Exploring the Interplay Between Glycated Albumin, AGEs, and Inflammation in Old Patients with CKD
Abstract
1. Introduction
2. Methods
2.1. Patients and Study Design
2.2. Glycated Albumin Assay
2.3. AGEs Quantification
2.4. Quantification of sRAGE, esRAGE and cRAGE
2.5. Interleukins Quantification
2.6. Statistical Analysis
3. Results
3.1. General Characteristics of the Population
3.2. Products of Glycation and Their Receptors
3.3. Correlations of Glycated Albumin
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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Overall Population | Diabetics | Non-Diabetics | p-Value * | |
---|---|---|---|---|
n = 122 | n = 67 | n = 55 | ||
General characteristics | ||||
Age, years | 77.7 ± 11.3 | 78.8 ± 7.6 | 76.4 ± 14.4 | 0.240 |
Sex (m/f,%) | 72/28 | 76/24 | 68/32 | 0.309 |
BMI, Kg/m2 | 27.8 ± 4.7 | 28.7 ± 5.2 | 26.7 ± 4.0 | 0.178 |
eGFR, mL/min/1.73 m2 | 24 ± 11 | 27 ± 11 | 22 ± 10 | 0.008 |
Proteinuria, mg/24 h | 525 (1049) | 600 (1569) | 435 (990) | 0.301 |
Serum albumin, g/dL | 4.05 ± 0.35 | 4.03 ± 0.37 | 4.07 ± 0.34 | 0.457 |
HbA1c, mmol/mol | 47.2 ± 11.1 | 51.5 ± 10.8 | 38.3 ± 4.3 | <0.0001 |
Glycemia, mg/dL | 116 ± 38 | 137 ± 39 | 91 ± 10 | 0.0084 |
Total cholesterol, mg/dL | 168 ± 36 | 165 ± 35 | 170 ± 37 | 0.483 |
HDL cholesterol, mg/dL | 53 ± 18 | 52 ± 15 | 55 ± 21 | 0.324 |
Triglycerides, mg/dL | 126 ± 54 | 133 ± 56 | 118 ± 50 | 0.126 |
Inflammatory markers | ||||
CRP, mg/dL | 0.215 (0.315) | 0.240 (0.380) | 0.200 (0.280) | 0.142 |
TNFα, pg/mL | 13.7 (10.2) | 13.9 (10.1) | 13.7 (10.1) | 0.660 |
IL-6, pg/mL | 3.1 (4.0) | 3.4 (4.0) | 3.0 (3.8) | 0.238 |
MCP-1, pg/mL | 408 (218) | 403 (207) | 408 (241) | 0.884 |
Overall Population | Diabetics | Non-Diabetics | p-Value * | |
---|---|---|---|---|
GA, % | 19.7 (6.2) | 22.0 (7.1) | 17.5 (5.4) | 0.0001 |
AGEs, arbitrary units | 3032 ± 789 | 2931 ± 763 | 3156 ± 809 | 0.118 |
sRAGEs, pg/mL | 1895 (1370) | 1876 (1178) | 1935 (1912) | 0.316 |
esRAGEs, pg/mL | 542 (354) | 527 (346) | 562 (387) | 0.204 |
cRAGEs, pg/mL | 1341 (1048) | 1300 (786) | 1347 (1375) | 0.341 |
Overall Population | Diabetics | Non-Diabetics | |
---|---|---|---|
Kidney function | |||
GA vs. eGFR | ρ = 0.189; p = 0.037 | ρ = 0.107; p = 0.385 | ρ = 0.043; p = 0.752 |
GA vs. Proteinuria | ρ = 0.056; p = 0.769 | ρ = −0.004; p = 0.978 | ρ = −0.104; p = 0.418 |
Metabolic parameters | |||
GA vs. HbA1c | ρ = 0.525; p ≤ 0.0001 | ρ = 0.434; p = 0.0008 | ρ = 0.174; p = 0.377 |
GA vs. serum albumin | ρ = −0.031; p = 0.735 | ρ = −0.146; p = 0.241 | ρ = 0.194; p = 0.154 |
Glycosilation products | |||
GA vs. AGEs | ρ = 0.028; p = 0.535 | ρ = 0.144; p = 0.243 | ρ = 0.185; p = 0.174 |
GA vs. sRAGES | ρ = −0.074; p = 0.418 | ρ = 0.101; p = 0.412 | ρ = −0.171; p = 0.208 |
GA vs. cRAGES | ρ = −0.059; p = 0.518 | ρ = 0.126; p = 0.310 | ρ = −0.167; p = 0.219 |
GA vs. esRAGES | ρ = −0.130; p = 0.155 | ρ = −0.031; p = 0.798 | ρ = −0.123; p = 0.368 |
Inflammatory markers | |||
GA vs. CRP | ρ = 0.072; p = 0.427 | ρ = 0.411; p = 0.413 | ρ = 0.056; p = 0.683 |
GA vs. TNFα | ρ = −0.060; p = 0.531 | ρ = 0.260; p = 0.838 | ρ = −0.272; p = 0.600 |
GA vs. IL-6 | ρ = −0.048; p = 0.614 | ρ = −0.052; p = 0.684 | ρ = −0.226; p = 0.125 |
GA vs. MCP-1 | ρ = −0.072; p = 0.489 | ρ = −0.009; p = 0.946 | ρ = −0.196; p = 0.247 |
Count | R2 | Adj R2 | F | p-Value | |
---|---|---|---|---|---|
Overall model | 122 | 0.101 | 0.080 | 4.825 | 0.010 |
Regression coefficients | |||||
Coeff | Std. Error | Std Coeff. | t-Value | p-Value | |
Intercept | 10.762 | 3.786 | 10.762 | 2.843 | 0.0056 |
eGFR | 0.034 | 0.080 | 0.044 | 0.420 | 0.6759 |
HbA1c | 0.222 | 0.078 | 0.303 | 2.861 | 0.0053 |
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Vettoretti, S.; Caldiroli, L.; Molinari, P.; Villa, A.; Corsi Romanelli, M.M.; Vianello, E.; Dozio, E.; Genovesi, S. Exploring the Interplay Between Glycated Albumin, AGEs, and Inflammation in Old Patients with CKD. Metabolites 2025, 15, 515. https://doi.org/10.3390/metabo15080515
Vettoretti S, Caldiroli L, Molinari P, Villa A, Corsi Romanelli MM, Vianello E, Dozio E, Genovesi S. Exploring the Interplay Between Glycated Albumin, AGEs, and Inflammation in Old Patients with CKD. Metabolites. 2025; 15(8):515. https://doi.org/10.3390/metabo15080515
Chicago/Turabian StyleVettoretti, Simone, Lara Caldiroli, Paolo Molinari, Amanda Villa, Massimiliano M. Corsi Romanelli, Elena Vianello, Elena Dozio, and Simonetta Genovesi. 2025. "Exploring the Interplay Between Glycated Albumin, AGEs, and Inflammation in Old Patients with CKD" Metabolites 15, no. 8: 515. https://doi.org/10.3390/metabo15080515
APA StyleVettoretti, S., Caldiroli, L., Molinari, P., Villa, A., Corsi Romanelli, M. M., Vianello, E., Dozio, E., & Genovesi, S. (2025). Exploring the Interplay Between Glycated Albumin, AGEs, and Inflammation in Old Patients with CKD. Metabolites, 15(8), 515. https://doi.org/10.3390/metabo15080515