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Record W7117168061 · doi:10.1002/alz70855_100929

Sialylated Clusterin Binds CD33 to Regulate Microglial Functions in Alzheimer's Disease

2025· article· en· W7117168061 on OpenAlexaff
Kanayo Satoh, Ye Zhou, Roger B. Dodd, Masahiro Enomoto, Yalun Zhang, Christopher Böhm, F.-C. Chen, Seema Qamar, Mamunur Rashid, Jean Sévalle, Beatrice Acheson, Deniz Ghaffari, Jennifer K Griffin, M. G. Wilson, P. E. Fraser, Elizabeth M. Bradshaw, Peter St George‐Hyslop

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicClusterin in disease pathology
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsClusterinMicrogliaCD33DiseaseHomeostasisAmyloid (mycology)Amyloid βGalectin

Abstract

fetched live from OpenAlex

BACKGROUND: The sialic-acid binding immunoglobulin-like lectin 3 receptor (Siglec-3 / CD33) expressed on microglia, regulates immune functions relevant to Alzheimer's disease (AD). Clusterin (CLU) and apolipoprotein E (ApoE) are soluble, sialylated proteins implicated in AD pathogenesis through genetic associations and their interactions with amyloid-beta (Aβ). However, the role of these proteins as potential CD33 ligands remains unclear. This study explores whether CLU and/or ApoE bind CD33 and examines the functional impact of these interactions on Aβ uptake and amyloid plaque clearance. METHODS: The binding of CD33 to CLU and ApoE was assessed through co-immunoprecipitation using U937 cells (endogenously expressing CD33) and HEK293 cells (expressing exogenous CD33). Quantitative bio-layer interferometry (BLI) and microscale thermophoresis determined binding affinities, focusing on the role of CD33's Arg119 sialic acid binding site. In situ proximity ligation assays (PLA) and co-immunoprecipitation from AD and control human brain lysates validated in vivo interactions. Functional assays examined Aβ uptake and amyloid plaque clearance in monocytes and U937 cells, with or without CLU treatment. RESULTS: The quantitative binding assay revealed that CLU, but not ApoE, was a sialylation-dependent ligand for CD33, binding with high affinity (Kd = 28.9 ± 10.3 nM). Binding required an intact Arg119 residue and dimeric CD33 structure. PLA and co-immunoprecipitation studies demonstrated colocalization of CD33 and CLU on microglia in AD brains, especially near amyloid plaques. Functionally, sialylated CLU inhibited Aβ uptake in monocytes from CD33 "CC" risk allele carriers and reduced amyloid plaque clearance in U937 cells. Desialylated CLU showed no significant effects. Notably, CLU + Aβ oligomers induced stronger CD33 ITIM signaling than CLU alone, enhancing phosphorylation and SHP-1 recruitment. CONCLUSION: This study identifies CLU as a specific CD33 ligand and highlights its role in modulating microglial functions via CD33 ITIM signaling. Sialylated CLU inhibits Aβ uptake and amyloid plaque clearance, suggesting a potential mechanism underlying microglial dysfunction in AD. These findings underscore the therapeutic potential of targeting the CD33-CLU axis to restore microglial homeostasis and enhance amyloid clearance 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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 teacher head, not a consensus.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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