D LESCHE¹, V SIGURDARDOTTIR², C BOVET¹, CR LARGIADÈR¹, U CHRISTIANS³, P MOHACSI², J SISTONEN<sup>1

1</sup>Institute of Clinical Chemistry, University Hospital Bern, University of Bern, Bern, Switzerland, ²Department of Cardiology, Swiss Cardiovascular Centre, University Hospital Bern, Bern, Switzerland, ³Clinical Research and Development, Department of Anesthesiology, University of Colorado, Aurora, Colorado, USA

Tacrolimus (TAC) and everolimus (ERL) are the mainstay of immunosuppressive therapy after heart transplantation (HTx). However, the largely unexplained inter-individual variability in therapy response represents an important clinical problem, as it results in reduced drug effectiveness increasing the risk of graft rejection and severe adverse drug reactions. Novel biomarkers predictive of immunosuppressive therapy outcomes in HTx recipients and an improved understanding of the mechanisms underlying the high variability are thus of great clinical importance. Metabolomics provides a new avenue to discover biomarkers and identify pathways related to drug response by characterizing and comparing metabolic profiles in biological samples. In this study, we aimed to use both non-targeted and targeted metabolomics to study TAC and ERL response in HTx recipients.
Patients with a mean age of 54.4 years (±15.7) receiving either ERL (n=42) or TAC-based (n=39) immunosuppressive therapy after HTx were recruited at the University Hospital of Bern. Lithium heparin plasma and EDTA whole blood samples were collected for non-targeted (i.e. broad semi-quantitative measurement of small molecules) and targeted (i.e. quantification of TAC and ERL main metabolites) profiling, respectively.
Non-targeted metabolic profiling based on Ultra-High Performance Liquid Chromatography and Time-of-Flight mass spectrometry (UPLC-TOF-MS) revealed over 6000 metabolic features belonging to a variety of metabolite classes such as phospholipids, bile acids, amino acids, and fatty acids. Principal component and discriminant analyses will be used to identify metabolic patterns related to inter-individual differences in drug dose requirement and adverse drug reactions. Similarly, the quantitative measurement of TAC and ERL metabolites by LC-MS/MS will provide further insight into their potential relevance to therapeutic outcomes.