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Record W7121574556 · doi:10.1002/alz70856_105743

Plasma proteome‐wide analysis of dementia risk mechanistically implicates synaptic biomarkers

2025· article· en· W7121574556 on OpenAlexaff
Keenan A. Walker, JINGSHA CHEN, Shi Liu, Yunju Yang, Myriam Fornage, Linda Zhou, Pascal Schlosser, Aditya Surapaneni, Morgan E Grams, Zhongsheng Peng, Gabriela Gómez, Adrienne Tin, Ron C. Hoogeveen, Kevin J. Sullivan, Peter R. Ganz, Joni V. Lindbohm, M Kivimaki, Alejo Nevado‐Holgado, Noel J. Buckley, Rebecca F. Gottesman, Thomas H. Mosley, Eric Boerwinkle, Christie M Ballantyne, Josef Coresh

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsDementiaBiomarkerDiseaseAlzheimer's diseaseSynaptic plasticityNeurotransmission

Abstract

fetched live from OpenAlex

BACKGROUND: Although numerous biological processes have been implicated in Alzheimer's disease (AD) pathogenesis, plasma biomarkers have been largely limited to measures of amyloid-b and p-tau. We used a large-scale plasma and brain tissue proteomic analyses to (i) identify early plasma biomarkers of AD and (ii) assess the mechanistic relevance of identified proteins. METHOD: We applied the SomaScan proteomic platform to measure the abundance of 4,877 plasma proteins among middle-aged adults in the ARIC study. Dementia was assessed over the subsequent 25-year period. Cox proportional hazards models adjusted for demographic characteristics and cardiovascular risk factors were used to relate each plasma protein to 25-year dementia risk. Using brain tissue proteomic results from the ROSMAP cohort, we (i) examined the extent to which identified proteins were differentially expressed in AD, (ii) identified brain tissue protein quantitative trait loci (pQTL), and (iii) used two-sample Mendelian randomization to assess the causal link between candidate plasma proteins and AD dementia. RESULT: In proteome-wide analyses of 10,981 adults (baseline age: 60 (SD 6); 21% Black; 54% women), we identified 32 plasma proteins associated with subsequent dementia risk, most of which were involved in biological processes such as proteostasis, immunity, extracellular matrix organization, and synaptic function (CPLX1, CPLX2, CBLN4). Synaptic proteins CPLX1 and CPLX2 were upregulated in plasma among those at risk for dementia over a 25-year follow-up period, whereas CBLN was down-regulated among individuals at risk for dementia over a 15-year follow-up period. While the majority of the 32 dementia-associated proteins were expressed across multiple tissue, synaptic proteins were primarily expressed in the central nervous system (CNS), and each synaptic protein was down-regulated in AD brains, compared to control brains. Brain tissue pQTLs were identified for CPLX1. Two-sample Mendelian randomization supported the causal link between brain CPLX1 levels and AD dementia (Z=2.13; p = 0.03). CONCLUSION: These results suggest that synaptic proteins are released from the CNS into the blood well before symptom onset. Synaptic proteins measured in blood, such as CPLX1, may represent mechanistically relevant biomarkers of AD dementia risk.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.018
GPT teacher head0.303
Teacher spread0.285 · 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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