Parkinson9s disease (PD) is the second most common neurodegenerative disease and the most common synucleinopathy, as alpha-synuclein (α-syn), a prion-like protein, plays an important pathophysiological role in its onset and progression. Although neuropathological changes begin many years before the onset of motor manifestations, diagnosis still relies on the identification of the motor symptoms, which hinders to formulate an early diagnosis. Since α-syn misfolding and aggregation precede clinical manifestations, the possibility to identify these phenomena in PD patients would allow us to recognize the disease at the earliest, premotor phases, as a consequence of the transition from a clinical to a molecular diagnosis. Seed amplification assays (SAAs) are a group of techniques that currently support the diagnosis of prion subacute encephalopathies, namely Creutzfeldt Jakob disease. These techniques enable the detection of minimal amounts of prions in cerebrospinal fluid (CSF) and other matrices of affected patients. Recently, SAAs have been successfully applied to detect misfolded α-syn in CSF, olfactory mucosa, submandibular gland biopsies, skin and saliva, of patients with PD and other synucleinopathies. In these categories, they can differentiate PD and dementia with Lewy bodies (DLB) from control subjects, even in the prodromal stages of the disease. In terms of differential diagnosis, SAAs satisfactorily differentiated PD, DLB, and multiple system atrophy (MSA) from non-synucleinopathy parkinsonisms. The kinetic analysis of the SAA fluorescence profiles allowed the identification of synucleinopathy-dependent α-syn fibrils conformations, commonly referred to as strains, which have demonstrated diagnostic potential in differentiating among synucleinopathies, especially between Lewy body diseases (PD, DLB) and MSA. In front of these highly promising data, which make the α-syn seeding activity detected by SAAs as the most promising diagnostic biomarker for synucleinopathies, there are still preanalytical and analytical issues, mostly related to the assay standardization, which need to be solved. In this review, we discuss the key findings supporting the clinical application of α-syn SAAs to identify PD and other synucleinopathies, the unmet needs, and future perspectives.

INTRODUCTION: Lewy body disease, a frequently observed co‐pathology in Alzheimer's disease (AD), can be identified antemortem in cerebrospinal fluid (CSF) by α‐synuclein seed amplification assay (αS‐SAA). The prevalence and clinical impact of CSF αS‐SAA positivity in AD are still unknown.METHODS: αS‐SAA was performed on CSF samples from 240 AD patients (preclinical, prodromal, and dementia stages), 85 controls, 84 patients with Parkinson's disease (PD), and 21 patients with PD with dementia or dementia with Lewy bodies. In AD patients, associations between αS‐SAA positivity and cognitive changes were also evaluated.RESULTS: In agreement with available neuropathological studies, αS‐SAA positivity was observed in 30% of AD patients (vs 9% in controls), and was associated with cognitive decline, visuospatial impairment, and behavioral disturbances.DISCUSSION: αS‐SAA positivity in AD patients reflects the prevalence observed in neuropathological series and is associated with a worse clinical outcome. These data confirm the validity of CSF αS‐SAA positivity as biomarker of synucleinopathy.

The accumulation and deposition of α-synuclein aggregates in brain tissue is the main event in the pathogenesis of different neurodegenerative disorders grouped under the term of synucleinopathies. They include Parkinson's disease, dementia with Lewy bodies and multiple system atrophy. To date, the diagnosis of any of these disorders mainly relies on the recognition of clinical symptoms, when the neurodegeneration is already in an advanced phase. In the last years, several efforts have been carried out to develop new diagnostic tools for early diagnosis of synucleinopathies, with special interest to Parkinson's disease. The Protein-Misfolding Cyclic Amplification (PMCA) and the Real-Time Quaking-Induced Conversion (RT-QuIC) are ultrasensitive protein amplification assays for the detection of misfolded protein aggregates. Starting from the successful application in the diagnosis of human prion diseases, these techniques were recently tested for the detection of misfolded α-synuclein in brain homogenates and cerebrospinal fluid samples of patients affected by synucleinopathies. So far, only a few studies on a limited number of samples have been performed to test PMCA and RT-QuIC diagnostic reliability. Neverthless, these assays have shown very high sensitivity and specificity in detecting synucleinopathies even at the pre-clinical stage. Despite the application of PMCA and RT-QuIC for α-synuclein detection in biological fluids is very recent, these techniques seem to have the potential for identifying subjects that will be likely to develop synucleinopathies.

In Alzheimer’s disease (AD), the contribution of pathophysiological mechanisms other than amyloidosis and tauopathy is now widely recognized, although not clearly quantifiable by means of fluid biomarkers. We aimed to identify quantifiable protein biomarkers reflecting neuroinflammation in AD using multiplex proximity extension assay (PEA) testing. Cerebrospinal fluid (CSF) samples from patients with mild cognitive impairment due to AD (AD-MCI) and from controls, i.e., patients with other neurological diseases (OND), were analyzed with the Olink Inflammation PEA biomarker panel. A machine-learning approach was then used to identify biomarkers discriminating AD-MCI (n: 34) from OND (n: 25). On univariate analysis, SIRT2, HGF, MMP-10, and CXCL5 showed high discriminatory performance (AUC 0.809, p = 5.2 × 10⁻⁴, AUC 0.802, p = 6.4 × 10⁻⁴, AUC 0.793, p = 3.2 × 10⁻³, AUC 0.761, p = 2.3 × 10⁻³, respectively), with higher CSF levels in AD-MCI patients as compared to controls. These same proteins were the best contributors to the penalized logistic regression model discriminating AD-MCI from controls (AUC of the model 0.906, p = 2.97 × 10⁻⁷). The biological processes regulated by these proteins include astrocyte and microglia activation, amyloid, and tau misfolding modulation, and blood-brain barrier dysfunction. Using a high-throughput multiplex CSF analysis coupled with a machine-learning statistical approach, we identified novel biomarkers reflecting neuroinflammation in AD. Studies confirming these results by means of different assays are needed to validate PEA as a multiplex technique for CSF analysis and biomarker discovery in the field of neurological diseases.