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As Japan becomes a super-aged society, the disease landscape is shifting, and the number of patients with age-related cardiovascular conditions, such as heart failure and atrial fibrillation, is rapidly increasing. Cardiovascular diseases are highly complex conditions involving a multifaceted interplay between genetic and environmental factors, making it difficult to fully elucidate their pathogenesis. Heart failure, in particular, the final manifestation of these conditions, is considered an “ultra-complex disease.” However, recent advances in data science have enabled the analysis of the deep phenotypes of cardiovascular diseases, which are among the most information-rich of all disease categories, and the integration of this data with vast amounts of genomic and other omics information generated by cutting-edge analytical technologies.

We previously reported that pressure overload in the mouse heart induces DNA damage in cardiomyocytes, leading to ischemia and heart failure through the upregulation of p53 expression (Nature, 2007). More recently, using advanced techniques such as myocardial single-cell analysis, we demonstrated the critical role of myocardial DNA damage and elevated p53 expression in the pathogenesis of human heart failure (Nat Commun. 2017, 2018, 2022; Circulation 2024; JACC Heart Fail 2024). Furthermore, we identified IGFBP7, recognized as a predictive marker for heart failure severity through machine learning (Nat Commun. 2022), as a protein secreted by senescent cardiomyocytes and endothelial cells in response to DNA damage, contributing to heart failure development. Importantly, we found that a vaccine targeting IGFBP7 can suppress the onset of heart failure (Circulation 2024). Advances in emerging technologies have enabled deeper insights into the molecular mechanisms driving heart failure, offering new avenues for therapeutic development.