ReviewJournal of neurology2026
Biomarkers stewardship in parkinsonism: integrating alpha-synuclein seed amplification assays and neurofilament light chain into diagnostic pathways and patient communication.
Review in Journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Parkinsonism encompasses Parkinson's disease (PD) and atypical syndromes including dementia with Lewy bodies (DLB), multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS), where early clinical differentiation remains challenging. This narrative review synthesizes evidence for two complementary biomarker families: alpha-synuclein seed amplification assays (α-synuclein SAA; including real-time quaking-induced conversion and protein misfolding cyclic amplification) as pathology-proximal markers of α-synuclein seeding and neurofilament light chain (NfL) as a marker of neuroaxonal injury and neurodegeneration burden. CSF α-synuclein SAA demonstrates high diagnostic accuracy for PD and DLB, but its performance is context-dependent, with reduced sensitivity in normosmic PD, some genetic subgroups (especially LRRK2-associated PD), very early or anatomically restricted Lewy pathology, and assay protocols not optimized for MSA strains. Recent biological classification frameworks, including SynNeurGe and neuronal α-synuclein disease integrated staging system (NSD-ISS), place SAA centrally in research definitions; however, clinical implementation requires a stewardship layer that preserves clinical judgment, recognizes S-negative genetic or atypical presentations, and avoids equating SAA positivity with a single clinical diagnosis. NfL reliably differentiates PD/DLB from atypical parkinsonian disorders, but interpretation requires age-, matrix-, and platform-specific cutoffs and attention to confounders, such as renal function, body mass index, diabetes, peripheral neuropathy, and vascular comorbidity. This review proposes pragmatic algorithms integrating pre-test probability, α-synuclein SAA, NfL, imaging, genetics, and patient communication. It emphasizes on how to explain positive, negative, and prodromal biomarker results without overdiagnosis, while acknowledging mixed pathologies and uncertain prognostic implications.
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