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Record W4390194928 · doi:10.1002/alz.072360

Dissociable influences of maternal vs paternal Alzheimer’s risk on neurocognitive and cardiovascular health in men and women

2023· article· en· W4390194928 on OpenAlexaff
Chloé Savignac, Frédéric St‐Onge, Sylvia Villeneuve, AmanPreet Badhwar, Sarah A. Gagliano Taliun, Sali M.K. Farhan, Maiya R. Geddes, Yasser Iturria‐Medina, Judes Poirier, R. Nathan Spreng, Danilo Bzdok

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMila - Quebec Artificial Intelligence InstituteMontreal Neurological Institute and HospitalMontreal Heart InstituteInstitut Universitaire de Gériatrie de MontréalMcGill Genome CentreUniversité de MontréalAlzheimer Society of CanadaDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsNeurocognitiveDiseaseProbandApolipoprotein ECohortPopulationPhenomeCognitive declineMedicineDementiaDemographyPsychologyCognitionBiologyGeneticsInternal medicinePhenotypePsychiatryMutationGene

Abstract

fetched live from OpenAlex

Abstract Background Parental history of sporadic Alzheimer’s disease (AD) is considered a prime risk factor since at least the late 1980s. Routinely used clinical samples of at‐risk individuals (8‐16 subjects) may conceal weaker population‐based effects, especially those of paternal inheritance. We performed a phenome‐wide examination of the dissociable influences of maternal vs. paternal AD risk on male vs. female probands in the largest single‐site family‐based at‐risk AD cohort: PREVENT‐AD. Method We built sex‐specific PLS‐regression models in which the APOE genotypes (e.g., ɛ3/3, ɛ3/4, ɛ3/2) were estimated based on ∼1,000 patient visits, each covering ∼260 risk indicators, to derive three APOE‐driven intermediate phenotypes (IPs). We examined how much the three IPs vary with regard to sex and maternal vs. paternal AD lineage across the phenome. We assessed the sex‐specific and lineage‐specific variation of the IPs over a 4‐year follow‐up period. Lastly, we examined how matri‐ vs. patrilinear AD risk captured by the IPs were expressed in AD‐vulnerable brain structures. Result Across IPs, we linked patrilinear AD risk to verbal‐numerical cognition and cardiovascular health in males. In contrast, we linked matrilinear AD risk to memory performance in both sexes. Over time, the mean difference in cognitive performance decreases with regard to sex but increases with regard to AD lineage. Cis‐ and trans‐generational sex effects in neocortex subregions (e.g., mPFC, PCu) were captured by the first and second IPs, respectively. The third IP mainly captured trans‐generational sex effects in hippocampus subregions (e.g., CA1, CA4). Conclusion We uncovered IPs of AD susceptibility differently expressed in male and female probands and affected by the diagnosed parent’s sex. Maternal inheritance highlighted memory performance in both sexes, whereas paternal inheritance was particularly linked to cardiovascular health in males. The inheritance of the IPs was reflected in the brain structure at both superficial and deeper layers of the cortex. As the first study of its kind, our cross‐generational analysis of matri‐ vs. patrilinear AD risk bridges the epidemiological and clinical literature by leveraging the power of ∼1,000 patient visits. Our completely data‐driven framework ultimately dissociated phenotypes of maternal and paternal AD risk single‐handedly expressed in male and female probands.

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)0.003
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0020.000

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 head0.273
Teacher spread0.254 · 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
Published2023
Admission routes1
Has abstractyes

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