Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

RNA-seq of the atrioventricular node from a model of heart failure


ABSTRACT: Heart failure is associated with atrioventricular (AV) node dysfunction, and AV node dysfunction in the setting of heart failure is associated with an increased risk of mortality and heart failure hospitalisation. This study aims to understand the causes of AV node dysfunction in heart failure by studying changes in the whole nodal transcriptome. The mouse transverse aortic constriction model of heart failure was studied; functional changes were assessed using electrocardiography and echocardiography and the transcriptome of the AV node was quantified using RNA-seq. Heart failure was associated with a significant increase in the PR interval, indicating a slowing of AV node conduction and AV node dysfunction, and significant changes in 3,077 transcripts (5.6% of the transcriptome). Many systems were affected: transcripts supporting AV node conduction were downregulated and there were changes in transcripts identified by GWAS as determinants of the PR interval. In addition, there was evidence of remodelling of the sarcomere, a shift from fatty acid to glucose metabolism, and remodelling of the extracellular matrix. There was evidence of the causes of this widespread remodelling of the AV node: evidence of dysregulation of multiple intracellular signalling pathways, dysregulation of 109 protein kinases and 148 transcription factors, and an immune response with a proliferation of neutrophils, monocytes, macrophages and B lymphocytes and a dysregulation of 40 cytokines. In conclusion, inflammation and a widespread transcriptional remodelling of the AV node underlies AV node dysfunction in heart failure.

INSTRUMENT(S): Illumina HiSeq 4000

ORGANISM(S): Mus musculus

SUBMITTER:  

PROVIDER: E-MTAB-12384 | biostudies-arrayexpress |

SECONDARY ACCESSION(S): ERP143409

REPOSITORIES: biostudies-arrayexpress

Similar Datasets

2024-04-25 | PXD031084 | Pride
2017-04-20 | GSE86306 | GEO
2017-04-20 | GSE86310 | GEO
2008-10-21 | E-GEOD-11040 | biostudies-arrayexpress
2009-06-02 | E-GEOD-13614 | biostudies-arrayexpress
2009-06-02 | GSE13614 | GEO
2024-09-10 | GSE250173 | GEO
2014-08-01 | GSE10318 | GEO
2014-08-01 | E-GEOD-10318 | biostudies-arrayexpress
2011-10-11 | E-GEOD-32517 | biostudies-arrayexpress