Clinical diagnosis of Parkinson's disease (PD), multiple system atrophy (MSA) and dementia with Lewy bodies (DLB) is challenging, especially in the early stages. Each disease is associated with distinct conformers of misfolded alpha-synuclein (maS) which form typical protein aggregates in the brain and represent key disease biomarkers. Thus, detection and characterization of intracerebral maS aggregates allow a definite diagnosis. The recent development of ultrasensitive assays enabled the detection of maS and other potential new biomarkers in peripheral tissues, although with several limitations. Here, the investigators propose to combine the expertise of leading and young researchers in the field of neurology, structural and molecular biology, biophysics and machine learning to perform ultrasensitive and multi-omics analyses of olfactory mucosa (OM), blood and urine of PD, MSA and DLB patients for detecting and characterizing key peripheral biomarkers allowing accurate disease recognition.
PD (Postuma et al., 2015), MSA (Palma et al., 2018), DLB (McKeith et al., 2017), OND including acquired and hereditary ataxic syndrome with known etiology, progressive supranuclear palsy, corticobasal degeneration, and motor neuron disease.
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PD (n=20), MSA (n=20), DLB (n=20), OND (n=10, including acquired and hereditary ataxic syndrome with known etiology, progressive supranuclear palsy, corticobasal degeneration, and motor neuron disease) and HS (n=10).
Cohort
Prospective
Not listed
Identify a predictive model for the diagnosis of PD, MSA and DLB
To identify a predictive model for the diagnosis of PD, MSA and DLB based on the integration of: * Demographic and clinical: sex, age, comorbidities, disease duration and severity, current medications, cognitive status, the presence of bradykinesia, rigidity, tremors, orthostatic hypotension, autonomic failure, parkinsonism, visual hallucinations, cerebellar syndrome, dementia, rapid eye movement sleep behavior disorder; * Instrumental data: MRI, dopamine-transporter single-photon emission computerized tomography (DAT-SPECT), iodine-131-meta-iodobenzylguanidine (MIBG), fluorodeoxyglucose positron emission tomography (FDG-PET); * Results obtained from the biochemical, structural and RT-QuIC analyses of olfactory mucosa, blood and urine samples (gathered in detailed in the secondary outcomes measures paragraph).
Analysis of olfactory functions.
To evaluate whether PD, DLB and MSA are characterized by different olfactory dysfunctions and if this can be exploited to discriminate the pathologies. Subjects will undergo olfactory evaluation by UPSIT test and divided in Normosmic, Hyposmic and Anosmic.
Evaluation of RT-QuIC accuracy in detecting maS in OM, blood- and urine-derived EVs
To study the distribution of maS in different peripheral tissues (urine, blood and olfactory mucosa) collected from the same patient with a clinical diagnosis of PD, MSA and DLB, by RT-QuIC.
Ultrasensitive detection and measurement of known or potential new biomarkers in OM, blood and urine of enrolled patients by Simoa SR-X.
To analyze if the levels of 181-p-tau (pg/mL), 231-p-tau (pg/mL) and neurofilament light chains (NfL, pg/mL) are altered in the biological samples analysed (urine, blood and OM) compared to subjects with non-neurodegenerative pathology (HS) and if these values differ in such a way as to discriminate the pathologies (PD, MSA and DLB). The assessment of these components will be pursued using Simoa SX-R.
Ultrasensitive detection and measurement of known or potential new biomarkers in OM, blood and urine of enrolled patients by ELISA.
To analyze if the levels of alpha-synuclein (pg/mL) and synapsin-III (pg/mL) are altered in the biological samples analysed (urine, blood and OM) compared to subjects with non-neurodegenerative pathology (HS) and if these values differ in such a way as to discriminate the pathologies (PD, MSA and DLB). These key proteins will be evaluated by ELISA.
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