Transcriptomics of cardiac biopsies reveals differences in patients with or without diagnostic parameters for heart failure with preserved ejection fraction.

Heart failure affects 2-3% of adult Western population. Prevalence of heart failure with preserved left ventricular (LV) ejection fraction (HFpEF) increases. Studies suggest HFpEF patients to have altered myocardial structure and functional changes such as incomplete relaxation and increased cardiac stiffness. We hypothesised that patients undergoing elective coronary bypass surgery (CABG) with HFpEF characteristics would show distinctive gene expression compared to patients with normal LV physiology. Myocardial biopsies for mRNA expression analysis were obtained from sixteen patients with LV ejection fraction ≥45%. Five out of 16 patients (31%) had echocardiographic characteristics and increased NTproBNP levels indicative of HFpEF and this group was used as HFpEF proxy, while 11 patients had Normal LV physiology. Utilising principal component analysis, the gene expression data clustered into two groups, corresponding to HFpEF proxy and Normal physiology, and 743 differentially expressed genes were identified. The associated top biological functions were cardiac muscle contraction, oxidative phosphorylation, cellular remodelling and matrix organisation. Our results also indicate that upstream regulatory events, including inhibition of transcription factors STAT4, SRF and TP53, and activation of transcription repressors HEY2 and KDM5A, could provide explanatory mechanisms to observed gene expression differences and ultimately cardiac dysfunction in the HFpEF proxy group.

Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.

Analysis of the pattern of proteins or messengerRNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics. This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call "spatial transcriptomics," that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics.