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Record W4205690343 · doi:10.1002/alz.057523

Leukotriene receptor antagonist use is associated with slower cognitive decline in Alzheimer’s disease

2021· article· en· W4205690343 on OpenAlexaff
Lisa Y. Xiong, Michael Ouk, Che‐Yuan Wu, Jennifer S. Rabin, Krista L. Lanctôt, Nathan Herrmann, Sandra E. Black, Jodi D. Edwards, Walter Swardfager

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of OttawaSunnybrook Health Science CentreHeart and Stroke FoundationHealth Sciences CentreSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsMontelukastDementiaMedicineAlzheimer's diseaseDonepezilAsthmaCognitive reserveAudiologyPediatricsGerontologyInternal medicinePsychologyDisease

Abstract

fetched live from OpenAlex

Abstract Background Repurposing of leukotriene receptor antagonists (LTRAs), originally developed for asthma, is currently being explored in the treatment Alzheimer’s disease (AD). Animal studies have shown that administration of the LTRA montelukast has neuroprotective effects and can improve memory and cognition in rodents; however, there is limited evidence supporting the neuroprotective effects of LTRAs in humans. Methods Participants with AD dementia were identified in the National Alzheimer's Coordinating Center database. LTRA (montelukast or zafirlukast) users were propensity matched 1:3 to non‐users on age, sex, education, body mass index, smoking history, concomitant use of medications for dementia and other respiratory medications (for allergy, chronic obstructive pulmonary disease, and asthma), APOE ε4 carrier status, CDR® Dementia Staging Instrument global score, and vascular brain disease. Cognitive domains including immediate and delayed memory (Weschler Memory Scale Revised – Logical Memory IA and IIA), psychomotor processing speed (Digit Symbol), and language (Animals, Vegetables, and Boston Naming Test) were compared between users and non‐users in mixed‐effects linear or Poisson regression models, as appropriate for the data distribution, yielding unstandardized regression coefficients (B) and rate ratios (RR), respectively. Results Among n=604 people with AD dementia (mean age 75.3±10.0 years, 59.3% female, mean education 14.0±4.0 years, 55.1% APOE ε4 carriers, mean follow‐up 2.5±2.6 years), LTRA use was associated with a slower decline in psychomotor processing speed, as measured by the Digit Symbol test (Β=1.466 [0.253,2.687] symbols/year), and a slower decline in language, as measured by Animals (Β=0.541 [0.215,0.866]animals/year), Vegetables (B=0.309 [0.056,0.561] vegetables/year), and the Boston Naming Test (B=0.529 [0.005,1.053] words/year). Effect sizes were relatively small (range 0.069‐0.101) and persisted after controlling for a 10% false discovery rate. LTRA use was not associated with a change in performance for immediate (RR=1.047 [0.970,1.129]) or delayed memory (RR=1.062 [0.929,1.215]). Conclusion These results indicate that use of an LTRA may have benefits for preserving function for select cognitive domains in individuals with AD dementia. The leukotriene pathway may represent a target for the treatment of AD dementia and the role of leukotrienes and their receptors in cognitive decline warrants further investigation.

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)0.004
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.319
Teacher spread0.278 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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