A key molecular signature for Parkinson’s disease (PD) is neurotoxic aggregation of the protein alpha synuclein (α-syn). With pathological changes occurring years prior to the onset of symptoms, there is a great need for biomarkers to support earlier and more accurate diagnoses before extensive neurological injury occurs. Aggregated α-syn has recently become accessible to measure in-vivo as a potential biomarker. In particular, α-syn aggregates can be detected in cerebrospinal fluid (CSF) of affected individuals. CSF collection is a highly invasive technique however, requiring specialised medical staff that make it impractical as an initial assessment. We propose instead that reflex tears, a non-invasive and easily accessible biofluid, might be a suitable first assessment to identify aggregated α-syn.
We have developed a seeded amplification assay (SAA) that sensitively detects minimal concentrations of α-syn aggregates to differentiate reflex tears collected from 42 PD and 27 age-matched control participants. Adapted from established methods, our assay uses laboratory prepared and purified monomeric α-syn to amplify any aggregated α-syn signal in the reflex tear samples. We hypothesise that PD reflex tears will include sufficient misfolded α-syn to accelerate aggregation of monomeric α-syn. Reflex tears were collected from each eye using a standard Schirmer test and eluted for assessment using the SAA assay.
Half-times (h) for the PD group (mean = 20.63, SD = 4.55) were significantly faster than the control group (mean = 25.11, SD = 5.79), t = 3.6, p < 0.001. Measured by Cohen’s d, there was a large effect size (d = 0.88), and the area under receiver operating curve for half-times was 0.76 (95% confidence interval: 0.633 – 0.879; p < .001). The accelerated aggregation observed in the PD group suggests our assay successfully detects α-syn aggregates in reflex tears.
These findings represent promising progress toward developing a non-invasive biomarker screening tool for aggregated α-syn in PD. Our assay has future utility to improve diagnostic validity, monitor disease progression and map success of disease-modifying treatments.