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Inflammation and hemostasis may increase the risk of kidney function decline, but data from prospective studies are sparse.
The Atherosclerosis Risk in Communities (ARIC) Study, a prospective observational cohort.
We used data from the 14,854 middle aged adults from 4 different US communities.
Markers of inflammation and hemostasis were examined.
Risk of kidney function decline associated with these markers was studied. Glomerular filtration rate (GFR) was calculated from serum creatinine using the 4-variable MDRD Study equation. Chronic kidney disease (CKD) was defined as 1) a decline in estimated GFR below 60 mL/min/1.73 m2 from above 60 at baseline, or 2) a hospitalization discharge or death coded for CKD. Serum creatinine was measured at baseline and at the 3 and 9-year follow-up visits. Hazard ratios (HR) of CKD associated with increased levels of inflammatory and hemostatic variables were estimated by multivariate Cox proportional hazards regression.
1,787 cases of CKD developed between 1987 and 2004. After adjusting for demographics, smoking, blood pressure, diabetes, lipids, prior myocardial infarction, antihypertensive use, alcohol use, year of marker measurement, and baseline renal function using estimated GFR, the risk of incident CKD rose with increasing quartiles of white blood cell count (HR Q4 vs. Q1=1.30, 95% CI= (1.12–1.50); P trend = 0.001), fibrinogen (1.25, (1.09–1.44); <0.001), von Willebrand Factor (1.46, (1.26–1.68); <0.001), and factor VIIIc (1.39, (1.20–1.60); <0.001). A strong inverse association was found between serum albumin and risk of CKD (0.63, (0.55–0.72); <0.001). No independent association was found with levels of factor VIIc.
Although we lacked a direct measure of kidney function, associations were robust to case definitions.
Markers of inflammation and hemostasis are associated with a greater risk of kidney function decline. Findings suggest that inflammation and hemostasis are antecedent pathways for CKD.
Several risk factors for atherosclerotic cardiovascular disease (CVD) including hypertension and diabetes, also play a role in the development of chronic kidney disease (CKD).1–4 Findings from recent studies suggest that markers of inflammation and hemostasis, many of which predict CVD, may also predict kidney function decline5, 6, and damage.7 The significant overlap between hemostatic and inflammatory processes suggests that these factors should be examined together.
Elevated white blood cell count (WBC) and low serum albumin predicted progression of kidney disease in a nationally representative sample of adults and in the elderly.5, 6, 8, 9 However, data on other inflammatory markers and markers of hemostasis are conflicting and sparse. C-reactive protein (CRP) was not associated with progression of CKD in the Modification of Diet in Renal Disease (MDRD) Study, but was associated with declining kidney function in the elderly.6, 10 Plasma levels of fibrinogen and factor VII were found to predict kidney function decline in the elderly in one study, but these findings have not been observed in other populations.6
In the current study, we explore the association between circulating levels of several markers of inflammation and hemostasis and declining kidney function in a middle-aged, population-based cohort, the Atherosclerosis Risk in Communities (ARIC) Study. We hypothesized that increased levels of markers of inflammation and hemostasis are associated with an increased risk of kidney function decline after adjusting for potential confounders and baseline kidney function.
The Atherosclerosis Risk in Communities (ARIC) Study is a prospective biracial observational cohort of 15,792 individuals between the ages of 45 and 64. Participants were drawn from a probability based sample from four U.S. communities (Forsyth County, NC; Jackson, MS; suburban Minneapolis, MN; and Washington County, MD). Participants took part in examinations starting with the baseline visit between 1987 and 1989. Individuals had follow-up examinations approximately every three years at community clinics, as well as annual follow-up telephone interviews. Hospitalized events were ascertained through December 31, 2004. Details of the ARIC cohort have been published elsewhere.11
All participants with prevalent CKD at baseline (baseline estimated GFR < 60 mL/min/1.73m2; n=457), were excluded from these analyses.
Incident CKD was defined as either 1) an estimated glomerular filtration rate (GFR) falling below 60 mL/min/1.73 m2, representing stages 3–5 of chronic kidney disease, at the 3-or 9-year follow-up visit, or 2) a death or hospitalization with CKD.12
Deaths and hospitalizations through 2004 were identified via annual participant interviews, local hospital discharge lists, and county death certificates, and included all those coded (International Classification of Diseases, Ninth Revision (ICD-9)) for chronic renal disease (581–583.91, 585–588.91), hypertensive renal disease (403–403.91), hypertensive heart and renal disease (404–404.93), unspecified disorder of kidney and ureter (593.9), diabetes with renal manifestations (250.40–250.43), kidney transplant, renal dialysis or adjustment/ fitting of catheter (V42.0, V45.1 or V56), or either hemodialysis (39.95) or peritoneal dialysis (54.98) without simultaneous acute renal failure (584, 586, 788.9, and 958.5). Corresponding ICD-10 codes were used for deaths after ICD-10 implementation.
