Faster reaction times of CSF Alpha-Synuclein Seed Amplification Assay predict the Diffuse Malignant subtype of Parkinson’s Disease at 10-year follow-up
Bibliographic record
Abstract
Abstract Background Data-driven approaches identified Mild Motor Predominant (MMP), Intermediate (IM), and Diffuse Malignant (DM) as Parkinson’s Disease (PD) subtypes with different motor and non-motor impairment at diagnosis. It remains unclear whether these subtypes remain stable over time or whether they represent distinct biological substrates. The alpha-synuclein seed amplification assay in CSF (CSF-αSyn-SAA) might provide further insights. Objective to evaluate the association between baseline CSF-αSyn-SAA parameters and 10-year clinical evolution of PD subtypes. Methods 323 sporadic PD patients from PPMI dataset were classified as MMP, IM, or DM at baseline and 10-year follow-up based on motor, cognitive, sleep and dysautonomia features. CSF-αSyn-SAA parameters were collected at baseline using a 150-hrs protocol. CSF Aβ1-42, tTau and pTau181, CSF and serum NfL were also considered at baseline. Results Reaction times (T50, TTT) and area under the curve (AUC) respectively were shorter and larger in DM compared to IM/MMP. The difference in baseline amplification parameters was more evident when comparing subtypes based on 10-year clinical features (T50, η2=0.036; TTT, η2=0.031; AUC, η2=0.033; all p values < 0.05) than when comparing subtypes based on baseline clinical features (T50, η2=0.012; TTT, η2=0.012; AUC, η2=0.013; all p<0.05). Shorter T50 and TTT at baseline were associated with greater risk of DM versus MMP at 10-year follow-up (T50, OR=3.3, 95%CI: 1.3-8.1, p=0.010; TTT, OR=4.6, 95%CI: 1.8-11.6, p=0.001). Aβ, Tau and NfL were similar between groups. Conclusions Baseline CSF-αSyn-SAA parameters predicted long-term PD progression. Faster reactions were associated with a more severe 10-year PD phenotype considering motor and non-motor features. Plain Language Summary Background The diagnosis of Parkison’s Disease is drastically changing by the development of Alpha-Synuclein Seed Amplification Assay. The assay enables, for the first time, the detection of pathological forms of alpha-synuclein in cerebrospinal fluid in living patients. Alpha-Synuclein Seed Amplification is very accurate in discerning individuals with Parkinson’s Disease versus healthy subjects, but it remains unknown whether it can also inform about prognosis. Objective We assessed the ability of the assay to predict the 10-year clinical progression of Parkinson’s Disease. Methods Public data from an international cohort were used. At time of diagnosis, we classified 323 individuals with Parkinson’s Disease into three clinical subtypes: Mild Motor Predominant, Intermediate, and Diffuse Malignant. These subtypes were characterized by a progressively increasing burden of motor and non-motor symptoms. Subjects with available follow-up data were re-classified using the same subtypes after 10 years of disease. Time-dependent signal changes of Alpha-Synuclein Seed Amplification Assay in Cerebrospinal Fluid were measured at baseline and used to predict the 10-year phenotype. Results Firstly, we found that subtypes were not stable categories. Around a half of participants changed subtype over time, mostly shifting towards a more aggressive one. Notably, our results showed that faster reactions on Alpha-Synuclein Seed Amplification Assay at baseline were associated with a 10-year phenotype more aggressive in terms of motor symptoms, dysautonomia, sleep and cognitive impairment, i.e the Diffuse Malignant subtype. Conclusion Characteristics of the assay underlying the final positivity or negativity outcomes performed at a milder and early stage of PD may identify a subgroup of subjects that are more likely to undergo a more rapid clinical deterioration. Further studies, however, are needed to confirm and expand this result.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".