Systemic Inflammation Precedes Microalbuminuria in Diabetes
Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olm...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Florian G. Scurt [verfasserIn] Jan Menne [verfasserIn] Sabine Brandt [verfasserIn] Anja Bernhardt [verfasserIn] Peter R. Mertens [verfasserIn] Hermann Haller [verfasserIn] Christos Chatzikyrkou [verfasserIn] Sadayoshi Ito [verfasserIn] Josphe L. Izzo [verfasserIn] Andrzeij Januszewicz [verfasserIn] Shigerhiro Katayama [verfasserIn] Albert Mimram [verfasserIn] Ton J. Rabelink [verfasserIn] Eberhard Ritz [verfasserIn] Luis M. Ruilope [verfasserIn] Lars C. Rump [verfasserIn] Giancarlo Viberti [verfasserIn] Herrman Haller [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Übergeordnetes Werk: |
In: Kidney International Reports - Elsevier, 2016, 4(2019), 10, Seite 1373-1386 |
|---|---|
| Übergeordnetes Werk: |
volume:4 ; year:2019 ; number:10 ; pages:1373-1386 |
| Links: |
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| DOI / URN: |
10.1016/j.ekir.2019.06.005 |
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| Katalog-ID: |
DOAJ047928832 |
|---|
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| 245 | 1 | 0 | |a Systemic Inflammation Precedes Microalbuminuria in Diabetes |
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| 520 | |a Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation | ||
| 653 | 0 | |a Diseases of the genitourinary system. Urology | |
| 700 | 0 | |a Jan Menne |e verfasserin |4 aut | |
| 700 | 0 | |a Sabine Brandt |e verfasserin |4 aut | |
| 700 | 0 | |a Anja Bernhardt |e verfasserin |4 aut | |
| 700 | 0 | |a Peter R. Mertens |e verfasserin |4 aut | |
| 700 | 0 | |a Hermann Haller |e verfasserin |4 aut | |
| 700 | 0 | |a Christos Chatzikyrkou |e verfasserin |4 aut | |
| 700 | 0 | |a Sadayoshi Ito |e verfasserin |4 aut | |
| 700 | 0 | |a Josphe L. Izzo |e verfasserin |4 aut | |
| 700 | 0 | |a Andrzeij Januszewicz |e verfasserin |4 aut | |
| 700 | 0 | |a Shigerhiro Katayama |e verfasserin |4 aut | |
| 700 | 0 | |a Jan Menne |e verfasserin |4 aut | |
| 700 | 0 | |a Albert Mimram |e verfasserin |4 aut | |
| 700 | 0 | |a Ton J. Rabelink |e verfasserin |4 aut | |
| 700 | 0 | |a Eberhard Ritz |e verfasserin |4 aut | |
| 700 | 0 | |a Luis M. Ruilope |e verfasserin |4 aut | |
| 700 | 0 | |a Lars C. Rump |e verfasserin |4 aut | |
| 700 | 0 | |a Giancarlo Viberti |e verfasserin |4 aut | |
| 700 | 0 | |a Herrman Haller |e verfasserin |4 aut | |
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10.1016/j.ekir.2019.06.005 doi (DE-627)DOAJ047928832 (DE-599)DOAJc233dfea8bc24170947f739946206627 DE-627 ger DE-627 rakwb eng RC870-923 Florian G. Scurt verfasserin aut Systemic Inflammation Precedes Microalbuminuria in Diabetes 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation Diseases of the genitourinary system. Urology Jan Menne verfasserin aut Sabine Brandt verfasserin aut Anja Bernhardt verfasserin aut Peter R. Mertens verfasserin aut Hermann Haller verfasserin aut Christos Chatzikyrkou verfasserin aut Sadayoshi Ito verfasserin aut Josphe L. Izzo verfasserin aut Andrzeij Januszewicz verfasserin aut Shigerhiro Katayama verfasserin aut Jan Menne verfasserin aut Albert Mimram verfasserin aut Ton J. Rabelink verfasserin aut Eberhard Ritz verfasserin aut Luis M. Ruilope verfasserin aut Lars C. Rump verfasserin aut Giancarlo Viberti verfasserin aut Herrman Haller verfasserin aut In Kidney International Reports Elsevier, 2016 4(2019), 10, Seite 1373-1386 (DE-627)881695580 (DE-600)2887223-X 24680249 nnns volume:4 year:2019 number:10 pages:1373-1386 https://doi.org/10.1016/j.ekir.2019.06.005 kostenfrei https://doaj.org/article/c233dfea8bc24170947f739946206627 kostenfrei http://www.sciencedirect.com/science/article/pii/S246802491931383X kostenfrei https://doaj.org/toc/2468-0249 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 4 2019 10 1373-1386 |
