Integrated systems approach identifies risk regulatory pathways and key regulators in coronary artery disease

Area of Science:

• Cardiovascular Research
• Systems Biology
• Genomics

Background:

• Coronary artery disease (CAD) is a prevalent heart condition with poorly understood molecular mechanisms.
• Regulatory pathways are critical in disease pathogenesis, making their identification crucial for understanding CAD.
• Advances in high-throughput data necessitate novel computational approaches to dissect complex diseases.

Purpose of the Study:

• To develop an integrated systems approach for identifying CAD risk regulatory pathways and key regulators.
• To elucidate the molecular mechanisms and regulatory information flow in CAD initiation and progression.
• To propose a novel method for prioritizing upstream regulators in disease pathways.

Main Methods:

• A CAD-related core subnetwork was identified using a random walk algorithm on a curated transcription factor (TF) and microRNA (miRNA) regulatory network.
• Candidate risk regulatory pathways were extracted via a breadth-first search (BFS) algorithm.
• Pathway prioritization was performed using multiple CAD-associated data sources, and upstream regulators were ranked with a new measure.

Main Results:

• An integrated systems approach successfully identified risk regulatory pathways in CAD.
• A novel measure was proposed and applied to prioritize key upstream regulators.
• The phosphatase and tensin homolog (PTEN) was identified as a potential key regulator in the dysregulation of identified risk pathways.

Conclusions:

• The developed approach effectively identifies risk regulatory pathways and key regulators in CAD.
• PTEN is implicated as a significant regulator in the context of CAD pathogenesis.
• Understanding regulatory pathway dynamics offers insights into CAD etiology and progression.