease (PD). We characterized and compared distinctive cerebrospinal fluid (CSF)-derived EVs in PD and atypical parkinsonisms (AP), aiming to integrate a diagnostic model based on immune profiling of plasma-derived EVs via artificial intelligence. Plasma- and CSF-derived EVs were isolated from patients with PD, multiple system atrophy (MSA), AP with tauopathies (AP-Tau), and healthy controls. Expression levels of 37 EV surface markers were measured by a flow cytometric bead-based platform and a diagnostic model based on expression of EV surface markers was built by supervised learning algorithms. The PD group showed higher amount of CSF-derived EVs than other groups. Among the 17 EV surface markers differentially expressed in plasma, eight were expressed also in CSF of a subgroup of PD, 10 in MSA, and 6 in AP-Tau. A two-level random forest model was built using EV markers co-expressed in plasma and CSF. The model discriminated PD from non-PD patients with high sensitivity (96.6%) and accuracy (92.6%). EV surface marker characterization bolsters the relevance of inflammation in PD and it underscores the role of EVs as pathways/biomarkers for protein aggregation-related neurodegenerative diseases.
| S-EPMC7996605 | biostudies-literature