Integrative network analysis interweaves the missing links in cardiomyopathy diseasome

Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy's genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, including NOS3, MMP2 and SIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research.

Automated summary

Cardiomyopathies are a common and progressive cause of heart failures. These diseases have complex interactions with other diseases, and understanding their molecular mechanisms is essential. By using network medicine techniques, we identified candidate genes associated with cardiomyopathies and found strong associations with brain, cancer, and metabolic diseases. Through integrated analysis of molecular pathways and experimental data, we identified important candidate genes related to abnormal heart phenotype. This study expands our understanding of the genetic associations of cardiomyopathies with other diseases and holds significant potential in cardiomyopathy research.