Serum creatinine was measured using a modified kinetic Jaffe reaction.13 Serum creatinine concentration was corrected for interlaboratory differences and calibrated to the Cleveland Clinic laboratory measurements by subtraction of 0.24 mg/dL at visits 1 and 2, and addition of 0.18 mg/dL at visit 4. Glomerular filtration rate (GFR) was estimated using the 4-variable Modification of Diet in Renal Disease Study equation developed at the Cleveland Clinic: estimated GFR = 186.3 × (serum creatinine [mg/dL]1.154) × (age0.203) × (0.742 if female) × (1.21 if African American).14
As a sensitivity analysis, models were run using an alternative CKD progression definition defined as either 1) an increase in creatinine of >=0.4 mg/dL from baseline to the 3-or 9-year follow-up visit, representing twice the normal short-term variation in creatinine, or 2) a hospitalization or death with CKD.15
Clinic examinations included interviews conducted by trained interviewers collecting demographic and lifestyle characteristics as well as physiological information including anthropometrics, blood pressure, and venipuncture. Hematologic measurements were made from blood drawn from the antecubital vein after an 8 hour fast. Processing of samples was conducted according to a standardized protocol and plasma specimens were stored at −70°C. Detailed methods for blood processing and measurement of hemostatic variables have been published previously.16, 17
Fibrinogen was measured by the thrombin-time titration method; von Willebrand factor (VWF) antigen by ELISA; factor VII activity (VIIc) and factor VIII activity (VIIIc) by clotting assays.18
Measurements repeated on a sample of participants over several weeks yielded reliability coefficients of 0.72 for fibrinogen, 0.68 for von Willebrand factor, 0.78 for factor VIIc, and 0.86 for factor VIIIc.19
Prevalent diabetes mellitus was defined as a fasting glucose level ≥126 mg/dL, nonfasting glucose level ≥200 mg/dL, or a history of or treatment for diabetes. Three seated blood pressure measurements were taken by certified technicians using a random-zero sphygmomanometer after 5 minutes of rest. The mean of the last two measurements was used for analysis. Self-reported antihypertensive medication use was verified by inspection of bottles. Prevalent myocardial infarction (MI) included a self-reported physician diagnosis or an MI revealed on the electrocardiogram conducted during the baseline visit. Enzymatic methods were used to obtain total plasma cholesterol and triglycerides. LDL cholesterol was calculated using the Friedewald equation20 (exclusive of those with incalculable LDL due to triglyceride values over 400 mg/dL). Participants with severely elevated triglycerides, and thus missing LDL, were assigned the mean LDL value, and an indicator for the presence of calculated LDL was included in the models. Smoking status was determined by self-reported cigarette smoking.
Analyses were limited to 14,854 ARIC participants, excluding those with missing baseline serum creatinine values (n=150), with missing values for diabetes or hypertension (n=118), those missing lipids (n=69), with race other than African American or white (n=47), African-Americans at Minnesota and Washington Co. field centers (n=54), with prevalent CKD (n=457) or with missing values for all hemostatic and inflammatory markers (n=43). All analyses were conducted using Stata version 9.2 software.21
Demographic and health characteristics of CKD cases were compared to those of non-cases using chi-squared and t-tests. Hemostatic and inflammatory markers were treated as continuous variables in standard deviation (SD) units, as well as categorized into quartiles for some analyses. Kaplan-Meier survival estimates were plotted by quartiles of each marker and differences in survival across quartiles were tested by log-rank tests. Proportional hazards regression was used to estimate unadjusted and adjusted hazard ratios (HR) and 95% confidence intervals (CI). Proportionality of hazards over time was confirmed by the Schoenfeld test for each of the factors under study (all p >0.06).” Multivariate adjusted models included age, race, sex, systolic blood pressure, diabetes status, hypertension medication use, prevalent MI, smoking, alcohol use, log triglycerides, HDL cholesterol, LDL cholesterol, year of marker measurement, and estimated baseline GFR. Fully adjusted models were also run separately for cases meeting each CKD outcome criterion. Linearity of associations with CKD was assessed by significance (p<0.05) of quadratic terms and by plots of residuals. Quadratic terms were significant for serum albumin and factor VIIc but linear estimates are reported as they were very similar, and the most easily interpretable.
The continuous association between each of the markers and incident CKD was predicted from a Poisson regression model including a fifth-order polynomial for each marker, adjusted to the incidence rate for a 60 year old white man with a baseline eGFR of 90 mL/min/1.73 m2. Additionally, to assess whether the association of the markers with CKD risk was affected by measurement error in baseline estimated GFR, analyses were repeated using Poisson regression models incorporating measurement error estimation using regression calibration.22–24
Results were similar to those from primary analyses and therefore are not reported.
