Vesicular MicroRNA as Potential Biomarkers of Viral Rebound
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Subjects
2.2. Quantitation of HIV-1 RNA, CD4 and CD8 T Lymphocytes
2.3. Purification of Extracellular Vesicles
2.4. EV Flow Cytometry Analysis
2.5. MicroRNA Quantification
2.6. Transmission Electron Microscopy
2.7. Statistical Analysis
3. Results
3.1. HIV-1 Replication Could Be Induces the Production of Large EVs
3.2. MicroRNA Content of Large versus Small EVs
3.3. Correlation between EV MicroRNA Content and Demographic/Clinical Parameters
3.4. Principal Component Analysis of the EV Measurement/Viral Replication Association
3.5. MicroRNA 29a, 146a, and 155 Copies per Small EV and Mir-155 Copies in Large EV as Potential Biomarkers of Viral Rebound
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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Control (n = 60) | HIV+ (n = 235) | p-Value | HIV+ | HIV+ Viral Load Detectable | |||||
---|---|---|---|---|---|---|---|---|---|
Viremic (n = 85) | ART > 6 Months, Viral Load Undetectable (n = 128) | p-Value | ART-Naïve (n = 17) | ART-Treated (n = 68) | p-Value | ||||
Male, n (%) | 14 (23.3) | 68 (28.9) | 0.3880 | 28 (32.9) | 31 (24.2) | 0.1636 | 6 (35.3) | 22 (32.4) | 0.8175 |
Female sex workers: n (%) | 96 (40.9) | 30 (35.3) | 63 (49.2) | 0.1208 | 2 (11.8) | 28 (41.2) | 0.0536 | ||
Men who have sex with men: n (%) | 40 (17.0) | 19 (22.3) | 20 (15.6) | 4 (23.5) | 15 (22.1) | ||||
Age (y) | 27 | 36 | <0.0001 | 35 | 38 | 0.0553 | 37 | 35 | 0.9577 |
(22–32) | (30–44) | (30–42) | (32–45) | (27–4) | (30–42) | ||||
<20 | 3 (5.0) | 5 (2.1) | <0.0001 | 2 (2.4) | 2 (1.6) | 0.2670 | 1 (5.9) | 1 (1.5) | 0.4993 |
20–29 | 34 (56.7) | 37 (15.7) | 17 (20.0) | 16 (12.5) | 4 (23.5) | 13 (19.1) | |||
30–39 | 19 (31.7) | 94 (40.0) | 37 (43.5) | 49 (38.3) | 5 (29.4) | 32 (47.0) | |||
40–49 | 4 (6.6) | 70 (29.8) | 20 (23.5) | 47 (36.7) | 5 (29.4) | 15 (22.1) | |||
≥ 50 | 29 (12.3) | 9 (10.6) | 14 (10.9) | 2 (11.8) | 7 (10.3) | ||||
HIV duration (month) | NA | 36 (14–117) | 31 (8–72) | 55 (24–120) | 0.0313 | 8 (1–72) | 36 (12–72) | 0.9891 | |
CD4 T cells/µL | 992 (794–1276) | 466 (330–696) | <0.0001 | 382 (213–561) | 513 (386–755) | <0.0001 | 583 (318–742) | 354 (188–507) | 0.0860 |
CD8 T cells/µL | 584 (447–715) | 770 (543–1089) | <0.0001 | 841 (573–1049) | 736 (536–1093) | 0.6081 | 794 (570–1036) | 848 (544–1016) | 0.7852 |
CD4/CD8 | 1.8 (1.4–2.1) | 0.6 (0.4–1.0) | <0.0001 | 0.5 (0.3–0.8) | 0.7 (0.5–1.0) | <0.0001 | 0.6 (0.4–1.0) | 0.4 (0.3–0.7) | 0.0185 |
ART, n (%) | NA | 206 (87.7%) | 68 (80.0%) | NA | NA | NA | |||
