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Record W7117310677 · doi:10.1002/alz70856_102379

Alzheimer and Neurodegeneration Biomarkers in Mild Cognitive Impairment with Lewy Body Disease in COMPASS‐ND

2025· article· en· W7117310677 on OpenAlexaff
Richard Camicioli, Sandra E. Black, Michael Borrie, Howard Chertkow, Jennifer G Cooper, Desmarais Philippe, Roger A. Dixon, Myrlene Gee, Ging‐Yuek Robin Hsiung, Zahinoor Ismail, Stephen Joza, Mario Masellis, Oury Monchi, Manuel Montero‐Odasso, Krista Nelles, R. B. Postuma, Shady Rahayel, Eric E. Smith, Cheryl L. Wellington

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHôpital du Sacré-Cœur de MontréalMcGill UniversityMontreal Neurological Institute and HospitalUniversity of TorontoWestern UniversityInstitut Universitaire de Gériatrie de MontréalHotchkiss Brain InstituteUniversity of CalgaryCentre Hospitalier de l’Université de MontréalUniversity of British ColumbiaSunnybrook Health Science CentreLawson Health Research InstituteBaycrest HospitalUniversity of Alberta
Fundersnot available
KeywordsNeurodegenerationBiomarkerPathologicalDiseaseCognitive impairmentLewy bodyAlzheimer's diseaseLewy body disease

Abstract

fetched live from OpenAlex

BACKGROUND: Mild Cognitive Impairment (MCI) may be caused by mixed pathologies. Blood markers indicative of Alzheimer pathology or neurodegeneration have not been extensively explored in patients with MCI who have features of Lewy Body disease (LB-MCI) (cognitive fluctuations, parkinsonism, hallucinations, and REM-sleep behavior disorder (RBD)). We compared plasma levels of amyloid beta (Aß), tau, glial-fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) between participants in COMPASS-ND who met criteria for LB-MCI with participant with MCI without these features, healthy controls (HC), and participants with Parkinson's disease (PD) with and without MCI. METHOD: Participants with MCI, HC, and PD were recruited as part of the COMPASS-ND study and underwent assessment of demographic and clinical features. Participants with MCI were classified as LB-MCI based on one or more criteria for LB disease. Plasma biomarkers were determined for amyloid species (Aß 42/40 ratio), tau-181, GFAP, and (NfL using Simoa. Groups were compared using ANOVA with post hoc comparisons. Age and sex adjustment was done in ANCOVA models. RESULT: Among participants with MCI in COMPASS-ND, there were 159 (97 M/62 F) with MCI but without LB features and 105 (46 M/32 F) with one or more of the LB-MCI criteria. There were 161 HC (54 M/107 F), 79 PD (42 M/37 F), and 41 PD-MCI (35 M/7 F). The Aß 42/40 ratio and tau-181 differed between groups, with the LB-MCI group showing a lower Aß 42/40 ratio and higher tau-181 than the other groups. Post hoc comparison indicated that the ratio was lower in LB-MCI than HC, PD, and PD-MCI while tau-181 was higher than HC, PD, and MCI without LB features. GFAP and NfL did not differ across groups. Age and sex adjustment did not alter the main findings. CONCLUSION: In COMPASS-ND, participants with features of LB-MCI showed a biomarker profile suggestive of high Alzheimer co-pathology. Higher tau-181 suggests that these individuals might have a higher pathological burden than the other groups. The influence of other co-pathologies (i.e., vascular) and the influence on outcomes will be examined in this cohort. Future studies should examine for the presence of synuclein pathology across these groups.

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)0.001
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.021
GPT teacher head0.308
Teacher spread0.287 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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