Published online before print February 16, 2004, doi: 10.1161/01.HYP.0000120125.08867.42
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(Hypertension. 2004;43:791.)
© 2004 American Heart Association, Inc.
Scientific Contributions |
C-Reactive Protein Modifies the Relationship Between Blood Pressure and Microalbuminuria
From the Department of Medicine (E.M.S., S.J.L.B., R.O.B.G.), Trial Coordination Center (H.L.H.), Department of Epidemiology & Statistics (J.G.M.B.), Department of Nephrology (P.E.d.J.), Department of Medicine, Department of Clinical Pharmacology (D.d.Z.), University Medical Center, Groningen, The Netherlands.
Correspondence to Dr D. de Zeeuw, Professor and Head, Department of Clinical Pharmacology, University Medical Center, Ant. Deusinglaan 1, 9713 AV, PO Box 196, Groningen, The Netherlands. E-mail d.de.zeeuw{at}med.rug.nl
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Abstract |
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C-reactive protein (CRP) and microalbuminuria reflect intimately related components of the atherosclerotic disease process. Epidemiological studies found only modest associations between CRP and microalbuminuria. Blood pressure, one of the components of the metabolic syndrome in the general population, is the main determinant of microalbuminuria in diabetes and hypertension. We questioned whether CRP modifies the relationship of blood pressure and other cardiovascular risk factors with microalbuminuria in a cross-sectional study in 8592 inhabitants from Groningen, The Netherlands. The crude data showed an increase in the prevalence of microalbuminuria with increasing CRP quartiles (4.8, 9.6, 14.5, and 18.6%, P<0.0001). On stratification for cardiovascular risk factors, the data revealed a significant and positive interaction between mean arterial pressure (MAP) and quartiles of CRP with respect to the risk of microalbuminuria (Wald statistic 9.2, P=0.03). In subjects with a MAP <90 mm Hg, a nonsignificant trend in the association between CRP quartiles and microalbuminuria was found (prevalence: 3.9%, 5.8%, 6.6%, 8.7%; P=0.11). This trend was much steeper and significant in subjects with an MAP >90 mm Hg (prevalence: 6.7%, 13.6%, 20.4%, 25.1%; P<0.0001). Controlling for other risk factors in multivariate analyses, the positive interaction persisted (P=0.0004). No significant interactions between other risk factors and CRP with respect to the risk of microalbuminuria were encountered. Thus, CRP modifies the relation between blood pressure and microalbuminuria.
Key Words: cardiovascular diseases • blood pressure • risk factors • kidney • albuminuria
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Introduction |
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C-reactive protein (CRP), a sensitive marker of (sub)clinical inflammation, is thought to represent the state of chronic low-grade inflammation of the arterial vessel wall at atherosclerotic sites.1 CRP consistently predicts cardiovascular (CV) outcome.2–4 Microalbuminuria is also an established risk marker for future cardiovascular events in various populations.5,6 The appearance of low levels of albumin in the urine is thought to be the consequence of generalized endothelial damage along the vascular tree, including the glomerulus.7
Blood pressure has been shown to be the main determinant of microalbuminuria in diabetes and hypertension.8 Many other CV risk factors, which cluster within the metabolic syndrome, have been shown to relate to microalbuminuria in the population.9,10 Because CRP and microalbuminuria reflect closely related components of the same disease processes, one might anticipate a strong relationship between them. However, studies that investigated this relationship in large populations only found weak associations.11,12 Interdependence between CRP and other cardiovascular risk factors with the risk of microalbuminuria may have been overlooked.
We questioned whether elevated serum CRP levels modify the relation of blood pressure and other CV risk factors with microalbuminuria.