ART duration (month) | NA | 34 (13–85) | 24 (8–62) | 38 (21–96) | 0.0231 | NA | 24 (8–62) | ||
Undetectable HIV viral load (<20 copies/mL), n (%) | NA | 150 (63.8) | NA | NA | NA | NA | |||
HIV-1 viral load (copies/mL) | NA | 30,032 | 30,032 | NA | 17,330 | 1446 | |||
NA | (108–33,978) | (108–33,978) | NA | (3,032–39,416) | (82–24,578) | 0.2958 |
Group Used as Control | ||||||
---|---|---|---|---|---|---|
HIV-Negative | ART-Naïve, Undetectable Viral Load | Reference Patients | ||||
AUC (95% CI) | p-Value | AUC (95% CI) | p-Value | AUC (95% CI) | p-Value | |
miR-29a copies, large EVs | 0.52 (0.43–0.62) | 0.6006 | 0.63 (0.47–0.78) | 0.1548 | 0.58 (0.38–0.77) | 0.4274 |
miR-29a copies, small EVs | 0.71 * (0.63–0.80) | <0.0001 | 0.60 (0.45–0.76) | 0.2686 | 0.50 (0.35–0.65) | 0.9600 |
miR-29a copies per large EV | 0.65 (0.56–0.74) | 0.0016 | 0.50 (0.31–0.69) | 0.9911 | 0.54 (0.31–0.76) | 0.7099 |
miR-29a copies per small EV | 0.80 (0.73–0.88) | <0.0001 | 0.88 (0.49–0.97) | <0.0001 | 0.73 (0.55–0.90) | 0.0255 |
miR-146a copies, large EVs | 0.54 (0.44–0.63) | 0.4420 | 0.72 * (0.61–0.83) | 0.0133 | 0.60 (0.43–0.78) | 0.2914 |
miR-146a copies, small EVs | 0.81 (0.74–0.88) | <0.0001 | 0.63 (0.52–0.75) | 0.1348 | 0.66 (0.48–0.83) | 0.1082 |
miR-146a copies per large EV | 0.56 (0.46–0.65) | 0.2285 | 0.62 (0.45–0.80) | 0.1695 | 0.54 (0.34–0.74) | 0.6801 |
miR-146a copies per small EV | 0.89 (0.83–0.94) | <0.0001 | 0.68 (0.55–0.81) | 0.0502 | 0.77 (0.61–0.93) | 0.0054 |
miR-155 copies, large EVs | 0.51 (0.41–0.60) | 0.8914 | 0.80 * (0.70–0.90) | 0.0007 | 0.76 (0.63– 0.90) | 0.0084 |
miR-155 copies, small EVs | 0.63 (0.54–0.72) | 0.0093 | 0.52 (0.35–0.69) | 0.8010 | 0.61 (0.46–0.75) | 0.2891 |
miR-155 copies per large EV | 0.68 * (0.59–0.77) | 0.0002 | 0.62 (0.45–0.78) | 0.1674 | 0.52 (0.29–0.75) | 0.8367 |
miR-155 copies per small EV | 0.76 (0.68–0.85) | <0.0001 | 0.97 (0.93–100) | <0.0001 | 0.87 (0.77–0.97) | 0.0006 |
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Bazié, W.W.; Boucher, J.; Traoré, I.T.; Kania, D.; Somé, D.Y.; Alary, M.; Gilbert, C. Vesicular MicroRNA as Potential Biomarkers of Viral Rebound. Cells 2022, 11, 859. https://doi.org/10.3390/cells11050859
Bazié WW, Boucher J, Traoré IT, Kania D, Somé DY, Alary M, Gilbert C. Vesicular MicroRNA as Potential Biomarkers of Viral Rebound. Cells. 2022; 11(5):859. https://doi.org/10.3390/cells11050859
Chicago/Turabian StyleBazié, Wilfried Wenceslas, Julien Boucher, Isidore Tiandiogo Traoré, Dramane Kania, Diane Yirgnur Somé, Michel Alary, and Caroline Gilbert. 2022. "Vesicular MicroRNA as Potential Biomarkers of Viral Rebound" Cells 11, no. 5: 859. https://doi.org/10.3390/cells11050859