Accurate Detection of α-Synuclein Seeds in Cerebrospinal Fluid from Isolated Rapid Eye Movement Sleep Behavior Disorder and Patients with Parkinson's Disease in the DeNovo Parkinson (DeNoPa) Cohort

ABSTRACT

Background

Misfolded α-synuclein (αSyn) aggregates (αSyn-seeds) in cerebrospinal fluid (CSF) are biomarkers for synucleinopathies such as Parkinson's disease (PD). αSyn-seeds have been detected in prodromal cases with isolated rapid eye movement sleep behavior disorder (iRBD).

Objectives

The objective of this study was to determine the accuracy of the αSyn–seed amplification assay (αS-SAA) in a comprehensively characterized cohort with a high proportion of PD and iRBD CSF samples collected at baseline.

Methods

We used a high-throughput αS-SAA to analyze 233 blinded CSF samples from 206 participants of the DeNovo Parkinson Cohort (DeNoPa) (113 de novo PD, 64 healthy controls, 29 iRBD confirmed by video polysomnography). Results were compared with the final diagnosis, which was determined after up to 10 years of longitudinal clinical evaluations, including dopamine-transporter–single-photon emission computed tomography (DAT-SPECT) at baseline, CSF proteins, Movement Disorder Society–Unified Parkinson's Disease Rating Scale, and various cognitive and nonmotor scales.

Results

αS-SAA detected αSyn-seeds in baseline PD-CSF with 98% accuracy. αSyn-seeds were detected in 93% of the iRBD cases. αS-SAA results showed higher agreement with the final than the initial diagnosis, as 14 patients were rediagnosed as non-αSyn aggregation disorder. For synucleinopathies, αS-SAA showed higher concordance with the final diagnosis than DAT-SPECT. Statistically significant correlations were found between assay parameters and disease progression.

Conclusions

Our results confirm αS-SAA accuracy at the first clinical evaluation when a definite diagnosis is most consequential. αS-SAA conditions reported here are highly sensitive, enabling the detection of αSyn-seeds in CSF from iRBD just months after the first symptoms, suggesting that αSyn-seeds are present in the very early prodromal phase of synucleinopathies. Therefore, αSyn-seeds are clear risk markers for synuclein-related disorders, but not for time of phenoconversion. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The clinical diagnosis of Parkinson's disease (PD) relies on the presence of motor symptoms such as bradykinesia with concomitant rigidity and/or resting tremor. At the time of diagnosis, up to 70% of dopaminergic neurons are degenerated and the disease is already advanced.¹ In addition, early symptoms, confounding diseases (mimics), and lack of an accessible objective diagnostic test contribute to a misdiagnosis rate as high as 42%, even for movement disorders specialists.² Thus, an objective diagnostic test verifying different parkinsonian syndromes would significantly reduce both the time to reach the final diagnosis and the rate of misdiagnosis.

The degeneration of dopaminergic neurons is estimated to start many years before the onset of motor symptoms.³ Several studies have shown that isolated rapid eye movement sleep behavior disorder (iRBD)⁴ is prodromal for α-synucleinopathies such as PD, dementia with Lewy bodies (DLB), and multiple system atrophy (MSA).^5-8 The time from iRBD diagnosis to phenoconversion ranges from months to 29 years, but not all individuals phenoconvert within this timeframe.^5-8 Therefore, there is great interest in finding tools to determine which iRBD individuals will develop a parkinson syndrome, which type of disease, and most important, in which timeframe phenoconversion will occur. This would be invaluable for neuroprotective clinical trials that seek to slow or halt disease progression before the manifestation of motor symptoms.

PD etiology is unknown, but α-synuclein (αSyn) is closely associated with the origin of the disease, if not the culprit itself.⁹ Misfolded αSyn aggregates (αSyn-seeds) are found as Lewy bodies in PD and DLB or as glial cytoplasmic inclusions in MSA.¹⁰ Hence, these diseases are commonly referred to as synucleinopathies. Recently, αSyn-seed amplification assays (αS-SAAs) have facilitated the validation of αSyn-seeds in cerebrospinal fluid (CSF) as biomarkers for synucleinopathies. This is now offered to patients in the United States under Clinical Laboratory Improvement Amendments registration as a laboratory-developed test. Several independent groups have shown the accuracy of αS-SAAs in the clinical stage of the disease (under the names real-time quaking-induced conversion, protein misfolding cyclic amplification, or SAA), with most reporting sensitivity and specificity >90%.^11-19 However, only one subcohort of 30 PD cases has been reported to include CSF samples collected soon after PD diagnosis (<2 years), when αS-SAA would be most relevant clinically.^{15, 19} Remarkably, high αS-SAA positivity rates in CSF have been reported for iRBD (83%–100%) in cohorts that present 6% to 62% phenoconversion rates.^{14, 20, 21} Conversely, only 39% positivity was reported for a subcohort (18 participants) of the iRBD arm of the DeNovo Parkinson (DeNoPa) cohort, including seven phenoconverters.²¹ The low detection was explained by decreased specificity of clinical diagnosis at enrollment due to earlier identification of iRBD patients from community cases compared with other cohorts.²¹ No strong correlation between αS-SAA parameters and phenoconversion has been found to date, and it remains unknown if αSyn-seeds appear in CSF of iRBD cases at onset or later in the prodromal stage. Here, we evaluated CSF samples collected during the early PD stages and from patients with iRBD and the correlated kinetic parameters to clinical progression and neurological test results.