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Methods |
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Study Design
This study is part of the PREVEND study (Prevention of REnal and Vascular ENdstage Disease) in Groningen, The Netherlands. PREVEND investigates the natural course of microalbuminuria in relation to renal and cardiovascular morbidity and mortality in the general population. All inhabitants aged 28 to 75 years (n=85 421) were asked to send in a morning urine sample and to complete a brief questionnaire on demographics and renal and cardiovascular morbidity. A total of 40 856 subjects responded. Pregnant women and subjects using insulin were excluded. All subjects with an albumin concentration of >10 mg/L in their morning urine sample plus a random sample of the population with a morning urine albumin excretion <10 mg/L were invited to our outpatient clinic. A detailed overview of this protocol is described elsewhere.13 All subjects completed an extensive questionnaire on demographics, renal and cardiovascular history, and information on pharmacy data. Furthermore, they underwent investigations in 2 visits: anthropometry, automated blood pressure measurements after 10 minutes of supine rest with a Dinamap XL Model 9300 device (Johnson & Johnson Medical, Tampa, Fla), collection of two 24-hour urine samples after thorough oral instructions, and fasting blood samples. A total of 8592 subjects completed the 2 visits.
This study was approved by the medical ethics committee and conducted in accordance with the guidelines of the declaration of Helsinki. All participants who attended the outpatient clinic gave written informed consent.
Laboratory Measurements
Urinary volume and albumin were measured in each collection. Urinary albumin concentrations were determined by nephelometry with a threshold of 2.3 mg/L and intra-assay and interassay coefficients of variation of <2.2 and <2.6, respectively (Dade Behring Diagnostic, Marburg, Germany). High sensitive CRP was also determined by nephelometry with a threshold of 0.175 mg/L and intra-assay and interassay coefficients of <4.4% and 5.7%, respectively (BNII N; Dade Behring). Urinary leukocyte and erythrocyte counts were determined by urine sticks (Nephur+leuco; Boehringer Mannheim, Mannheim, Germany). Plasma glucose and serum cholesterol were determined by Kodak Ektachem dry chemistry (Eastman Kodak, Rochester, NY).
Calculations, Definitions, and Exclusion: Response Variable
The albumin levels (mg) of the two 24-hour urine collections were averaged. Microalbuminuria was defined as a mean urinary albumin level of 30 to 300 mg per 24 hours.
Predictor Variables
The last 2 blood pressure values of both visits were averaged; thus, blood pressure data are based on the average of 4 blood pressure values. Mean arterial pressure (MAP) was calculated as one third of the average systolic blood pressure plus two thirds of the average diastolic blood pressure (mm Hg). Body mass index (BMI) was calculated as the ratio of weight (kg) and height squared (m2). Smoking was defined as never (reference category), current, and past smoking. Other independent variables were age, gender, waist circumference, serum cholesterol, plasma glucose, and antihypertensive and/or lipid-lowering therapy.
Exclusion Criteria
We excluded 451 subjects with leukocyturia and/or erythrocyturia, 304 subjects with type 2 diabetes (fasting glucose >7.0 mmol/L or nonfasting glucose >11.1 mmol/L or use of antidiabetic drugs), 55 subjects with renal disease, 89 subjects with macroalbuminuria (>300 mg/24 h), and 76 subjects with a CRP level >20 mg/L. The data set contained missing data on diabetes (n=73) and CRP (n=360). Thus, 7184 subjects were eligible for analyses. A total of 900 subjects were identified as having microalbuminuria.
Statistical Methods
Continuous data are reported as mean±SD. Differences between groups were assessed with 
2 analysis or ANOVA. Because our cohort is a sample of the general population with of a supplement of microalbuminuric subjects, and because microalbuminuria is the outcome variable of interest, the results of our analyses cannot be simply extrapolated to the general population. To make such extrapolation possible, we performed design based logistic regression analyses, taking into account unequal probability of selection to ensure unbiased estimates. We used STATA 7.0 (Stata Statistical Software) to perform these "complex survey analyses."
To test linearity in the logit of continuous variables, we used the Box-Tidwell transformation, which adds a term of the form x·ln(x) to the model, where x represents a continuous variable.14 If the coefficient for this variable is significant, then there is evidence for nonlinearity in the logit. If nonlinearity was present, then we divided this variable into deciles and subsequently selected the scale of the independent variable. We assured linearity of the ß coefficients by log-transformation of CRP. The logits of the remaining variables were linear.
