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Record W2538536654 · doi:10.1177/1747493016672085

Platelet glycoprotein gene Ia C807T, HPA-3, and Ibα VNTR polymorphisms are associated with increased ischemic stroke risk: Evidence from a comprehensive meta-analysis

2016· review· en· W2538536654 on OpenAlexaboutno aff
Hua Liu, Yi Wang, Jian Zheng, Guangming Li, Tao Chen, Jianguo Lei, Yiting Mao, Jun Wang, Wei Liu, Ge Zhao, Mark Tacey, Bernard Yan

Bibliographic record

VenueInternational Journal of Stroke · 2016
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsOdds ratioMeta-analysisMedicineGenotypePublication biasAlleleConfidence intervalGlycoprotein IbInternal medicineGeneticsFunnel plotBioinformaticsStroke (engine)OncologyPlatelet membrane glycoproteinGeneBiologyPlatelet

Abstract

fetched live from OpenAlex

Background/aims Platelet glycoproteins play a crucial role in the initial stage of thrombus formation and may contribute to the pathophysiology of atherosclerosis. Polymorphisms in glycoprotein genes alter the function of the protein, possibly leading to increased risk of ischemic stroke. However, previous genetic association studies that examined the relationship between glycoprotein genes polymorphisms and ischemic stroke have yielded inconsistent results. This study aimed to evaluate the association between glycoprotein genes and ischemic stroke by the application of meta-analysis. Methods Relevant studies were identified by an extensive search through databases. The quality of included studies was assessed independently using the Newcastle-Ottawa Scale. Allele and genotype frequencies for each included study were extracted. The odds ratio (OR) with 95% confidence interval (95%CI) was calculated using a random-effects or fixed-effects model. Q statistic was used to evaluate homogeneity, and a meta-regression model was used to explore the study-level variables and to describe the heterogeneity in included studies. Egger's test and funnel plot were used to assess publication bias. Results A total of 60 studies (9 polymorphisms) were included and identified in the current meta-analysis. The Newcastle-Ottawa Scale scores ranged from 7 to 9 except for two studies with Newcastle-Ottawa Scale scores of 6. The T allele or TT genotype of the glycoprotein Ia C807T polymorphism were associated with an increased susceptibility to ischemic stroke in combined population (807T allele: OR, 95%CI: 1.24, 1.03-1.50, p = 0.02) or Asian populations (807T allele: OR, 95%CI: 1.31, 1.10-1.54, p = 0.002 and 807TT genotype: OR, 95%CI: 1.53, 1.13-2.08, p = 0.006, respectively), and the Ser allele of HPA-3 was associated with increased risk of ischemic stroke in combined population or in Asians (OR, 95%CI: 1.21, 1.04-1.40, p = 0.01 or 1.54, 1.18-2.01, p = 0.001). Of note, the Ser/Ser genotype was more common in Asians (OR, 95%CI: 2.09, 1.40-3.13, p < 0.001). For glycoprotein Ibα variable number tandem repeat, only B allele showed a mild significant association with ischemic stroke risk in combined population or in Caucasians (OR, 95%CI: 2.17, 1.04-4.55, p = 0.04 or 1.79, 1.02-3.13, p = 0.04). There was no significant association between HPA-1, HPA-2, HPA-4, HPA-5, glycoprotein Ibα-5 T/C as well as Ia G873A polymorphisms and increased risk of ischemic stroke. Conclusions We found that glycoprotein Ia C807T T allele or the TT genotype, the Ser-allele of HPA-3 and B allele of glycoprotein Ibα variable number tandem repeat polymorphisms were associated with increased risk for ischemic stroke. Future studies with larger sample sizes will be necessary to confirm the results. In addition, analyses of ischemic stroke subtypes and gene-gene and gene-environment interactions are warranted.

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)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.036
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.055
GPT teacher head0.320
Teacher spread0.264 · 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 designMeta-analysis
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".

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Citations29
Published2016
Admission routes1
Has abstractyes

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