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Record W4312086180 · doi:10.1002/alz.069285

Plasma levels of an N‐terminal tau fragment predict core AD and neurodegenerative biomarkers in autosomal dominant Alzheimer’s disease: Findings from DIAN

2022· article· en· W4312086180 on OpenAlexaff
Stephanie A. Schultz, Lei Liu, Beth L. Ostaszewski, Colleen Fitzpatrick, Chengjie Xiong, Anne M. Fagan, James M. Noble, Pedro Rosa‐Neto, Martin R. Farlow, John C. Morris, Richard J. Perrin, Mathias Jucker, Clifford R. Jack, Celeste M. Karch, Brian A. Gordon, Keith A. Johnson, Eric McDade, Reisa A. Sperling, Randall J. Bateman, Dennis J. Selkoe, Jasmeer P. Chhatwal

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsNeurodegenerationCognitive declineClinical Dementia RatingDementiaInternal medicineOncologyAlzheimer's diseaseMedicineCerebrospinal fluidDiseasePathologyNeurosciencePsychology

Abstract

fetched live from OpenAlex

Abstract Background Blood based biomarkers that predict cognitive decline and Alzheimer’s disease (AD) pathology have the potential to accelerate AD therapeutic development and improve clinical care. Prior work suggests that plasma biomarkers of tau pathology (particularly post‐translational modifications of tau) may be highly useful in diagnosis and risk stratification for AD‐related neurodegeneration and cognitive decline. Levels of tau species lacking truncation of the N‐terminal region, particularly plasma and cerebrospinal fluid (CSF) levels of N‐terminal tau fragment 1 (NT1), have previously been shown to predict cognitive decline, neurodegeneration, and tau pathology in preclinical and symptomatic late‐onset AD. Here we examined plasma NT1 as a possible predictor of cognitive, clinical, pathologic, and neurodegenerative trajectories in autosomal dominant AD (ADAD) using data from the Dominantly Inherited Alzheimer Network Observational Study (DIAN‐Obs). Methods Associations between plasma NT1 levels and Mini‐Mental State Exam (MMSE), Clinical Dementia Rating SumBox® (CDR‐SB), hippocampal volume (HV), estimated years to symptom onset (EYO), Pittsburgh‐Compound‐B PET, and CSF Aβ42, and p‐tau181 were assessed using linear regression (150 pathogenic variant carriers, 81 non‐carriers; mean[SD] carrier age = 40.1 [10.4] years and EYO = ‐5.4 [10.4]). Plasma NT1 was measured using the Quanterix HD‐X platform. PET, MRI, clinical, and biofluid measures were derived using previously described procedures in DIAN‐Obs. Results Cross‐sectional plasma NT1 levels in ADAD carriers were significantly associated with MMSE, CDR‐SB, HV, and p‐tau181 even after adjusting for EYO (Table 1; Figure 1). NT1 levels statistically diverged between carriers and non‐carriers 6.8 years before estimated symptom onset (Figure 2). In contrast, plasma NT1 levels were not significantly correlated with measures of β‐amyloid pathology after adjusting for EYO. Conclusion Plasma NT1 levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with CSF measures of tau pathology, but NT1 levels were not strongly associated with CSF or PET measures of β‐amyloid pathology, unlike some previously‐studied plasma tau measures. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1 may be a useful biomarker of AD‐related tau pathology and neurodegeneration across a broad spectrum of disease.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.304
Teacher spread0.262 · 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
Published2022
Admission routes1
Has abstractyes

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