In multivariate analyses, including interactions, continuous variables were centralized to their mean values. A P<0.05 (2-sided) was used for all variables and interaction terms as the nominal level of statistical significance.
The following procedures were conducted to validate the robustness of the model. The 24-hour urine collections are prone to collection errors; thus, misclassification of subjects having either no microalbuminuria or microalbuminuria could have occurred. Therefore, we also analyzed our data with exclusion of subjects with >20% difference in 24-hour urinary creatinine excretion levels between the 2 collections. In a separate analysis, we analyzed the data defining the occurrence of microalbuminuria when present in both urine collections.15 We also analyzed our data with exclusion of subjects with CRP levels >10 mg/L16 and the level of suspected and clinically manifest inflammation. In another analysis, we added subjects with macroalbuminuria to the subjects defined as having microalbuminuria. These procedures did not affect any association or interaction.
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Results |
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Detailed characteristics of our study cohort are given in Table 1. Age, MAP, BMI, waist circumference, glucose, and cholesterol increased significantly with increasing CRP levels (P<0.0001). The proportion of current and past smokers increased with increasing CRP levels as compared with never-smokers (P<0.0001). More subjects used antihypertensive or lipid-lowering therapy with increasing CRP levels (P<0.0001). More female subjects were present in the highest CRP quartile (P<0.0001).
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Among subjects with a blood pressure below the median population level, the trend in the association between CRP and microalbuminuria was not significant (P=0.11), whereas this trend was significant in subjects with high MAP (P<0.0001) (Table 2). All other risk factors showed a significant trend in the association between CRP and albuminuria in both strata (low versus high, no use versus use). Compared with subjects with a MAP below the median level (90 mm Hg), subjects with a MAP above the median level were more likely to have microalbuminuria in presence of an elevated CRP (Wald statistic for the interaction 9.2, P=0.03). In subjects with a low MAP, the prevalence of microalbuminuria increased 
2-fold (from 3.9% to 8.7%), whereas in subjects with an elevated MAP the prevalence of microalbuminuria increased 4-fold (from 6.7% to 25.1%). Stratification for other cardiovascular risk factors did not yield significant interactions with CRP for the presence of microalbuminuria. Table 3 provides the multivariate design-based logistic regression model, in which the association of the studied risk factors and interactions with the presence of microalbuminuria is shown. Factors, which significantly increased the odds of having microalbuminuria, were age, waist circumference, cholesterol (negatively), lipid-lowering therapy, and current smoking. MAP and CRP were found interdependently; the interaction between CRP and MAP contributed significantly to the multivariate model (P=0.0004). Thus, blood pressure positively modified the association between CRP and microalbuminuria. Other interactions between risk factors and CRP did not significantly improve the model. Also, no significant interactions between MAP and other risk factors were encountered. We also tested interactions of those risk factors showing significant associations with microalbuminuria in the multivariate analysis, ie, age, waist circumference, cholesterol, and current smoking, without significant improvement of the model.
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The interaction between levels of CRP and MAP with the estimated prevalence of microalbuminuria is graphically depicted in the Figure. The arbitrarily chosen CRP values of 0.2, 1.0, 3.0, and 10.0 mg/L correspond to the 5th, 50th, 75th, and 95th percentiles of its distribution, respectively. Considering a MAP of 100 (eg, 140/80 mm Hg), the prevalence of microalbuminuria is increased 2-times in subjects with a CRP of 3 mg/L compared with subjects with a CRP of 1 mg/L. It is important to consider that this plot is created from the multivariate regression formula using centralized variables. Thus, these lines represent the estimated prevalence of microalbuminuria in a never-smoking male with an average age (48.4 years), BMI (25.9 kg/m2), waist circumference (93 cm), glucose (4.7 mmol/L), cholesterol (5.6 mmol/L), and not using antihypertensive or lipid-lowering drugs. Consequently, the risk of having microalbuminuria would be higher in subjects with higher values for these factors, except for cholesterol. For example, the prevalence of microalbuminuria in smoking males aged 65 years using an antihypertensive drug with a BMI of 27 kg/m2, MAP 100 mm Hg, waist circumference 100 cm, glucose 6.0 mmol/L, cholesterol 6.0 mmol/L, and a CRP level of 3 mg/L is 20%.
