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.

Figure 1

Functional assignment of genes differentially expressed in responders and non-responders compared with control individuals with normal left ventricular ejection fraction. Significance (−log P-value) of the association, which is dependent on the number of genes in the class, for canonical pathways (A) and toxic functions in the heart (C) as assigned by Ingenuity Pathway Analysis version 8.6. Numbers of genes repressed and induced in comparison with the control group are displayed (B and D).

Figure 2

Negative inotropic activity of cardiac autoantibodies in responders and non-responders. Negative inotropic activity was determined by measuring percentage change of maximum cell shortening of RCM during immunoglobulin G superfusion compared with the baseline value. Green, responders; red, non-responders.

Figure 3

Assessment of the value of clinical parameters (A), gene signature (B), and a combination of gene signature and antibody status (C) for the classification of responders and non-responders at BL. The correlation of the individual patients to the responder template is displayed in the left column, and that to the non-responder template in the right column. Green, responders; red, non-responders. Validity of the classification of patients into responders or non-responders increases with the degree of positive correlation to the corresponding template (maximum value 1) and negative correlation with the other template (minimum value −1).

Figure 4

Expression patterns of the four signature genes commonly identified with the support vector machine and random forest analysis. The mean of normalized signal intensities and the standard deviation of expression values of genes coding for RANBP1 (ras-related nuclear binding protein 1), RGS10 (regulator of G-protein signaling 10), UBE3B (ubiquitin protein ligase E3B), and USP22 (ubiquitin specific peptidase 22) (P-value, the Mann–Whitney test) are displayed for controls (Co, n = 8, open bars), responders (R, n = 24, green bars), and non-responders (NR, n = 16, red bars) at baseline (BL).

Figure 5

Simulation of robustness of the prediction of therapy outcome. The robustness of the prediction based on the expression of the four signature genes, negative inotropic activity of antibodies, and their combination was determined by adding a random noise to the parameter values of each sample prior to the classification to simulate the variation of values in the population. Added random noise is displayed on the X-axis as fold-values of the standard deviation (SD). Predictions are based on the expression level of four signature genes (red line), negative inotropic activity of antibodies (blue line), and a combination of both values (black line).