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

Ameling S, Herda LR, Hammer E, Steil L, Teumer A, Trimpert C, Dörr M, Kroemer HK, Klingel K, Kandolf R, Völker U, Felix SB - Eur. Heart J. (2012)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Interfakultäres Institut für Genetik und Funktionelle Genomforschung, Universitätsmedizin Greifswald, Friedrich-Ludwig-Jahn-Strasse 15a, Greifswald D - 17487, Germany.

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.

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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).
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EHS330F4: 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).

Mentions: Since gene expression was distinctively different in responders and non-responders when compared with controls, we used two independent methods, an SVM algorithm and an RF analysis to develop a robust classifier which might distinguish responders and non-responders before the start of therapy. Four genes [ras-related nuclear binding protein 1 (RANBP1), regulator of G-protein signaling 10 (RGS10), ubiquitin protein ligase E3B (UBE3B), and ubiquitin specific peptidase 22 (USP22), Figure 4] were consistently identified as good predictors by the two different algorithms. This discriminating four-gene signature revealed a much better prediction performance than clinical parameters (correlation coefficient cut-off value 0.33 instead of 1 for clinical parameters, Figure 3B and Supplementary material online, Figure S9). Here, responders displayed a good correlation to the responder template and, as expected, anti-correlation to the non-responder templates, respectively. However, prediction performance was lower for non-responders, because a subgroup of those patients did not display the expected correlation with the non-responder template and anti-correlation with the responder template. By far, the best prediction was accomplished when gene signature and NIA of autoantibodies were combined (Figure 3C), because clear assignments to the groups of responders and non-responders could be accomplished with both templates for all but one patient (correlation coefficient cut-off value −0.28).Figure 4


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

Ameling S, Herda LR, Hammer E, Steil L, Teumer A, Trimpert C, Dörr M, Kroemer HK, Klingel K, Kandolf R, Völker U, Felix SB - Eur. Heart J. (2012)

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).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3584995&req=5

EHS330F4: 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).
Mentions: Since gene expression was distinctively different in responders and non-responders when compared with controls, we used two independent methods, an SVM algorithm and an RF analysis to develop a robust classifier which might distinguish responders and non-responders before the start of therapy. Four genes [ras-related nuclear binding protein 1 (RANBP1), regulator of G-protein signaling 10 (RGS10), ubiquitin protein ligase E3B (UBE3B), and ubiquitin specific peptidase 22 (USP22), Figure 4] were consistently identified as good predictors by the two different algorithms. This discriminating four-gene signature revealed a much better prediction performance than clinical parameters (correlation coefficient cut-off value 0.33 instead of 1 for clinical parameters, Figure 3B and Supplementary material online, Figure S9). Here, responders displayed a good correlation to the responder template and, as expected, anti-correlation to the non-responder templates, respectively. However, prediction performance was lower for non-responders, because a subgroup of those patients did not display the expected correlation with the non-responder template and anti-correlation with the responder template. By far, the best prediction was accomplished when gene signature and NIA of autoantibodies were combined (Figure 3C), because clear assignments to the groups of responders and non-responders could be accomplished with both templates for all but one patient (correlation coefficient cut-off value −0.28).Figure 4

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Interfakultäres Institut für Genetik und Funktionelle Genomforschung, Universitätsmedizin Greifswald, Friedrich-Ludwig-Jahn-Strasse 15a, Greifswald D - 17487, Germany.

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.

Show MeSH
Related in: MedlinePlus