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Multiancestry Genome-Wide Association Study of Aortic Stenosis Identifies Multiple Novel Loci in the Million Veteran Program

2023· article· en· W4321374003 on OpenAlexaff
Aeron Small, Gina M. Peloso, Jason Linefsky, Jayashri Aragam, Ashley Galloway, Vidisha Tanukonda, Lu-Chen Wang, Zhi Yu, Margaret Sunitha Selvaraj, Eric Farber‐Eger, Michael Baker, Shefali S. Verma, Simon Lee, Michael Preuß, Marylyn D. Ritchie, Scott M. Damrauer, Daniel J. Rader, Quinn S. Wells, Ruth J. F. Loos, Steven A. Lubitz, George Thanassoulis, Kelly Cho, Peter W.F. Wilson, Pradeep Natarajan, Christopher J. O’Donnell

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesNational Center for Advancing Translational SciencesNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteNovartis Institutes for BioMedical ResearchNational Institutes of HealthVanderbilt University Medical CenterBoston Scientific CorporationEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBroad InstituteVanderbilt UniversityGenentechAstraZenecaU.S. Department of Veterans Affairs
KeywordsMedicineStenosisGenome-wide association studyGeneticsInternal medicineGeneSingle-nucleotide polymorphismGenotypeBiology

Abstract

fetched live from OpenAlex

Background: Calcific aortic stenosis (CAS) is the most common valvular heart disease in older adults and has no effective preventive therapies. Genome-wide association studies (GWAS) can identify genes influencing disease and may help prioritize therapeutic targets for CAS. Methods: We performed a GWAS and gene association study of 14 451 patients with CAS and 398 544 controls in the Million Veteran Program. Replication was performed in the Million Veteran Program, Penn Medicine Biobank, Mass General Brigham Biobank, BioVU, and BioMe, totaling 12 889 cases and 348 094 controls. Causal genes were prioritized from genome-wide significant variants using polygenic priority score gene localization, expression quantitative trait locus colocalization, and nearest gene methods. CAS genetic architecture was compared with that of atherosclerotic cardiovascular disease. Causal inference for cardiometabolic biomarkers in CAS was performed using Mendelian randomization and genome-wide significant loci were characterized further through phenome-wide association study. Results: We identified 23 genome-wide significant lead variants in our GWAS representing 17 unique genomic regions. Of the 23 lead variants, 14 were significant in replication, representing 11 unique genomic regions. Five replicated genomic regions were previously known risk loci for CAS ( PALMD, TEX41, IL6, LPA, FADS ) and 6 were novel ( CEP85L, FTO, SLMAP, CELSR2, MECOM, CDAN1 ). Two novel lead variants were associated in non-White individuals ( P <0.05): rs12740374 ( CELSR2 ) in Black and Hispanic individuals and rs1522387 ( SLMAP ) in Black individuals. Of the 14 replicated lead variants, only 2 (rs10455872 [ LPA ], rs12740374 [ CELSR2 ]) were also significant in atherosclerotic cardiovascular disease GWAS. In Mendelian randomization, lipoprotein(a) and low-density lipoprotein cholesterol were both associated with CAS, but the association between low-density lipoprotein cholesterol and CAS was attenuated when adjusting for lipoprotein(a). Phenome-wide association study highlighted varying degrees of pleiotropy, including between CAS and obesity at the FTO locus. However, the FTO locus remained associated with CAS after adjusting for body mass index and maintained a significant independent effect on CAS in mediation analysis. Conclusions: We performed a multiancestry GWAS in CAS and identified 6 novel genomic regions in the disease. Secondary analyses highlighted the roles of lipid metabolism, inflammation, cellular senescence, and adiposity in the pathobiology of CAS and clarified the shared and differential genetic architectures of CAS with atherosclerotic cardiovascular diseases.

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)0.001
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.350
Teacher spread0.309 · 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

Citations72
Published2023
Admission routes1
Has abstractyes

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