1 Materials and Methods

1.1 Study Participants

Study participants were part of the DeNoPa cohort (PD, healthy controls [HC], iRBD). Inclusion criteria have been described previously,²² and exclusion criteria are described in Supplementary Methods in Appendix S1. Briefly, PD patients had to be (1) newly diagnosed with PD according to the UK Brain Bank Criteria (at least two of resting tremor, rigidity, bradykinesia), (2) aged between 40 and 85 years, (3) not exposed to levodopa (l-dopa) during the 4 weeks prior to study enrollment and exposed for less than 2 weeks if previously exposed.²²

Rapid eye movement sleep behavior disorder was diagnosed through video polysomnography by experienced raters (C.T., F.S.-D., M.L.M.) on two consecutive nights according to established criteria.^23-25 All participants were examined by movement disorder specialists at baseline (BL) and follow-up (B.M., C.T., J.E., S.S.). Follow-up visits for PD and HC were scheduled biannually. Final diagnosis in this study refers to the consensus diagnosis after up to 10 years of follow-up, including initial dopamine-transporter–single-photon emission computed tomography (DAT-SPECT), biannual clinical evaluations, l-dopa challenge, lasting response to l-dopa, and the emergence of advanced PD features such as motor fluctuations or l-dopa–induced dyskinesias. Brain autopsy was available for nine study participants of the DeNoPa cohort (seven PD, one MSA, and one HC) who died during the 10-year follow-up. In 100% of cases, the neuropathological diagnosis was consistent with the clinical consensus diagnosis by movement disorder specialists (B.M., C.T., J.E., S.S.). Abnormal/pathological DAT-SPECT was determined by a specialist in nuclear medicine by visual inspection or quantification. Other neurological disorders (OND) refer to definite diagnoses other than PD, and non-PD refers to uncertain diagnoses only known to be inconsistent with PD. Atypical PD (progressive supranuclear palsy [PSP], DLB, MSA) was diagnosed according to the established criteria.^26-28

All participants were evaluated according to the revised Movement Disorder Society–Unified Parkinson's Disease Rating Scale (MDS-UPDRS).²⁹ Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA)³⁰ and the Mini-Mental State Examination.³¹ Further evaluations of cognitive domains and nonmotor symptoms comprised the Non-Motor Symptoms Questionnaire (NMS)³² and Geriatric Depression Scale (GDS).³³ Additional tests are described in the Supplementary Methods in Appendix S1. HCs were matched using frequency matching.

1.2 CSF Samples

CSF collection has been described previously²² (Supplementary Methods in Appendix S1). A total of 233 CSF samples from 206 individuals were analyzed in this study. To analyze a high number of cross-sectional samples, we analyzed samples from either BL or follow-up. In total, CSF samples were collected on average 22 months after the first symptoms, and 58 (51%) were collected within 12 months of the first symptoms. A total of 56 iRBD CSF samples from 29 patients were collected at enrollment (on average 5.7 years after the first reported iRBD symptoms). Figure 1 describes the samples used in this study. CSF αSyn, β-amyloid 1–42, total tau protein (t-tau), and phosphorylated tau protein (p-tau181) were quantified as previously described.³⁴ Additional measurements included neurofilament light chain, neurogranin, and YKL-40 (Supplementary Methods in Appendix S1).

FIG 1

Baseline (BL) and final diagnoses and α-synuclein (αS)–seed amplification assay (SAA) analysis of the DeNovo Parkinson Cohort (DeNoPa). A total of 233 cerebrospinal fluid (CSF) samples from 206 individuals were analyzed in this study (Parkinson's disease [PD], isolated rapid eye movement sleep behavior disorder [iRBD], healthy controls [HC]). A total of 113 PD-CSF samples were analyzed, one per PD patient, collected at BL (87), V2 (18), V3 (7), and V4 (1). A total of 64 HC-CSF samples were analyzed, one per HC participant, collected at BL (50), V2 (8), V3 (4), V4 (1), and V5 (1). Visits for PD and HC were scheduled biannually. A total of 56 iRBD-CSF samples from 29 patients were analyzed and collected at BL, and various follow-up visits were scheduled either annually or biannually. Of the PD-CSF cases, 96/113 were αS-SAA(+); 94/96 αS-SAA(+) PD-CSF cases had a synucleinopathy final diagnosis. Of the PD-CSF cases, 17/133 were αS-SAA(−); 12/17 αS-SAA(−) PD-CSF cases had a nonsynucleinopathy final diagnosis. Of the HC-CSF cases, 62/64 were αS-SAA(−), with 64/64 cases remaining free of neurodegenerative disease until the end of the study. Of the iRBD-CSF samples, 53/56 were αS-SAA(+). DLB, dementia with Lewy bodies; Dx, diagnosis; MSA, multiple system atrophy; PSP, progressive supranuclear palsy.