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Discussion |
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Our study shows that CRP modifies the relation between blood pressure and microalbuminuria. CRP did not modify the relation between other cardiovascular risk factors and microalbuminuria.
Most scientific reports on the association between inflammatory parameters (fibrinogen, sialic acid) and microalbuminuria come from small studies of subjects with type 1 and 2 diabetes12,17 who encounter an increased risk for diabetic nephropathy and/or cardiovascular disease. Data on the association between CRP, as measured by highly sensitive assays, and microalbuminuria are scarce at the level of the general population. The Insulin Resistance Atherosclerosis Study (IRAS) only found a modest correlation (adjusted r=0.06) between CRP and microalbuminuria in a large nondiabetic cohort. In a multivariate analysis, CRP did not significantly increase the odds of having microalbuminuria.12 The only study that found a significant association between CRP and microalbuminuria, also after controlling for other risk factors, was performed by Pannacciulli et al.11 This study was conducted, however, in a selected population consisting of 103 obese, nondiabetic, and premenopausal women. In one prospective study, a 50% increase in baseline levels of CRP predicted a 17% increase in risk for microalbuminuria in the general population.18 Possible effect modification was not investigated in the latter 2 studies. The IRAS investigators did study possible interaction. However, the relation between CRP and microalbuminuria was found similar in strata of gender, ethnicity, or diabetic status. It is uncertain whether the investigators performed studies of potential interactions with other risk factors. Our data show that elevated CRP enhances the relationship between blood pressure and microalbuminuria. This interaction was found independently of other co-variates and interactions in the multivariate analysis.
Systemic blood pressure is the most important determinant of microalbuminuria in diabetes and hypertension.8,19 Functional abnormalities, indicative of impaired glomerular autoregulation, and structural changes in the glomerulus can be observed in diabetes and hypertension.20–22 Albuminuria may therefore occur as a result of direct transmission of raised systemic pressure to the glomerulus23,24 and/or permselectivity changes of the glomerular filter.25 Blood pressure is already known to relate to albuminuria in the population,8 a fact that we confirmed in the present study. A new finding of our study shows that the relation was more pronounced in subjects with an elevated CRP level. Inflammation is implicated in early endothelial dysfunction3,26 and more advanced atherosclerosis.27 Therefore, CRP may be a marker of vascular disease, which indicates impaired autoregulation of glomerular pressure and/or dysfunction of the glomerular endothelium. Both of these factors may enhance microalbuminuria.
The associations of microalbuminuria with age, blood pressure, lipid-lowering therapy, and CRP suggest the presence of the metabolic syndrome in subjects with microalbuminuria. CRP has been shown to be associated with measures of insulin resistance, like fasting hyperinsulinemia28 and impaired glucose disposal rate during a euglycemic hyperinsulinemic clamp.29 In diabetes and hypertension, insulin resistance has also been related to microalbuminuria,30–32 although not in all studies.33,34 Moreover, CRP and microalbuminuria both predict incident cases of type 2 diabetes, which underlines their role in insulin resistance.35,36 Because we did not measure insulin sensitivity or insulin concentrations, we cannot exclude that our findings relate more directly to insulin resistance than to CRP.
