Sex-dependent transcriptional control of cardiac electrophysiology by histone acetylation modifiers based on the GTEx database

Abstract

AbstractDevelopment of safer drugs based on epigenetic modifiers, e.g. histone deacetylase inhibitors (HDACi), requires better understanding of their effects on cardiac electrophysiology. Using RNAseq data from the genotype-tissue-expression database (GTEx), we created models that link the abundance of chromatin modifiers, such as histone acetylation enzymes (HDAC/SIRT/HATs), and the gene expression of ion channels (IC) via select cardiac transcription factors (TFs) in male and female adult human hearts (left ventricle, LV). Gene expression data (transcripts per million, TPM) from GTEx donors (21 to 70 y.o.) were filtered, normalized and transformed to Euclidian space to allow quantitative comparisons in 84 female and 158 male LVs. Sex-specific partial least-square (PLS) regression models, linking gene expression data for HDAC/SIRT/HATs to TFs and to ICs gene expression, revealed tight co-regulation of cardiac ion channels by HDAC/SIRT/HATs, with stronger clustering in the male LV. Co-regulation of genes encoding excitatory and inhibitory processes in cardiac tissue by the histone modifiers may help their predominantly net-neutral effects on cardiac electrophysiology. ATP1A1, encoding for the Na/K pump, represented an outlier - with orthogonal regulation by the histone modifiers to most of the ICs. The HDAC/SIRT/HAT effects were mediated by strong (+) TF regulators of ICs, e.g. MEF2A and TBX5, in both sexes. Furthermore, for male hearts, PLS models revealed a stronger (+)/(-) mediatory role on ICs for NKX25 and TGF1B/KLF4, respectively, while RUNX1 exhibited larger (-) TF effects on ICs in females. Male-trained PLS models of HDAC/SIRT/HAT effects on ICs underestimated the effects on some ICs in females. Insights from the GTEx dataset about the co-expression and transcriptional co-regulation of histone-modifying enzymes, transcription factors and key cardiac ion channels in a sex-specific manner can help inform safer drug design.