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Association between serum bilirubin and estimated glomerular filtration rate among diabetic patients.

1. Introduction

Serum bilirubin may protect against inflammation, cardiovascular disease (CVD), and all-cause mortality in adults [1, 2]. Moreover, current evidences demonstrate that mildly elevated serum bilirubin may confer potent antioxidant properties, as indicated by its ability to scavenge peroxyl radicals and to inhibit oxidation of low-density lipoprotein (LDL) derived lipids [3,4]. Lots of studies have shown a positive relationship between serum bilirubin and estimated glomerular filtration rate (eGFR) [5-9], showing that serum bilirubin has a potential renoprotective effect. We also demonstrated an independent positive association between serum bilirubin and eGFR in both genders among elderly persons [10]. Therefore, it is reasonable to speculate that serum bilirubin levels maybe negatively correlated with diabetic nephropathy and renal function among diabetic patients.

Several cross-sectional studies have shown that low serum bilirubin levels were significantly associated with decreased eGFR, and negatively associated with diabetic nephropathy in a hospital-based sample of diabetic patients [6, 7]. In a cohort of Japanese type 2 diabetic patients, Mashitani et al. [9, 11] demonstrated that serum bilirubin levels were prospectively associated with diabetic nephropathy progression, independent of possible confounders. In contrast, Targher et al. [12] found that serum bilirubin was negatively associated with eGFR, considering serum bilirubin as a renal risk factor. Thus, a relationship between serum bilirubin and renal function remains controversial.

We evaluated the relationship of serum bilirubin with confounding risk factors such as renal function, as well as hypertension, hyperglycemia, and lipids, using cross-sectional data from the Nomura study [10].

2. Methods

2.1. Subjects. Patients for this investigation were recruited among consecutive diabetic patients aged [greater than or equal to] 50 years that visited the Medical Department of Seiyo Municipal Nomura Hospital. Patients with serum bilirubin > 2.0mg/dL and severe cardiorenal (e.g., Gilbert's syndrome) or nutritional disorders that would affect blood pressure, lipid, and glucose metabolism were excluded. Thus, 509 persons were enrolled in the study. All procedures were approved by the Ethics Committee of Seiyo Municipal Nomura Hospital, and written informed consent was obtained from each patient.

2.2. Evaluation of Confounding Factors. Information on demographic characteristics and confounding factors was collected using clinical files in all cases. Body mass index (BMI) was calculated by dividing weight (in kilograms) by the square of the height (in meters). We measured systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the right upper arm of patients while in a sedentary position using a standard sphygmomanometer or an automatic oscillometric blood pressure recorder. Smoking status was quantified based on daily consumption and duration of smoking (pack-year) irrespective of the difference between current and past smoking status: never, light (<20 pack-year), moderate (20-39 pack-year), and heavy ([greater than or equal to] 40 pack-year). Total cholesterol (T-C), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG), creatinine (enzymatic method), uric acid, and serum bilirubin were measured during a fasting condition within 24 hours after admission. Low-density lipoprotein cholesterol (LDL-C) level was calculated by the Friedewald formula [13], and those patients with TG levels [greater than or equal to] 400 mg/dL were excluded. eGFR was calculated using CKD-EPI equations modified by a Japanese coefficient ([eGFR.sub.CKDEPI]): male, Cr [less than or equal to] 0.9 mg/dL, 141 x [(Cr/0.9).sup.-0,411] x [0.993.sup.age] x 0.813; Cr > 0.9 mg/dL, 141 x [(Cr/0.9).sup.-1.209] x [0.993.sup.age] x 0.813; female, Cr [less than or equal to] 0.7 mg/ dL, 144 x [(Cr/0.7).sup.-0,329] x [0.993.sup.age] x 0.813; Cr > 0.7 mg/dL, 144 x [(Cr/0.7).sup.-1,209] x [0.993.sup.age] x 0.813 [14]. Histories of antihypertensive, antidyslipidemic, and antidiabetic medication use were also evaluated. Moreover, ischemic stroke, ischemic heart disease, and peripheral vascular disease were defined as CVD.

2.3. Statistical Analysis. All values are expressed as the mean [+ or -] standard deviation (SD), unless otherwise specified, and in the cases of parameters with nonnormal distribution (such as TG, FPG, and serum bilirubin), the data are shown as median (interquartile range) values. In all the analyses, parameters with nonnormal distributions were used after log-transformation. Statistical analysis was performed using IBM SPSS Statistics Version 21 (Statistical Package for Social Science Japan, Inc., Tokyo, Japan). Pearson's correlations were calculated in order to characterize the associations between various characteristics and eGFR. A multiple regression model was employed to evaluate the contribution of each confounding factor to eGFR. Subjects were divided into four groups based on the stage of eGFR (stage 1, eGFR [greater than or equal to] 90; stages 2, 89.9 to 60; stage 3a, 59.9 to 45.0; stage 3b, 44.9 to 30.0; stage 4, <30 mL/min/1.73 [m.sup.2]) and quartile of serum bilirubin (Q-1, 0.13-0.50; Q-2, 0.51-0.70; Q-3, 0.71-1.00; Q-4, 1.01-1.97 mg/dL), and logistic regression analyses were used to test significant determinants of CKD serving as the dichotomous outcome variable. To examine the consistency of the observed association between serum bilirubin levels and eGFR, we performed subgroup analyses by age (<80, [greater than or equal to] 80 years), medication (such as antihypertensive, antidyslipidemic, and antidiabetic agents) (absence, presence), serum uric acid (first-second tertiles, third tertile), and CVD (absence, presence), and interaction between serum bilirubin and the subgroups was analyzed by a general linear model. A value of P < 0.05 was considered significant.

3. Results

3.1. Subject Background Factors of the Subjects. Table 1 shows the value of background factor of the subjects. The subjects comprised 230 men aged 77 [+ or -] 10 (range, 50-100) years and 279 women aged 81 [+ or -] 10 (range, 50-101) years. Mean uric acid, Cr, and eGFR in the study sample were 5.5 [+ or -] 2.1 (SD) mg/dL, 1.1 [+ or -] 0.9 mg/dL, and 56.0 [+ or -] 20.2 mL/min/1.73 [m.sup.2] with 1.0% stage 1, 51.5% stage 2, 21.2% stage 3a, 14.5% stage 3b, and 12.8% stage 4, respectively. Median serum bilirubin level was 0.7 (interquartile range, 0.5-1.0) mg/dL. Prevalence of antihypertensive, antidyslipidemic, antidiabetic medication, and CVD was 56.2%, 8.4%, 43.6%, and 40.1%, respectively.

[FIGURE 1 OMITTED]

3.2. Relationship of Risk Factors, including Serum Bilirubin and eGFR. Table 2 shows the relationship between participant characteristics and eGFR. Serum bilirubin (r = 0.22, P < 0.001) along with age, DBP, prevalence of antihypertensive medication, TG, HDL-C, LDL-C, and serum uric acid correlated significantly with eGFR (Figure 1). Stepwise multiple regression analysis using eGFR as an objective variable, adjusted for risk factors as explanatory variables, showed that serum bilirubin ([beta] = 0.13, P < 0.001) was significantly and independently associated with eGFR, in addition to gender, age, prevalence of antihypertensive medication, HDL-C, and serum uric acid.

3.3. Relationship between Serum Bilirubin Categories and Risk for Reduced eGFR (Stages 3 + 4 or Stages 3b + 4). Table 3 shows the odds ratio of renal dysfunction for each quartile increase in serum bilirubin. eGFR values decreased significantly and progressively with decreasing serum bilirubin. The prevalence of eGFR < 60 mL/min/1.73 [m.sup.2] (stages 3 + 4) for each quartile in serum bilirubin was 40.8% Q-4, 43.2% Q-3, 51.1% Q-2, and 58.9% Q-1, respectively. Compared with Q-4 in serum bilirubin, nonadjusted, age and gender-adjusted, and multivariate-adjusted odds ratios {95% confidence interval (CI)} of stages 3 + 4 for Q-1 in serum bilirubin were 2.08 (1.25-3.44), 1.82 (1.07-3.09), and 1.53 (0.83-2.81), respectively. Moreover, the prevalence of eGFR < 45 mL/min/1.73 [m.sup.2] (stages 3b + 4) for each quartile in serum bilirubin was 17.6% Q-4, 21.6% Q-3, 27.4% Q-2, and 42.7% Q-1, respectively. Compared with Q-4, nonadjusted, age and gender-adjusted, and multivariate-adjusted odds ratios (95% CI) of stages 3b + 4 for Q-1 were 3.50 (1.95-6.23), 3.12 (1.72-5.65), and 3.53 (1.71-7.26), respectively.