1.3 α-Syn Seed Amplification Assay

The αS-SAA conditions used here have been described in detail elsewhere.^{19, 15} Briefly, CSF samples were blindly analyzed in triplicate (40 μL/well) in a reaction mixture containing 0.3 mg/mL recombinant α-Syn (Amprion [California, USA]; catalog number S2020), 100 mM piperazine-N,N′-bis(2-ethanesulfonic acid) (PIPES) pH 6.50, 500 mM sodium chloride, 10 μM thioflavin T, and one bovine serum albumin (BSA)–blocked 2.4-mm silicon nitride G3 bead (Tsubaki-Nakashima [Georgia, USA]). Beads were blocked in 1% BSA 100 mM PIPES pH 6.50 and washed with 100 mM PIPES pH 6.50. αS-SAA was performed in 96-well plates (Costar [New York, USA], catalog number 3916) using a FLUOstar Omega fluorometer (BMG [Ortenberg, Germany]). Plates were orbitally shaken at 800 rpm for 1 minute every 29 minutes at 37°C. Results from three replicates were considered input for a three-output probabilistic algorithm (Supplementary Material), where samples were labeled “positive,” “negative,” or “inconclusive.”¹⁵ Maximum fluorescence (F_max), time to reach 50% F_max (T₅₀), slope, and the coefficient of determination for the fitting were calculated for each replicate using a sigmoidal equation available in Mars data analysis software (BMG). The time to reach the 5000 relative fluorescence units (RFU) threshold (TTT) was calculated with a user-defined equation in Mars.

1.4 Statistical Analysis

Calculations were performed with R (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria). Group comparisons (PD, HC, iRBD, phenoconverter) were performed using the nonparametric Kruskal–Wallis test and for sex comparisons using the χ² test. For continuous sum scores, longitudinal modeling for all dependent variables was performed via a random-intercept linear mixed model. Dependent variables were transformed to the square root scale to achieve normal distributions of the residual errors in the models, which were checked by q-q plots of the residual errors. All models were adjusted for age, sex, and levodopa equivalent daily dose. The kinetic parameters of the αS-SAA were transformed to log10 and added to the models as a BL covariate to assess their predictive association with the longitudinal expression of the clinical outcome. Thus, only αS-SAA kinetic parameters from samples collected at BL (Table 1) were correlated to BL demographic, clinical (Table 1 and Table S1), and biofluid parameters (Table S2.). Correlations between αS-SAA parameters at BL and clinical outcomes were estimated using a nonparametric Spearman coefficient. Adjustment for multiple testing was undertaken, and the false discovery rate was controlled at 5% with the Benjamini–Hochberg procedure.³⁵

TABLE 1. Baseline demographic and clinical data of participants with baseline cerebrospinal fluid samples from the DeNovo Parkinson Cohort

Parameter	HC (N = 50)	PD (N = 71)	iRBD (N = 19)	iRBD converter (N = 8)	P value
Sex, n (%)					0.418
Male	35 (70.0)	52 (73.2)	11 (57.9)	7 (87.5)
Female	15 (30.0)	19 (26.8)	8 (42.1)	1 (12.5)
Age, years					0.046
Mean (SD)	66 (6.8)	63.070 (9.466)	68.597 (8.480)	65.177 (5.973)
Median (Q1, Q3)	67 (62.250, 69)	64 (57, 70)	72 (62.5, 75)	66.210 (64.75, 67.25)
Minimum–maximum	44–84	41–82	51–77	52–73
BMI(kg/m^2)					0.269
Mean (SD)	26.859 (4.514)	27.981 (4.271)	27.084 (4.154)	26.159 (1.543)
Median (Q1, Q3)	25.838 (24.226, 29.173)	27.616 (25.048, 29.619)	26.493 (24.103, 29.561)	26.662 (25.092, 27.288)
Minimum–maximum	19.271–42.253	20.089–44.789	20.797–34.136	23.504–27.757
MDS-UPDRS Part III score					<0.001
Mean (SD)	0.680 (1.477)	21.803 (10.861)	2.158 (2.267)	4.750 (3.694)
Median (Q1, Q3)	0 (0, 0)	21.0 (13.0, 28.0)	1.000 (0.500, 3.000)	4.500 (1.750, 7.500)
Minimum–maximum	0–6	3–54	0–7	0–10
MDS-UPDRS total score					<0.001
Mean (SD)	3.720 (3.902)	35.345 (16.324)	16.368 (8.187)	18.250 (10.025)
Median (Q1, Q3)	2.000 (1.000, 5.000)	34.000 (24.000, 46.500)	16.000 (12.000, 18.500)	19.500 (12.500, 24.750)
Minimum–maximum	0.000–15.000	5.000–84.000	2.000–35.000	4.000–32.000
HY Stage					<0.001
Mean (SD)	0.000 (0.000)	1.972 (0.736)	0.053 (0.229)	0.000 (0.000)
Median (Q1, Q3)	0.000 (0.000, 0.000)	2.000 (1.000, 2.500)	0.000 (0.000, 0.000)	0.000 (0.000, 0.000)
Minimum–maximum	0.000–0.000	1.000–3.000	0.000–1.000	0.000–0.000
MMSE total					0.526
Mean (SD)	28.571 (1.190)	28.357 (1.263)	28.222 (1.629)	29.000 (0.577)
Median (Q1, Q3)	29.000 (28.000, 29.000)	29.000 (28.000, 29.000)	28.500 (28.000, 29.000)	29.000 (29.000, 29.000)
Minimum–maximum	26.000–30.000	25.000–30.000	24.000–30.000	28.000–30.000
Missing	1	1	1	1
MoCA total					0.415
Mean (SD)	25.700 (2.410)	24.718 (2.987)	24.947 (3.188)	25.250 (3.059)
Median (Q1, Q3)	25.000 (24.250, 27.000)	25.000 (23.000, 27.000)	26.000 (24.000, 27.000)	26.000 (22.750, 26.500)
Minimum–maximum	19.000–30.000	16.000–30.000	17.000–29.000	21.000–30.000

