The Possible Effect of β-Blocker Use on the Circulating MMP-2/TIMP-2 System in Patients with Chronic Kidney Disease on Conservative Treatment
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Participants
2.2. Laboratory Methods
2.3. Statistical Analysis
3. Results
3.1. The Characteristics of Patients with CKD Treated and Not Treated with β-Blockers
3.2. The Relationship between the Use of β-Blockers and MMP-2 and TIMP-2 Concentrations in the Whole Group of Patients with CKD
3.3. The Effect of β-Blocker Treatment on MMP-2 and TIMP-2 Levels and the MMP-2/TIMP-2 Ratio in Patients with CKD
3.4. The Effect of β-Blocker Treatment on Proinflammatory Cytokines and the Marker of Oxidative Stress—Cu/Zn SOD— Levels
3.5. The Factors Affecting the MMP-2/TIMP-2 System in the β-Blockers (+) Group and β-Blockers (−) Group
3.6. The Effect of Calcium Channel Antagonists (CCA) on the MMP-2/TIMP-2 System, Oxidative Status, and Proinflammatory Cytokines in the β-Blockers (+) Group and β-Blockers (−) Group
3.7. Variables Independently Predicting the MMP-2/TIMP-2 System in the β-Blockers Group (+) and β-Blockers (−) Group
4. Discussion
Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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β-Blockers (+), n = 23 | β-Blockers (−), n = 27 | p Value | |
---|---|---|---|
Age, years | 53.43 ± 12.70 | 53.48 ± 17.74 | 0.897 |
Male sex, % | 57 | 59 | 0.886 |
eGFR, mL/min/1.73 m2 | 17.5 (9.7–42.6) | 18.7 (12.8–33.8) | 0.535 |
CKD, stage 1, % | 0 | 4 | 0.332 |
CKD, stage 2, % | 17 | 15 | 0.849 |
CKD, stage 3, % | 17 | 19 | 0.856 |
CKD, stage 4, % | 17 | 19 | 0.856 |
CKD, stage 5, % | 48 | 42 | 0.673 |
SBP, mm Hg | 136.90 ± 11.23 | 134.23 ± 14.26 | 0.471 |
DBP, mm Hg | 88.57 ± 7.27 | 84.62 ± 7.20 | 0.695 |
Heart rate, bpm | 73.3 ± 8.9 | 68.8 ± 9.5 | 0.562 |
RBC, 1012/L | 3.63 ± 0.72 | 3.45 ± 0.57 | 0.334 |
Hemoglobin, g/dL | 11.13 ± 2.35 | 10.70 ± 1.98 | 0.490 |
WBC, 109/L | 6.41 ± 1.95 | 6.49 ± 2.62 | 0.560 |
Glucose, mg/dL | 90.0 (81.0–100.0) | 93.5 (85.0–117.0) | 0.474 |
Albumin, g/dL | 3.12 ± 0.71 | 3.07 ± 0.77 | 0.814 |
Total protein, g/dL | 6.10 ± 1.22 | 6.10 ± 1.17 | 0.999 |
Total cholesterol, mg/dL | 208.0 (175.0–223.0) | 190.0 (170.0–219.0) | 0.338 |
Triglycerides, mg/dL | 170 (115–265) | 152 (80–291) | 0.448 |
Cardiovascular disease, % | 48 | 37 | 0.432 |
Smokers, % | 9 | 19 | 0.316 |
Diabetic nephropathy, % | 37 | 30 | 0.652 |
Glomerulonephritis, % | 37 | 47 | 0.475 |
Polycystic kidney disease, % | 17 | 19 | 0.854 |
Hypertensive nephropathy, % | 9 | 4 | 0.234 |
Diuretics, % | 26 | 15 | 0.166 |
Converting enzyme inhibitors/sartans % | 65 | 52 | 0.176 |
Calcium channel antagonists, % | 74 | 52 | 0.110 |
α-adrenoceptor antagonists, % | 13 | 4 | 0.123 |
Statin, % | 9 | 19 | 0.316 |
β-Blockers (+) | β-Blockers (−) | |||
---|---|---|---|---|
MMP-2 | TIMP-2 | MMP-2 | TIMP-2 | |
Sex, male = 1 | R = 0.031 NS | R = 0.008 NS | χ2 = 4.518 p = 0.034 | χ2 = 2.706 NS |
