Evidence map›Paper›PMID 41757373›Full record

ReviewParkinson's disease2026

Towards a Biologically Defined Diagnosis: Incorporating Pathophysiological Measures Into Parkinson's Disease Clinical Criteria.

Angus McNamara, Laura M Carr, Irina Baetu, Mark Jenkinson, Lyndsey Collins-Praino

Abstract readReview
In one paragraph

Review in Parkinson's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Angus McNamaraSchool of Biomedicine, University of Adelaide, Adelaide, South Australia, Australia, adelaide.edu.au.ORCID https://orcid.org/0000-0002-5160-5435
Laura M CarrSchool of Biomedicine, University of Adelaide, Adelaide, South Australia, Australia, adelaide.edu.au.ORCID https://orcid.org/0000-0002-6008-1389
Irina BaetuSchool of Psychology, University of Adelaide, Adelaide, South Australia, Australia, adelaide.edu.au.ORCID https://orcid.org/0000-0002-5565-7136
Mark JenkinsonAustralian Institute for Machine Learning, School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, South Australia, Australia, adelaide.edu.au.ORCID https://orcid.org/0000-0001-6043-0166
Lyndsey Collins-PrainoSchool of Biomedicine, University of Adelaide, Adelaide, South Australia, Australia, adelaide.edu.au.ORCID https://orcid.org/0000-0002-4380-7600

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease is the second most common neurodegenerative disorder worldwide, as well as being the fastest-growing neurological disorder. Furthermore, PD corresponds to a significant burden on those diagnosed, their caregivers and healthcare systems, highlighting the critical need for early and accurate diagnosis. Effective diagnosis is essential not only for timely intervention but also for the development of disease-modifying treatments, which are currently unavailable for PD management. Historically, PD diagnosis and characterisation was heavily reliant on clinical presentation, which are only present after significant neurodegeneration has already occurred. Because of this, there is a consensus amongst the scientific community to transition away from clinical features and instead redefine PD diagnosis and staging based on biological presentation. This review discusses historical developments in clinical diagnostic criteria for PD as well as the role the recently developed frameworks such as SynNeurGe and the Neuronal alpha-Synuclein Disease-Integrated Staging System (NSD-ISS) will play in the further advancements of diagnostic practices. Furthermore, substantial research efforts into the pathobiology of PD have led to the development of novel in vivo assessments capable of detecting critical biomarkers of PD. Specialised imaging modalities, particularly nuclear imaging and magnetic resonance imaging, and biomarkers of α-synuclein pathology demonstrate high sensitivity and specificity for not only early diagnosis but also differential diagnosis between other parkinsonisms. Beyond diagnostic reforms, it is also important to identify markers that could serve as indicators of clinical course to aid in tailoring personalised treatment strategies. Therefore, this review also summarises key pathobiological hallmarks of PD beyond α-synuclein pathology, namely, dopaminergic denervation, copathologies and underlying indicators of neurodegeneration, such as iron deposition and neuroinflammation. Furthermore, strategies to assess such pathologies and their potential utility in the current paradigm shift towards biological characterisation are discussed.

Identifiers

PMID41757373
PMCPMC12934250

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.