• Abbreviations: HC, healthy controls; PD, Parkinson's disease; iRBD, isolated rapid eye movement sleep behavior disorder; SD, standard deviation; Q1, quartile 1; Q3, quartile 3; BMI, b'Body-Mass-Index; MDS-UPDRS, Movement Disorder Society–Unified Parkinson's Disease Rating Scale; HY, Hoehn and Yahr Stage; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment.

2 Data Sharing

All relevant data are in the article and its Supporting Information files. Additional data are available on request.

3 Results

3.1 DeNoPA—Final Diagnosis of BL PD and HC Participants

A total of 113 CSF samples (74 men, 39 women) from cases initially enrolled as PD were available (Fig. 1). Of the 113 PD patients, 99 (87.6%) had a final synucleinopathy diagnosis: 95 PD (84.1%), two DLB (1.8%), and two MSA (1.8%) (Fig. 2A). The other 14 (12.4%) PD patients had a nonsynucleinopathy as a final clinical diagnosis: three (2.7%) vascular PD (vPD), five (4.4%) essential tremor (ET) and/or dystonic tremor (DT), two (1.8%) restless legs syndrome (RLS), and four (3.5%) PSP. In these misdiagnosed cases, the average time from PD diagnosis to non-PD diagnosis was 3.7 ± 2.6 years, whereas the average time from non-PD to final OND diagnosis was 1.9 ± 2.5 years.

FIG 2

Statistical analysis of α-synuclein–seed amplification assay (αS-SAA) results from Parkinson's disease (PD) cases. (A) Of the 113 baseline (BL)-PD cases, 87.6% had a final synucleinopathy diagnosis (PD, dementia with Lewy bodies [DLB], multiple system atrophy [MSA]), whereas 12.4% had a nonsynucleinopathy final diagnosis (vascular PD [vPD], essential tremor [ET]/dystonic tremor [DT], restless legs syndrome [RLS], progressive supranuclear palsy [PSP]). Of the BL-PD cases, 96/113 were positive in αS-SAA (αS-SAA(+)); of the 96 αS-SAA(+) cases, 97.9% had a final synucleinopathy diagnosis (PD, DLB, MSA), whereas only 2% had a nonsynucleinopathy final diagnosis (vPD, ET/DT). Of the BL-PD cases, 100/113 had dopamine-transporter–single-photon emission computed tomography (DAT-SPECT) available, and 97/100 patients had abnormal DAT-SPECT (DaTscan(+)); of the 97 DaTscan(+) cases, 89.7% had a final synucleinopathy diagnosis (PD, DLB, MSA), whereas 10.3% had a nonsynucleinopathy final diagnosis (vPD, ET/DT, RLS, PSP). (B) Spearman correlation matrix of αS-SAA kinetic parameters (maximum fluorescence [Fmax], time to reach 50% Fmax [T50], time to reach the 5000 relative fluorescence units (RFU) threshold [TTT], and slope), neurological test scores (Body-Mass-Index [BMI], Movement Disorder Society–Unified Parkinson's Disease Rating Scale [MDS-UPDRS], Mild cognitive impairment [MCI], Mini-Mental State Examination [MMSE], Montreal Cognitive Assessment Test [MoCA], Parkinson's Disease Nonmotor Symptom Questionnaire [PD NMS], Beck Depression Inventory [BDI], Geriatric Depression Scale [GDS], Montgomery-Åsberg Depression Rating Scale [MADRS], Wechsler Memory Scale [WMS-R], Visual Object and Space Perception Battery [VOSP], Stroop Test [STROOP], Autonomic Scale for Outcomes in Parkinson's Disease [Scopa-AUT]), and laboratory workup (CSF total tau protein [t-tau], CSF phosphorylated tau protein [p-tau181], CSF α-synuclein [CSF αSyn), neurofilament light chain [NFL], white blood count [WBC], red blood count [RBC]) for αS-SAA(+) PD cases. The upper triangle of the matrix shows the nonparametric Spearman coefficient for each correlation, with blue indicating a positive correlation and red indicating a negative correlation. The intensity of color shows the value of the coefficient from 0 to 1. The lower triangle of the matrix shows the false discovery rate (FDR)–adjusted significant P values. FDR adjustments are according to the Benjamini–Hochberg procedure.³⁵ Values below 0.01 are shown as 0. Nonsignificant values (0.05) are left blank for layout convenience. [Color figure can be viewed at wileyonlinelibrary.com]

The 64 participants in the HC group remained free of neurodegenerative disease during follow-up. Table 1 and Table S1 describe the demographics and clinical scores for those whose CSF samples were analyzed at BL.

