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Record W7117107372 · doi:10.1002/alz70855_104816

Coordinated multi‐cellular responses to Alzheimer's disease pathology reveal sex‐specific resilience signatures

2025· article· en· W7117107372 on OpenAlexaff
Gabriele Vilkaite, Lijun An, Yu Xiao, Inès Hristovska, Chris Gaiteri, Alexa Pichet Binette, Niklas Mattsson‐Carlgren, Jacob W. Vogel

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsDiseaseMulticellular organismComponent (thermodynamics)Resilience (materials science)Programmed cell deathPsychological resilienceFight-or-flight response

Abstract

fetched live from OpenAlex

BACKGROUND: Alzheimer's disease (AD) triggers multicellular transcriptomic responses that may reflect and moderate disease progression. While most studies observe these likely-concurrent cell-specific changes independently, the current study investigates multi-cellular associations with AD phenotypes. METHOD: We analyzed single-nuclei transcriptomics from the dorsolateral prefrontal cortex (DLPFC) of 427 donors (ROSMAP, Mathys et al.; 2.3M cells). Metacells were generated using k-nearest neighbor clustering, and hierarchical gene clustering identified cell-type-specific gene modules (Figure 1). AD-related gene modules (AGMs) were identified as clusters that showed cross-validated associations with any disease phenotypes. AGMs underwent gene-set enrichment analysis and were entered into a partial least squares (PLS) analysis, deriving multicellular interactions simultaneously predicting multiple AD neuropathological measures and clinical features. RESULT: We identified 28 AGMs across 11 cell subtypes. Cross-validation of PLS regression led to selection of three components, while permutation testing confirmed the model's non-random structure (Figure 2A). Component 1 reflected a combinatorial effect of all significant AD-related gene clusters responding to increased pathology, being strongly associated with amyloid-β (Aβ), tau and TDP-43 pathology, and negatively with APOE E2 carriage (Figure 2B-F). Components 2 (men) and 3 (women) highlighted potential sex-specific resilience responses, positively associated with age and Aβ but negatively with tau pathology (Figure 2B-F). Gene-set enrichment (Figure 3) revealed Component 1 to involve downregulation of defense responses and upregulation of cell junction and adhesion across vulnerable neuronal types, perhaps indicating movement away from defense and toward glia-mediated self-destructive processes. Enrichment further suggested that components 2 and 3 involved oligodendrocyte-mediated synaptic remodeling and neuronal immune/defense responses, with component 2 (men) involving L6B excitatory neurons and component 3 (women) more involving RORB-GABRG excitatory and PVALB-HTR4 inhibitory neurons. Astrocytes and oligodendrocyte precursor cells contributed opposing loadings relative to each other in components 2 and 3. CONCLUSION: Multiple cell types exhibit concurrent shifts, suggesting potential multi-cellular associations with AD pathology. Changes in the first component reflected a generalized response to neurodegenerative pathology, likely representing neuronal death processes of selective neuronal subpopulations. In contrast, two additional multicellular responses emerged, suggesting sex-specific cellular activity moderating resilience to AD pathology. Coordinated cell-type-specific alterations underscore the need to address cross-cellular interactions in AD.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.324
Teacher spread0.294 · 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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