SBP | R = 0.163 NS | R = 0.463 p = 0.035 | R = 0.180 NS | R = 0.150 NS |
RBC | R = −0.500 p = 0.015 | R = −0.509 p = 0.013 | R = −0.142 NS | R = −0.075 NS |
Hemoglobin | R = −0.510 p = 0.013 | R = −0.556 p = 0.006 | R = −0.102 NS | R = −0.046 NS |
Interleukin 6 | R = 0.458 p = 0.028 | R = 0.390 p = 0.066 | R = 0.101 NS | R = 0.061 NS |
TNF-α | R = 0.419 p = 0.046 | R = 0.230 NS | R = 0.042 NS | R = 0.062 NS |
Cu/Zn SOD | R = −0.066 NS | R = 0.077 NS | R = 0.382 p = 0.049 | R = 0.549 p = 0.003 |
Albumin | R = −0.586 p = 0.002 | R = −0.290 NS | R = −0.471 p = 0.030 | R = −0.300 NS |
Total protein | R = −0.544 p = 0.008 | R = −0.082 NS | R = −0.273 NS | R = −0.056 NS |
Diabetic nephropathy | χ2 = 0.016 NS | χ2 = 0.020 NS | χ2 = 6.497 p = 0.011 | χ2 = 6.618 p = 0.010 |
Glomerulonephritis | χ2 = 4.422 p = 0.035 | χ2 = 2.782 NS | χ2 = 6.253 p = 0.010 | χ2 = 6.367 p = 0.012 |
Calcium channel antagonists | χ2 = 6.199 p = 0.013 | χ2 = 7.475 p = 0.006 | χ2 = 0.514 NS | χ2 = 0.019 NS |
Independent Variable | Regression Coefficient (β) | Standard Error | p Values | |
---|---|---|---|---|
MMP-2 | albumin | −0.553 | 0.181 | <0.001 |
RBC | −0.512 | 0.178 | 0.016 | |
TIMP-2 * | MMP-2 | 0.740 | 0.132 | <0.001 |
SBP | 0.297 | 0.132 | 0.038 |
Independent Variable | Regression Coefficient (β) | Standard Error | p Values | |
---|---|---|---|---|
MMP-2 | Cu/Zn SOD | 0.734 | 0.208 | 0.005 |
albumin | −0.682 | 0.242 | 0.018 | |
TIMP-2 * | MMP-2 | 0.739 | 0.113 | <0.001 |
glomerulonephritis | −0.264 | 0.112 | 0.028 |
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Kopańko, M.; Zabłudowska, M.; Pawlak, D.; Sieklucka, B.; Krupa, A.; Sokołowska, K.; Ziemińska, M.; Pawlak, K. The Possible Effect of β-Blocker Use on the Circulating MMP-2/TIMP-2 System in Patients with Chronic Kidney Disease on Conservative Treatment. J. Clin. Med. 2024, 13, 1847. https://doi.org/10.3390/jcm13071847
Kopańko M, Zabłudowska M, Pawlak D, Sieklucka B, Krupa A, Sokołowska K, Ziemińska M, Pawlak K. The Possible Effect of β-Blocker Use on the Circulating MMP-2/TIMP-2 System in Patients with Chronic Kidney Disease on Conservative Treatment. Journal of Clinical Medicine. 2024; 13(7):1847. https://doi.org/10.3390/jcm13071847
Chicago/Turabian StyleKopańko, Magdalena, Magdalena Zabłudowska, Dariusz Pawlak, Beata Sieklucka, Anna Krupa, Katarzyna Sokołowska, Marta Ziemińska, and Krystyna Pawlak. 2024. "The Possible Effect of β-Blocker Use on the Circulating MMP-2/TIMP-2 System in Patients with Chronic Kidney Disease on Conservative Treatment" Journal of Clinical Medicine 13, no. 7: 1847. https://doi.org/10.3390/jcm13071847
APA StyleKopańko, M., Zabłudowska, M., Pawlak, D., Sieklucka, B., Krupa, A., Sokołowska, K., Ziemińska, M., & Pawlak, K. (2024). The Possible Effect of β-Blocker Use on the Circulating MMP-2/TIMP-2 System in Patients with Chronic Kidney Disease on Conservative Treatment. Journal of Clinical Medicine, 13(7), 1847. https://doi.org/10.3390/jcm13071847