Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling
Abstract
:1. Background
2. Methods
2.1. Study Population
2.2. Definition of Risk Factors
2.3. Imaging Analysis
2.4. Biological Samples and ECFC Growth
2.5. Assessment of ECFCs Phenotype
2.6. Culture of ECFCs in 3D Mini Vessels
2.7. Statistical Analysis
3. Results
3.1. Baseline Characterisation of ECFCs
3.2. Spontaneous Growth and Effect of Clinical Characteristics
3.3. ECFC Phenotype Reflects the Coronary Artery Disease State of the Patient from Which They Were Derived
3.3.1. Functional Imprint of Coronary Artery Disease
3.3.2. Molecular ECFC Phenotype Associated with Coronary Artery Disease Burden
3.4. ECFCs Grown in 3D Mini Vessels
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristic | Whole Cohort (n = 828) | ECFC Growth (n = 178) | No ECFC Growth (n = 650) | p Value |
---|---|---|---|---|
Age, mean (SD) | 60.9 (11.9) | 62.1 (11.9) | 60.6 (11.9) | 0.14 |
Female, n (%) | 379 (45.8) | 92 (51.7) | 287 (44.2) | 0.07 |
Hypertension, n (%) | 319 (38.5) | 81 (45.5) | 238 (36.7) | 0.03 |
Diabetes mellitus, n (%) | 69 (8.3) | 13 (7.3) | 56 (9.4) | 0.58 |
Hypercholesterolaemia, n (%) | 476 (57.5) | 103 (57.9) | 373 (57.4) | 0.91 |
Significant smoking history, n (%) | 190 (22.9) | 43 (24.2) | 147 (22.6) | 0.67 |
Current smoker, n (%) | 59 (7.1) | 10 (5.6) | 49 (7.5) | 0.38 |
BMI, mean, (SD) | 27.1 (5.0) | 27.3 (5.1) | 26.3 (4.8) | 0.02 |
BMI >30 kg/m2, n (%) | 191 (23.1) | 30 (16.9) | 161 (24.8) | 0.03 |
Significant family history CAD, n (%) | 163 (19.7) | 29 (16.3) | 134 (20.6) | 0.20 |
SMuRFs—mean, (SD) | 1.27 (0.96) | 1.35 (0.87) | 1.25 (0.98) | 0.24 |
0 SMuRFs, n (%) | 185 (22.3) | 27 (15.2) | 158 (24.3) | <0.01 |
Coronary artery calcium score—median, (IQR) | 10 (0–177) | 7.97 (0–140) | 11 (0-193) | 0.67 |
Calcified plaque present (CACS > 0) | 494 (59.7) | 109 (61.2) | 385 (59.2) | 0.63 |
Gensini score—median, IQR | 4 (0–13) | 3 (0–10) | 4 (0–14) | 0.27 |
CAD present (Gensini > 0) | 547 (66.1) | 119 (66.9) | 428 (65.9) | 0.80 |
Obstructive disease > 50% stenosis—n, (%) | 165 (19.9) | 25 (14.0) | 140 (21.5) | 0.03 |
Medication use: | ||||
Anti-coagulant—n, (%) | 76 (9.2) | 18 (10.1) | 58 (8.9) | 0.63 |
Anti-platelet agent—n, (%) | 145 (17.5) | 32 (18.0) | 113 (17.4) | 0.85 |
Statin—n, (%) | 282 (34.1) | 66 (37.1) | 216 (33.2) | 0.34 |
Beta-blocker—n, (%) | 122 (14.7) | 21 (11.8) | 101 (15.6) | 0.21 |
ACE/ARB agent—n, (%) | 256 (30.9) | 63 (35.4) | 193 (29.7) | 0.15 |
Target (n CAD− vs. n CAD+) | CAD− (mean ± SEM) | CAD+ (mean ± SEM) | p Value |
---|---|---|---|
NOX2: - CACS (14 vs. 17) - Gensini (6 vs. 19) | 1.00 ± 0.21 1.00 ± 0.26 | 0.93 ± 0.23 1.19 ± 0.23 | 0.92 0.68 |
NOX4: - CACS (11 vs. 14) - Gensini (6 vs. 19) | 1.00 ± 0.27 1.00 ± 0.47 | 1.48 ± 0.36 1.26 ± 0.26 | 0.30 0.63 |
eNOS:- CACS (14 vs. 16) - Gensini (9 vs. 21) | 1.00 ± 0.30 1.00 ± 0.34 | 1.34 ± 0.45 1.77 ± 0.49 | 0.54 0.34 |
AKT: - CACS (13 vs. 18) - Gensini (8 vs. 23) | 1.00 ± 0.47 1.00 ± 0.60 | 0.93 ± 0.27 0.70 ± 0.18 | 0.90 0.53 |
pAKT: - CACS (13 vs. 18) - Gensini (8 vs. 23) | 1.00 ± 0.17 1.00 ± 0.21 | 1.43 ± 0.37 1.09 ± 0.26 | 0.31 0.84 |
pAKT/AKT: - CACS (13 vs. 18) - Gensini (8 vs. 23) | 1.00 ± 0.24 1.00 ± 0.30 | 0.66 ± 0.13 0.84 ± 0.16 | 0.16 0.62 |
ERK:- CACS (12 vs. 18) - Gensini (7 vs. 23) | 1.00 ± 0.13 1.00 ± 0.18 | 1.36 ± 0.25 1.20 ± 0.19 | 0.28 0.60 |
pERK: - CACS (12 vs. 18) - Gensini (7 vs. 23) | 1.00 ± 0.41 1.00 ± 0.63 | 1.82 ± 0.67 1.69 ± 0.55 | 0.31 0.52 |
pERK/ERK: - CACS (12 vs. 18) - Gensini (7 vs. 23) | 1.00 ± 0.35 1.00 ± 0.50 | 1.26 ± 0.46 1.26 ± 0.39 | 0.69 0.73 |
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Besnier, M.; Finemore, M.; Yu, C.; Kott, K.A.; Vernon, S.T.; Seebacher, N.A.; Genetzakis, E.; Furman, A.; Tang, O.; Davis, R.L.; et al. Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling. Antioxidants 2021, 10, 1547. https://doi.org/10.3390/antiox10101547
Besnier M, Finemore M, Yu C, Kott KA, Vernon ST, Seebacher NA, Genetzakis E, Furman A, Tang O, Davis RL, et al. Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling. Antioxidants. 2021; 10(10):1547. https://doi.org/10.3390/antiox10101547
Chicago/Turabian StyleBesnier, Marie, Meghan Finemore, Christine Yu, Katharine A. Kott, Stephen T. Vernon, Nicole A. Seebacher, Elijah Genetzakis, Anamarija Furman, Owen Tang, Ryan L. Davis, and et al. 2021. "Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling" Antioxidants 10, no. 10: 1547. https://doi.org/10.3390/antiox10101547
APA StyleBesnier, M., Finemore, M., Yu, C., Kott, K. A., Vernon, S. T., Seebacher, N. A., Genetzakis, E., Furman, A., Tang, O., Davis, R. L., Hansen, T., Psaltis, P. J., Bubb, K. J., Wise, S. G., Grieve, S. M., Di Bartolo, B. A., & Figtree, G. A. (2021). Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling. Antioxidants, 10(10), 1547. https://doi.org/10.3390/antiox10101547