Dataset Information

Predicting Cerebrospinal Fluid Alpha-Synuclein Seed Amplification Assay Status from Demographics and Clinical Data.

ABSTRACT:

Objective

To 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.

Methods

Uni- 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.

Results

The 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.

Conclusion

Data-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.

SUBMITTER: Venuto CS

PROVIDER: S-EPMC11326325 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Publications

Predicting Cerebrospinal Fluid Alpha-Synuclein Seed Amplification Assay Status from Demographics and Clinical Data.

Venuto Charles S CS Herbst Konnor K Chahine Lana M LM Kieburtz Karl K

medRxiv : the preprint server for health sciences 20250307

<h4>Objective</h4>To 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.<h4>Methods</h4>Uni- 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 seedin ...[more]

PMID: 39148857

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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: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:The development of in vitro seed amplification assays (SAA) detecting misfolded alpha-synuclein (αSyn) in cerebrospinal fluid (CSF) and other tissues has provided a pathology-specific biomarker for Lewy body disease (LBD). However, αSyn SAA diagnostic performance in early pathological stages or low Lewy body (LB) pathology load has only been assessed in small cohorts. Moreover, the relationship between SAA kinetic parameters, the number of αSyn brain seeds and the LB pathology burden assessed by immunohistochemistry has never been systematically investigated. We tested 269 antemortem CSF samples and 138 serially diluted brain homogenates from patients with and without neuropathological evidence of LBD in different stages by the αSyn Real-Time Quaking-Induced Conversion (RT-QuIC) SAA. Moreover, we looked for LB pathology by αSyn immunohistochemistry in a consecutive series of 604 Creutzfeldt-Jakob disease (CJD)-affected brains. αSyn CSF RT-QuIC showed 100% sensitivity in detecting LBD in limbic and neocortical stages. The assay sensitivity was significantly lower in patients in early stages (37.5% in Braak 1 and 2, 73.3% in Braak 3) or with focal pathology (50% in amygdala-predominant). The average number of CSF RT-QuIC positive replicates significantly correlated with LBD stage. Brain homogenate RT-QuIC showed higher sensitivity than immunohistochemistry for the detection of misfolded αSyn. In the latter, the kinetic parameter lag phase (time to reach the positive threshold) strongly correlated with the αSyn seed concentration in serial dilution experiments. Finally, incidental LBD prevalence was 8% in the CJD cohort. The present results indicate that (a) CSF RT-QuIC has high specificity and sufficient sensitivity to detect all patients with LB pathology at Braak stages > 3 and most of those at stage 3; (b) brain deposition of misfolded αSyn precedes the formation of LB and Lewy neurites; (c) αSyn SAA provides "quantitative" information regarding the LB pathology burden, with the lag phase and the number of positive replicates being the most promising variables to be used in the clinical setting.

Dataset Information

Predicting Cerebrospinal Fluid Alpha-Synuclein Seed Amplification Assay Status from Demographics and Clinical Data.

Objective

Methods

Results

Conclusion

Publications

Predicting Cerebrospinal Fluid Alpha-Synuclein Seed Amplification Assay Status from Demographics and Clinical Data.

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