Abstract

Background: Detection of the pathological and disease-associated alpha-synuclein (αSynD) in the brain is required to formulate the definitive diagnosis of multiple system atrophy (MSA) and Parkinson's disease (PD). We recently showed that αSynD can be detected in the olfactory mucosa (OM) of MSA and PD patients. For this reason, we have performed the first interlaboratory study based on α-synuclein Real-Time Quaking-Induced Conversion (αSyn_RT-QuIC) analysis of OM samples collected from PD and MSA patients with the parkinsonian (MSA-P) and cerebellar (MSA-C) phenotypes.

Methods: OM samples were prospectively collected from patients with a probable diagnosis of MSA-P (n = 20, mean disease duration 4.4 years), MSA-C (n = 10, mean disease duration 4 years), PD (n = 13, mean disease duration 8 years), and healthy control subjects (HS) (n = 11). Each sample was analyzed by αSyn_RT-QuIC in two independent specialized laboratories, one located in Italy (ITA-lab) and one located in the USA (USA-lab). Both laboratories have developed and used harmonized αSyn_RT-QuIC analytical procedures. Results were correlated with demographic and clinical data.

Results: The αSyn_RT-QuIC analysis reached a 96% interrater agreement of results (IAR) between laboratories (Kappa = 0.93, 95% CI 0.83-1.00). In particular, αSyn_RT-QuIC seeding activity was found in the OM of 9/13 patients with PD (sensitivity 69%, IAR 100%) and 18/20 patients with MSA-P (sensitivity 90%, IAR 100%). Interestingly, samples collected from patients with MSA-C did not induce αSyn_RT-QuIC seeding activity, except for one subject in USA-lab. Therefore, we found that MSA-P and MSA-C induced opposite effects. Regardless of disease diagnosis, the αSyn_RT-QuIC seeding activity correlated with some clinical parameters, including the rigidity and postural instability.

Conclusions: Our study provides evidence that OM-αSynD may serve as a novel biomarker for accurate clinical diagnoses of PD, MSA-P, and MSA-C. Moreover, αSyn_RT-QuIC represents a reliable assay that can distinguish patients with MSA-P from those with MSA-C, and may lead to significant advancements in patients stratification and selection for emerging pharmacological treatments and clinical trials.