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Record W4406201478 · doi:10.1002/alz.092285

ApoE4 Status Moderates the Association between Vascular Risks, Cerebral Perfusion and Cognitive Performance in a Southeast Asian Population

2024· article· en· W4406201478 on OpenAlexaboutno aff
Smriti Ghildiyal, Ashwati Vipin, Gurveen Kaur Sandhu, See Ann Soo, Pricilia Tanoto, Fatin Zahra Zailan, Yi Jin Leow, Faith Phemie Hui En Lee, Shan Yao Liew, Isabelle Yu Zhen Tan, Maleeha Azam, Dilip Kumar, Chao Dang, James Xiao Yuan Chen, Nagaendran Kandiah

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsAssociation (psychology)CognitionCerebral perfusion pressurePerfusionPopulationMedicinePsychologySoutheast asiaCardiologyInternal medicineNeuroscienceHistoryEnvironmental healthPsychotherapistAncient history

Abstract

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Abstract Background Factors contributing to cognitive decline in adults include vascular risk factors (hypertension, hyperlipidemia, diabetes), lower education, age, Apolipoprotein E4(ApoE4) and cerebral hypoperfusion. The interplay between aging and vascular processes disrupts cerebral hemodynamics, heightening the risk of cognitive impairment and neurological disorders. Similarly, ApoE4 gene increases the risk of vascular‐related cognitive impairment and small vessel disease. The interaction between vascular risk factors, cerebral perfusion and ApoE4 carrier status on cognitive performance needs further exploration in a Southeast Asian population. Method 601 participants(Age=62.53±10.19) were recruited from the community‐based BIOCIS study at Dementia Research Centre(Singapore). Participants with a research diagnosis of Subjective Cognitive Decline(SCD), Mild Cognitive Impairment(MCI) or dementia were included and stratified into midlife (45‐65, n=327) and later‐life (>65, n=274). Participants were administered global cognitive tests: Montreal Cognitive Assessment(MoCA), Visual Cognitive Assessment Test(VCAT), and a comprehensive neuropsychological test battery including tests for episodic memory(EM). Vascular risk factors included averaged systolic blood pressure(BP) and fasting HBA1C levels. ApoE allelic variation was determined via Taqman SNP genotyping qRT‐PCR methodology. Arterial Spin Labelling MRI data was used to quantify cerebral perfusion using the BASIL toolbox. Result During midlife, linear regression analyses indicted elevated levels of vascular risk factors(BP and HBA1C) and positive ApoE4 carrier status were associated with poorer cognitive performance. The results demonstrated a significant interaction effect between BP and ApoE4 carrier status on global cognition: VCAT(β=‐0.031, p=0.050), MoCA (β=‐0.037, p=0.045) and between HBA1C and ApoE4 carrier status on EM scores: RAVLT delayed trial(β=‐2.68, p=0.001). During later‐life, lowered levels of cerebral perfusion were associated with poorer cognitive performance in ApoE4 carriers only. The results found a marginally significant interaction effect between cerebral perfusion and ApoE4 carrier status on global cognition: VCAT(β=0.2286, p=0.060), and EM: RAVLT delayed (β=0.298, p=0.024), WAIS‐Logical Story (β=0.392, p=0.007). All results remained significant despite controlling for age, education, syndrome severity and consumption of medication. Conclusion The presence of ApoE4 allele and vascular risk factors lead to a decline in global cognition and EM scores during midlife for a Southeast Asian population. ApoE4 moderates the relationship between reduced cerebral perfusion and poorer global cognition and EM scores in later‐life. Aggressively treating vascular risk during midlife, especially for ApoE4 carriers may prevent further cognitive decline during later‐life.

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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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
Published2024
Admission routes1
Has abstractyes

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