| spelling |
10.1016/j.ekir.2019.06.005 doi (DE-627)DOAJ047928832 (DE-599)DOAJc233dfea8bc24170947f739946206627 DE-627 ger DE-627 rakwb eng RC870-923 Florian G. Scurt verfasserin aut Systemic Inflammation Precedes Microalbuminuria in Diabetes 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation Diseases of the genitourinary system. Urology Jan Menne verfasserin aut Sabine Brandt verfasserin aut Anja Bernhardt verfasserin aut Peter R. Mertens verfasserin aut Hermann Haller verfasserin aut Christos Chatzikyrkou verfasserin aut Sadayoshi Ito verfasserin aut Josphe L. Izzo verfasserin aut Andrzeij Januszewicz verfasserin aut Shigerhiro Katayama verfasserin aut Jan Menne verfasserin aut Albert Mimram verfasserin aut Ton J. Rabelink verfasserin aut Eberhard Ritz verfasserin aut Luis M. Ruilope verfasserin aut Lars C. Rump verfasserin aut Giancarlo Viberti verfasserin aut Herrman Haller verfasserin aut In Kidney International Reports Elsevier, 2016 4(2019), 10, Seite 1373-1386 (DE-627)881695580 (DE-600)2887223-X 24680249 nnns volume:4 year:2019 number:10 pages:1373-1386 https://doi.org/10.1016/j.ekir.2019.06.005 kostenfrei https://doaj.org/article/c233dfea8bc24170947f739946206627 kostenfrei http://www.sciencedirect.com/science/article/pii/S246802491931383X kostenfrei https://doaj.org/toc/2468-0249 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 4 2019 10 1373-1386 |
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10.1016/j.ekir.2019.06.005 doi (DE-627)DOAJ047928832 (DE-599)DOAJc233dfea8bc24170947f739946206627 DE-627 ger DE-627 rakwb eng RC870-923 Florian G. Scurt verfasserin aut Systemic Inflammation Precedes Microalbuminuria in Diabetes 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation Diseases of the genitourinary system. Urology Jan Menne verfasserin aut Sabine Brandt verfasserin aut Anja Bernhardt verfasserin aut Peter R. Mertens verfasserin aut Hermann Haller verfasserin aut Christos Chatzikyrkou verfasserin aut Sadayoshi Ito verfasserin aut Josphe L. Izzo verfasserin aut Andrzeij Januszewicz verfasserin aut Shigerhiro Katayama verfasserin aut Jan Menne verfasserin aut Albert Mimram verfasserin aut Ton J. Rabelink verfasserin aut Eberhard Ritz verfasserin aut Luis M. Ruilope verfasserin aut Lars C. Rump verfasserin aut Giancarlo Viberti verfasserin aut Herrman Haller verfasserin aut In Kidney International Reports Elsevier, 2016 4(2019), 10, Seite 1373-1386 (DE-627)881695580 (DE-600)2887223-X 24680249 nnns volume:4 year:2019 number:10 pages:1373-1386 https://doi.org/10.1016/j.ekir.2019.06.005 kostenfrei https://doaj.org/article/c233dfea8bc24170947f739946206627 kostenfrei http://www.sciencedirect.com/science/article/pii/S246802491931383X kostenfrei https://doaj.org/toc/2468-0249 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 4 2019 10 1373-1386 |