3.2 DeNoPA—αS-SAA Analysis of CSF Samples from PD and HC Participants

CSF samples were blindly analyzed, and assay results were compared with the final diagnosis that was considered the gold standard (Fig. 1). The αS-SAA detected αSyn-seeds in CSF and was considered positive (αS-SAA(+)) in 96 (85%) of the 113 cases that were diagnosed with PD at BL. Of the 99 patients with a final synucleinopathy diagnosis, 94 (95%) were αS-SAA(+), including 91 (92%) PD, one (1%) DLB, and two (2%) parkinsonian subtype of MSA (MSA-P). One of the MSA-P samples presented the low fluorescence signature previously reported.³⁶ αSyn-seeds were not detected (αS-SAA(−)) in the other five (5.1%) cases with synucleinopathies, which included four (4%) PD and one (1%) DLB. Thus, of the 96 αS-SAA(+) patients, there were 91 (94.8%) PD, one (1%) DLB, two (2.1%) MSA, one (1%) vPD, and one (1%) ET (Fig. 2A). Of the 14 cases without a synucleinopathy, 12 were αS-SAA(−), and one vPD and one ET were αS-SAA(+). Of the 64 HC participants, 62 (96.9%) were αS-SAA(−). The two positive samples did not show any symptoms consistent with prodromal disease.

αS-SAA results agreed with the final diagnosis of synucleinopathy in 95% of cases, whereas the agreement in the HC control group reached approximately 97%. Because a highly sensitive and specific assay is needed during the early stages of synucleinopathy, we calculated sensitivity and specificity using only samples from BL. Of the 74 cases with a final synucleinopathy diagnosis and BL-CSF samples, 70 were αS-SAA(+), for an estimated sensitivity of 94.6% (95% confidence interval [CI], 86.7%–98.5%). Of the 50 HC participants with BL-CSF samples, 49 were αS-SAA(−), for an estimated specificity of 98% (95% CI, 89.4%–100%). Considering a synucleinopathy prevalence of 389 cases for every 100,000 people,³⁷ the assay presents a BL accuracy of 98% (95% CI, 93.7%–99.7%). All 39 final PD cases with CSF collected ≤1 year from first symptoms were αS-SAA(+). The high specificity of the assay was also observed when analyzing BL-CSF samples from PD cases with final nonsynucleinopathy diagnoses, as 12 (85.7%) of the 14 cases were αS-SAA(−).

3.3 DeNoPA—αS-SAA Results in PD Patients Stratified by DAT-SPECT Status

DAT-SPECT was available at enrollment for 100 (88.5%) of the 113 PD patients, and 97 were considered abnormal/pathological. Of the 97 PD cases with abnormal DAT-SPECT [PD-DAT(+)], 87 (89.7%) had a final synucleinopathy diagnosis (84 PD, one DLB, two MSA-P) (Fig. 2A). Three other subjects with neurodegenerative parkinsonian type, but nonsynucleinopathy, were PSP (3.1%). The other seven participants had a final nonsynucleinopathy diagnosis: three (3.1%) ET, two (2%) RLS, two (2%) vPD. Of the 87 PD-DAT(+), 82 (94.3%) were αS-SAA(+) (80 PD, two MSA-P), and four PD and one DLB were PD-DAT(+) and αS-SAA(−). Remarkably, eight of the 10 PD-DAT(+) with final nonsynucleinopathy were αS-SAA(−) using CSF collected at BL in nine of the 10 cases (one PSP-CSF sample was collected at a follow-up). The three PD cases with normal DAT-SPECT were diagnosed with ET, ET/DT, and vPD, which were all αS-SAA(−). The final diagnoses for the 13 PD cases without DAT-SPECT included 11 PD, one PSP, and one DLB. The PSP case was αS-SAA(−), whereas the other 12 cases were αS-SAA(+).

3.4 Estimation of Correlation Between αS-SAA Parameters and Clinical Parameters of PD Cases

Kinetic parameters such as F_max (RFU), T₅₀ (hours), TTT (hours), and slope (RFU/h) were calculated for all PD samples. Mean and median values of these parameters were determined for each sample, including the three technical replicates and their correlation with clinical test scores, and laboratory workup was estimated (Fig. 2B). Clinical scores did not present relevant correlations with kinetic parameters, whereas significant but weak correlations were observed between T₅₀ and TTT and the concentration of CSF biomarkers such as β-amyloid 1–42, tau, p-tau181, and αSyn.

3.5 DeNoPa—iRBD

The iRBD group included 29 patients (20 men and 9 women). On average, enrollment occurred 5.35 ± 4.0 years after the first symptoms, as reported by the patients and/or respective partners (range, 0.42 to 12 years). Of the 29 cases, eight (27.6%) phenoconverted after 11.4 ± 4.7 years from the first symptoms (range, 6.3–20.2 years) and 3.8 ± 3 years from enrollment (range, 0.5–8.2 years). The mean age at phenoconversion was 69.3 ± 4.8 years. Of the eight phenoconverters, five (62.5%) developed PD, and three (37.5%) developed DLB. Patients have been clinically followed from enrollment for 6.6 ± 2 years on average (range, 2.3–9.5 years).

