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Record W4295681943 · doi:10.1001/jamacardio.2022.2970

Burden of Rare Genetic Variants in Spontaneous Coronary Artery Dissection With High-risk Features

2022· article· en· W4295681943 on OpenAlexaffabout
Yu Wang, Andrew Starovoytov, Andrea M. Murad, Kristina L. Hunker, Liam R. Brunham, Jun Z. Li, Jacqueline Saw, Santhi K. Ganesh

Bibliographic record

VenueJAMA Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsVancouver General HospitalUniversity of British Columbia
FundersNational Heart, Lung, and Blood Institute
KeywordsScadGenome-wide association studyMedicineExome sequencingGenetic associationGeneticsExomeBioinformaticsBiologyGeneInternal medicinePhenotypeGenotypeSingle-nucleotide polymorphismMyocardial infarction

Abstract

fetched live from OpenAlex

Importance: The emerging genetic basis of spontaneous coronary artery dissection (SCAD) has been defined as both partially complex and monogenic in some patients, involving variants predominantly in genes known to underlie vascular connective tissue diseases (CTDs). The effect of these genetic influences has not been defined in high-risk SCAD phenotypes, and the identification of a high-risk subgroup of individuals may help to guide clinical genetic evaluations of SCAD. Objective: To identify and quantify the burden of rare genetic variation in individuals with SCAD with high-risk clinical features. Design, Setting, and Participants: Whole-exome sequencing (WES) was performed for subsequent case-control association analyses and individual variant annotation among individuals with high-risk SCAD. Genetic variants were annotated for pathogenicity by in-silico analysis of genes previously defined by sequencing for vascular CTDs and/or SCAD, as well as genes prioritized by genome-wide association study (GWAS) and colocalization of arterial expression quantitative trait loci. Unbiased genome-wide association analysis of the WES data was performed by comparing aggregated variants in individuals with SCAD to healthy matched controls or the Genome Aggregation Database (gnomAD). This study was conducted at a tertiary care center. Individuals in the Canadian SCAD Registry genetics study with a high-risk SCAD phenotype were selected and defined as peripartum SCAD, recurrent SCAD, or SCAD in an individual with family history of arteriopathy. Main Outcomes and Measures: Burden of genetic variants defined by DNA sequencing in individuals with high-risk SCAD. Results: This study included a total of 336 participants (mean [SD] age, 53.0 [9.5] years; 301 female participants [90%]). Variants in vascular CTD genes were identified in 17.0% of individuals (16 of 94) with high-risk SCAD and were enriched (OR, 2.6; 95% CI, 1.6-4.2; P = 7.8 × 10-4) as compared with gnomAD, with leading significant signals in COL3A1 (OR, 13.4; 95% CI, 4.9-36.2; P = 2.8 × 10-4) and Loeys-Dietz syndrome genes (OR, 7.9; 95% CI, 2.9-21.2; P = 2.0 × 10-3). Variants in GWAS-prioritized genes, observed in 6.4% of individuals (6 of 94) with high-risk SCAD, were also enriched (OR, 3.6; 95% CI, 1.6-8.2; P = 7.4 × 10-3). Variants annotated as likely pathogenic or pathogenic occurred in 4 individuals, in the COL3A1, TGFBR2, and ADAMTSL4 genes. Genome-wide aggregated variant testing identified novel associations with peripartum SCAD. Conclusions and Relevance: In this genetic study, approximately 1 in 5 individuals with a high-risk SCAD phenotype harbored a rare genetic variant in genes currently implicated for SCAD. Genetic screening in this subgroup of individuals presenting with SCAD may be considered.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.217
Teacher spread0.211 · 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 teacher head, 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".

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Citations25
Published2022
Admission routes2
Has abstractyes

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