NeuralCipher Research overview
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This study aimed to identify and validate a robust, generalizable panel of plasma protein biomarkers to improve diagnostic precision in Parkinson's disease. We analysed plasma samples from 12 patients with [18F]-FP-CIT PET-confirmed Parkinson's disease and 15 healthy controls using the Olink Target 96 Inflammation Panel to identify differentially expressed proteins. Candidate biomarkers were subsequently validated through absolute quantification using Luminex and Olink Flex platforms in an independent cohort of 46 patients with Parkinson's disease and 33 amyloid-negative and cognitively normal control participants. To assess generalizability, the findings were replicated across multiple heterogeneous populations using large-scale datasets from the UK Biobank and Global Neurodegeneration Proteomics Consortium (GNPC) cohorts. Markers of neurodegeneration [neurofilament light chain (NfL)] and Alzheimer's disease [phosphorylated tau (pTau181), amyloid β [Aβ]42, Aβ40] co-pathology were measured using the single molecule array platform. Our analyses revealed elevated levels of interleukin (IL)-10 and IL-17C and reduced levels of urokinase plasminogen activator (uPA) and neurotrophin-3 (NTF3) in patients with Parkinson's disease. These findings were confirmed in the validation cohort. Multitarget models demonstrated superior diagnostic performance over individual markers, with the combination of IL-17C and uPA achieving the highest discrimination (area under the curve = 0.780). External validation in the UK Biobank and GNPC datasets confirmed consistent directional changes of three candidates (IL-17C, NTF3 and uPA), reinforcing the biological relevance of these markers. Notably, while NfL levels were significantly elevated in Parkinson's disease, no significant differences were observed for pTau181 levels or Aβ42/Aβ40 ratios. These findings identify a specific plasma protein panel, particularly the combination of IL-17C and uPA, as a robust and generalizable diagnostic signature that captures fundamental pathophysiological aspects of Parkinson's disease and enhances diagnostic precision alongside established biomarkers.
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