3.6 DeNoPa—Detection of αSyn-Seeds by αS-SAA in CSF from iRBD

Including samples from enrollment and follow-up, 56 CSF samples from 29 iRBD patients were analyzed. Of the iRBD CSF samples, 53 (94.6%) were αS-SAA(+), and 27 (93.1%) patients of the total 29 iRBD patients had an αS-SAA(+) sample at enrollment or follow-up (Fig. 1). Moreover, 25 (92.6%) of the 27 CSF samples collected at enrollment were αS-SAA(+). This level of detection at BL is 64.8% higher than previously reported for a subcohort of these samples and a different assay.²¹ All eight phenoconverters were αS-SAA(+) at enrollment. Interestingly, two iRBD patients with CSF samples collected only 8 and 9 months after the onset of first symptoms were αS-SAA(+) (Fig. 3). Two iRBD cases had in total three αS-SAA(−) CSF samples and did not phenoconvert to manifest disease during the duration of the available follow-up (8.2 and 6.8 years after their enrollment).

FIG 3

Depiction of the timeline of seven longitudinal iRBD cases from the onset of first symptoms through the duration of the study. The timeline is measured in years, with the patient identification noted on the far left. Occurrence of iRBD Dx and BL Eval is noted, along with various CSF collections and the associated αS-SAA(+) result. Phenoconversion is included for the four iRBD cases who phenoconverted from iRBD to synucleinopathy, with the final diagnosis (PD, DLB) specified in parentheses. αS, α-synuclein; BL Eval, baseline evaluation; CSF, cerebrospinal fluid; DLB, dementia with Lewy bodies; Dx, diagnosis; iRBD, isolated rapid eye movement sleep behavior disorder; PD, Parkinson's disease; SAA, seed amplification assay.

3.7 DeNoPa—Longitudinal Detection of αSyn-Seeds by αS-SAA in CSF from iRBD

Seven iRBD cases had longitudinal CSF samples available. Some samples were collected very close to the onset of first symptoms, and some before and after phenoconversion (Fig. 3).

Patient 1963 was diagnosed with iRBD 1.25 years after the onset of first symptoms. CSF collection at enrollment was 8 years after diagnosis, and five samples were collected over 2.92 years, all αS-SAA(+). By the end of this study, 15.3 years after iRBD diagnosis, this patient has not phenoconverted. Patient 1982 was diagnosed with iRBD 9.33 years after first symptoms, and CSF collection was performed 1.92 years later. Seven CSF samples were collected over 5 years, and the final sample was collected 0.67 years after PD phenoconversion. All CSF samples were αS-SAA(+), and there were no differences in kinetic parameters (T₅₀, TTT, F_max, and slope) between samples collected before or after phenoconversion.

Three other patients had follow-ups biannually from enrollment and two phenoconverted. Patient 1797 was diagnosed with iRBD at enrollment, 10.5 years after first symptoms. Follow-up was approximately 8 years, and five samples were collected, all αS-SAA(+). Patient 1709 was diagnosed with iRBD at enrollment, 5.5 years after initial symptoms, and phenoconverted to DLB 1.67 years later. CSF was collected at enrollment and 1.83 years after phenoconversion, and all samples were αS-SAA(+) and showed similar aggregation profiles. Patient 1660 was diagnosed with iRBD at enrollment, 3.17 years after first symptoms. Four CSF samples were collected over the next 6.16 years when the patient phenoconverted to PD. All four CSF samples were positive without evident change in the aggregation profile before and after phenoconversion. Finally, patients 1929 (DLB phenoconverter) and 2242 were evaluated at enrollment very soon after the onset of first symptoms, 0.67 and 0.75 years, respectively. In addition to the initial CSF sample at enrollment, both patients had CSF collected 2 years afterward. All four samples were αS-SAA(+).

3.8 Correlation Between Clinical and αS-SAA Parameters in the iRBD Subcohort

Kinetic αS-SAA parameters from the iRBD group were correlated to neurological test scores and biofluid workup. Several significant correlations were found (Fig. 4). The mean and median F_max negatively correlated to the total MDS-UPDRS (−0.54, −0.57) and the p-tau/t-tau ratio (−0.73, −0,82), whereas T₅₀ and TTT (both mean and median) positively correlated with the CSF/serum albumin ratio (0.69, 0.67, 0.68, 0.69). Interestingly, there were significant correlations between αS-SAA kinetic parameters and phenoconversion despite the low number of phenoconverters. Longitudinal changes in the MDS-UPDRS Part III score showed a negative association with the log10(mean F_max) measured at enrollment after adjusting for sex, age, and the diagnosis group (P = 0.047). MDS-UPDRS Part III, MDS-UPDRS total, NMS sum, and GDS sum scores showed a negative association with the log10(median F_max) measured at BL after adjusting for sex, age, and the diagnosis group (P = 0.045, P = 0.028, P = 0.012, and P = 0.043, respectively). Because of the negative values on the log scale, this means the greater the F_max the greater the clinical scores are and the worse the disease status is. In reference to the HC group as a base category, the PD group led the contribution to the progression of the total MDS-UPDRS, followed by the iRBD phenoconverters, and lastly the nonphenoconverter iRBD group. This is consistent with the temporal progression from healthy to prodromal to motor disease. The model for the MoCA total score showed significant positive associations with the log10 (mean slope) (P = 0.007) and log10 (median slope) (P = 0.011) at BL, meaning the slower the amplification in the elongation phase, the more pronounced cognitive decline.

