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Record W4410808770 · doi:10.1093/brain/awaf200

CSF proteomics of semorinemab Alzheimer’s disease trials identifies cell-type specific signatures

2025· article· en· W4410808770 on OpenAlexaff
Alyaa M. Abdel‐Haleem, Ellen Casavant, Balázs István Tóth, Edmond Teng, Cecília Monteiro, Nikhil J Pandya, Caspar Glock, Casper C. Hoogenraad, Brad A. Friedman, Felix L. Yeh, Veronica G. Anania, Gloriia Novikova

Bibliographic record

VenueBrain · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsRoche (Canada)
FundersGenentechRoche
KeywordsProteomicsClinical trialClinical endpointCerebrospinal fluidAlzheimer's diseaseDiseaseMedicineInternal medicinePlaceboBioinformaticsOncologyPathologyNeuroscienceBiologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Targeting of tau pathology has long been proposed as a potential therapeutic strategy for Alzheimer's disease (AD). Semorinemab is a humanized IgG4 monoclonal antibody that binds to all known isoforms of full-length tau with high affinity and specificity. Semorinemab's safety and efficacy have been studied in two phase 2 randomized, double-blind, placebo-controlled, parallel-group clinical trials: Tauriel (prodromal-to-mild AD; NCT03289143; in which semorinemab failed to demonstrate clinical efficacy) and Lauriet (mild-to-moderate AD; NCT03828747. However, semorinemab was associated with a significant slowing in progression in a co-primary end point of cognition only in Lauriet but not in Tauriel. Proteomic profiling of CSF collected in these trials was performed to gain a better understanding of the effect of semorinemab in light of the different clinical outcomes. CSF was collected from a subset of patients at baseline and after 49 or 73 weeks in Tauriel and baseline and after 49 or 61 weeks in Lauriet. Samples were analysed using single-shot field asymmetric ion mobility spectrometry-data independent acquisition-mass spectrometry (FAIMS-DIA-MS) and analysed with Spectronaut and MS Stats. Proteomics results were integrated with publicly available single-nucleus brain datasets to contextualize cellular expression profiles of differentially expressed proteins. A novel proteomics dataset was generated using more than 250 CSF samples where more than 3500 proteins were detected. Treatment-associated proteomic signatures were defined for each clinical trial as the set of proteins significantly elevated in the treatment arm in the respective trial. Integration of the corresponding gene signatures with brain single-nucleus RNA-sequencing datasets from AD and healthy age-matched controls revealed that the Lauriet signature genes were enriched in microglia, while Tauriel signature genes were more broadly expressed across brain cell types. Furthermore, the Lauriet gene signature was significantly upregulated in microglia from AD patients compared to non-demented controls. The elevation of proteins such as CHI3L1 and GPNMB with treatment suggested an activated glial state. This study demonstrates the utility of CSF clinical proteomics to assess the pharmacodynamic response of semorinemab and contributes to our understanding of how an anti-tau antibody influences disease-relevant pathophysiology 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)0.002
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.060
GPT teacher head0.368
Teacher spread0.308 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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