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10.1016/j.ekir.2019.06.005 doi (DE-627)DOAJ047928832 (DE-599)DOAJc233dfea8bc24170947f739946206627 DE-627 ger DE-627 rakwb eng RC870-923 Florian G. Scurt verfasserin aut Systemic Inflammation Precedes Microalbuminuria in Diabetes 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation Diseases of the genitourinary system. Urology Jan Menne verfasserin aut Sabine Brandt verfasserin aut Anja Bernhardt verfasserin aut Peter R. Mertens verfasserin aut Hermann Haller verfasserin aut Christos Chatzikyrkou verfasserin aut Sadayoshi Ito verfasserin aut Josphe L. Izzo verfasserin aut Andrzeij Januszewicz verfasserin aut Shigerhiro Katayama verfasserin aut Jan Menne verfasserin aut Albert Mimram verfasserin aut Ton J. Rabelink verfasserin aut Eberhard Ritz verfasserin aut Luis M. Ruilope verfasserin aut Lars C. Rump verfasserin aut Giancarlo Viberti verfasserin aut Herrman Haller verfasserin aut In Kidney International Reports Elsevier, 2016 4(2019), 10, Seite 1373-1386 (DE-627)881695580 (DE-600)2887223-X 24680249 nnns volume:4 year:2019 number:10 pages:1373-1386 https://doi.org/10.1016/j.ekir.2019.06.005 kostenfrei https://doaj.org/article/c233dfea8bc24170947f739946206627 kostenfrei http://www.sciencedirect.com/science/article/pii/S246802491931383X kostenfrei https://doaj.org/toc/2468-0249 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 4 2019 10 1373-1386 |
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10.1016/j.ekir.2019.06.005 doi (DE-627)DOAJ047928832 (DE-599)DOAJc233dfea8bc24170947f739946206627 DE-627 ger DE-627 rakwb eng RC870-923 Florian G. Scurt verfasserin aut Systemic Inflammation Precedes Microalbuminuria in Diabetes 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation Diseases of the genitourinary system. Urology Jan Menne verfasserin aut Sabine Brandt verfasserin aut Anja Bernhardt verfasserin aut Peter R. Mertens verfasserin aut Hermann Haller verfasserin aut Christos Chatzikyrkou verfasserin aut Sadayoshi Ito verfasserin aut Josphe L. Izzo verfasserin aut Andrzeij Januszewicz verfasserin aut Shigerhiro Katayama verfasserin aut Jan Menne verfasserin aut Albert Mimram verfasserin aut Ton J. Rabelink verfasserin aut Eberhard Ritz verfasserin aut Luis M. Ruilope verfasserin aut Lars C. Rump verfasserin aut Giancarlo Viberti verfasserin aut Herrman Haller verfasserin aut In Kidney International Reports Elsevier, 2016 4(2019), 10, Seite 1373-1386 (DE-627)881695580 (DE-600)2887223-X 24680249 nnns volume:4 year:2019 number:10 pages:1373-1386 https://doi.org/10.1016/j.ekir.2019.06.005 kostenfrei https://doaj.org/article/c233dfea8bc24170947f739946206627 kostenfrei http://www.sciencedirect.com/science/article/pii/S246802491931383X kostenfrei https://doaj.org/toc/2468-0249 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 4 2019 10 1373-1386 |
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Florian G. Scurt @@aut@@ Jan Menne @@aut@@ Sabine Brandt @@aut@@ Anja Bernhardt @@aut@@ Peter R. Mertens @@aut@@ Hermann Haller @@aut@@ Christos Chatzikyrkou @@aut@@ Sadayoshi Ito @@aut@@ Josphe L. Izzo @@aut@@ Andrzeij Januszewicz @@aut@@ Shigerhiro Katayama @@aut@@ Albert Mimram @@aut@@ Ton J. Rabelink @@aut@@ Eberhard Ritz @@aut@@ Luis M. Ruilope @@aut@@ Lars C. Rump @@aut@@ Giancarlo Viberti @@aut@@ Herrman Haller @@aut@@ |
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Scurt</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Systemic Inflammation Precedes Microalbuminuria in Diabetes</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. 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Florian G. Scurt Jan Menne Sabine Brandt Anja Bernhardt Peter R. Mertens Hermann Haller Christos Chatzikyrkou Sadayoshi Ito Josphe L. Izzo Andrzeij Januszewicz Shigerhiro Katayama Albert Mimram Ton J. Rabelink Eberhard Ritz Luis M. Ruilope Lars C. Rump Giancarlo Viberti Herrman Haller |
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systemic inflammation precedes microalbuminuria in diabetes |