After a mean follow-up time of almost 14 and a half years (for a total of 213,548 person-years), there were 1,787 incident cases of CKD among 14,854 persons. Characteristics of the study population are shown in Table 1. At baseline, persons who subsequently developed CKD were more likely to use hypertension medications, have diabetes, and have blood pressure, higher cholesterol, triglyceride, WBC, fibrinogen, von Willebrand Factor, Factor VIIc and VIIIc concentrations. Persons who subsequently developed CKD also had a higher baseline creatinine and lower albumin and lower baseline estimated GFR compared to persons who did not develop CKD.
Kaplan-Meier plots by quartile of each factor are shown in Figure 1. Progressively higher quartiles of WBC, fibrinogen, factor VIIIc, and VWF and lower quartiles of albumin were associated with higher risk of CKD. Patterns across quartiles of factor VIIc were less consistent.
In unadjusted analyses (Table 2), the hazard ratio (HR) of CKD was significantly higher for the highest compared to the lowest quartile of WBC, fibrinogen, von Willebrand Factor (VWF), factor VIIc, and factor VIIIc. A strong inverse association was found for serum albumin for the highest versus the lowest quartile (HR=0.68; 95% CI 0.60, 0.77). After adjustment for cardiovascular and kidney disease risk factors and baseline kidney function, the relative hazards associated with low albumin were nearly unaltered (HR =0.63; 95% CI 0.55, 0.72) while those associated with greater WBC, fibrinogen, VWF, and factor VIIIc, were somewhat attenuated (Table 2).
Associations were generally robust to changes in case definitions. Defining cases by hospitalization ICD-9 codes (n=959), however, resulted in somewhat stronger associations than defining cases by decreased GFR (n=1085; n=257 identified as both types of cases). Lower albumin (p-trend<0.001) and greater VWF (p-trend=0.04) were significantly related to the risk of decreased GFR. Lower albumin (p<0.001) and higher VWF (p-trend<0.001), fibrinogen (p-trend=0.001) and Factor VIIIc (p-trend=0.02) also were significantly associated with higher risk of a serum creatinine increase of ≥ 0.4 mg/dL.”
Incidence rates of CKD by concentration of each of the hemostatic and inflammatory markers that were estimated using minimally adjusted (for age, race, sex and eGFR) fifth-order polynomial models for each of the markers (Figure 2) show graded associations across the entire range of each marker. These plots were consistent with quadratic terms that were found to be statistically significant for albumin and factor VIIc, and showed mostly linear relationships with other markers.
Assessment for interaction with any factor by sex, race, diabetes or prior MI are shown in Table 3. There was evidence for a stronger association of factor VIIc with risk of CKD in African Americans compared to whites (p-interaction=0.03). Albumin, fibrinogen, and factor VIIIc were all more strongly associated with CKD among persons with diabetes compared to persons without diabetes (p-interactions <0.01).
There was borderline evidence for a stronger association of WBC and fibrinogen with risk of CKD in African Americans compared to whites (p=0.08 and p=0.09, respectively). Analyses using race-specific quartiles resulted in similar hazard ratios where WBC quartiles were still more strongly associated with incident CKD among African Americans than whites (p-interaction = 0.004). WBC and von Willebrand factor are more strongly associated with CKD risk among individuals with compared to those without diabetes (p=0.06 for both) while risk among men is more strongly associated with fibrinogen than risk among women (p=0.07). WBC, fibrinogen, von Willebrand factor, and factor VIIIc were positively associated with risk of CKD in all subgroups examined. It is not surprising that von Willebrand factor and factor VIIIc have similar associations with risk of CKD as these two factors are highly correlated (due to plasma binding) as seen in Table 4.
Our results suggest that markers of inflammation and hemostasis also are associated with the risk of kidney function decline in middle-aged persons. In this study, increased levels of WBCs, fibrinogen, factor VIIIc and VWF, and reduced levels of serum albumin, were associated with greater occurrences of CKD.
Among the strengths of the current study are the large, population-based sample and the relatively long follow-up time (a mean follow-up time of more than 14 years. In addition, the ARIC cohort is very well characterized and has a large number of African Americans, a group at particularly high risk for CKD. This study assessed multiple inflammatory and hemostatic markers, and included extensive data on potential confounders.
Because measures for albuminuria were available only at visit 4, we could only exclude prevalent cases of CKD stage 3 or greater; therefore, our sample may include individuals with prevalent CKD stage 1 or 2 at baseline. Also among the limitations of the current study is the lack of a direct measure of kidney function. Direct measurement of kidney function is impractical in large cohorts and this limitation is common among such studies. However, we found associations to be robust to case definitions, as they persisted when defining cases based solely on coded hospitalizations and deaths. The stronger association observed when limiting the case definition to hospitalizations and deaths is likely due to the greater specificity of this definition and limiting to more severe cases (cases among individuals who were admitted to the hospital.