3.4. Relationship of Serum Bilirubin and eGFR within Selected Subgroups. Next, to control potential confounding factors, the data were further stratified by gender, age, medication (antihypertensive, antidyslipidemic, and antidiabetic agents), serum uric acid (first-second tertiles, third tertile), and prevalence of CVD (Table 4). The standardized coefficients for eGFR were significant in all subgroups other than the prevalence of CVD, and there were significant interactions only between the two groups regarding CVD.

4. Discussion

To examine the possible contribution of decreased serum bilirubin to renal dysfunction among diabetic persons, we studied the relationship between potential confounding risk factors including serum bilirubin and eGFR. This study showed a graded decrease in eGFR with decreasing serum bilirubin. Individuals with hypobilirubinemia (first quartile of serum bilirubin, <0.50mg/dL) showed increased risk for stage 3b CKD (eGFR < 45 mL/min/1.73 [m.sup.2]). Moreover, the strength of serum bilirubin level as an independent determinant of eGFR was similar to those of known factors such as gender, age, prevalence of antihypertensive medication, HDL-C, and serum uric acid. To our knowledge, few epidemiologic studies have quantified the link between decreased serum bilirubin and renal dysfunction in diabetic patients. Thus, we think that serum bilirubin levels may be utilized as a provisional new confounding factor of diabetic nephropathy that can be measured easily and applied in medical practice.

Several studies have shown that decreased serum bilirubin is a risk factor for the development of CKD among type 2 diabetic individuals. Inoguchi et al. [15] showed a lower prevalence of vascular complications as well as reduced markers of oxidative stress and inflammation in patients with Gilbert's syndrome, which is a congenital hyperbilirubinemia, and diabetes. A community-based cross-sectional study in Korea [7] found that total serum bilirubin levels were negatively correlated with 24-hour proteinuria and positively associated with eGFR after adjusting for potential confounding factors in 612 diabetic patients. Fukui et al. [6] found that serum bilirubin level was independently and negatively associated with albuminuria in a hospitalbased cross-sectional study in 633 Japanese type 2 diabetic patients. In addition, it was shown that serum bilirubin levels were higher in patients without diabetic nephropathy than in those with diabetic nephropathy. In a longitudinal cohort study of 12,823 Korean male workers without CKD or proteinuria at baseline, higher serum direct bilirubin levels were significantly associated with a lower risk of developing CKD (eGFR, <60 mL/min/1.73 [m.sup.2]), even after adjusting for potential confounding factors [5]. In the single-center longitudinal observational cohort study of type 2 diabetic patients, Toya et al. [11] found that higher serum bilirubin levels, within the normal range, were associated with a lower risk of progression from microalbuminuria to macroalbuminuria. In a hospital-based study of 2,678 US diabetic outpatients (mean age: 55 [+ or -] 18 years), Targher et al. [12] found that serum bilirubin levels were negatively associated with eGFR. However, in that study, no adjustment was made for potential confounding factors. Longitudinal data from 2,511 type 2 diabetic Japanese patients showed that multivariable-adjusted odds ratios for progression from microalbuminuria to macroalbuminuria for the second, third, and fourth quartiles of serum bilirubin levels were 0.89 (95% CI 0.49-1.58), 0.93 (0.47-1.83), and 0.33 (0.13-0.84), respectively. However, this trend disappeared after adjustment for hemoglobin level [9]. In our hospital-based sample of 509 individuals, we found that decreased serum bilirubin levels were significantly associated with decreased eGFR, and multivariate adjusted-odds ratio of hypobilirubinemia (0.13-0.50 mg/dL) for stage 3b (eGFR < 45mL/min/1.73[m.sup.2]) was 3.53 (1.71-7.26).

