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Updated: Jan 11, 2026

Single Cell Transcriptional Profiling of Adult Mouse Cardiomyocytes
Published on: December 28, 2011
Transcriptomic and proteomic profiling shows dysregulated immune and metabolic pathways in arrhythmogenic
Deniz Akdis1, Lukas Weidmann2, Paolo Nanni3
1Department of Cardiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
Insights
Arrhythmogenic cardiomyopathy (ACM) is a genetic heart condition. This study identified key molecular pathways and potential biomarkers, OCIAD1 and desmoyokin, in ACM patients, offering new diagnostic insights.
Area of Science:
- Cardiovascular Research
- Molecular Biology
- Genetics
Background:
- Arrhythmogenic cardiomyopathy (ACM) is a hereditary heart disease marked by fibrofatty tissue replacement and arrhythmias.
- The precise mechanisms driving ACM and reliable disease markers are not fully understood.
Purpose of the Study:
- To comprehensively analyze the myocardial transcriptome and proteome in ACM patients.
- To identify potential plasma and tissue biomarkers for ACM diagnosis and understanding.
Main Methods:
- Integrated transcriptomic (RNA sequencing) and proteomic (mass spectrometry) analysis of myocardial tissues from ACM, dilated cardiomyopathy (DCM), and healthy control groups.
- Differential expression and pathway enrichment analyses to pinpoint key biological processes.
- Validation of selected targets using immunofluorescence and plasma enzyme-linked immunosorbent assays (ELISA).
Main Results:
- Significant dysregulation of 3030 mRNAs and 206 proteins in ACM compared to healthy controls.
- Key pathways implicated in ACM include immune activation, inflammation, extracellular matrix remodeling, and mitochondrial stress.
- OCIAD1 and desmoyokin were consistently upregulated at both transcript and protein levels and detected in plasma, distinguishing ACM patients.
Conclusions:
- Integrated multi-omics analysis reveals critical pathways in ACM pathogenesis.
- OCIAD1 and desmoyokin show promise as specific candidate biomarkers for arrhythmogenic cardiomyopathy.
Aims:
Arrhythmogenic cardiomyopathy (ACM) is a hereditary heart disease characterized by fibrofatty myocardial replacement and a predisposition to malignant ventricular arrhythmias. The underlying pathomechanisms remain incompletely understood, and specific disease markers are sparse. This study aimed to characterize the myocardial transcriptome and proteome in ACM patients and assess whether key identified molecules were also detectable in plasma and tissue samples.
Methods And Results:
Myocardial tissues were obtained from ACM and dilated cardiomyopathy (DCM) patients as well as healthy controls (n = 10/group). Transcriptomic profiling was performed by RNA sequencing and proteomic profiling by label-free liquid chromatography-tandem mass spectrometry. Differential expression and pathway enrichment analyses were performed to identify key biological processes. Selected targets were validated by tissue immunofluorescence and plasma ELISA. Transcriptomic analysis revealed 3030 dysregulated mRNAs in ACM versus healthy controls and 120 versus DCM. Enriched clusters in ACM versus healthy controls were related to immune activation, inflammation, extracellular matrix remodelling and mitochondrial stress; redox and metabolic processes, cell junction regulation and immune responses were enriched clusters in ACM versus DCM. Proteomics identified 206 and 65 differentially expressed proteins, respectively. Three novel proteins, UCHL1, OCIAD1 and desmoyokin, were consistently up-regulated at transcript and protein levels. The latter two were confirmed in myocardial tissue staining and showed elevated plasma levels in ACM compared with DCM and controls.
Conclusion:
This integrated transcriptomic and proteomic study of myocardial tissue and plasma from patients with ACM compared with those with DCM and healthy controls, identified key dysregulated pathways, involving immune response, inflammation and oxidative and mitochondrial stress. Desmoyokin and OCIAD1, in particular, may represent specific candidate biomarkers for ACM.
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