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Record W4402759478 · doi:10.1101/2024.09.23.24314220

Distinct Longitudinal Clinical-Neuroanatomical Trajectories in Parkinson’s Disease Clinical Subtypes: Insight Towards Precision Medicine

2024· preprint· en· W4402759478 on OpenAlexaff
Seyed‐Mohammad Fereshtehnejad, Roqaie Moqadam, Houman Azizi, Ronald B. Postuma, Mahsa Dadar, Anthony E. Lang, Connie Marras, Yashar Zeighami

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteMontreal Neurological Institute and HospitalToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsParkinson's diseasePrecision medicineDiseaseNeuroscienceMedicinePhysical medicine and rehabilitationPsychologyPathology

Abstract

fetched live from OpenAlex

ABSTRACT Background Parkinson’s disease (PD) varies widely across individuals in clinical manifestations and course of progression. Identification and characterization of distinct biological subtypes could help explain this heterogeneity, identify the underlying pathophysiology, and predict disease progression across the subgroups of PD. Objective We aimed to compare long-term trajectories of various motor and non-motor clinical features, as well as patterns of brain atrophy between PD subtypes, using longitudinally acquired brain MRIs. Methods Data on 421 individuals with early-stage PD was retrieved from the Parkinson’s Progression Markers Initiative (PPMI), with an average follow-up time of 8.2 years until February 2024. Participants were classified into three clinical subtypes at the de novo stage using a previously validated subtyping criteria based on major motor and non-motor classifiers (early cognitive impairment, REM sleep behavior disorder (RBD), dysautonomia): ‘mild-motor predominant’ (n=223), ‘intermediate’ (n=146), and diffuse-malignant (n=52). To investigate the pattern of brain atrophy, we used T1-weighted MRIs from a subset of the PPMI population with at least two MRIs obtained, which consisted of 134 PD individuals and 60 healthy controls. Deformation-based morphometry (DBM) maps were calculated and mixed effect models were used to examine the interaction between PD subtypes and rate of atrophy across brain regions, controlling for sex and age at baseline. Results Compared to the ‘mild motor-predominant’ subtype, participants who were categorized as diffuse-malignant PD at baseline experienced greater worsening in motor severity ( p =0.007), cognition ( p <0.0001) and activities of daily living (ADL) ( p <0.0001) after 8 years. Individuals with diffuse-malignant PD showed a significantly higher rate of atrophy across multiple brain regions, including precuneus, paracentral lobule, inferior temporal gyrus, fusiform gyrus, and lateral hemisphere of the cerebellum (corrected p <0.05). Conclusion Our study revealed a distinct pattern of long-term progression in various motor and non-motor clinical outcomes between different subtypes of idiopathic PD. Furthermore, we demonstrated an accelerated atrophy pattern within several brain regions in the diffuse-malignant PD subtype. These findings suggest a more widespread and aggressive neurodegenerative process in a subgroup of people with PD, favoring the existence of diverse underlying pathophysiology with clinical relevance for future precision medicine in PD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.394
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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