Dataset Information

α-Synuclein Seed Amplification Assays in the Diagnosis of Synucleinopathies Using Cerebrospinal Fluid-A Systematic Review and Meta-Analysis.

ABSTRACT:

Background

Real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA) have been developed to detect minute amounts of amyloidogenic proteins via amplification techniques and have been used to detect misfolded α-synuclein (αSyn) aggregates in the cerebrospinal fluid (CSF) and other source materials of patients with Parkinson's Disease and other synucleinopathies.

Objectives

The aim of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of αSyn seed amplification assays (αSyn-SAAs), including RT-QuIC and PMCA, using CSF as source material to differentiate synucleinopathies from controls.

Methods

The electronic MEDLINE database PubMed was searched for relevant articles published until June 30, 2022. Study quality assessment was performed using the QUADAS-2 toolbox. A random effects bivariate model was exploited for data synthesis.

Results

Our systematic review identified 27 eligible studies according to the predefined inclusion criteria, of which 22 were included in the final analysis. Overall, 1855 patients with synucleinopathies and 1378 non-synucleinopathies as control subjects were included in the meta-analysis. The pooled sensitivity and specificity to differentiate synucleinopathies from controls with αSyn-SAA were 0.88 (95% CI, 0.82-0.93) and 0.95 (95% CI, 0.92-0.97), respectively. Evaluating the diagnostic performance of RT-QuIC in a subgroup analysis for the detection of patients with multiple system atrophy the pooled sensitivity decreased to 0.30 (95% CI, 0.11-0.59).

Conclusions

While our study clearly demonstrated a high diagnostic performance of RT-QuIC and PMCA for differentiating synucleinopathies with Lewy bodies from controls, results for the diagnosis of multiple system atrophy were less robust.

SUBMITTER: Grossauer A

PROVIDER: S-EPMC10187020 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

α-Synuclein Seed Amplification Assays in the Diagnosis of Synucleinopathies Using Cerebrospinal Fluid-A Systematic Review and Meta-Analysis.

Grossauer Anna A Hemicker Greta G Krismer Florian F Peball Marina M Djamshidian Atbin A Poewe Werner W Seppi Klaus K Heim Beatrice B

Movement disorders clinical practice 20230315 5

<h4>Background</h4>Real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA) have been developed to detect minute amounts of amyloidogenic proteins via amplification techniques and have been used to detect misfolded α-synuclein (αSyn) aggregates in the cerebrospinal fluid (CSF) and other source materials of patients with Parkinson's Disease and other synucleinopathies.<h4>Objectives</h4>The aim of this systematic review and meta-analysis was to evaluate th ...[more]

