Evidence map›Paper›PMID 36131050›Full record

ReviewNature reviews. Cardiology2023

Genetics and mechanisms of thoracic aortic disease.

Elizabeth Chou, James P Pirruccello, Patrick T Ellinor, Mark E Lindsay

Open access · greenAbstract readReview
In one paragraph

Review in Nature reviews. Cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
9.3field-weighted citation impact, top 1% of its field
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

37 citing papers in PubMed, 66 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
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  7. Review
  8. Article
  9. Genetic Causes of Thoracic Aortic Aneurysm: A Review.Methodist DeBakey cardiovascular journal · 2026
    Review
  10. Article
  11. Article
  12. Article
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  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Mitochondrial NADNature cardiovascular research · 2025
    Article
  20. Article
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

4 authors at 1 institution in 1 country.

Elizabeth ChouDivision of Vascular and Endovascular Surgery, Massachusetts General Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0002-0997-6785
James P PirruccelloHarvard Medical School, Boston, MA, USA.
Patrick T EllinorHarvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-2067-0533
Mark E LindsayHarvard Medical School, Boston, MA, USA. lindsay.mark@mgh.harvard.edu.ORCID http://orcid.org/0000-0001-6724-7938
Broad Institute · US

Funding

IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
MULTIDISCIPLINARY RESEARCH TRAINING IN CARDIOLOGYT32HL007208 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Patrick Thomas Ellinor, David E Sosnovik · 1985 to 2026
$16.1M
The Role of HDAC9/MITR in the Pathogenesis of Thoracic Aortic Aneurysm (TAA)R01HL130113 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI LINDSAY, MARK E · 2016 to 2020
$2.0M
Mentoring in Arrhythmia ResearchK24HL105780 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI ELLINOR, PATRICK THOMAS · 2011 to 2020
$1.2M
Deep learning to enable the genetic analysis of aortaK08HL159346 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PIRRUCCELLO, JAMES · 2021 to 2025
$827k
NHLBI NIH HHS K08 HL159346NHLBI NIH HHS K24 HL105780NHLBI NIH HHS R01 HL092577NHLBI NIH HHS R01 HL130113NHLBI NIH HHS T32 HL007208
6 · The paper itself

Abstract

Aortic disease has many forms including aortic aneurysm and dissection, aortic coarctation or abnormalities in aortic function, such as loss of aortic distensibility. Genetic analysis in humans is one of the most important experimental approaches in uncovering disease mechanisms, but the relative infrequency of thoracic aortic disease compared with other cardiovascular conditions such as coronary artery disease has hindered large-scale identification of genetic associations. In the past decade, advances in machine learning technology coupled with large imaging datasets from biobank repositories have facilitated a rapid expansion in our capacity to measure and genotype aortic traits, resulting in the identification of dozens of genetic associations. In this Review, we describe the history of technological advances in genetic discovery and explain how newer technologies such as deep learning can rapidly define aortic traits at scale. Furthermore, we integrate novel genetic observations provided by these advances into our current biological understanding of thoracic aortic disease and describe how these new findings can contribute to strategies to prevent and treat aortic disease.

Indexed as

Aortic AneurysmAortic Aneurysm, ThoracicAortic CoarctationAortic DiseasesAortaHumans

Identifiers

PMID36131050
PMCPMC12175203
OpenAlexW4296700852

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.