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Updated: Jun 5, 2025

Quantitative Analysis of Cellular Composition in Advanced Atherosclerotic Lesions of Smooth Muscle Cell Lineage-Tracing Mice
Published on: February 20, 2019
Genetics architecture of spontaneous coronary artery dissection in an Italian cohort
Marta Casula1, Daniela Marchetti2, Lucia Trevisan3
1Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy.
Abstract:
Spontaneous coronary artery dissection (SCAD) is a relevant non-atherosclerotic cause of acute coronary syndrome with a complex genetic architecture. Recent discoveries have highlighted the potential role of miRNAs and protein-coding genes involved in the processing of small RNAs in the pathogenesis of SCAD. Furthermore, there may be a connection between SCAD and the increased cardiovascular risk observed in fragile X premutation carriers as well as a correlation with pathogenetic variants in genes encoding for collagen and extracellular matrix, which are related to connective tissue disorders (CTDs). In our cohort of 15 Italian SCAD patients, a total of 37 rare variants were identified in 34 genes using whole exome sequencing (WES) and TRIO-WES analysis when both parents were available. Three likely pathogenic/pathogenetic variants were found in genes previously associated with SCAD and CTDs (COL3A1, COL1A2, and SMAD3) and 26 variants of uncertain significance in genes previously associated with SCAD and CTDs. TRIO-WES analysis revealed 7 de novo variants, 1 of which was found in a potential novel candidate gene (DROSHA). In addition, a premutation allele of 55 ± 2 CGG repeats in the promoter of the FMR1 gene was identified in two related SCAD patients by test for CGG-repeat expansions in the 5'-UTR of the FMR1 gene. Our findings suggest various potential mechanisms such as mRNA toxicity, miRNA regulation, alteration of collagen, and the extracellular matrix architecture, all of which could disrupt vascular homeostasis, and finally, WES and TRIO-WES have proven to be the most powerful approaches for characterizing the genetic background of SCAD.
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