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Record W4210602489 · doi:10.1212/wnl.0000000000200035

Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline

2022· article· en· W4210602489 on OpenAlexfundno aff

Bibliographic record

VenueNeurology · 2022
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsnot available
FundersAvid RadiopharmaceuticalsIXICOGIESKES-STRIJBIS FONDSAmsterdam NeuroscienceStichting DioraphteUniversity College London Hospitals NHS Foundation TrustSanofiEuropean CommissionUniversity College LondonZonMwKyowa Kirin Pharmaceutical DevelopmentNederlandse Organisatie voor Wetenschappelijk OnderzoekWeston Brain InstituteNational Institute for Health and Care ResearchTeva Pharmaceutical IndustriesAlzheimer NederlandEU Joint Programme – Neurodegenerative Disease ResearchBiogen
KeywordsCognitive declineAssociation (psychology)NeurodegenerationCognitionNeuroimagingDisease

Abstract

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<h3>Background and Objectives</h3> Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD). <h3>Methods</h3> We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker. <h3>Result</h3> We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%–19%). N biomarkers were modestly to moderately correlated (range <i>r</i> −0.28 – 0.58). Serum NfL and GFAP correlated most strongly (<i>r</i> 0.58, <i>p</i> &lt; 0.01). T-tau was strongly correlated with p-tau (<i>r</i> 0.89, <i>p</i> &lt; 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11–2.09]; 1.51 [1.05–2.17]; 1.50 [1.04–2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β −0.17 to −0.11, <i>p</i> &lt; 0.05), but only HV remained associated beyond Aβ and p-tau (β −0.13 [SE 0.04]; <i>p</i> &lt; 0.05). <h3>Discussion</h3> In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T. <h3>Classification of Evidence</h3> This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.

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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)0.001
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 score0.014
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.316
Teacher spread0.301 · 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

Citations76
Published2022
Admission routes1
Has abstractyes

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