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Record W4362692986 · doi:10.1161/circgen.122.003968

Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes

2023· review· en· W4362692986 on OpenAlexaff
Mengyao Yu, Matthew Aguirre, Meiwen Jia, Ketrin Gjoni, Aldo Córdova‐Palomera, Chad J. Munger, Dulguun Amgalan, X. Rosa, Alexandre C. Pereira, Catherine Tcheandjieu, Christine E. Seidman, Jonathan G. Seidman, Martin Tristani‐Firouzi, Wendy K. Chung, Elizabeth Goldmuntz, Deepak Srivastava, Ruth J. F. Loos, Nathalie Chami, Heather J. Cordell, Martina Dreßen, B. Mueller-Myhsok, Harald Lahm, Markus Krane, Katherine S. Pollard, J Engreitz, Sarah A. Gagliano Taliun, Bruce D. Gelb, James R. Priest

Bibliographic record

VenueCirculation Genomic and Precision Medicine · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Center for Research ResourcesNational Heart, Lung, and Blood Institute
KeywordsOdds ratioMinor allele frequencyGeneticsBiologyAlleleHeart diseaseGenome-wide association study1000 Genomes ProjectAllele frequencyGeneInternal medicineMedicineSingle-nucleotide polymorphismGenotype

Abstract

fetched live from OpenAlex

Background: Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. Methods: We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. Results: Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P =1.49×10 −8 ) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P =1.46×10 − 8 ) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9 . A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P =2.6×10 − 8 ) physically interacts with NCAM1 ( P FDR =1.86×10 − 27 ), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. Conclusions: We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.

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)0.002
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: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.057
GPT teacher head0.355
Teacher spread0.297 · 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
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

Citations13
Published2023
Admission routes1
Has abstractyes

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