A panel of nine cerebrospinal fluid biomarkers may identify patients with atypical parkinsonian syndromes

Abstract

BACKGROUND: Patients presenting with parkinsonian syndromes share many clinical features, which can make diagnosis difficult. This is important as atypical parkinsonian syndromes (APSs) such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and corticobasal syndrome (CBS) carry a poor prognosis, compared with patients with Parkinson's disease (PD). In addition, there is overlap between APS and dementia diseases, such as Alzheimer's disease (AD) and frontotemporal dementia (FTD). OBJECTIVE: To use a panel of cerebrospinal fluid (CSF) biomarkers to differentiate patients with APS from PD and dementia. METHODS: A prospective cohort of 160 patients and 30 control participants were recruited from a single specialist centre. Patients were clinically diagnosed according to current consensus criteria. CSF samples were obtained from patients with clinical diagnoses of PD (n=31), PSP (n=33), CBS (n=14), MSA (n=31), AD (n=26) and FTD (n=16). Healthy, elderly participants (n=30) were included as controls. Total τ (t-τ), phosphorylated τ (p-τ), β-amyloid 1-42 (Aβ42), neurofilament light chain (NFL), α-synuclein (α-syn), amyloid precursor protein soluble metabolites α and β (soluble amyloid precursor protein (sAPP)α, sAPPβ) and two neuroinflammatory markers (monocyte chemoattractant protein-1 and YKL-40) were measured in CSF. A reverse stepwise regression analysis and the false discovery rate procedure were used. RESULTS: CSF NFL (p<0.001), sAPPα (p<0.001) and a-syn (p=0.003) independently predicted diagnosis of PD versus APS. Together, these nine biomarkers could differentiate patients with PD from APS with an area under the curve of 0.95 and subtypes of APS from one another. There was good discriminatory power between parkinsonian groups, dementia disorders and healthy controls. CONCLUSIONS: A panel of nine CSF biomarkers was able to differentiate APS from patients with PD and dementia. This may have important clinical utility in improving diagnostic accuracy, allowing better prognostication and earlier access to potential disease-modifying therapies.