Myocardial gene expression profiles and cardiodepressant autoantibodies predict response of patients with dilated cardiomyopathy to immunoadsorption therapy.

ABSTRACT

AIMS: Immunoadsorption with subsequent immunoglobulin G substitution (IA/IgG) represents a novel therapeutic approach in the treatment of dilated cardiomyopathy (DCM) which leads to the improvement of left ventricular ejection fraction (LVEF). However, response to this therapeutic intervention shows wide inter-individual variability. In this pilot study, we tested the value of clinical, biochemical, and molecular parameters for the prediction of the response of patients with DCM to IA/IgG. METHODS AND RESULTS: Forty DCM patients underwent endomyocardial biopsies (EMBs) before IA/IgG. In eight patients with normal LVEF (controls), EMBs were obtained for clinical reasons. Clinical parameters, negative inotropic activity (NIA) of antibodies on isolated rat cardiomyocytes, and gene expression profiles of EMBs were analysed. Dilated cardiomyopathy patients displaying improvement of LVEF (≥20 relative and ≥5% absolute) 6 months after IA/IgG were considered responders. Compared with non-responders (n = 16), responders (n = 24) displayed shorter disease duration (P = 0.006), smaller LV internal diameter in diastole (P = 0.019), and stronger NIA of antibodies. Antibodies obtained from controls were devoid of NIA. Myocardial gene expression patterns were different in responders and non-responders for genes of oxidative phosphorylation, mitochondrial dysfunction, hypertrophy, and ubiquitin-proteasome pathway. The integration of scores of NIA and expression levels of four genes allowed robust discrimination of responders from non-responders at baseline (BL) [sensitivity of 100% (95% CI 85.8-100%); specificity up to 100% (95% CI 79.4-100%); cut-off value -0.28] and was superior to scores derived from antibodies, gene expression, or clinical parameters only. CONCLUSION: Combined assessment of NIA of antibodies and gene expression patterns of DCM patients at BL predicts response to IA/IgG therapy and may enable appropriate selection of patients who benefit from this therapeutic intervention.