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Systemic Inflammation Precedes Microalbuminuria in Diabetes |
| abstract |
Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation |
| abstractGer |
Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation |
| abstract_unstemmed |
Aim: The aim of the case-control study was to investigate if serum biomarkers indicative of vascular inflammation and endothelial dysfunction can predict the development of microalbuminuria in patients with diabetes mellitus type 2. Methods: Among participants enrolled in the ROADMAP (Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention) and observational follow-up (OFU) studies, a panel of 15 serum biomarkers was quantified from samples obtained at initiation of the study and tested for associations with the development of new-onset microalbuminuria during follow-up. A case-control study was conducted with inclusion of 172 patients with microalbuminuria and 188 matched controls. Nonparametric inferential, nonlinear regression, mediation, and bootstrapping statistical methods were used for the analysis. Results: The median follow-up time was 37 months. At baseline, mean concentrations of C-X-C motif chemokine ligand 16 (CXCL-16), transforming growth factor (TGF)–β1 and angiopoietin-2 were higher in patients with subsequent microalbuminuria. In the multivariate analysis, after adjustment for age, sex, body mass index, glycated hemoglobin, duration of diabetes, low-density lipoprotein (LDL), smoking status, blood pressure, baseline urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), time of follow-up and cardiovascular disease, CXCL-16 (odds ratio [OR] 2.60, 95% confidence interval [CI] 1.71–3.96), angiopoietin-2 (OR 1.50, 95% CI 1.14–1.98) and TGF-β1 (OR 1.03, 95% CI 1.01–1.04) remained significant predictors of new-onset microalbuminuria (P < 0.001). Inclusion of these biomarkers in conventional clinical risk models for prediction of microalbuminuria increased the area under the curve (AUC) from 0.638 to 0.760 (P < 0.001). Conclusion: In patients with type 2 diabetes, elevated plasma levels of CXCL-16, angiopoietin-2, and TGF-β1 are independently predictive of microalbuminuria. Thus, these serum markers improve renal risk models beyond established clinical risk factors. Keywords: albuminuria, atheromatosis, cardiovascular disease, diabetic kidney disease, inflammation |
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Systemic Inflammation Precedes Microalbuminuria in Diabetes |
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https://doi.org/10.1016/j.ekir.2019.06.005 https://doaj.org/article/c233dfea8bc24170947f739946206627 http://www.sciencedirect.com/science/article/pii/S246802491931383X https://doaj.org/toc/2468-0249 |
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Jan Menne Sabine Brandt Anja Bernhardt Peter R. Mertens Hermann Haller Christos Chatzikyrkou Sadayoshi Ito Josphe L. Izzo Andrzeij Januszewicz Shigerhiro Katayama Albert Mimram Ton J. Rabelink Eberhard Ritz Luis M. Ruilope Lars C. Rump Giancarlo Viberti Herrman Haller |
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Jan Menne Sabine Brandt Anja Bernhardt Peter R. Mertens Hermann Haller Christos Chatzikyrkou Sadayoshi Ito Josphe L. Izzo Andrzeij Januszewicz Shigerhiro Katayama Albert Mimram Ton J. Rabelink Eberhard Ritz Luis M. Ruilope Lars C. Rump Giancarlo Viberti Herrman Haller |
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10.1016/j.ekir.2019.06.005 |
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2024-07-03T14:59:23.682Z |
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|
| score |
7.401622 |