FIG 4

Spearman correlation matrix of α-synuclein–seed amplification assay (αS-SAA) kinetic parameters (maximum fluorescence [Fmax], time to reach 50% F_max [T50], time to reach the 5000 relative fluorescence units (RFU) threshold [TTT], and slope), neurological test scores (Body-Mass-Index [BMI], Movement Disorder Society–Unified Parkinson's Disease Rating Scale [MDS-UPDRS], Mini-Mental State Examination [MMSE], Montreal Cognitive Assessment Test [MoCA], Parkinson's Disease Nonmotor Symptom Questionnaire [PD NMS], Beck Depression Inventory [BDI], Geriatric Depression Scale [GDS], Montgomery-Åsberg Depression Rating Scale [MADRS], Wechsler Memory Scale [WMS-R], Visual Object and Space Perception Battery [VOSP], Stroop Test [STROOP], Autonomic Scale for Outcomes in Parkinson's Disease [Scopa-AUT]), and biofluid workup (CSF total tau protein [t-tau], CSF phosphorylated tau protein [p-tau181], CSF α-synuclein [CSF αSyn), neurofilament light chain [NFL], white blood count [WBC], red blood count [RBC]) for αS-SAA(+) isolated rapid eye movement sleep behavior disorder cases. The upper triangle of the matrix shows the nonparametric Spearman coefficient for each correlation, with blue indicating positive correlation and red indicating negative correlation. The intensity of color shows the value of the coefficient from 0 to 1. The lower triangle of the matrix shows the false discovery rate (FDR)–adjusted significant P values. FDR adjustments are according to the Benjamini–Hochberg procedure.³⁵ Values below 0.01 are shown as 0. Nonsignificant values (0.05) are left blank for layout convenience. The matrix shows the nonparametric Spearman coefficient for each correlation, with red indicating positive correlation and blue indicating a negative correlation. The intensity of color shows the value of the coefficient from 0 to 1. [Color figure can be viewed at wileyonlinelibrary.com]

4 Discussion

Performing early and reliable diagnoses of synucleinopathies is a longstanding clinical challenge. In 2016, Rizzo and colleagues reported that there had been a complete lack of improvement in PD diagnosis for a quarter of a century.³⁸ In the past few years, αS-SAAs have demonstrated high accuracy in detecting αSyn-seeds in CSF.^11-19 Nevertheless, most reports used CSF collected from patients in the moderate to late stages of the disease when the clinical diagnosis is reinforced by typical motor and nonmotor features of PD. We have previously evaluated our αS-SAA conditions using de novo PD samples from the Parkinson's Progression Marker Initiative(PPMI), but our study was limited by the low number of cases (n = 30).¹⁵ Hence, in the current study we evaluated αS-SAA accuracy at the time of the initial clinical assessment against the final diagnosis, which we considered to be the “true diagnosis,” acknowledging that pathology is the current gold standard. αS-SAA performed with 94.6% sensitivity and 97% specificity, giving an overall 98% accuracy for synucleinopathies. These results match our previous report (96% sensitivity and 97% specificity)¹⁵ and strongly suggest that αS-SAA can significantly improve the diagnosis of synucleinopathies at first assessment, when accurate diagnosis would be most impactful in the clinical setting. In this cohort, differential diagnosis of non-PD in the absence of αS-SAA took 3.7 years. Thus, the use of αS-SAA by general and specialized neurologists would significantly shorten the time to final diagnosis from years to days. With emerging data from other cohorts with more MSA patients, it looks like the kinetic of αS-SAA can even distinguish between PD and MSA.^{36, 39}

DAT-SPECT detects dopaminergic degeneration using a radiopharmaceutical probe against dopamine transporter⁴⁰ and is used to distinguish between PD and PD mimics such as ET or psychogenic PD, but it is not specific for synucleinopathies. Only 89.7% of cases with pathologic DAT-SPECT had a final synucleinopathy diagnosis, whereas αS-SAA reached 95% agreement with the final diagnosis in the same subcohort. Higher disagreement between DAT-SPECT and final PD diagnosis was expected because PD mimics such as PSP also present dopaminergic degeneration with pathogenic DAT-SPECT. In this regard, 80% of nonsynucleinopathy cases with abnormal DAT-SPECT (including all PSP cases) were αS-SAA(−). Our study is one of the first to compare these two methods and provide evidence that αS-SAA is more accurate for synucleinopathy diagnosis. DAT-SPECT inaccuracy cannot be explained by pharmacologic interference because all patients were monitored for drugs known to hamper the results.⁴¹

Most PD cases do not present prodromal iRBD symptoms,⁴² but iRBD cases are of great interest because these patients will be subject to future prevention trials (https://www.ppmi-info.org/study-design/path-to-prevention-platform-trial). Of iRBD cases, 93.1% were αS-SAA(+), regardless of the sampling time, as well as 92.6% of BL samples. Remarkably, αSyn-seeds were readily detected in iRBD CSF samples collected just months after the first iRBD symptoms were disclosed by the patients. The high sensitivity is comparable with αS-SAA conditions reported by others,^{14, 20} including the Oxford and Italian cohorts reported by Poggiolini and colleagues.²¹ However, a subcohort of the DeNoPa iRBD arm (n = 18) analyzed by Poggiolini and colleagues on different assay conditions reported only 39% sensitivity, which was explained by lower diagnostic specificity due to earlier enrollment from community cases. However, our results suggest that most DeNoPa iRBD cases are in fact prodromal synucleinopathy cases, and they were probably found positive because of the higher sensitivity of the assay used here. These results suggest that preclinical detection of αSyn-seeds is feasible because αS-SAA readily amplified αSyn-seeds from very early iRBD samples. It remains to be seen if early and perhaps preclinical detection of αSyn-seeds is possible in incidental Lewy bodies and also more accessible in tissues such as the olfactory mucosa or other biological fluids.

