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Design of the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) Study

2010· review· en· W2138358802 on OpenAlexfundaboutno aff
Michael Preuß, Inke R. König, John R. Thompson, Jeanette Erdmann, Devin Absher, Themistocles L. Assimes, Stefan Blankenberg, Eric Boerwinkle, Li Chen, L. Adrienne Cupples, Alistair S. Hall, Eran Halperin, Christian Hengstenberg, Hilma Hólm, Reijo Laaksonen, Mingyao Li, Winfried März, Ruth McPherson, Kiran Musunuru, Christopher P. Nelson, Mary Susan Burnett, Stephen E. Epstein, Christopher J. O’Donnell, Thomas Quertermous, Daniel J. Rader, Robert Roberts, Arne Schillert, Kāri Stefánsson, Alexandre F.R. Stewart, Guðmar Þorleifsson, Benjamin F. Voight, George A. Wells, Andreas Ziegler, Sekar Kathiresan, Muredach P. Reilly, Nilesh J. Samani, Heribert Schunkert

Bibliographic record

VenueCirculation Cardiovascular Genetics · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of General Medical SciencesDaiichi Sankyo EuropeNational Cancer InstituteNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteMedical Research CouncilNational Institutes of HealthBritish Heart FoundationWellcome TrustFondation de FranceBundesministerium für Bildung und ForschungNational Research CentreUniversity of PennsylvaniaAlnylam PharmaceuticalsPfizerHeart and Stroke Foundation of CanadaUniversity of North Carolina at Chapel HillAcademia SinicaEuropean CommissionBroad InstituteSanofiCystic Fibrosis FoundationDeutsche ForschungsgemeinschaftGlaxoSmithKlineDivision of Cancer Epidemiology and Genetics, National Cancer InstituteIsrael Science FoundationChildren's Hospital of PhiladelphiaAstraZenecaCanadian Institutes of Health ResearchNational Science Foundation
KeywordsGenome-wide association studyMyocardial infarctionCoronary artery diseaseInternal medicineGenotypingImputation (statistics)Genetic epidemiologyMedicineGenetic associationSingle-nucleotide polymorphismMeta-analysisCardiologyEpidemiologyBioinformaticsGeneticsGenotypeBiologyGene

Abstract

fetched live from OpenAlex

BACKGROUND: Recent genome-wide association studies (GWAS) of myocardial infarction (MI) and other forms of coronary artery disease (CAD) have led to the discovery of at least 13 genetic loci. In addition to the effect size, power to detect associations is largely driven by sample size. Therefore, to maximize the chance of finding novel susceptibility loci for CAD and MI, the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium was formed. METHODS AND RESULTS: CARDIoGRAM combines data from all published and several unpublished GWAS in individuals with European ancestry; includes >22 000 cases with CAD, MI, or both and >60 000 controls; and unifies samples from the Atherosclerotic Disease VAscular functioN and genetiC Epidemiology study, CADomics, Cohorts for Heart and Aging Research in Genomic Epidemiology, deCODE, the German Myocardial Infarction Family Studies I, II, and III, Ludwigshafen Risk and Cardiovascular Heath Study/AtheroRemo, MedStar, Myocardial Infarction Genetics Consortium, Ottawa Heart Genomics Study, PennCath, and the Wellcome Trust Case Control Consortium. Genotyping was carried out on Affymetrix or Illumina platforms followed by imputation of genotypes in most studies. On average, 2.2 million single nucleotide polymorphisms were generated per study. The results from each study are combined using meta-analysis. As proof of principle, we meta-analyzed risk variants at 9p21 and found that rs1333049 confers a 29% increase in risk for MI per copy (P=2×10⁻²⁰). CONCLUSION: CARDIoGRAM is poised to contribute to our understanding of the role of common genetic variation on risk for CAD and MI.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.032
metaresearch head score (Gemma)0.035
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.035
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.084
GPT teacher head0.309
Teacher spread0.225 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Meta-analysis
Domainnot available
GenreMethods · Protocol

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

Citations195
Published2010
Admission routes2
Has abstractyes

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