Background Heart failure (HF) is a major public health burden. Mineralocorticoid receptor antagonists (MRAs) reduce hospitalisation and improve survival in patients with HF with reduced ejection fraction (HFrEF) but the widespread use of MRAs is limited by adverse effects including hyperkalaemia. The use of biomarkers to guide therapy may enable earlier treatment or minimise side effects from unnecessary therapies. We have previously described mineralocorticoid receptor responsive genes in monocytes/macrophages and hypothesised that response to MRAs can be detected in this cell population. Therefore, we aimed to identify biomarkers for predicting response to MRAs to facilitate personalised treatment of HF.
Methods We performed microarray-based transcriptome profiling of monocytes obtained from six patients with HFrEF, before and after three months of MRA treatment. Multidimensional scaling (MDS) was employed to visualise sample similarity followed by differential expression analysis. Top differentially expressed genes (DEGs) implicated in cardiovascular pathophysiology were validated by RT-qPCR.
Results Three patients demonstrated improvement in left ventricular ejection fraction (LVEF) after 12 months of MRA treatment (Group 1), whereas the other three patients exhibited minimal functional response to MRAs (Group 2). The MDS plot revealed a distinct separation of males from females. Paired analysis of Group 1 samples (before vs after MRA treatment) identified 319 unique DEGs (estimated fold-change ≥ 2, q-value < 0.05); 1 upregulated, 318 downregulated). Group 2 had 1 unique DEG. RT-qPCR confirmed down-regulation of 12 of the top DEGs in Group 1. Additionally, cluster differentiation (CD) markers CD14, CD163 and CD68 were upregulated in Group 1 but downregulated in Group 2.
Conclusion Our results show MRA treatment can significantly alter the monocyte transcriptomic profile. Further research is needed to establish the utility of these DEGs as biomarkers for early prediction of MRA treatment-response in patients with HF, and to define sex-specific differences.