From clinical phenotypes to molecular precision: multimodal biomarkers for progressive supranuclear palsy

Prodromal Recognition of Non-Motor Symptoms and Biomarkers in Parkinson's Disease

The diagnosis of Parkinson's disease (PD) is often delayed due to over-reliance on motor manifestations, despite the fact that pathological changes including abnormal aggregation of alpha-synuclein (α-syn) and progressive dopaminergic neuronal loss in the substantia nigra pars compacta begin years before overt symptoms emerge. This interval, termed the prodromal phase, represents a critical window for potential intervention. This review summarizes the application value of non-motor symptoms (NMS) and their biomarkers in prodromal identification. Evidence on four NMS categories, namely isolated rapid eye movement sleep behavior disorder (iRBD), autonomic dysfunction, sensory impairment, and neuropsychiatric symptoms, is synthesized. Fluid biomarkers including cerebrospinal fluid (CSF) α-syn seed amplification assay, plasma proteins, and urine proteins, as well as neuroimaging tools including magnetic resonance imaging striatal metrics and meta-iodobenzylguanidine scintigraphy, are evaluated. The findings indicate that while iRBD and CSF α-syn seed amplification assay offer strong predictive value, no single modality suffices for reliable prodromal screening. A multi-modal strategy combining clinical symptoms, fluid markers, and imaging data appears more promising. By consolidating dispersed evidence across subspecialties, this review aims to offer clinicians and researchers an integrated reference for selecting and refining early detection strategies.

Defining the underlying pathology of corticobasal syndrome using clinical features and biomarkers.

Neuropathological correlates of imaging in dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is a common yet underdiagnosed neurodegenerative dementia, characterised neuropathologically by nigrostriatal dopaminergic degeneration and widespread α-synuclein aggregation. Clinical diagnosis remains challenging due to marked heterogeneity in presentation and substantial overlap with Alzheimer's disease (AD), resulting in diagnostic delays and frequent misdiagnosis. The ability to identify underlying pathological processes ante-mortem is essential to improve diagnostic accuracy, refine prognosis, stratify patients for clinical trials, and ultimately enable personalised therapeutic approaches. Over recent decades, major advances have been made in the development of neuroimaging biomarkers that reflect key features in Lewy body disease pathology, many of which have informed diagnostic criteria. In addition to dopaminergic dysfunction and α-synuclein pathology, co-existing neuropathologies including amyloid-β, tau, neuroinflammation, and vascular changes are increasingly recognised as important modifiers of clinical phenotype and disease trajectory in DLB. This review summarises the current landscape of neuroimaging modalities in DLB and critically examines their relationships with confirmed neuropathological correlates. We discuss indicative biomarkers such as striatal dopamine imaging and 123I-metaiodobenzylguanidine myocardial scintigraphy, alongside supportive imaging markers derived from structural magnetic resonance imaging and Fluorodeoxyglucose Positron Emission Tomography (FDG-PET). Emerging PET approaches targeting α-synuclein, as well as established amyloid and tau-PET techniques for assessing co-pathologies, are reviewed in the context of post-mortem validation studies. Finally, we consider Translocator protein PET imaging as a marker of neuroinflammation and highlight key methodological limitations and knowledge gaps. Together, these neuroimaging-pathological correlations provide critical insights into disease mechanisms and outline future directions toward earlier, biologically informed diagnosis and precision medicine in DLB.

Imaging Biomarkers in Parkinson's Disease and Movement Disorders: Emerging Insights from Multimodal Neuroimaging.

This editorial introduces a special issue detailing the rapid evolution of multimodal neuroimaging biomarkers for Parkinson's disease (PD) and related movement disorders. Advances in MRI, including quantitative susceptibility mapping for iron dysregulation, neuromelanin-sensitive MRI, diffusion tensor imaging for free water quantification, metabolic spectroscopy, and functional network mapping, are reviewed. The integrated application of these modalities demonstrates that PD neurodegeneration cannot be captured by a single biomarker. Instead, these complementary tools define overlapping biological dimensions of the disease, spanning dopaminergic neuronal integrity, microstructural injury, glymphatic impairment, vascular abnormalities, and large-scale network reorganization. Furthermore, the integration of artificial intelligence and machine learning allows for the extraction of multidimensional patterns, improving the differential diagnosis between PD and atypical parkinsonian syndromes like multiple system atrophy and progressive supranuclear palsy. We conclude that while these multimodal biomarkers offer unprecedented mechanistic insights into disease progression and therapeutic response, their ultimate value depends on successful clinical translation. Moving forward, it would be essential for the field to prioritize standardized acquisition protocols, automated post-processing pipelines, and accessible reporting frameworks to implement these powerful research tools into routine clinical environments.

Modern Directions in Early Biomarker Diagnostics of Parkinson's Disease

Background: Parkinson’s disease (PD) is the fastest-growing neurological disorder globally. Traditional diagnosis, which relies on motor symptoms, is associated with a 15–24% error rate and occurs after significant loss of dopaminergic neurons. Early biomarker identification is essential for biological redefinition of PD and timely intervention.Objective: To synthesize evidence from the past five years on minimally invasive biomarkers and assess whether multimodal panels offer greater diagnostic precision than single tests.Methods: A systematic review of PubMed and Scopus (January 2021–January 2026) was conducted per PRISMA guidelines, including meta-analyses and original studies on α-synuclein seed amplification assays (SAA), neuronally derived extracellular vesicles (LIEVs), neurofilament light chain (NfL), and advanced imaging (OCT-A, MRI).Results: SAA exhibited 96% sensitivity in GBA1 mutation carriers and 98.6% in hyposmic individuals with dopaminergic deficits, but only 67.5% in LRRK2 carriers. Serum LIEV-associated α-synuclein distinguished prodromal cases with high precision (AUC=0.91). NfL predicted functional decline (OR=2.54) up to five years before diagnosis. Advanced neuroimaging and skin RT-QuIC tests showed diagnostic accuracies from 82% to 100%.Conclusion: PD diagnosis is shifting from clinical observation to biological profiling. Multimodal biomarker panels integrating molecular, microvascular, and imaging data provide the most precise risk stratification, enabling timely, targeted neuroprotective interventions by rehabilitation specialists.

Multiple system atrophy: cure and care.

Multiple system atrophy (MSA) is a rare and rapidly progressive neurodegenerative disorder characterized by a variable combination of autonomic failure, parkinsonism, and cerebellar ataxia, with a median survival of 8-10 years from symptom onset. Its aetiology remains poorly understood, as most cases are sporadic and environmental contributors remain unclear. Neuropathologically, MSA is defined by the accumulation of α-synuclein within oligodendroglial cells, forming glial cytoplasmic inclusions that drive widespread neurodegeneration in striatonigral and olivopontocerebellar systems. Recent advances in diagnostic criteria and biomarker development have improved disease recognition; however, early diagnosis remains challenging, particularly during the prodromal phase, when clinical features overlap with other α-synucleinopathies. Advances in fluid biomarkers and multimodal imaging are expected to facilitate earlier detection, improve diagnostic accuracy, and provide more robust tools for monitoring disease progression. Therapeutic development has largely focused on targeting α-synuclein pathology, but these approaches have not yet demonstrated consistent clinical benefit, highlighting the biological complexity of MSA. In the absence of curative treatments, management remains largely supportive, aimed at symptom control, particularly addressing autonomic dysfunction and motor impairment. Emerging care models, including telemedicine and multidisciplinary management, are reshaping clinical practice and may improve access to specialized care. Bridging advances in pathophysiology with patient-centred care will be essential for improving outcomes in MSA.