MétaCan
Menu
Back to cohort
Record W3100299358 · doi:10.1093/brain/awaa342

Stage-specific links between plasma neurofilament light and imaging biomarkers of Alzheimer’s disease

2020· article· en· W3100299358 on OpenAlexafffund
Andréa L. Benedet, Antoine Leuzy, Tharick A. Pascoal, Nicholas J. Ashton, Sulantha Mathotaarachchi, Mélissa Savard, Joseph Therriault, Min Su Kang, Mira Chamoun, Michael Schöll, Eduardo R. Zimmer, Serge Gauthier, Aurélie Labbe, Henrik Zetterberg, Pedro Rosa‐Neto, Kaj Blennow

Bibliographic record

VenueBrain · 2020
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMontreal Neurological Institute and HospitalHEC MontréalMcGill University
FundersH2020 European Research CouncilNational Institutes of HealthWallenberg Centre for Molecular and Translational MedicineUK Dementia Research InstituteVetenskapsrådetCanada Foundation for InnovationNational Institute on AgingAlzheimer's AssociationConsortium canadien en neurodégénérescence associée au vieillissementCanadian Institutes of Health ResearchWeston Brain InstituteNorthern California Institute for Research and EducationAbbVieUniversity of Southern CaliforniaBioClinicaNational Institute of Biomedical Imaging and BioengineeringTorsten Söderbergs StiftelseAlzheimer's Disease Neuroimaging InitiativeU.S. Department of Defense
KeywordsDementiaPittsburgh compound BAlzheimer's diseaseNeurodegenerationAlzheimer's Disease Neuroimaging InitiativeAtrophyNeuroimagingMedicinePsychologyDiseaseInternal medicineAmyloid (mycology)White matterPathologyNeuroscienceOncologyMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Neurofilament light (NfL) is a marker of neuroaxonal injury, a prominent feature of Alzheimer's disease. It remains uncertain, however, how it relates to amyloid and tau pathology or neurodegeneration across the Alzheimer's disease continuum. The aim of this study was to investigate how plasma NfL relates to amyloid and tau PET and MRI measures of brain atrophy in participants with and without cognitive impairment. We retrospectively examined the association between plasma NfL and MRI measures of grey/white matter volumes in the Alzheimer's Disease Neuroimaging Initiative [ADNI: n = 1149; 382 cognitively unimpaired control subjects and 767 cognitively impaired participants (mild cognitive impairment n = 420, Alzheimer's disease dementia n = 347)]. Longitudinal plasma NfL was measured using single molecule array (Simoa) technology. Cross-sectional associations between plasma NfL and PET amyloid and tau measures were independently assessed in two cohorts: ADNI [n = 198; 110 cognitively unimpaired, 88 cognitively impaired (MCI n = 67, Alzheimer's disease dementia n = 21), data accessed October 2018]; and Translational Biomarkers in Aging and Dementia [TRIAD, n = 116; 74 cognitively unimpaired, 42 cognitively impaired (MCI n = 16, Alzheimer's disease dementia n = 26), data obtained November 2017 to January 2019]. Associations between plasma NfL and imaging-derived measures were examined voxel-wise using linear regression (cross-sectional) and linear mixed effect models (longitudinal). Cross-sectional analyses in both cohorts showed that plasma NfL was associated with PET findings in brain regions typically affected by Alzheimer's disease; associations were specific to amyloid PET in cognitively unimpaired and tau PET in cognitively impaired (P < 0.05). Longitudinal analyses showed that NfL levels were associated with grey/white matter volume loss; grey matter atrophy in cognitively unimpaired was specific to APOE ε4 carriers (P < 0.05). These findings suggest that plasma NfL increases in response to amyloid-related neuronal injury in preclinical stages of Alzheimer's disease, but is related to tau-mediated neurodegeneration in symptomatic patients. As such, plasma NfL may a useful measure to monitor effects in disease-modifying drug trials.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.052
GPT teacher head0.309
Teacher spread0.257 · 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.

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

Citations115
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueBrainSame topicAlzheimer's disease research and treatmentsFrench-language works237,207