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Record W3083544402 · doi:10.1038/s41467-020-17558-x

Chromosome 1q21.2 and additional loci influence risk of spontaneous coronary artery dissection and myocardial infarction

2020· article· en· W3083544402 on OpenAlexafffund
Jacqueline Saw, Min‐Lee Yang, Mark Trinder, Catherine Tcheandjieu, Chang Xu, Andrew Starovoytov, Isabelle Birt, Michael R. Mathis, Kristina L. Hunker, Ellen M. Schmidt, Linda Jackson, Natalia Fendrikova-Mahlay, Matthew Zawistowski, Chad M. Brummett, Sebastian Zoellner, Alexander Katz, Dawn M. Coleman, Kirby Swan, Christopher J. O’Donnell, Themistocles L. Assimes, Xiang Zhou, Jun Z. Li, Heather L. Gornik, James C. Stanley, Liam R. Brunham, Santhi K. Ganesh

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaUniversity of British Columbia Hospital
FundersNational Institute of Neurological Disorders and StrokeNIH Office of the DirectorNational Center for Advancing Translational SciencesNational Human Genome Research InstituteNational Institute on Drug AbuseMichael Smith Health Research BCA. Alfred Taubman Medical Research InstituteNational Cancer InstituteCleveland ClinicNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteHeart and Stroke Foundation of CanadaU.S. Department of Veterans AffairsNational Center for Research ResourcesGeorgia Clinical and Translational Science AllianceCommon FundUniversity of MichiganNational Institutes of HealthOffice of Dietary SupplementsOffice of Research and DevelopmentCanadian Institutes of Health ResearchNational Science Foundation
KeywordsMyocardial infarctionInternal medicineCardiologyScadMedicineCoronary artery diseaseChromosomeGeneticsBiologyGene

Abstract

fetched live from OpenAlex

Abstract Spontaneous coronary artery dissection (SCAD) is a non-atherosclerotic cause of myocardial infarction (MI), typically in young women. We undertook a genome-wide association study of SCAD (N cases = 270/N controls = 5,263) and identified and replicated an association of rs12740679 at chromosome 1q21.2 ( P discovery+replication = 2.19 × 10 −12 , OR = 1.8) influencing ADAMTSL4 expression. Meta-analysis of discovery and replication samples identified associations with P < 5 × 10 −8 at chromosome 6p24.1 in PHACTR1 , chromosome 12q13.3 in LRP1 , and in females-only, at chromosome 21q22.11 near LINC00310 . A polygenic risk score for SCAD was associated with (1) higher risk of SCAD in individuals with fibromuscular dysplasia ( P = 0.021, OR = 1.82 [95% CI: 1.09–3.02]) and (2) lower risk of atherosclerotic coronary artery disease and MI in the UK Biobank ( P = 1.28 × 10 −17 , HR = 0.91 [95% CI :0.89–0.93], for MI) and Million Veteran Program ( P = 9.33 × 10 −36 , OR = 0.95 [95% CI: 0.94–0.96], for CAD; P = 3.35 × 10 −6 , OR = 0.96 [95% CI: 0.95–0.98] for MI). Here we report that SCAD-related MI and atherosclerotic MI exist at opposite ends of a genetic risk spectrum, inciting MI with disparate underlying vascular biology.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.257
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 designObservational
Domainnot available
GenreEmpirical

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

Citations98
Published2020
Admission routes2
Has abstractyes

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