Some methodological issues have to be addressed. First, our data are of cross-sectional nature, which makes temporal and causal inferences impossible. Second, we have to discuss possible selection bias. Our cohort consists of a selected sample of subjects with an elevated urinary albumin excretion (UAE >10 mg/L) and a randomly selected sample of control subjects (UAE <10 mg/L). This sampling affects absolute values and point estimates; therefore, the generalizability of our findings for the general population may be questioned (internal validity). However, to control for our sampling procedure, we conducted design-based analyses, which allow generalization of the outcome data to the population at large. Third, misclassification of subjects having microalbuminuria could occur because of partly collected samples. To control for the effect of collection errors, we have validated the data in various ways as mentioned in the statistical methods section. These validation procedures did not affect the outcome of the analyses. We also validated our data by exclusion of subjects with suspected clinical inflammation (CRP>10 mg/L). This also did not affect the results.
In our study, all participants collected two 24-hour urine samples to assess urinary albumin excretion. Other studies used urinary albumin/creatinine ratio (A/C ratio), determined in a morning urine sample, to assess the presence of microalbuminuria,12,18 except for the study by Pannacciulli et al, which also used two 24-hour urine collections.11 Assessment of 24-hour urinary albumin excretion is considered the preferred method. Although the A/C ratio is accepted as an alternative to detect the presence of microalbuminuria, urinary creatinine excretion depends on the amount of muscle mass, which is variable for several biological parameters (gender, age, body weight, exercise).37 This could be a reason that these studies did not find an interaction of CRP and blood pressure, which is also related to these parameters, with the risk of microalbuminuria.
We used MAP as the blood pressure variable of interest. We also calculated our data including both systolic and diastolic blood pressure in the analyses. Interestingly, the interaction of blood pressure with CRP on the risk of microalbuminuria was equally found for systolic as well as diastolic blood pressure (data not shown).
Perspectives
Our study shows the novel finding of effect modification by CRP of the relation between blood pressure and microalbuminuria. The observed interaction is important for our understanding of the pathophysiology of increased urinary albumin excretion in the general population. Elevated CRP levels indicate systemic low-grade inflammation. Inflammation apparently increases the likelihood of increased glomerular leakage of albumin in response to blood pressure. This glomerular leakage may involve either increased transmission of systemic blood pressure or decreased barrier function of the glomerulus.
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Acknowledgments |
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We thank Dade Behring (Marburg, Germany) for supplying equipment (Behring Nephelometer II) and analytes for the determination of high-sensitive C-reactive protein and urinary albumin. This study is financially supported by grant E.013 of the Dutch Kidney Foundation and by grant 99.103 of the Dutch Heart Foundation. We thank Jacko J. Duker and Janneke W. J. T. van der Wal-Hanewald for their elaborate work and technical support.
The PREVEND study group includes Paul E. de Jong, Gerjan Navis, Ron T. Gansevoort, Jacobien C. Verhave, Department of Medicine, Division of Nephrology; Dick de Zeeuw, Wiek H. van Gilst, Rob H. Henning, Department of Clinical Pharmacology; Reinold O.B. Gans, Stephan J.L. Bakker, Andries J. Smit, Arie M. van Roon, Erik M. Stuveling, Department of Medicine, Division of Vascular Medicine; Dirk-Jan van Veldhuisen, Hans L. Hillege, Ad J. van Boven, Folkert W. Asselbergs, Corine P. Baljé-Volkers, Department of Cardiology; Bruce H.R. Wolffenbuttel, Robin P.F. Dullaart, Susan E. Borggreve, Department of Medicine, Division of Endocrinology; Gerard J. te Meerman, Geert T. Spijker, Department of Medical Genetics; Vaclav Fidler, Johannes G. M. Burgerhof, Department of Epidemiology and Statistics; Lolkje T.W. de Jong-van den Berg, Maarten J. Postma, Department of Pharmaco-Epidemiology; Jaap H.J. Muntinga, Department of Medical Physiology; University Medical Center Groningen; Diederick E. Grobbee, Department of Epidemiology, Julius Center, Utrecht.
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Footnotes |
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A list of the PREVEND study group members is given in the Acknowledgments.
Received December 5, 2003; first decision December 24, 2003; accepted January 14, 2004.
