MétaCan
Menu
Back to cohort
Record W4206458189 · doi:10.1101/2021.12.18.21267994

Vascular risk burden is a key player in the early progression of Alzheimer’s disease

2021· preprint· en· W4206458189 on OpenAlexafffund
João Pedro Ferrari‐Souza, Wagner S. Brum, Lucas Augusto Hauschild, Lucas Uglione Da Ros, Pâmela C.L. Ferreira, Bruna Bellaver, Douglas Teixeira Leffa, Andrei Bieger, Cécile Tissot, Marco Antônio De Bastiani, Guilherme Povala, Andréa Lessa Benedet, Joseph Therriault, Nicholas J. Ashton, Henrik Zetterberg, Kaj Blennow, Sheila Cristina Ouriques Martins, Diogo O. Souza, Pedro Rosa‐Neto, Thomas K. Karikari, Tharick A. Pascoal, Eduardo R. Zimmer

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
FundersNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchNational Institutes of HealthH. Lundbeck A/SServierEisaiGenentechIXICOConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorNorthern California Institute for Research and EducationMcGill UniversityF. Hoffmann-La RocheUniversity of Southern CaliforniaPfizerBiogenBioClinicaNovartis Pharmaceuticals CorporationNational Alliance for Research on Schizophrenia and DepressionU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbMeso Scale DiagnosticsAlzheimer's AssociationFoundation for the National Institutes of Health
KeywordsMedicineCognitive declineDiseaseNeurodegenerationPathophysiologyInternal medicineRisk factorStroke (engine)Alzheimer's diseaseContext (archaeology)Vascular dementiaDementiaCardiologyPsychology

Abstract

fetched live from OpenAlex

Abstract Understanding whether vascular risk factors synergistically potentiate Alzheimer’s disease progression is important in the context of emerging treatments for preclinical Alzheimer’s disease. The existence of a synergistic relationship could suggest that the combination of therapies targeting Alzheimer’s disease pathophysiology and vascular risk factors might potentiate treatment outcomes. In the present retrospective cohort study, we tested whether vascular risk factor burden interacts with Alzheimer’s disease pathophysiology to accelerate neurodegeneration and cognitive decline in cognitively unimpaired subjects. We evaluated 503 cognitively unimpaired participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Baseline vascular risk factor burden was calculated considering the history of cardiovascular disease, hypertension, diabetes mellitus, hyperlipidemia, stroke or transient ischemic attack, smoking, atrial fibrillation, and left ventricular hypertrophy. Alzheimer’s disease pathophysiology was evaluated using cerebrospinal fluid (CSF) amyloid-β 1-42 (Aβ 1-42 ) reflecting brain amyloidosis (A) and tau phosphorylated at threonine 181 (p-tau 181 ) reflecting brain tau pathology (T). Individuals were dichotomized as having an elevated vascular risk factor burden (V+ if having two or more vascular risk factors) and as presenting preclinical Alzheimer’s disease [(AT)+ if having abnormal CSF p-tau 181 and Aβ 1-42 levels]. Neurodegeneration was assessed with plasma neurofilament light (NfL) and global cognition with the modified version of the Preclinical Alzheimer’s Cognitive Composite. Linear mixed-effects models revealed that an elevated vascular risk factor burden synergistically interacted with Alzheimer’s disease pathophysiology to drive longitudinal increases in plasma NfL levels (β = 5.08, P = 0.016) and cognitive decline (β = −0.43, P = 0.020). Additionally, we observed that vascular risk factor burden was not associated with CSF Aβ 1-42 or p-tau 181 changes over time. Survival analysis demonstrated that individuals with preclinical Alzheimer’s disease and elevated vascular risk factor burden [(AT)+V+] had a significantly greater risk of clinical progression to cognitive impairment (adjusted Hazard Ratio = 3.5, P < 0.001). Our results support the notion that vascular risk factor burden and Alzheimer’s disease pathophysiology are independent processes; however, they synergistically lead to neurodegeneration and cognitive decline. These findings can help in providing the blueprints for the combination of vascular risk factor management and Alzheimer’s disease pathophysiology treatment in preclinical stages. Moreover, we observed plasma NfL as a robust marker of disease progression that may be used to track therapeutic response in future 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)0.001
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 score0.010
Threshold uncertainty score0.704

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 science0.0000.001
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 head0.032
GPT teacher head0.343
Teacher spread0.311 · 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

Citations18
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuemedRxivSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207