PMID: 37205253

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Project description:Several studies have confirmed the α-synuclein real-time quaking-induced conversion (RT-QuIC) assay to have high sensitivity and specificity for Parkinson's disease. However, whether the assay can be used as a robust, quantitative measure to monitor disease progression, stratify different synucleinopathies and predict disease conversion in patients with idiopathic REM sleep behaviour disorder remains undetermined. The aim of this study was to assess the diagnostic value of CSF α-synuclein RT-QuIC quantitative parameters in regard to disease progression, stratification and conversion in synucleinopathies. We performed α-synuclein RT-QuIC in the CSF samples from 74 Parkinson's disease, 24 multiple system atrophy and 45 idiopathic REM sleep behaviour disorder patients alongside 55 healthy controls, analysing quantitative assay parameters in relation to clinical data. α-Synuclein RT-QuIC showed 89% sensitivity and 96% specificity for Parkinson's disease. There was no correlation between RT-QuIC quantitative parameters and Parkinson's disease clinical scores (e.g. Unified Parkinson's Disease Rating Scale motor), but RT-QuIC positivity and some quantitative parameters (e.g. Vmax) differed across the different phenotype clusters. RT-QuIC parameters also added value alongside standard clinical data in diagnosing Parkinson's disease. The sensitivity in multiple system atrophy was 75%, and CSF samples showed longer T50 and lower Vmax compared to Parkinson's disease. All RT-QuIC parameters correlated with worse clinical progression of multiple system atrophy (e.g. change in Unified Multiple System Atrophy Rating Scale). The overall sensitivity in idiopathic REM sleep behaviour disorder was 64%. In three of the four longitudinally followed idiopathic REM sleep behaviour disorder cohorts, we found around 90% sensitivity, but in one sample (DeNoPa) diagnosing idiopathic REM sleep behaviour disorder earlier from the community cases, this was much lower at 39%. During follow-up, 14 of 45 (31%) idiopathic REM sleep behaviour disorder patients converted to synucleinopathy with 9/14 (64%) of convertors showing baseline RT-QuIC positivity. In summary, our results showed that α-synuclein RT-QuIC adds value in diagnosing Parkinson's disease and may provide a way to distinguish variations within Parkinson's disease phenotype. However, the quantitative parameters did not correlate with disease severity in Parkinson's disease. The assay distinguished multiple system atrophy patients from Parkinson's disease patients and in contrast to Parkinson's disease, the quantitative parameters correlated with disease progression of multiple system atrophy. Our results also provided further evidence for α-synuclein RT-QuIC having potential as an early biomarker detecting synucleinopathy in idiopathic REM sleep behaviour disorder patients prior to conversion. Further analysis of longitudinally followed idiopathic REM sleep behaviour disorder patients is needed to better understand the relationship between α-synuclein RT-QuIC signature and the progression from prodromal to different synucleinopathies.

Project description:BackgroundAggregation of α-synuclein (α-syn) is a prominent feature of Parkinson's disease (PD) and other synucleinopathies. Currently, α-syn seed amplification assays (SAAs) using cerebrospinal fluid (CSF) represent the most promising diagnostic tools for synucleinopathies. However, CSF itself contains several compounds that can modulate the aggregation of α-syn in a patient-dependent manner, potentially undermining unoptimized α-syn SAAs and preventing seed quantification.MethodsIn this study, we characterized the inhibitory effect of CSF milieu on detection of α-syn aggregates by means of CSF fractionation, mass spectrometry, immunoassays, transmission electron microscopy, solution nuclear magnetic resonance spectroscopy, a highly accurate and standardized diagnostic SAA, and different in vitro aggregation conditions to evaluate spontaneous aggregation of α-syn.ResultsWe found the high-molecular weight fraction of CSF (> 100,000 Da) to be highly inhibitory on α-syn aggregation and identified lipoproteins to be the main drivers of this effect. Direct interaction between lipoproteins and monomeric α-syn was not detected by solution nuclear magnetic resonance spectroscopy, on the other hand we observed lipoprotein-α-syn complexes by transmission electron microscopy. These observations are compatible with hypothesizing an interaction between lipoproteins and oligomeric/proto-fibrillary α-syn intermediates. We observed significantly slower amplification of α-syn seeds in PD CSF when lipoproteins were added to the reaction mix of diagnostic SAA. Additionally, we observed a decreased inhibition capacity of CSF on α-syn aggregation after immunodepleting ApoA1 and ApoE. Finally, we observed that CSF ApoA1 and ApoE levels significantly correlated with SAA kinetic parameters in n = 31 SAA-negative control CSF samples spiked with preformed α-syn aggregates.ConclusionsOur results describe a novel interaction between lipoproteins and α-syn aggregates that inhibits the formation of α-syn fibrils and could have relevant implications. Indeed, the donor-specific inhibition of CSF on α-syn aggregation explains the lack of quantitative results from analysis of SAA-derived kinetic parameters to date. Furthermore, our data show that lipoproteins are the main inhibitory components of CSF, suggesting that lipoprotein concentration measurements could be incorporated into data analysis models to eliminate the confounding effects of CSF milieu on α-syn quantification efforts.

