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Article . 2022 . Peer-reviewed
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Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies

Authors: Reichart, Daniel; Lindberg, Eric L.; Maatz, Henrike; Miranda, Antonio M. A.; Viveiros, Anissa; Shvetsov, Nikolay; Gärtner, Anna; +47 Authors

Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies

Abstract

Pathogenic variants in genes that cause dilated cardiomyopathy (DCM) and arrhythmogenic cardiomyopathy (ACM) convey high risks for the development of heart failure through unknown mechanisms. Using single-nucleus RNA sequencing, we characterized the transcriptome of 880,000 nuclei from 18 control and 61 failing, nonischemic human hearts with pathogenic variants in DCM and ACM genes or idiopathic disease. We performed genotype-stratified analyses of the ventricular cell lineages and transcriptional states. The resultant DCM and ACM ventricular cell atlas demonstrated distinct right and left ventricular responses, highlighting genotype-associated pathways, intercellular interactions, and differential gene expression at single-cell resolution. Together, these data illuminate both shared and distinct cellular and molecular architectures of human heart failure and suggest candidate therapeutic targets.

Countries
Germany, Germany, United Kingdom
Keywords

EXPRESSION, DYNAMICS, Cardiomyopathy, Dilated, Cardiomyopathy, General Science & Technology, Heart Ventricles, 610, PROTEIN, Hasso-Plattner-Institut für Digital Engineering gGmbH, DETERMINANTS, MOUSE, DISEASE, Article, Atlases as Topic, ENDOTHELIN-1, Dilated, Humans, RNA-Seq, Arrhythmogenic Right Ventricular Dysplasia, Cell Nucleus, Heart Failure, Science & Technology, RECEPTOR, Multidisciplinary Sciences, SURVIVAL, Science & Technology - Other Topics, ddc:570, Single-Cell Analysis, Transcriptome

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    174
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
174
Top 1%
Top 10%
Top 0.1%
Green
bronze