Single-cell and spatial mapping of human diabetic cardiomyopathy

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In patients with diabetes mellitus, the presence of myocardial dysfunction in the absence of coronary artery disease, valvular disease or conventional cardiovascular risk factors, such as hypertension and dyslipidemia, has led to the term diabetic cardiomyopathy. Diabetic cardiomyopathy is characterized by myocardial fibrosis, dysfunctional remodeling, and associated diastolic and later systolic- dysfunction. The underlying mechanisms are unclear and specific therapies do not exist. We have access to a unique biobank with samples of ventricular myocardium of 140 transplanted diabetic cardiomyopathy patients and will utilize 20 rejected donor hearts, 20 ischemic cardiomyopathy and 20 monogenetic cardiomyopathy specimens as references. The ventricular tissue is available from orthotopic heart-transplantations (HTx) and/or ventricular assist device implantations. We will utilize high resolution spatial transcriptomics (DBIT-seq, 5µm) combined with snRNA and snATAC seq to map human diabetic cardiomyopathy at unprecedented resolution. We will multiplex specimen and demultiplex using genetic variability (SNPs) to increase throughput and decrease costs. We will apply state-of-the-art as well as novel bespoke computational methodologies with the ultimative goal to identify mechanisms and therapeutic targets.