Evidence map›Paper›PMID 39730912›Full record

ArticleJournal of molecular medicine (Berlin, Germany)2025

Rare variants in cardiomyopathy genes predispose to cardiac injury in severe COVID-19 patients of African or Hispanic ancestry.

Hui-Qi Qu, Matthew S Delfiner, Chethan Gangireddy, Anjali Vaidya, Kenny Nguyen, Isaac R Whitman, JuFang Wang, Jianliang Song, Michael R Bristow, Charles F McTiernan and 3 more

Abstract read
In one paragraph

Article in Journal of molecular medicine (Berlin, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Hui-Qi Qu *The Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0001-9317-4488
Matthew S DelfinerDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Chethan GangireddyDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Anjali VaidyaDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Kenny NguyenThe Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Isaac R WhitmanDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
JuFang WangDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Jianliang SongDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Michael R BristowDivision of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Charles F McTiernanDivision of Cardiology, Heart and Vascular Institute, University of Pittsburgh, Pittsburgh, PA, USA.
Glenn S GerhardDepartment of Human Genetics and Molecular Biochemistry, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Hakon HakonarsonThe Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA. hakonarson@chop.edu.
Arthur M FeldmanDepartment of Medicine, Division of Cardiology, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA. arthur.feldman@tuhs.temple.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In one of the earliest reports from China during COVID-19, it was noted that over 20% of patients hospitalized with the disease had significant elevations of troponin, a marker of myocardial tissue damage, that put them at a higher risk. In a hypothesis-independent whole exome sequencing (WES) study in hospitalized COVID-19 patients of diverse ancestry, we observed putative enrichment in pathogenic variants in genes known to be involved in the pathogenesis of cardiomyopathy. This observation led us to hypothesize that the observed high morbidity and mortality in these patients might be due to the presence of rare genetic factors that had previously been silent but became relevant as a consequence of the severe stress inflicted by an infection with SARS-CoV-2. To test this hypothesis, we analyzed our WES data generated from a cohort of 325 patients sequentially admitted for COVID-19 infection. In this predominantly minority population (53.9% African ancestry and 37.9% Hispanic/Latin ancestry), our initial analysis screen identified 263 variants that were identified as highly deleterious (HD) from a total of 26,661 variants of interest that represented 215 genes. Of those, we identified 46 genes (in 58 patients) harboring rare HD coding variants that were previously implicated in dilated cardiomyopathy and were considered as disease initiators for the severe COVID-19 in this study. These findings offer valuable insights into the molecular mechanisms and genetic susceptibility to heart injury in severe COVID-19. KEY MESSAGES: COVID-19 may cause cardiac damage in some affected patients without a plausible biological explanation. Our study reveals an enrichment of highly deleterious variants linked to cardiomyopathy in severe COVID-19 patients. Genetic profiling unveils the molecular basis of severe COVID-19-related heart injury, potentially aiding in patient stratification.

Indexed as

CardiomyopathiesCOVID-19Genetic Predisposition to DiseaseHeart InjuriesHispanic or LatinoAdultAgedBlack or African AmericanExome SequencingFemaleHumansMaleMiddle AgedSARS-CoV-2AfricanCardiomyopathyCOVID-19Myocardial injurySARS-CoV-2

Identifiers

PMID39730912
PMCPMC11799050

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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.