Seed-Amplification Assay (RT-QuIC) — vendor / study rows (Russo 2020 / Onia 2021 / Pankha 2014 / Arnold 2021 / Brown 2023 / Brookmeyer 2021 / Olucium 2023 / Groves 2018), Quantification opener (Kinetics readouts, Single-seed level, PrP-QuIC modeling, factors influencing lag time)

Seed-Amplification Assay (RT-QuIC) — study rows

citation	cohort	method	findings
(Russo, 2020 #2587) Caughey lab BioFIND moderate-to-advanced PD		RT-QuIC, CSF	PPMI subjects (30-90 HC and 20 SWEDD); threshold of 5500 RFU was used to determine the time to threshold (TT). We did not otherwise observe significant correlations of kinetic parameters with assay results (AbbVie, Amprion, Caughey). There were some notable correlations between assay parameters and clinical metrics. For instance, disease duration positively correlated to Caughey αSyn-SAA Fmax (r = +0.53, p = 0.007, n = 24), and negatively to Caughey TTT (r = -0.46, p = 0.025, n = 24), and AbbVie αSyn-SAA TTT (r = -0.42, p = 0.039, n = 25). The only significant correlations to motor severity at the time of sampling represented by combined OR (Avgaard) Amprion αSyn-SAA TTT (r = -0.36, p = 0.06, n = 36) and Amprion αSyn-SAA TTT (r = -0.038, p = 0.005, n = 25). Furthermore the additional Q5 BioMarker score is correlated to total UPDRS scores reported in the seven HEAD2HEAD comparisons studies. (Tomic et al. 2017, PMID 28168168) is moderate to severe even with sublimited (P = 0.0091); IS Sym-SAA TTT (r = -0.86, p = 0.005, n = 21).
(Onia, 2021 #2585) Caughey lab BioFIND moderate-to-advanced PD		RT-QuIC, CSF	108 PD and 85 HC; PPMI correlations were observed between various assay-response parameters (TS) and PD clinical measures (MDRS) or other CSF fluid-analytics (TS) times showed a positive correlation with CSF α-Syn (rh=183) levels, whereas maximum fluorescence with TS positive correlated with PD UPDRS-III (RPP) and UPDRS-III TS. CSF SAA tested CSF analysis to detect rep-PD; No CSF tests/% specificity for PD CSF (n=39) of 9% Specificity.
(Pankha, 2014 #2606 OFFRAA cohort Oxford Discovery PROBOG)	Exploratory: OFFRAA cohort (Oxford Discovery Project, Inverigorate Memory Aging) → validation OPDC cohort	RT-QuIC, Brain, CSF, & PMCA	RBD MSA RBD PSP PSP IPS PSP a-syn aging not RT-QuIC
(Arnold, 2021 #2588 Lou 6 portland VA Medical Center)	USA	RT-QuIC, Brain, CSF	155 PD and 95 HC; Results: RT-QuIC was 75% specificity of 96.1% of the iSyn-SAA to identify patients with limbic/neocortical pathology from postmortem CSF. Sensitivity to detect amygdala-predominant pathology was only 14.3%, suggesting aSyn pathological load in amygdala-pred path is too low (Supplementary Table S2). However, TS0 and maximum fluorescence values, values from either assay, did not correlate to UPDRS, H&y, CSF aSyn (Supplementary Information Table S3).
(Dr. Hatano in correspondence)	RT-QuIC: statistically significant correlations with H&Y stages and UPDRS-III but with duration
(Russo, 2020 #1820)	RBD, MSA, DLB, PD, PAF	RT-QuIC, CSF Brain	Results: 21 12 max 1.0; 6.5 12 (1) 21 in RT-QuIC. There was a sensitivity of 97.8% and specificity of 88.1% of the αSyn-SAA to identify patients with limbic/neocortical pathology from postmortem CSF. Sensitivity to detect amygdala-predominant pathology was only 14.3%, suggesting aSyn pathological load in amygdala-pred path is too low.
(Brown 2023 #2588), important: German cohort, 50 patients enriched for prodromal alpha	RBD MSA DLB PD PAF PD-MCI	Brain CSF	RT-QuIC fluorescence, CSF NfL, Synuclein, aSyn fibril (in spike)
(Brookmeyer 2021 #2616) German	156 PD and DLB patients enriched for different cohorts	forms with mutations in GBA parkin PINK1, DJ1, and LRRK2. A subgroup of 100 PD patients was also analysed longitudinally. We correlated kinetic seeding parameters of RT-QuIC across genetic forms and CSF aSyn levels of CSF aSyn levels of molecular pathways linked to a-Syn proteinasis. Overall 95% of PD and 95% of DLB patients showed positive RT-QuIC. α-Syn seeding activity. Seeding profiles were significantly associated with mutation status across the spectrum of genetic LBD: GBA1 mutations were associated with α-Syn seeding parameters indicative of a higher amount and aggressive nature of α-Syn aggregates in resource genes; and in none of those with α-Syn seeding ability indicate a less aggressive nature of seeds. Of these all from this paper showed seeding compared to 70% of unitypsia DLB. Among PD patients those with severe GBA mutations showed faster activity based on RT-QuIC kinetic parameters and the highest proportion of samples with a Sub of a positive replicates in DLB patients 100% with GBA mutations showed positive α-Syn seeding compared to 78% of unitypsia DLB patients. Among PD patients those with severe GBA mutations have unique pathophysiologic differentiating PD versus controls (one area under the curve (AUC) 0.96 (95% confidence interval (CI) 0.99-0.998 in PD vs DLB cases (AUC 0.94 (95% CI 0.86-0.99) in PD vs DLB) RT-QuIC also showed high diagnostic performance in differentiating PD versus controls (one area under the curve (AUC) 0.86 (95% CI 0.85-0.99) and MSA (AUC 0.95 (95% CI 0.86-0.97)) and 0.99) in PD vs DLB cases (AUC 0.94 (95% CI 0.86-0.99). ThT fluorescence threshold was calculated as the average fluorescence for all samples within the first 10 h of incubation, plus three SD. A sample was considered positive overall when at least two of four replicate wells crossed this calculated threshold (End-point dilution).
(Olucium 2023 #2617) Hatten	Statistical method Spearman-Robin analysis SD-50 definition estimates of the concentrations of seeding activity, with giving positive reactions in 50% of replicate reactions, i.e., the 50% 'seeding doses' or SD-50s Unit SD50/mg (15 ul in usual sample volume) Dilution (positive reactions /4) 10⁻¹ × 10⁻³ × 10⁻⁵ 10-fold serial dilution SD50 result ~10⁻¹ × 10⁻⁹ SD50/mg CSF specimens had seeding activities that are substantially higher than the minimum detectable level of 1 SD50; on a per weight basis, seeding activity in brain tissue appeared to be 104-105 fold higher than the seeding activities measured in PD and DLB CSF specimens (Fig. 4).
(Stone et al., 2020, PMID 32041499)	Brain (no postmortem)
(Groves 2018 #2598 Caughey LAB CSF)	FujiAS-SST a-syn aggregates from G2-3 transgenic mice greatly increased immobilization formation in α-syn as compounds in comparison to wild-type α-syn suggesting that conformations far wild-type α-syn to be able to adopt are not compatible with that of A-SST aggregates from G2-3.

