MétaCan
Menu
← Back to cohort
Record W4402306262 · doi:10.1101/2024.09.05.24313131

Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorder

2024· preprint· en· W4402306262 on OpenAlexafffund
Stephen Joza, Aline Delva, Christina Tremblay, Andrew Vo, Marie Filiatrault, Max Tweedale, John‐Paul Taylor, John T. O’Brien, Michael Firbank, Alan Thomas, Paul C. Donaghy, Johannes Klein, Petr Dušek, Stanislav Mareček, Zsóka Varga, Stéphane Lehéricy, Isabelle Arnulf, Marie Vidailhet, Jean‐Christophe Corvol, Jean‐François Gagnon, Ronald B. Postuma, Alain Dagher, Richard Camicioli, Howard Chertkow, Simon J.G. Lewis, Elie Matar, Kaylena A. Ehgoetz Martens, L. Churchill, Michael Sommerauer, Sinah Röttgen, Per Borghammer, Karoline Knudsen, Allan K. Hansen, Dario Arnaldi, Beatrice Orso, Pietro Mattioli, Luca Roccatagliata, Oury Monchi, Shady Rahayel

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversité de MontréalUniversity of WaterlooBaycrest HospitalWomen and Children’s Health Research InstituteMontreal General HospitalInstitut Universitaire de Gériatrie de MontréalUniversité du Québec à MontréalHôpital du Sacré-Cœur de MontréalMcGill UniversityUniversity of TorontoMontreal Neurological Institute and Hospital
FundersNIHR Newcastle Biomedical Research CentreMedical Research CouncilFonds de Recherche du Québec - SantéItalfarmacoCanadian Institutes of Health ResearchIpsenParkinson VerenigingH. Lundbeck A/SServierIdorsia PharmaceuticalsAgentura Pro Zdravotnický Výzkum České RepublikyÉlectricité de FranceNewcastle upon Tyne Hospitals NHS Foundation TrustEisaiElse Kröner-Fresenius-StiftungUniversität zu KölnCanada Research ChairsNewcastle UniversityBundesministerium für Bildung und ForschungMinisterstvo Školství, Mládeže a TělovýchovySeqirusParkinson's UKEuropean CommissionFondation Brain CanadaUniversity of AlbertaParkinson CanadaAgence Nationale de la RechercheAlzheimer SocietyAlzheimer's SocietyTauRx PharmaceuticalsParkinsonforeningenConsortium canadien en neurodégénérescence associée au vieillissementNational Institute on AgingNational Institute for Health and Care ResearchNovo NordiskJascha FondenEU Joint Programme – Neurodegenerative Disease ResearchNational Institutes of HealthRegeneron PharmaceuticalsNIHR Oxford Biomedical Research CentreBiogenNational Health and Medical Research CouncilInternational Parkinson and Movement Disorder SocietyAarhus UniversitetLundbeckfondenBrightFocus FoundationEli Lilly and Company
KeywordsAtrophySleep (system call)MedicineNeurosciencePsychologyPathologyComputer science

Abstract

fetched live from OpenAlex

Abstract Background Synucleinopathies manifest as a spectrum of disorders that vary in features and severity, including idiopathic/isolated REM sleep behaviour disorder (iRBD) and dementia with Lewy bodies. Patterns of brain atrophy in iRBD are already reminiscent of what is later seen in overt disease and are related to cognitive impairment, being associated with the development of dementia with Lewy bodies. However, how brain atrophy begins and progresses remains unclear. Methods A multicentric cohort of 1,134 participants, including 538 patients with synucleinopathies (451 with polysomnography-confirmed iRBD and 87 with dementia with Lewy bodies) and 596 healthy controls, was recruited from 11 international study centres and underwent T1-weighted MRI imaging and longitudinal clinical assessment. Scans underwent vertex-based cortical surface reconstruction and volumetric segmentation to quantify brain atrophy, followed by parcellation, ComBAT scan harmonization, and piecewise linear z-scoring for age and sex. We applied the unsupervised machine learning algorithm, Subtype and Stage Inference (SuStaIn), to reconstruct spatiotemporal patterns of brain atrophy progression and correlated the distinct subtypes with clinical markers of disease progression. Results SuStaIn identified two unique subtypes of brain atrophy progression: 1) a “cortical-first” progression subtype characterized by atrophy beginning in the frontal lobes followed by the temporal and parietal areas and remaining cortical areas, with the involvement of subcortical structures at later stages; and 2) a “subcortical-first” progression subtype, which involved atrophy beginning in the limbic areas, then basal ganglia, and only involving cortical structures at late stages. Patients classified to either subtype had higher motor and cognitive disease burden and were more likely to phenoconvert to overt disease compared with those that were not classifiable. Of the 84 iRBD patients who developed overt disease during follow-up, those with a subcortical-first pattern of atrophy were more likely to phenoconvert at earlier SuStaIn stages, particularly to a parkinsonism phenotype. Conversely, later disease stages in both subtypes were associated with more imminent phenoconversion to a dementia phenotype. Conclusions Patients with synucleinopathy can be classified into distinct patterns of atrophy that correlate with disease burden. This demonstrates insights into underlying disease biology and the potential value of categorizing patients in clinical trials.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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 routes2
Has abstractyes

Explore more

Same venuemedRxiv→Same topicParkinson's Disease Mechanisms and Treatments→French-language works237,207→