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Record W4404904682 · doi:10.1186/s40246-024-00699-1

The associations of candidate gene polymorphisms with aspirin resistance in patients with ischemic disease: a meta-analysis

2024· review· en· W4404904682 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHuman Genomics · 2024
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsHuman geneticsAspirinDiseaseMeta-analysisCandidate geneGeneBioinformaticsGeneticsMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Recently, extensive research has been conducted on the relationship between aspirin gene polymorphisms and aspirin resistance (AR) in patients with ischemic diseases. Among the numerous candidate genes, it remains unclear which ones are significantly associated with AR and could potentially serve as potential biomarkers for genetic testing before aspirin use. METHODS: Eligible articles were searched in PubMed, Embase, Cochrane Library, WanFang, CNKI and Sinomed. A cohort study examining the efficacy of aspirin in secondary prevention for patients with ischemic diseases, along with a discussion on genetic polymorphisms and their association with AR, has been included. The Newcastle-Ottawa Scale for assessing the quality of included studies. Odds ratios (OR) with 95% confidence intervals (CI) were used as measures of effect. Subgroup analyses were conducted based on different genotypes with the same genetic polymorphisms, different research regions and types of ischemic diseases. RESULTS: From 75 eligible articles, 94 candidate gene polymorphisms were analyzed. In the overall analysis, 25 genes were subjected to meta-analysis and 69 genes were systematically described. 23 gene polymorphisms were observed to be significantly associated with AR, including PTGS2(rs20417) (OR = 0.57, 95% CI: 0.44-0.73), ITGA2(rs1126643) (OR = 0.52, 95% CI: 0.29-0.93), and TbXA2R(rs1131882) (OR = 1.54, 95% CI: 1.09-2.18) were obtained from the combined analysis of this study, and 20 genes were systematically described in this study. Further subgroup analyses demonstrated that AA genotype for PTGS1(rs1330344) (OR = 0.56, 95%CI:0.43-0.74), C allele for PTGS1(rs5788) (OR = 0.51, 95%CI: 0.30-0.87) polymorphisms were significantly associated with AR. The polymorphisms of 13 genes, including PTGS1(rs1236913), have been studied only in Asia, GP6(rs1613662) has been studied only in Europe, and the polymorphisms of 5 genes, including ABCB1(rs1045642), showed different correlations with AR in various regions. The individuals with the PTGS1 (rs5788) variant who experienced an ischemic stroke (OR = 0.98, 95%CI: 0.54-1.67) may exhibit an elevated risk of AR compared to those with coronary artery disease (OR = 0.51, 95%CI: 0.3-0.87). CONCLUSIONS: Our meta-analysis indicates that PTGS2(rs20417), ITGA2(rs1126643), and TbXA2R(rs1131882) could be potential genetic biomarkers for AR. Among these, PTGS2 (rs20417) is particularly suggested for individuals in Asia with ischemic diseases before aspirin use, as the GC/CC genotype raises AR risk by 42% compared to GG. ITGA2 (rs1126643) increases AR risk by 48% in Asia with the TC/TC genotype versus CC. However, results for ABCB1(rs1045642) and GP1BA(rs2243093) vary by regions, requiring further research.

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.

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)0.000
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: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.319
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.302
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