Background:
Morphological changes or infiltration of immune cells caused by disease progression can manifest as changes in gene expression patterns. Likewise, healing processes can also be characterized through regenerative gene expression patterns. The dynamics between the expression of different genes can therefore give information about disease progression and remission. In this study, we measured gene expression in endomyocardial biopsies (EMB) from patients with heart failure at the time of diagnosis and correlated the data with the development of left ventricular ejection fraction (LVEF).
Methods:
A cohort of 49 patients with heart failure were enrolled in this study (mean age: 50 years, std dev. ±14 years, 24% female). LV-function was measured at baseline and 6-12 months after diagnosis. About half of the patients (n=27) showed a reduced follow-up LV-function (<45%; outcome group 1) and 22 patients showed a normal LV-function (>45%; outcome-group 2) at follow-up. Total RNA was extracted from endomyocardial biopsies and sequenced on an Illumina NextSeq500.
Results:
We found 162 differentially expressed genes between the two outcome groups. Out of these, a small set was selected which showed stable differential expression when confounding variables such as sex were accounted for. Among the differentially expressed genes, several were found which have a published involvement in cardiovascular processes. For instance, the top differentially expressed genes in patients with a good follow-up LVEF include myosin heavy chain 6 (MYH6), which can be associated with atrial septal defect and cardiomyopathy. Likewise, genes with higher expression in patients with poor follow-up LV-function include, Matrix Gla Protein (MGP), which is associated with calcification of the vasculature in patients with cardiovascular disease. Beyond these, several DEGs were found for which no involvement in cardiovascular disease is described yet and demand further research.
Conclusions:
Here, we present genes associated with normal or reduced outcome of LVEF. The changes in gene expression in patients with heart failure serve as predictors for assessing prognosis. This can shed further light on gene expression changes during heart failure. Furthermore, when integrated into individualized risk prediction models, quantification of gene expression serves as a valuable tool for clinicians in making treatment decisions.
