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Record W2179697345 · doi:10.1186/s12944-015-0154-7

The associations between proprotein convertase subtilisin/kexin type 9 E670G polymorphism and the risk of coronary artery disease and serum lipid levels: a meta-analysis

2015· review· en· W2179697345 on OpenAlexaff
Gaojun Cai, Bifeng Zhang, Ganwei Shi, Weijin Weng, Chunyan Ma, Yanbin Song, Zhang Ji

Bibliographic record

VenueLipids in Health and Disease · 2015
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMcMaster University
FundersJiangsu University
KeywordsMeta-analysisPCSK9Internal medicinePublication biasOdds ratioCoronary artery diseaseLipidologyProprotein convertaseConfidence intervalKexinMedicineAlleleClinical nutritionSubgroup analysisGastroenterologyGenetic modelLipid profileOncologyClinical chemistryGeneticsBiologyCholesterolLipoproteinLDL receptorGene

Abstract

fetched live from OpenAlex

BACKGROUND: Studies had investigated the associations between proprotein convertase subtilisin/kexin type 9 (PCSK9) E670G polymorphism and coronary artery disease (CAD) and lipid levels, but the results were controversial. Thus, we performed this meta-analysis to investigate the association between PCSK9 E670G polymorphism and lipid levels and the susceptibility to CAD. METHODS: All relevant articles according to the inclusion criteria were retrieved and included in the present meta-analysis. Odds ratios (ORs) with 95 % confidence interval (CI) were used to analyze the strength of the association between PCSK9 E670G polymorphism and the susceptibility to CAD. At the same time, the pooled standardized mean difference (SMD) with 95 % CI was used for the meta-analysis of PCSK9 E670G polymorphism and lipid levels. The publication bias was examined by using Begg's funnel plots and Egger's test. RESULTS: A total of seventeen studies met the inclusion criteria. For CAD association, the pooled effects indicated that the G allele carriers had higher risk of CAD than non-carriers in dominant genetic model (OR:1.601, 95 % CI: 1.314-1.951, P < 0.001), as well as in allelic genetic model (OR: 1.546, 95 % CI: 1.301-1.838, P < 0.001). When the subgroup analysis stratified by ethnicity and HWE was performed, the positive result existed in most of the subgroups. For lipid levels association, the pooled effects indicated that the G allele carriers had higher TC and LDL-C levels than the non-carriers (for TC, SMD: 0.126, 95 % CI: 0.023-0.229, P = 0.016; for LDL-C, SMD: 0.170, 95 % CI: 0.053-0.287, P = 0.004, respectively). There was no difference in the levels of TG and HDL-C between the G carriers and the non-carriers in the whole population (SMD: 0.031, 95 % CI: -0.048-0.110, P = 0.440; SMD: -0.123, 95 % CI: -0.251-0.006, P = 0.061, respectively). When the studies were stratified by ethnicity and type of study, the G carriers had higher TC levels than the non-carriers (SMD: 0.126, 95 % CI: 0.014-0.238, P = 0.027) in the non-Asian subgroup. The similar results existed in cohort subgroup. The association between PCSK9 E670G polymorphism and LDL-C levels was significant in all subgroups. Meanwhile, the G carriers had higher TG levels than the non-carriers (SMD: 0.113, 95 % CI: 0.012-0.214, P = 0.028) in the case-control subgroup. AG + GG genotypes had lower HDL-C levels than AA genotype in Asian subgroup (SMD: -0.224, 95 % CI: -0.423- -0.025, P = 0.027) and in case-control subgroup (SMD: -0.257, 95 % CI: -0.467--0.048, P = 0.016). CONCLUSIONS: The present meta-analysis concluded that PCSK9 E670G polymorphism was associated with CAD risk and lipid levels.

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)0.010
metaresearch head score (Gemma)0.015
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 score0.014
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0140.046
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 head0.107
GPT teacher head0.353
Teacher spread0.246 · 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".

Quick stats

Citations30
Published2015
Admission routes1
Has abstractyes

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