A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Area of Science:

• Genomics and Molecular Biology
• Cardiovascular Research
• Bioinformatics

Background:

• Cardiovascular diseases (CVDs) are a significant global health burden, with heart failure (HF) subtypes (dilated, ischemic, hypertrophic cardiomyopathies) being areas of intense research.
• Understanding the complex interplay of genetic and environmental factors in HF pathogenesis is crucial for developing effective treatments.

Purpose of the Study:

• To construct a Gene Regulatory Network (GRN) for Heart Failure (HF) by integrating data from multiple studies.
• To identify key transcription factors (TFs) and their regulatory roles in HF pathogenesis.
• To uncover novel regulators and pathways implicated in different types of cardiomyopathies.

Main Methods:

• Utilized a Partial Correlation Coefficient (PCC)-based algorithm within a meta-analysis framework to build the GRN.
• Integrated data from multiple independent studies to enhance the robustness of the findings.
• Analyzed regulatory associations between transcription factors and structural genes involved in cardiac function.

Main Results:

• Identified crucial regulatory associations between TFs and structural genes, impacting metabolic pathways (fatty acid metabolism, oxidative stress, epithelial-to-mesenchymal transition, coagulation).
• Discovered novel TF regulators: FPM315 and OVOL2 for dilated cardiomyopathies; TEAD1 and TEAD2 for dilated and ischemic cardiomyopathies.
• Uncovered pathway alterations in hypertrophic cardiomyopathy (adipogenesis, oxidative phosphorylation) and identified a role for IL2 STAT5 signaling in HF.

Conclusions:

• Transcription factor (TF) activity plays a critical role in the initiation and progression of cardiac diseases.
• The identified novel TFs and pathways represent potential therapeutic targets for managing heart failure and cardiomyopathies.
• This GRN approach provides valuable insights into the complex molecular mechanisms underlying cardiovascular diseases.