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Single Endothelial Cell mRNA Sequencing Better Captures the Severity of Coronary Artery Disease Than Targeted Total Arterial Markers of Inflammation and Senescence
Author(s) -
Mury Pauline,
Wünnemann Florian,
Beaudoin Mélissa,
Thorin-Trescases Nathalie,
Hébert Yves,
Pellerin Michel,
Carrier Michel,
Perrault Louis,
Lettre Guillaume,
Thorin Eric
Publication year - 2020
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2020.34.s1.09446
Subject(s) - coronary artery disease , myograph , medicine , atheroma , endothelial dysfunction , endothelium , artery , inflammation , cardiology , senescence , pathology
Endothelial dysfunction is the initial step towards atherosclerotic plaque development and coronary artery disease (CAD). Senescent endothelial cells (SnEC) have been linked to the atherosclerotic burden. In particular, the senescent‐associated secretory phenotype protein angiopoietin‐like 2 (ANGPTL2) was shown to be elevated in the plasma of CAD patients and related to the senescent cellular load in human internal mammary artery (IMA) segments discarded during coronary artery bypass grafting (CABG) surgery. We tested the hypothesis that the accumulation of vascular SnEC causes endothelial dysfunction and precedes the appearance of atherosclerotic lesions. Discarded atheroma‐free IMA segments from 12 patients (11 men and 1 woman, 69±3 years) were collected during consecutive elective CABG surgeries. Arterial rings of IMA segments were mounted in a wire myograph to record isometric changes in tension: arteries were pre‐contracted with U46619, a synthetic analogue of PGH 2 , and endothelium‐dependent relaxations to increasing concentrations of acetylcholine (ACh) were recorded. The maximal relaxation (E max ) and the concentration of ACh inducing 50% of relaxation (EC 50 ) were calculated. Afterwards total mRNA was extracted from the IMA segments. Vascular gene expression of ANGPTL2 and p21 (senescence markers), and CD68 and PAI‐1 (inflammatory markers) were assessed by RT‐qPCR. In parallel, single‐cell RNA sequencing was performed in IMA segments from two age‐matched male patients obtained either during elective (stable CAD) or emergency (unstable CAD, with numerous risk factors) procedures, and differential gene expression was specifically analyzed in vascular EC. Endothelium‐dependent relaxations were characterized by E max (56±7 %, [18–100%], n=12) and pD 2 (‐log EC 50 : 6.9±0.1 [5.8–7.3], n=12). Patients were divided into 2 groups according to their E max (< or > to 50%) to define low and high endothelial function; vascular gene expression of the 4 senescence and inflammatory markers were similar between the two groups, demonstrating that global arterial wall senescence and inflammation did not distinguish severity of endothelial dysfunction. We then used single‐cell mRNA sequencing and analysed the unbiased differential gene expression specifically in vascular EC. From the total IMA cellular counts, EC represented ~2%. Nine genes were identified that were differentially overexpressed in EC from unstable CAD patient that have been associated with senolytic drug targets and cardiovascular diseases (Table ), potentially attesting to the severity of endothelial dysfunction and CAD. In conclusion, unlike total arterial wall mRNA quantification, unbiased single‐cell mRNA sequencing identified differentially upregulated endothelial pathways that may contribute to the severity of the CAD by inducing precocious endothelial dysfunction and senescence.Top genes differentially expressed in endothelial cells between a stable and unstable CAD patient. Percentages represent the percent of endothelial cells expressing the gene in each patient dataset. P‐values are Bonferroni corrected.Stable CAD patient Unstable CAD patient p‐value Gene Associated CVD disorder or drug target0.0% 41.7% 0.00061 TGFB2 Atrial fibrillation0.0% 41.7% 0.00061 SQLE Statins2.9% 58.3% 0.00090 RPPH1 Quercetin (senolytic drug)7.1% 66.7% 0.00339 ARL14EP Systolic blood pressure25.7% 100.0% 0.00914 RPL17 Myocardial ischemia17.1% 83.3% 0.01556 IGFBP7 Ruptured aneurysm0.0% 33.3% 0.01699 TMEM8B Heart valve disorders0.0% 33.3% 0.01699 ZNF675 Congestive heart failure8.6% 66.7% 0.04848 SELL Vaso‐occlusive crisis

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