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APOE-ε4 is not associated with pure-tone hearing thresholds, visual acuity or cognition, cross-sectionally or over 3 years of follow up in the Canadian Longitudinal Study on Aging

2024· article· en· W4391264682 on OpenAlexaffabout
Paul Mick, Rasel Kabir, Malshi Karunatilake, M. Kathleen Pichora‐Fuller, Terry-Lyn Young, Yuri L. Sosero, Ziv Gan‐Or, Walter Wittich, Natalie A. Phillips

Bibliographic record

VenueNeurobiology of Aging · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsMemorial University of NewfoundlandUniversity of TorontoMcGill UniversitySaskatchewan Health AuthorityUniversité de MontréalUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsApolipoprotein EAudiologyCognitionVisual acuityPsychologyLongitudinal studyHearing lossAlleleMedicineInternal medicineOphthalmologyGeneticsBiologyPsychiatryDisease

Abstract

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Hearing loss and diminished visual acuity are associated with poorer cognition, but the underlying mechanisms are not understood. The apolipoprotein (APOE) ε4 allelic variant may drive the associations. We tested whether APOE-ε4 allele count (0, 1, or 2) was associated with declines in memory, executive function, pure-tone hearing threshold averages, and pinhole-corrected visual acuity among participants in the Canadian Longitudinal Study on Aging (CLSA). Methods: Multivariable linear mixed regression models were utilized to assess associations between APOE-ε4 allele count and each of the outcome variables. For each main effects model, interactions between APOE-ε4 and sex and age group (45-54-, 55-64-, 65-74-, and 75-85 years) respectively, were analyzed. Results: Significant associations were not observed in main effects models. Models including APOE-ε4*age (but not APOE-ε4*sex) interaction terms better fit the data compared to main effects models. In age group-stratified models, however, there were minimal differences in effect estimates according to allele count. Conclusions: APOE-ε4 allele count does not appear to be a common cause of sensory-cognitive associations in this large cohort. Hearing loss and vision loss are independently and jointly associated with faster rates of cognitive decline. Identifying mechanisms underlying sensory-cognitive associations is a research priority and is needed to inform public health efforts to reduce cognitive decline. Sensory impairment is highly prevalent and treatable, and if a cause-and-effect relationship exists with cognitive decline, treating sensory impairments could reduce rates of cognitive decline with age. On the other hand, if sensory-cognitive associations are the result of a common cause (e.g., a genetic predisposition for both sensory and cognitive impairment), then interventions aimed at reducing sensory loss would not be expected to have beneficial effects on cognition. The apolipoprotein E (APOE)-ε4 allele variant is associated with neurological diseases (e.g., Alzheimer’s disease) and non-neurological diseases (e.g., atherosclerosis). APOE-ε4 could be a common factor underlying associations between sensorineural losses and cognitive decline, but links between APOE-ε4 and both hearing and vision in the general population remain under-studied. Furthermore, the association between APOE-ε4 and cognition in healthy individuals is not as clear as the link between APOE-ε4 and Alzheimer’s disease. Therefore, we aimed to determine if APOE-ε4 allele count (the explanatory variable) was associated with differences in baseline and 3-year change in executive function, memory, pure-tone hearing thresholds, and visual acuity (the outcome variables). A secondary analysis of data collected in the Canadian Longitudinal Study on Aging (CLSA) was performed using data from two time points 3 years apart. Participants, aged 45-85 years, were recruited from 11 cities across Canada. Composite scores for executive function and memory were developed from five tests of cognition. Bilateral air-conduction pure-tone threshold averages and pinhole-corrected visual acuity in the better-seeing eye were used to measure hearing and vision, respectively. Linear mixed regression models assessed associations between APOE-ε4 allele count (as a categorical variable with 0 as the reference) and a.) baseline differences and b.) 3-year declines in each of the four outcome variables. Multivariable models adjusted for age, education, sex, race, heart disease, stroke, hypertension and diabetes. Interactions between APOE-ε4 and age group (45-54, 55-64, 65-74, and 75-85 years) and APOE-ε4 sex were tested. There were 27,765 participants in the CLSA comprehensive cohort but only 11,296 had complete data and were included. Individuals with complete data were more likely to be younger and healthier than those with partially missing data. In main effects models, APOE-ε4 was not associated with any of the sensory or cognitive outcome measures, either in terms of differences in baseline values or change over time. Regression models including the APOE-ε4*age interaction term (but not the APOE-ε4*sex interaction term) better fit the data than the corresponding main effects models. In age-stratified analyses most associations between APOE-ε4 and the outcome variables were still not significant. The exceptions were as follows: Two ε4 alleles predicted better baseline executive function in the 55-64 year old age group, and better baseline pure-tone average in the 45-54 year old age group. In the 65-74 year-old age group, one ε4 allele predicted worsening in visual acuity over time, whereas two ε4 alleles predicted improvements. APOE-ε4 allele count was not associated with poorer executive function, memory, pure-tone hearing thresholds or visual acuity, at baseline or over 3 years of follow-up, among a population-based sample of healthy 45-85 year old Canadians. Thus, the study does not support the hypothesis that APOE-ε4 is a common cause underlying associations between hearing or vision loss (respectively) and declines in each of executive function and memory.

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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)0.003
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 score0.230
Threshold uncertainty score0.463

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.126
GPT teacher head0.389
Teacher spread0.263 · 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".

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Citations3
Published2024
Admission routes2
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