Molecular mechanism leading to human coronary atherosclerosis assessed by proteomic analysis and RNA sequences

Abstract Background and Aims Atherosclerosis results from cellular and extracellular changes in the arterial wall, preceded by molecular shifts that initiate disease and drive tissue conversion, yet these changes are not yet fully described. More data are needed concerning these early changes in the coronary artery molecular landscape that signify the initiation of atherosclerosis and the subsequent tissue pheno-conversion to atherosclerotic plaque. This report summarizes results from a large biorepository of human coronary artery tissue, applying state-of-the-art omics technology, advanced data analytic methods, and an arterial organoid model system to predict molecular dynamics and identify potential regulatory mechanisms that could interrupt molecular changes that contribute to the earliest stages of disease pathogenesis. The long-term goal of this effort is to identify and develop new therapies to further mitigate the persistently high burden of clinical coronary disease. Methods Mass spectrometry-based proteomic analysis and RNA sequencing (RNASeq) were used to analyse proximal coronary arterial samples from young adults who died of trauma with no ante mortem suspicion of coronary disease n = 322, mean age (range): 34.1 years (15–59); sex: M-239, F-83; race: W-218, B-88, other-16. Despite the absence of clinical disease, 56% of samples had morphologic evidence of pre-clinical atherosclerosis. Analyses of the proteomic data (n = 1900 proteins) using state-of-the-art dimensionality reduction and deconvolution techniques generated an estimate of molecular disease progression (e.g. pseudo-time) and identified selected proteomic latent features (LFs) (i.e. large groups of co-ordinated proteins) associated with its initiation and progression. Computational genomics, machine learning models, and multi-omic network mapping of these proteomic LFs and associated mRNA gene transcripts suggested potential transcriptional regulators which were subsequently confirmed in publicly available single-cell coronary artery data. The effects of one of the leading regulatory transcription factors (TFs), MLXIPL, predicted to regulate two LFs, were further validated in a human arterial cell organoid model system. Results Four proteomic LFs, composed of n = 100 signature proteins/LF, exhibited distinct patterns with respect to disease progression false discovery rate (FDR) P .01. These LFs illuminate the earliest changes in the arterial proteome during tissue pheno-conversion from normal coronary artery to atherosclerotic plaque, including dramatic declines in mitochondrial energy biosynthesis proteins, evidence of vascular unit activation (including pericytes), and neurovascular and neuroimmune modulation (all FDR P .01). These early changes preceded the expected immune cell recruitment and innate immune response characteristic of atherosclerotic plaque formation. Analysis of transcriptional regulatory networks identified from RNASeq data highlighted both known and novel TFs and master regulators of LF proteins that may drive the initial and early stages of disease progression. Publicly available single-cell RNASeq data from normal and atherosclerotic coronary arteries validated the LFs and several of their likely master transcriptional regulators (all P .01); and manipulation of the levels of one of top regulatory TFs, MLXIPL, in human arterial cell organoids resulted in the expected changes in expression of the proteins associated with its two targeted LFs (P = .0003 and P .00001, respectively). Conclusions The unique nature of this human coronary biorepository with samples ranging from entirely normal to mature pre-clinical atherosclerotic plaque facilitated prediction of molecular disease progression and identification of several potential transcriptional regulators for further evaluation as potential novel targets to interrupt early initiation and progression of atherosclerotic coronary disease.