Our finding of an inverse relationship between serum albumin and the risk of declining kidney function could reflect inadequate nutrition and not inflammation. Evidence against this hypothesis is that the ARIC cohort comprised middle-aged, free-living individuals in whom significant malnutrition is unlikely. Findings with respect to serum albumin as a predictor of kidney function decline are consistent with findings from two other large cohorts and are consistent with levels of serum albumin that have been shown to predict coronary heart disease.5, 6, 25
This study also lacks measurement of urinary albumin, requiring CKD to be defined solely on hospitalizations and estimated GFR (the latter of which was there was no estimate after 1999). Lastly, as in any observational study, there is potential for reverse causation. However, we also observed the relative risk of CKD to be stronger with increasing follow-up time in several markers (results not shown), which helps in ruling out these concerns. Our findings are consistent with those of the Cardiovascular Health Study (CHS), which found several markers of inflammation and hemostasis, including increased levels of C-reactive protein, WBC, fibrinogen, factor VIIc, and reduced levels of albumin and hemoglobin associated with an increased risk of reduced kidney function.6, 8
They are also consistent with findings from follow-up of the Second National Health and Nutrition Survey (NHANES II), in which higher levels of WBCs and lower serum albumin were associated with an increased risk of kidney failure or death related to kidney disease.5 In addition, elevated WBC count has been associated with more rapid kidney disease progression among those with type 1 diabetes.9
Fibrinogen was inversely associated with estimated GFR among those with CKD in the Heart and Soul Study, but not associated among those with normal kidney function.26
These discrepancies could be explained by significant differences in the populations studied, with the MDRD study having more polycystic kidney disease or primary glomerular disease, and no persons with diabetic kidney disease. Our study population is similar to the CHS study population, though younger, which may explain why our findings are generally consistent with those of CHS. Still, there are important differences between the findings in CHS and those presented here. Factor VIIc was associated with reduced risk of GFR decline in CHS, but factor VIIc was not associated with decreased estimated GFR in our study. These results suggest that factor VIIc is not an important hemostatic predictor of declining kidney function. On the other hand, strong associations were seen for factor VIIIc and VWF with declining kidney function in this study. These factors were not measured in CHS. Unlike CHS, we found similar associations for all markers in both African Americans and Whites.
We found that the associations were stronger among individuals with diabetes than among those without diabetes for albumin, white blood cell count, fibrinogen, von Willebrand factor and factor VIIIc. The reasons for these findings are speculative. Advanced glycation endproducts (AGEs; glycated proteins) are driven forward by hyperglycemia and increased AGE levels are observed even in cases of uncomplicated diabetes.27 AGEs, which stimulate inflammatory cytokine production, have also been implicated in the progression to diabetic nephropathy28, 29 and involved in inflammatory disorders.28 It is possible that increased inflammatory factors among individuals with diabetes represent elevated levels of AGEs, in addition to a measure of inflammation from other causes.30 Because individuals with diabetes more often are overweight and obese, it is also possible that adipose tissue serves as a source of inflammation.31 Additional adjustment for body mass index or waist circumference did not meaningfully change the results. These findings could have important implications for the progression of diabetes-related nephropathy. Despite stronger associations among diabetic individuals for several of the risk factors studied, elevated levels of inflammatory and hemostatic factors were also associated with incident CKD among persons without diabetes. The analytes studied may also be markers or mediators of underlying disease, such as endothelial damage. Albuminuria, which is a potent predictor of kidney disease progression,32 is thought to represent systemic endothelial cell dysfunction.33 Unfortunately, we did not have measures of urinary albumin excretion available with which to test this hypothesis. Elevated levels of these analytes are also indicative of a prothrombotic state, which may directly or indirectly impact progression of kidney disease. For instance, hypertensive patients have been shown to experience changes in platelet physiology; specific changes differed by presence or absence of target organ damage and may be implicative of underlying cardiovascular disease pathology, such as that related to abnormal platelet activation and a procoagulant state.34 There has also been other evidence of an activated coagulation system among hypertensive patients with mild to moderate kidney dysfunction,35
These results add to a growing body of evidence suggesting that inflammation and hemostasis are important pathways in the progression of kidney disease that are independent of major traditional risk factors. While a specific mechanism that can be targeted for intervention has not been identified, these findings may help focus investigations into pathologic mechanisms for CKD and have implications for the development of prevention and treatment strategies designed to reduce the impact of kidney disease in the population.
The authors thank the staff and participants of the ARIC study for their important contributions.
Support: The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, and N01-HC-55022. The work described in this article was supported in part by grants 5R01-DK-076770-02, 5T32-HL-007024-33, and 5T32-RR-023253-02 from the National Institutes of Health.
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