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References |
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1. Ross R. Atherosclerosis-an inflammatory disease. N Engl J Med. 1999; 340: 115–126.
2. Kuller LH, Tracy RP, Shaten J, Meilahn EN. Relation of C-reactive protein and coronary heart disease in the MRFIT nested case-control study. Multiple Risk Factor Intervention Trial. Am J Epidemiol. 1996; 144: 537–547.
3. Ridker PM, Cushman M, Stampfer MJ, Tracy RP, Hennekens CH. Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. N Engl J Med. 1997; 336: 973–979.
4. Danesh J, Collins R, Appleby P, Peto R. Association of fibrinogen, C-reactive protein, albumin, or leukocyte count with coronary heart disease: meta-analyses of prospective studies. JAMA. 1998; 279: 1477–1482.
5. Hillege HL, Fidler V, Diercks GF, van Gilst WH, De Zeeuw D, van Veldhuisen DJ, Gans RO, Janssen WM, Grobbee DE, de Jong PE. Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population. Circulation. 2002; 106: 1777–1782.
6. Borch-Johnsen K, Feldt-Rasmussen B, Strandgaard S, Schroll M, Jensen JS. Urinary albumin excretion. An independent predictor of ischemic heart disease. Arterioscler Thromb Vasc Biol. 1999; 19: 1992–1997.
7. Deckert T, Feldt-Rasmussen B, Borch-Johnsen K, Jensen T, Kofoed-Enevoldsen A. Albuminuria reflects widespread vascular damage. The Steno hypothesis. Diabetologia. 1989; 32: 219–226.[CrossRef][Medline] [Order article via Infotrieve]
8. Mogensen CE. Systemic blood pressure and glomerular leakage with particular reference to diabetes and hypertension. J Intern Med. 1994; 235: 297–316.[Medline] [Order article via Infotrieve]
9. Halimi JM, Forhan A, Balkau B, Novak M, Wilpart E, Tichet J, Marre M. Is microalbuminuria an integrated risk marker for cardiovascular disease and insulin resistance in both men and women? J Cardiovasc Risk. 2001; 8: 139–146.[CrossRef][Medline] [Order article via Infotrieve]
10. Haffner SM, Stern MP, Gruber MK, Hazuda HP, Mitchell BD, Patterson JK. Microalbuminuria. Potential marker for increased cardiovascular risk factors in nondiabetic subjects? Arteriosclerosis. 1990; 10: 727–731.
11. Pannacciulli N, Cantatore FP, Minenna A, Bellacicco M, Giorgino R, De Pergola G. Urinary albumin excretion is independently associated with C-reactive protein levels in overweight and obese nondiabetic premenopausal women. J Intern Med. 2001; 250: 502–507.[CrossRef][Medline] [Order article via Infotrieve]
12. Festa A, D’Agostino R, Howard G, Mykkanen L, Tracy RP, Haffner SM. Inflammation and microalbuminuria in nondiabetic and type 2 diabetic subjects: the insulin resistance atherosclerosis study. Kidney Int. 2000; 58: 1703–1710.[CrossRef][Medline] [Order article via Infotrieve]
13. Pinto-Sietsma SJ, Janssen WM, Hillege HL, Navis G, De Zeeuw D, de Jong PE. Urinary albumin excretion is associated with renal functional abnormalities in a nondiabetic population. J Am Soc Nephrol. 2000; 11: 1882–1888.
