Transcriptome data analysis of primary cardiomyopathies reveals perturbations in arachidonic acid metabolism

10Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Introduction: Cardiomyopathies are complex heart diseases with significant prevalence around the world. Among these, primary forms are the major contributors to heart failure and sudden cardiac death. As a high-energy demanding engine, the heart utilizes fatty acids, glucose, amino acid, lactate and ketone bodies for energy to meet its requirement. However, continuous myocardial stress and cardiomyopathies drive towards metabolic impairment that advances heart failure (HF) pathogenesis. So far, metabolic profile correlation across different cardiomyopathies remains poorly understood. Methods: In this study, we systematically explore metabolic differences amongst primary cardiomyopathies. By assessing the metabolic gene expression of all primary cardiomyopathies, we highlight the significantly shared and distinct metabolic pathways that may represent specialized adaptations to unique cellular demands. We utilized publicly available RNA-seq datasets to profile global changes in the above diseases (|log2FC| ≥ 0.28 and BH adjusted p-val 0.1) and performed gene set analysis (GSA) using the PAGE statistics on KEGG pathways. Results: Our analysis demonstrates that genes in arachidonic acid metabolism (AA) are significantly perturbed across cardiomyopathies. In particular, the arachidonic acid metabolism gene PLA2G2A interacts with fibroblast marker genes and can potentially influence fibrosis during cardiomyopathy. Conclusion: The profound significance of AA metabolism within the cardiovascular system renders it a key player in modulating the phenotypes of cardiomyopathies.

Cite

CITATION STYLE

APA

Chauhan, P. K., & Sowdhamini, R. (2023). Transcriptome data analysis of primary cardiomyopathies reveals perturbations in arachidonic acid metabolism. Frontiers in Cardiovascular Medicine, 10. https://doi.org/10.3389/fcvm.2023.1110119

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free