Atherosclerosis is the leading cause of acute cardiovascular events, such as myocardial infarction and stroke, and is a significant risk factor for cardiovascular mortality. The detailed understanding of the immune mechanisms and cellular transformations involved in the pathogenesis of atherosclerosis is still limited, and the use of single-cell RNA sequencing (scRNAseq) has revealed new cellular functions and subpopulations associated with disease progression. This study aims to identify cellular subpopulations, molecular pathways, and changes in gene expression related to the development of atherosclerosis in human coronary arteries. Using scRNAseq, the study seeks to characterize the transcriptomic landscape of cells present in atherosclerotic plaques and identify molecular signatures that reveal individual predispositions to specific phenotypes, such as disease susceptibility and response to therapies. The research will be conducted at the Albert Einstein Israeli Hospital in São Paulo and will involve samples from coronary arteries and atherosclerotic plaques of the explanted hearts of patients who have undergone heart transplants as well as from discarded material of coronary artery bypass graft surgery (CABG). With an estimated sample size of 20-30 plaques, the data obtained will allow for a detailed analysis of the molecular mechanisms involved in atherosclerosis, contributing to the development of specific therapeutic targets.
Patients diagnosed with ischemic cardiomyopathy due to advanced atherosclerosis, undergoing heart transplantation;
Patients with coronary artery disease submitted to coronary artery bypass graft surgery (CABG)."
Aged between 40 and 75 years;
Signed informed consent form.
Patients with systemic inflammatory or autoimmune diseases;
History of cancer within the last 5 years or active malignancy;
Recent use (within the last 6 months) of immunosuppressive therapy.
Patients diagnosed with ischemic cardiomyopathy due to advanced atherosclerosis, undergoing heart transplantation.
Case-only
Prospective
Single Cell RNA Sequencing
Diagnostic testReprocessing Data normalization, dimensionality reduction, and clustering will be performed using the Seurat package (based on R). Cell types will be identified based on canonical marker gene expression. Cell Subpopulation Identification Clusters will be annotated based on signatures of known cell types (e.g., endothelial cells, smooth muscle cells, macrophages, etc.). Differential gene expression analysis will be conducted to identify disease-associated genes. Pathway and Function Enrichment Gene Set Enrichment Analysis (GSEA) and pathway analyses (e.g., KEGG, Reactome) will be carried out to investigate the biological processes and pathways driving atherosclerosis. Quality Control Sequencing reads will be assessed for quality using FASTQC, and low-quality reads will be filtered out. The Cell Ranger software (10x Genomics) will be used to align reads to the human genome and quantify gene expression at the single-cell level.
Concentration of Specific Cells Clusters And Macrophage / Linfocite Subpopulations : Create a high-resolution single-cell atlas of atherosclerotic plaques.
Determine the concentration of cellular clusters with specific inflammatory subpopulations determination to Create a high-resolution single-cell atlas of atherosclerotic plaques, revealing cell-specific transcriptional changes associated with the disease. The findings could identify new therapeutic targets for intervention in atherosclerosis and enhance the understanding of its molecular pathogenesis.
Concentration of interleukins and cellular subtypes by citometer flow to Identification of molecular signatures in atherosclerosis
The secondary objective is to identify molecular signatures that reveal individual predispositions to specific phenotypes, such as susceptibility to atherosclerosis, response to therapies, and other health characteristics, establishing the foundation for precision medicine and population health studies in Brazil by determining specific concentrations of pro and anti-inflammatory molecules and cell types.
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