14. Geurro VM, Johnson RA. Use of the Box-Cox transformation with binary response models. Biometrika. 1982; 69: 309–314.
15. Gomes MB, Goncalves MF. Is there a physiological variability for albumin excretion rate? Study in patients with diabetes type 1 and non-diabetic individuals. Clin Chim Acta. 2001; 304: 117–123.[CrossRef][Medline] [Order article via Infotrieve]
16. Kluft C, de Maat MP. Determination of the habitual low blood level of C-reactive protein in individuals. Ital Heart J. 2001; 2: 172–180.[Medline] [Order article via Infotrieve]
17. Navarro JF, Mora C, Maca M, Garca J. Inflammatory parameters are independently associated with urinary albumin in type 2 diabetes mellitus. Am J Kidney Dis. 2003; 42: 53–61.[CrossRef][Medline] [Order article via Infotrieve]
18. Jager A, van Hinsbergh VW, Kostense PJ, Emeis JJ, Nijpels G, Dekker JM, Heine RJ, Bouter LM, Stehouwer CD. C-reactive protein and soluble vascular cell adhesion molecule-1 are associated with elevated urinary albumin excretion but do not explain its link with cardiovascular risk. Arterioscler Thromb Vasc Biol. 2002; 22: 593–598.
19. Mimran A, Ribstein J, du CG. Microalbuminuria in essential hypertension. Curr Opin Nephrol Hypertens. 1999; 8: 359–363.[CrossRef][Medline] [Order article via Infotrieve]
20. Schmieder RE, Messerli FH, Garavaglia G, Nunez B. Glomerular hyperfiltration indicates early target organ damage in essential hypertension. JAMA. 1990; 264: 2775–2780.
21. Cerasola G, Cottone S, Mule G, Nardi E, Mangano MT, Andronico G, Contorno A, Li VM, Galione P, Renda F, Piazza G, Volpe V, Lisi A, Ferrara L, Panepinto N, Riccobene R. Microalbuminuria, renal dysfunction and cardiovascular complication in essential hypertension. J Hypertens. 1996; 14: 915–920.[Medline] [Order article via Infotrieve]
22. Ruilope LM, Rodicio JL. The kidney in arterial hypertension. Nephrol Dial Transplant. 2001; 16: 50–52.
23. Christensen PK, Hansen HP, Parving HH. Impaired autoregulation of GFR in hypertensive non-insulin dependent diabetic patients. Kidney Int. 1997; 52: 1369–1374.[Medline] [Order article via Infotrieve]
24. Brenner BM, Meyer TW, Hostetter TH. Dietary protein intake and the progressive nature of kidney disease: the role of hemodynamically mediated glomerular injury in the pathogenesis of progressive glomerular sclerosis in aging, renal ablation, and intrinsic renal disease. N Engl J Med. 1982; 307: 652–659.[Medline] [Order article via Infotrieve]
25. Cottone S, Cerasola G. Microalbuminuria fractional clearance and early renal permselectivity changes in essential hypertension. Am J Nephrol. 1992; 12: 326–329.[Medline] [Order article via Infotrieve]
26. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000; 342: 836–843.
27. Van DM, I, de Maat MP, Hak AE, Kiliaan AJ, Del Sol AI, Van Der Kuip DA, Nijhuis RL, Hofman A, Witteman JC. C-reactive protein predicts progression of atherosclerosis measured at various sites in the arterial tree: the Rotterdam study. Stroke. 2002; 33: 2750–2755.
28. Pradhan AD, Cook NR, Buring JE, Manson JE, Ridker PM. C-reactive protein is independently associated with fasting insulin in nondiabetic women. Arterioscler Thromb Vasc Biol. 2003; 23: 650–655.
29. McLaughlin T, Abbasi F, Lamendola C, Liang L, Reaven G, Schaaf P, Reaven P. Differentiation between obesity and insulin resistance in the association with C-reactive protein. Circulation. 2002; 106: 2908–2912.