Project description:ObjectiveTo develop and externally validate models to predict probabilities of alpha-synuclein (a-syn) positive or negative status in vivo in a mixture of people with and without Parkinson's disease (PD) using easily accessible clinical predictors.MethodsUni- and multi-variable logistic regression models were developed in a cohort of participants from the Parkinson Progression Marker Initiative (PPMI) study to predict cerebrospinal fluid (CSF) a-syn status as measured by seeding amplification assay (SAA). Models were externally validated in a cohort of participants from the Systemic Synuclein Sampling Study (S4) that had also measured CSF a-syn status using SAA.ResultsThe PPMI model training/testing cohort consisted of 1260 participants, of which 76% had manifest PD with a mean (± standard deviation) disease duration of 1.2 (±1.6) years. Overall, 68.7% of the overall PPMI cohort (and 88.0% with PD of those with manifest PD) had positive CSF a-syn SAA status results. Variables from the full multivariable model to predict CSF a-syn SAA status included age- and sex-specific University of Pennsylvania Smell Identification Test (UPSIT) percentile values, sex, self-reported presence of constipation problems, leucine-rich repeat kinase 2 (LRRK2) genetic status and pathogenic variant, and GBA status. Internal performance of the model on PPMI data to predict CSF a-syn SAA status had an area under the receiver operating characteristic curve (AUROC) of 0.920, and sensitivity/specificity of 0.881/0.845. When this model was applied to the external S4 cohort, which included 71 participants (70.4% with manifest PD for a mean 5.1 (±4.8) years), it performed well, achieving an AUROC of 0.976, and sensitivity/specificity of 0.958/0.870. Models using only UPSIT percentile performed similarly well upon internal and external testing.ConclusionData-driven models using non-invasive clinical features can accurately predict CSF a-syn SAA positive and negative status in cohorts enriched for people living with PD. Scores from the UPSIT were highly significant in predicting a-syn SAA status.

Project description:BackgroundPD diagnosis is based primarily on clinical criteria and can be inaccurate. Biological markers, such as α-synuclein aggregation, that reflect ongoing pathogenic processes may increase diagnosis accuracy and allow disease progression monitoring. Though α-synuclein aggregation assays have been published, reproducibility, standardization, and validation are key challenges for their development as clinical biomarkers.ObjectiveTo cross-validate two α-synuclein seeding aggregation assays developed to detect pathogenic oligomeric α-synuclein species in CSF using samples from the same PD patients and healthy controls from the BioFIND cohort.MethodsCSF samples were tested by two independent laboratories in a blinded fashion. BioFIND features standardized biospecimen collection of clinically typical moderate PD patients and nondisease controls. α-synuclein aggregation was measured by protein misfolding cyclic amplification (Soto lab) and real-time quaking-induced conversion (Green lab). Results were analyzed by an independent statistician.ResultsMeasuring 105 PD and 79 healthy control CSF samples, these assays showed 92% concordance. The areas under the curve from receiver operating characteristic curve analysis for the diagnosis of PD versus healthy controls were 0.93 for protein misfolding cyclic amplification, 0.89 for real-time quaking-induced conversion, and 0.95 when considering only concordant assay results. Clinical characteristics of false-positive and -negative subjects were not different from true-negative and -positive subjects, respectively.ConclusionsThese α-synuclein seeding aggregation assays are reliable and reproducible for PD diagnosis. Assay parameters did not correlate with clinical parameters, including disease severity or duration. This assay is highly accurate for PD diagnosis and may impact clinical practice and clinical trials. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Dataset Information

α-Synuclein Seed Amplification Assays in the Diagnosis of Synucleinopathies Using Cerebrospinal Fluid-A Systematic Review and Meta-Analysis.

Background

Objectives

Methods

Results

Conclusions

Publications

α-Synuclein Seed Amplification Assays in the Diagnosis of Synucleinopathies Using Cerebrospinal Fluid-A Systematic Review and Meta-Analysis.

Similar Datasets

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