Evidence map›Paper›PMID 37888120›Full record

ArticleJournal of personalized medicine2023

Identification of Genetic Variants Associated with Severe Myocardial Bridging through Whole-Exome Sequencing.

Tsung-Lin Yang, Jafit Ting, Min-Rou Lin, Wei-Chiao Chang, Chun-Ming Shih

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2023. 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
0.5field-weighted citation impact, top 28% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

5 authors at 3 institutions in 1 country.

Tsung-Lin YangGraduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.
Jafit TingDepartment of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan.ORCID 0000-0001-7918-8218
Min-Rou LinDepartment of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan.ORCID 0000-0003-0247-1984
Wei-Chiao ChangDepartment of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan.
Chun-Ming ShihGraduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.
Taipei Medical University · TWTaipei Medical University Hospital · TWWan Fang Hospital · TW

Funding

Taipei Medical University 111-5812-001-400
6 · The paper itself

Abstract

Myocardial bridging (MB) is a congenital coronary artery anomaly and an important cause of angina. The genetic basis of MB is currently unknown. This study used a whole-exome sequencing technique and analyzed genotypic differences. Eight coronary angiography-confirmed cases of severe MB and eight age- and sex-matched control patients were investigated. In total, 139 rare variants that are potentially pathogenic for severe MB were identified in 132 genes. Genes with multiple rare variants or co-predicted by ClinVar and CADD/REVEL for severe MB were collected, from which heart-specific genes were selected under the guidance of tissue expression levels. Functional annotation indicated significant genetic associations with abnormal skeletal muscle mass, cardiomyopathies, and transmembrane ion channels. Candidate genes were reviewed regarding the functions and locations of each individual gene product. Among the gene candidates for severe MB, rare variants in

Indexed as

cardiovascular diseaseDMDgenetic variantmyocardial bridgingSGCATTNwhole-exome sequencing

Identifiers

PMID37888120
PMCPMC10608235
OpenAlexW4387779352

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.