Evidence map›Paper›PMID 39170958›Full record

ReviewJACC. Basic to translational science2024

Genetics and Pharmacogenetics of Atrial Fibrillation: A Mechanistic Perspective.

Asia Owais, Miles Barney, Olivia Thao Ly, Grace Brown, Hanna Chen, Arvind Sridhar, Arif Pavel, Salman R Khetani, Dawood Darbar

Abstract readReview
In one paragraph

Review in JACC. Basic to translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. NovelBiomedicines · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Discovery ofDiagnostics (Basel, Switzerland) · 2025
    Article
  6. Review
  7. Article
  8. Review
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Asia OwaisDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Miles BarneyDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Olivia Thao LyDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Grace BrownDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Hanna ChenDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Arvind SridharDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Arif PavelDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.
Salman R KhetaniDepartment of Biomedical Engineering, University of Illinois, Chicago, Illinois, USA.
Dawood DarbarDivision of Cardiology, Department of Medicine, University of Illinois, Chicago, Illinois, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The heritability of atrial fibrillation (AF) is well established. Over the last decade genetic architecture of AF has been unraveled by genome-wide association studies and family-based studies. However, the translation of these genetic discoveries has lagged owing to an incomplete understanding of the pathogenic mechanisms underlying the genetic variants, challenges in classifying variants of uncertain significance (VUS), and limitations of existing disease models. We review the mechanistic insight provided by basic science studies regarding AF mechanisms, recent developments in high-throughput classification of VUS, and advances in bioengineered cardiac models for developing personalized therapy for AF.

Indexed as

arrhythmiagenome-wide association studyinduced pluripotent stem cell

Identifiers

PMID39170958
PMCPMC11334418

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.