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Record W4408673797 · doi:10.3389/fcvm.2025.1502985

Exploring associations between estrogen and gene candidates identified by coronary artery disease genome-wide association studies

2025· review· en· W4408673797 on OpenAlexaff
A. Aminbakhsh, Emilie T. Théberge, Elizabeth Burden, Cindy Kalenga Adejumo, Annabel Gravely, Anna Lehman, Tara Sedlak

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsVancouver Coastal HealthUniversity of British Columbia
Fundersnot available
KeywordsGenome-wide association studyGenetic associationSingle-nucleotide polymorphismCoronary artery diseaseMissing heritability problemCandidate geneBiologyGeneticsHeritabilityBioinformaticsDiseaseEstrogenGeneMedicineInternal medicineGenotype

Abstract

fetched live from OpenAlex

Introduction: Coronary artery disease (CAD) is the leading cause of death around the world, with epidemiological sex and gender differences in prevalence, pathophysiology and outcomes. It has been hypothesized that sex steroids, like estrogen, may contribute to these sex differences. There is a relatively large genetic component to developing CAD, with heritability estimates ranging between 40%-60%. In the last two decades, genome-wide association studies (GWAS) have contributed substantially to advancing the understanding of genetic candidates contributing to CAD. The aim of this study was to determine if genes discovered in CAD GWASs are affected by estrogen via direct modulation or indirect down-stream targets. Methods: A scoping review was conducted using MEDLINE and EMBASE for studies of atherosclerotic coronary artery disease and a genome-wide association study (GWAS) design. Analysis was limited to candidate genes with corresponding single nucleotide polymorphisms (SNPs) surpassing genome-wide significance and had been mapped to genes by study authors. The number of studies that conducted sex-stratified analyses with significant genes were quantified. A literature search of the final gene lists was done to examine any evidence suggesting estrogen may modulate the genes and/or gene products. Results: There were 60 eligible CAD GWASs meeting inclusion criteria for data extraction. Of these 60, only 36 had genome-wide significant SNPs reported, and only 3 of these had significant SNPs from sex-stratified analyses mapped to genes. From these 36 studies, a total of 61 genes were curated, of which 26 genes (43%) were found to have modulation by estrogen. All 26 were discovered in studies that adjusted for sex. 12/26 genes were also discovered in studies that conducted sex-stratified analyses. 12/26 genes were classified as having a role in lipid synthesis, metabolism and/or lipoprotein mechanisms, while 11/26 were classified as having a role in vascular integrity, and 3/26 were classified as having a role in thrombosis. Discussion: This study provides further evidence of the relationship between estrogen, genetic risk and the development of CAD. More sex-stratified research will need to be conducted to further characterize estrogen's relation to sex differences in the pathology and progression of CAD.

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)0.011
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0150.022
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.052
GPT teacher head0.300
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 designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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