Quantification

(A53T human aSyn included; PMCA CSF; CSF DLB, MSA vs CONTROL in CSF and plasma)

	content
(Anwar, et al., 2020, PMID 27918795)	Discriminated PD vs MSA vs CONTROLS in CSF and plasma
20210107	We will focus on serum-based RT-QuIC, in collaboration. If this scheme would be successful, it can be also applied to CSF-based RT-QuIC.
	Currently establishing → make it quantitative by 202402 (contract ending)
(20240218 800 monthly)	Serum α-syn enriched products from 7 synucleinopathy patients were procured from Juntendo Univ. Seeding activity was confirmed using those samples in Takeda’s experimental setups. As a next step, non-synucleinopathy specimens will be evaluated as important controls. (Kentaro Otake)

Kinetics readouts

readout	meaning
Lag time	Initial quantity of proteopathic seed; requires a smaller volume
Single-seed level (Vasovich, 2023 #2588) important: the concentration or the absolute number of αSyn monomers, modelling with EAa fig1. However, when we performed the SAA in spiked full blood serum, using the same concentration of reactant -5, we did not observe any α-S aggregation on the time scale of the experiment (~198 h, not fully shown, black line in Figure 5A). Interactions between the reactant α-S and blood components (albumin?) potentially intervene with the aSyn formation.

(Sis 2013 #2581):

1. Purification of PrP protein from mouse brain
2. Quantification of the PrP protein by quantitative WB
3. RT-Quic of serial concentrations of the purified protein → establishing calibration curve by modelling PrP (assist g) vs LAG
4. Additional showed that PrP27-30 concentrations in the brains obtained from prP-QuIC were comparable to those from quantitative immunoblotting at different time points after inoculation in mice (see also in Additional file 1: Table S1), indicating that qRT-QuIC is suited to measure the PrP27-30 concentrations.

(other factors are influencing lag time):

• if other factors are influencing lag time, eg drug has anti-aggregation capability and inhibits RT-QuIC response, eg emergence of a drug resistant prion strain or albumin (if serum)
• seed/substrate compatibility
• batch-to-batch variability in reagents (minor changes in monomer production can alter assay kinetics)

Currently sensitivity (linear vs non-linear):

• Vs brain aSyn level?
• Vs UPDRS?
• Vs UPDRS?
• Distribution of RT-QuIC readouts?

method (Quantification)

method	content
Dilutions of known (by WB) quantities of seed (ie purified seed)	Standard calibration curve is pre-determined