Evidence map›Paper›PMID 35939966›Full record

ReviewCurrent opinion in genetics & development2022

Statistical models of the genetic etiology of congenital heart disease.

Guojie Zhong, Yufeng Shen

Abstract readReview
In one paragraph

Review in Current opinion in genetics & development, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Guojie ZhongDepartment of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA; Integrated Program in Cellular, Molecular, and Biological Studies, Columbia University Irving Medical Center, New York, NY, USA.
Yufeng ShenDepartment of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA; JP Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA. Electronic address: ys2411@cumc.columbia.edu.

Funding

Identifying and applying genetic variation relevant to clinical outcomes for individuals with congenital heart diseaseU01HL153009 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHUNG, WENDY K, GELB, BRUCE D · 2020 to 2024
$2.3M
Integrate cancer genomics data in geneticstudies and diagnosis of developmental disordersR01GM120609 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEN, YUFENG · 2017 to 2021
$1.7M
NHLBI NIH HHS U01 HL153009NIGMS NIH HHS R01 GM120609
6 · The paper itself

Abstract

Congenital heart disease (CHD) is a collection of anatomically and clinically heterogeneous structure anomalies of heart at birth. Finding genetic causes of CHD can not only shed light on developmental biology of heart, but also provide basis for improving clinical care and interventions. The optimal study design and analytical approaches to identify genetic causes depend on the underlying genetic architecture. A few well-known syndromes with CHD as core conditions, such as Noonan and CHARGE, have known monogenic causes. The genetic causes of most of CHD patients, however, are unknown and likely to be complex. In this review, we highlight recent studies that assume a complex genetic architecture of CHD with two main approaches. One is genomic sequencing studies aiming for identifying rare or de novo risk variants with large genetic effect. The other is genome-wide association studies optimized for common variants with moderate genetic effect.

Indexed as

Genome-Wide Association StudyHeart Defects, CongenitalHeartHumansInfant, NewbornModels, Statistical

Identifiers

PMID35939966
PMCPMC10586490

What Socratic 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 Socratic graph.