Lastly, we evaluated if any kinetic parameter of aggregation correlated with a relevant clinical progression score or biofluid analyte for both PD and iRBD cohorts. Only weak correlations with clinical parameters were observed, in agreement with previous studies.^{18, 19, 43} However, correlations between assay parameters at BL with MDS-UPDRS, tau protein, and the CSF/blood albumin ratio warrant further investigation. The low rate of phenoconversion precluded us from conclusively comparing phenoconverters and iRBD, as the small sample size of the phenoconverters may exacerbate the significance of our findings. A model in which αSyn-seed levels increase preclinically and plateau at the prodromal stage of the disease is consistent with our results. Similar behaviors are well established in amyloid-β and prion protein in Alzheimer's disease and prion diseases, respectively. However, kinetic parameters could be affected by CSF analytes that act as amplification accelerators or inhibitors in a patient-dependent manner.^{12, 13, 16} CSF components modulating kinetic parameters have not been identified, but there are reports in the literature showing in vitro interactions between αSyn and human serum albumin, lipids, tau protein, and other proteins that may influence amplification.^44-47 In this cohort, slower amplification correlated with a higher CSF/serum albumin ratio.

In summary, our results show that αS-SAA represents a remarkable tool for the early and even prodromal detection of synucleinopathies and suggest that αSyn-seeds are present in CSF before phenoconversion. Thus, αS-SAA in its current form represents an excellent marker of state and trait. To be used as a screening tool for preventive trials in prodromal/symptom-free individuals, αS-SAA must be further developed to determine if preclinical amplification of αSyn-seeds is possible in noninvasive samples, such as saliva.^{48, 49} Ideally, such a tool will allow the exclusion of subjects with negative αS-SAA in future preventive trials with prodromal individuals.

Acknowledgments

We thank the sample donors and their families for supporting this research by participating in the DeNovo Parkinson Cohort study. This work was partially supported by The Michael J. Fox Foundation (Grant 21233 to L.C.-M.). Open Access funding enabled and organized by Projekt DEAL.

Author Roles

(1) Research Project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the First Draft, B. Review and Critique.

L.C.-M.: 1B, 2B, 3A, 3B

S.W.: 1C, 3A, 3B

C.M.F.: 1C, 2B, 3B

M.D.: 2A, 2B, 3B

E.L.: 1C, 3B

T.W.: 1C, 3B

Y.M.: 1C, 3B

M.S.: 1C, 3B

J.E.: 1C, 3B

F.S.-D.: 1C, 3B

M.-L.M.: 1C, 3B

S.S.: 1C, 3B

C.T.: 1C, 3B

C.S.: 1B, 3B

B.M.: 1A, 1B, 1C, 3B

Financial Disclosures

Financial Disclosures of All Authors (for the Preceding 12 Months): L.C.-M., C.S., C.M.F., and Y.M. are inventors of several patents related to the α-synuclein seed amplification assay (SAA; protein misfolding cyclic amplification [PMCA]) technology and are affiliated with Amprion Inc., a biotech company focusing on the commercial use of SAA (PMCA) for diagnosis of neurodegenerative diseases. Dr. Mollenhauer is on the advisory board of Amprion. F.S.-D. has received honoraria for lectures and consultancy from Ever Pharma, AbbVie, and BIAL. She served on an advisory board for Zambon. S.S. received institutional salaries supported by the EU Horizon 2020 research and innovation program under Grant Agreement 863664 and by The Michael J. Fox Foundation for Parkinson's Research under Grant Agreement MJFF-021923. He is supported by a Parkinson Progression Marker Initiative Early-Stage Investigators Funding Program fellowship of The Michael J. Fox Foundation for Parkinson's Research under Grant Agreement MJFF-022656. B.M. has received honoraria for consultancy from Roche, Biogen, AbbVie, Servier, 4D Pharma PLC, and Amprion; is a member of the executive steering committee of the Parkinson Progression Marker Initiative and principal investigator of the Systemic Synuclein Sampling Study of The Michael J. Fox Foundation for Parkinson's Research; and has received research funding from the Deutsche Forschungsgemeinschaft, EU (Horizon 2020), Parkinson Fonds Deutschland, Deutsche Parkinson Vereinigung, Parkinson's Foundation, Hilde-Ulrichs-Stiftung für Parkinsonforschung, and The Michael J. Fox Foundation for Parkinson's Research. Dr. Trenkwalder has no conflict of interest related to the research of this article; is an advisor of UCB, Ono, Abbvie, and Bial; and has received honorarium for lectures from Abbvie, Alexion, and Bial.

Open Research

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files. Additional data is available upon request.