Long-read Genome Sequencing and Risk Stratification of Myocardial Ischemia in Patients With Heart Transplantation

Background: Heart transplantation (HTx) is the treatment of choice for patients with end-stage heart failure who remain symptomatic despite optimal medical therapy. Even with best-practice follow-up care, one out of eight HTx patients eventually die of ischemic cardiomyopathy and recurrent acute myocardial infarction (AMI). Classical risk factors like the recipient indication for heart transplantation explain a fraction of adverse outcomes, but no conventional risk factor alone satisfactorily predicts the probability of cardiac allograft vasculopathy (CAV) or recurrent AMI in HTx patients; in addition, the underlying pathomechanisms are poorly understood.

Therefore, there is an urgent need for an improved understanding of the factors contributing to recurrent myocardial ischemia in HTx patients. Recent large-scale studies of the genetic architecture of coronary artery disease in the general population indicate that polygenic risk scores (PRS) explain more disease risk than any single non-genetic risk factor, but, due to a lack of longitudinal follow-up studies with deep phenotyping, PRS have not yet been widely adopted in clinical practice. Furthermore, current genetic studies are based on microarrays or short-read sequencing, severely limiting their ability to characterize the effect of complex or structural genetic variation, in the whole human genome as well as in key loci of potential importance for HTx outcomes, affecting, e.g., lipid metabolism (e.g. LPA) and immunogenetic compatibility (e.g. the major histocompatibility complex).

In summary, there is presently no study leveraging the improved ability to resolve human genomes with long-read sequencing technologies in a deeply phenotyped cohort for an improved understanding of recurring myocardial ischemia.

Study design and aims: In an innovative three-component study design, comprehensive phenotyping with the latest long-read sequencing technology and algorithmic advances in computational genomics to elucidate the interplay of genetic and non-genetic risk factors of myocardial ischemia in HTx patients at unprecedented resolution and pave the way towards detailed risk stratification and tailored treatment, will be combined

Significance and translational potential: By enabling the integrated analysis of structural variants, high-penetrance complex variants, and high-resolution immunogenetics, long-read sequencing will enable improved genetic models of the development of ischemia in HTx patients and contribute to an improved understanding of underlying pathomechanisms. Based on this, the investigators will be able to propose schemes to incorporate integrated risk scores in future clinical trials for personalized treatment stratification.