30. Yip J, Mattock MB, Morocutti A, Sethi M, Trevisan R, Viberti G. Insulin resistance in insulin-dependent diabetic patients with microalbuminuria. Lancet. 1993; 342: 883–887.[CrossRef][Medline] [Order article via Infotrieve]
31. Nosadini R, Cipollina MR, Solini A, Sambataro M, Morocutti A, Doria A, Fioretto P, Brocco E, Muollo B, Frigato F. Close relationship between microalbuminuria and insulin resistance in essential hypertension and non-insulin dependent diabetes mellitus. J Am Soc Nephrol. 1992; 3: S56–S63.[Abstract]
32. Mykkanen L, Zaccaro DJ, Wagenknecht LE, Robbins DC, Gabriel M, Haffner SM. Microalbuminuria is associated with insulin resistance in nondiabetic subjects: the Insulin Resistance Atherosclerosis Study. Diabetes. 1998; 47: 793–800.[Abstract]
33. Nielsen S, Schmitz O, Orskov H, Mogensen CE. Similar insulin sensitivity in NIDDM patients with normo- and microalbuminuria. Diabetes Care. 1995; 18: 834–842.[Abstract]
34. Toft I, Bonaa KH, Eikrem J, Bendiksen AL, Iversen H, Jenssen T. Microalbuminuria in hypertension is not a determinant of insulin resistance. Kidney Int. 2002; 61: 1445–1452.[CrossRef][Medline] [Order article via Infotrieve]
35. Mykkanen L, Haffner SM, Kuusisto J, Pyorala K, Laakso M. Microalbuminuria precedes the development of NIDDM. Diabetes. 1994; 43: 552–557.[Abstract]
36. Freeman DJ, Norrie J, Caslake MJ, Gaw A, Ford I, Lowe GD, O’Reilly DS, Packard CJ, Sattar N. C-reactive protein is an independent predictor of risk for the development of diabetes in the West of Scotland Coronary Prevention Study. Diabetes. 2002; 51: 1596–1600.
37. Mogensen CE, Vestbo E, Poulsen PL, Christiansen C, Damsgaard EM, Eiskjaer H, Froland A, Hansen KW, Nielsen S, Pedersen MM. Microalbuminuria and potential confounders. A review and some observations on variability of urinary albumin excretion. Diabetes Care. 1995; 18: 572–581.[Medline] [Order article via Infotrieve]
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D. Nitsch, D. F. Dietrich, A. von Eckardstein, J.-M. Gaspoz, S. H. Downs, P. Leuenberger, J.-M. Tschopp, O. Brandli, R. Keller, M. W. Gerbase, et al. Prevalence of renal impairment and its association with cardiovascular risk factors in a general population: results of the Swiss SAPALDIA study Nephrol. Dial. Transplant., April 1, 2006; 21(4): 935 - 944. [Abstract] [Full Text] [PDF]
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 N. Khosla and G. Bakris Lessons Learned from Recent Hypertension Trials about Kidney Disease Clin. J. Am. Soc. Nephrol., March 1, 2006; 1(2): 229 - 235. [Full Text] [PDF]
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G. Bakris Proteinuria: A Link to Understanding Changes in Vascular Compliance? Hypertension, September 1, 2005; 46(3): 473 - 474. [Full Text] [PDF]
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 J. Arnlov, J. C. Evans, J. B. Meigs, T. J. Wang, C. S. Fox, D. Levy, E. J. Benjamin, R. B. D'Agostino, and R. S. Vasan Low-Grade Albuminuria and Incidence of Cardiovascular Disease Events in Nonhypertensive and Nondiabetic Individuals: The Framingham Heart Study Circulation, August 16, 2005; 112(7): 969 - 975. [Abstract] [Full Text] [PDF]
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 R. Pedrinelli, G. Dell'Omo, V. Di Bello, G. Pellegrini, L. Pucci, S. Del Prato, and G. Penno Low-Grade Inflammation and Microalbuminuria in Hypertension Arterioscler Thromb Vasc Biol, December 1, 2004; 24(12): 2414 - 2419. [Abstract] [Full Text] [PDF]
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 G. L. Bakris, V. Fonseca, R. E. Katholi, J. B. McGill, F. H. Messerli, R. A. Phillips, P. Raskin, J. T. Wright Jr, R. Oakes, M. A. Lukas, et al. Metabolic Effects of Carvedilol vs Metoprolol in Patients With Type 2 Diabetes Mellitus and Hypertension: A Randomized Controlled Trial JAMA, November 10, 2004; 292(18): 2227 - 2236. [Abstract] [Full Text] [PDF]
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