A minimally Invasive Biomarker for Sensitive and Accurate Diagnosis of Parkinson’s Disease
Notice bibliographique
Résumé
ABSTRACT Importance Parkinson’s disease (PD), the second most common neurodegenerative disease, is pathologically characterized by intraneuronal deposition of misfolded alpha-synuclein aggregates (αSyn D ). αSyn D seeding activities in CSF and skin samples have shown great promise in PD diagnosis, but they require invasive procedures. Sensitive and accurate αSyn D seed amplification assay (αSyn-SAA) for more accessible and minimally invasive samples (such as blood and saliva) are urgently needed for PD pathological diagnosis in routine clinical practice. Objective To develop a sensitive and accurate αSyn-SAA biomarker using blood and saliva samples for sensitive, accurate and minimally invasive PD diagnosis. Design, Setting, and Participants This prospective diagnostic study evaluates serum and saliva samples collected from patients clinically diagnosed with PD or healthy controls (HC) without PD at an academic Parkinson’s and Movement Disorders Center from February 2020 to March 2024. Patients diagnosed with non-PD parkinsonism were excluded from this analysis. A total of 124 serum samples (82 PD and 42 HC) and 131 saliva samples (83 PD and 48 HC) were collected and examined by αSyn-SAA. Out of the 124 serum donors, a subset of 74 subjects (48 PD and 26 HC) also donated saliva samples during the same visits. PD patients with serum samples had a mean age of 69.21 years (range 44-88); HC subjects with serum samples had a mean age of 66.55 years (range 44-81); PD patients with saliva samples had a mean age of 69.58 years (range 49-87); HC subjects with saliva samples had a mean age of 64.71 years (range 30-81). Main Outcomes and Measures Serum and/or saliva αSyn D seeding activities from PD and HC subjects were measured by αSyn-SAA using the Real-Time Quaking-Induced Conversion (RT-QuIC) platform. These PD patients had extensive clinical assessments including MDS-UPDRS. For a subset of PD and HC subjects whose serum and saliva samples were both collected during the same visits, the αSyn D seeding activities in both samples from the same subjects were examined, and the diagnostic accuracies for PD based on the seeding activities in either sample alone or both samples together were compared. Results RT-QuIC analysis of αSyn D seeding activities in the 124 serum samples revealed a sensitivity of 80.49%, a specificity of 90.48%, and an accuracy of 0.9006 (AUC of ROC, 95% CI, 0.8472-0.9539, p <0.0001) for PD diagnosis. RT-QuIC analysis of αSyn D seeding activity in 131 saliva samples revealed a sensitivity of 74.70%, a specificity of 97.92%, and an accuracy of 0.8966 (AUC of ROC, 95% CI, 0.8454-0.9478, p <0.0001). When aSyn D seeding activities in the paired serum-saliva samples from the subset of 48 PD and 26 HC subjects were considered together, sensitivity was 95.83%, specificity was 96.15%, and the accuracy was 0.98 (AUC of ROC, 95% CI, 0.96-1.00, p <0.001), which are significantly better than when αSyn D seeding activities in either serum or saliva were used alone. For the paired serum-saliva samples, when specificity was set at 100% by elevating the αSyn-SAA cutoff values, a sensitivity of 91.7% and an accuracy of 0.9457 were still attained. Detailed correlation analysis revealed that αSyn D seeding activities in the serum of PD patients were correlated inversely with Montreal Cognitive Assessment (MoCA) score ( p =0.04), positively with Hamilton Depression Rating Scale (HAM-D) ( p =0.03), and weakly positively with PDQ-39 cognitive impairment score ( p =0.07). Subgroup analysis revealed that the inverse correlation with MoCA was only seen in males ( p =0.013) and weakly in the ≥70 age group ( p =0.07), and that the positive correlation with HAM-D was only seen in females ( p =0.04) and in the <70 age group ( p =0.01). In contrast, αSyn D seeding activities in the saliva of PD patients were inversely correlated with age at diagnosis ( p =0.02) and the REM sleep behavior disorder (RBD) status ( p =0.04), but subgroup analysis showed that the inverse correlation with age at diagnosis was only seen in males ( p =0.04) and in the <70 age group ( p =0.01). Conclusion and Relevance Our data show that concurrent RT-QuIC assay of αSyn D seeding activities in both serum and saliva can achieve high diagnostic accuracies comparable to that of CSF αSyn-SAA, suggesting that αSyn D seeding activities in serum and saliva together can potentially be used as a valuable biomarker for highly sensitive, accurate, and minimally invasive diagnosis of PD in routine clinical practice. αSyn D seeding activities in serum and saliva of PD patients correlate differentially with some clinical characteristics and in an age and sex-dependent manner. KEY POINTS Question Are αSyn D seeding activities in serum and saliva together a more sensitive and accurate diagnostic PD biomarker than αSyn D seeding activities in either sample type alone? Are αSyn D seeding activities in either serum or saliva correlated with any clinical characteristics? Findings Examinations of αSyn D seeding activities in 124 serum samples and 131 saliva samples from PD and heathy control subjects show that αSyn D seeding activities in both serum and saliva samples together can provide significantly more sensitive and accurate diagnosis of PD than either sample type alone. αSyn D seeding activities in serum or saliva exhibit varied inverse or positive correlations with some clinical features in an age and sex-dependent manner. Meaning αSyn D seeding activities in serum and saliva together can potentially be used as a valuable pathological biomarker for highly sensitive, accurate, and minimally invasive PD diagnosis in routine clinical practice and clinical studies, and αSyn D seeding activities in serum or saliva correlate with some clinical characteristics in an age and sex-dependent manner, suggesting some possible clinical utility of quantitative serum/saliva αSyn-SAA data.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».