Decoding the complex genetic causes of heart diseases using systems biology

Area of Science:

• Genomics and Bioinformatics
• Cardiovascular Disease Research
• Systems Biology

Background:

• Traditional methods for identifying disease genes are slow, despite advances in DNA sequencing.
• Inherited heart diseases often have complex polygenic causes, involving gene interactions and non-coding regions.
• Understanding these complexities is vital for interpreting genetic mutations.

Purpose of the Study:

• To review genomic and bioinformatics techniques for accelerating heart disease gene discovery.
• To introduce CardiacCode, an interactive web-resource for systems biology analysis of heart development and disease.
• To highlight the importance of integrating diverse genomic data for understanding complex heart conditions.

Main Methods:

• Review of state-of-the-art genomic and bioinformatics techniques.
• Development and utilization of a systems biology approach.
• Creation of an interactive web-resource (CardiacCode) with curated perturbation data.

Main Results:

• CardiacCode provides a cardiac-specific gene regulatory network (GRN) with 280 regulatory relationships.
• The resource integrates manually curated genetic and molecular perturbation data.
• The approach facilitates the inference of gene regulatory networks for heart diseases.

Conclusions:

• Integrating genomics, epigenomics, and transcriptomics with systems biology accelerates the discovery of complex heart disease genes.
• Interactive resources like CardiacCode are essential for advancing predictive and personalized genomic medicine.
• This approach addresses the unmet need for comprehensive tools in tackling human heart disease.