The mechanism by which serum bilirubin level is associated with a lower risk of CKD is not completely understood. Bilirubin has been described as the most powerful endogenous antioxidant substance in vitro [16] when acting alone and complexed with serum albumin to serve as a superoxide scavenger and peroxyl radical trapping antioxidant [17]. Hyperglycemia causes mitochondrial superoxide overproduction in vascular endothelial cells [18]. A recent study in a rodent model discovered a protective effect of bilirubin against diabetic nephropathy through inhibition of renal nicotinamide adenine dinucleotide phosphate- (NADPH-) dependent superoxide production and both hyperglycemia and angiotensin-II-induced production of reactive oxygen species [19]. Taken together, the present results suggest that bilirubin might have a protective role in the progression of diabetic nephropathy, particularly in diabetic patients with greater oxidative stress such as CVD. In our study, the standardized coefficient for eGFR was significant in the subgroup with prevalence of CVD, and there were significant interactions between the two groups regarding CVD.

We must be aware of the limitations to the present study. First, due to the cross-sectional study design, the present results are inherently limited in the ability to eliminate causal relationships between serum bilirubin and eGFR among diabetic patients. Second, our definition of eGFR is based on a single assessment of serum creatinine, which may introduce a misclassification bias. Third, estimating GFR listed as the CKD-EPI equation tends to be less accurate in subjects with normal renal function and CKD than GFR when inulin clearance is used, but is more accurate than serum creatinine or eGFR using the Modification of Diet in Renal Disease (MDRD) formula [14]. Fourth, in this study, CKD may have been misclassified with eGFR > 60 mL/min/1.73 [m.sup.2] and proteinuria as mildly reduced renal function because renal dysfunction was defined as reduced eGFR irrespective of the presence or absence of proteinuria. Therefore, the demographics and referral source may limit generalizability.

5. Conclusion

The present study showed that decreased serum bilirubin levels are strongly associated with decreased eGFR among diabetic patients. The underlying mechanism behind this relationship is unclear, but seems to be independent of traditional confounding risk factors such as age, hypertension, and dyslipidemia. For community-dwelling diabetic patients, prospective population-based studies are needed to investigate the mechanisms underlying this association.

http://dx.doi.org/10.1155/2015/480418

Conflict of Interests

The authors declare that they have no conflict of interests.

Acknowledgment

This study was supported in part by a research fund from the Japan Health Foundation.

References

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[14] M. Horio, E. Imai, Y. Yasuda, T. Watanabe, and S. Matsuo, "Modification of the CKD epidemiology collaboration (CKD-EPI) equation for Japanese: accuracy and use for population estimates," American Journal of Kidney Diseases, vol. 56, no. 1, pp. 32-38, 2010.

[15] T. Inoguchi, S. Sasaki, K. Kobayashi, R. Takayanagi, and T. Yamada, "Relationship between Gilbert syndrome and prevalence of vascular complications in patients with diabetes," Journal of the American Medical Association, vol. 298, no. 12, pp. 1398-1400, 2007.

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[19] M. Fujii, T. Inoguchi, S. Sasaki et al., "Bilirubin and biliverdin protect rodents against diabetic nephropathy by downregulating NAD(P)H oxidase," Kidney International, vol. 78, no. 9, pp. 905-919, 2010.

Takeaki Katoh, (1,2) Ryuichi Kawamoto, (1) Katsuhiko Kohara, (2) and Tetsuro Miki (2)

(1) Department of Community Medicine, Ehime University Graduate School of Medicine, Ehime 791-0295, Japan

(2) Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Ehime 791-0295, Japan

Correspondence should be addressed to Ryuichi Kawamoto; rykawamo@m.ehime-u.ac.jp

Received 27 October 2014; Revised 19 December 2014; Accepted 2 January 2015

Academic Editor: Hamadi Fetoui
Table 1: Characteristics of various risk factors of the subjects.

Characteristic (N = 509)                            Value

Gender male (%)                                     45.2
Age (years)                                    79 [+ or -] 10
Body mass index ([dagger]) (kg/[m.sup.2])     21.5 [+ or -] 3.9
Smoking status ([double dagger]) (%)          74.7/2.2/9.8/13.4
Systolic blood pressure (mmHg)                 137 [+ or -] 27
Diastolic blood pressure (mmHg)                75 [+ or -] 15
Antihypertensive medication (%)                     56.2
Triglycerides (mg/dL)                            82 (61-114)
HDL cholesterol (mg/dL)                        55 [+ or -] 17
LDL cholesterol (mg/dL)                        104 [+ or -] 35
Antidyslipidemic medication (%)                      8.4
Fasting blood glucose (mg/dL)                   151 (132-183)
Antidiabetic medication (%)                         43.6
Serum uric acid (mg/dL)                       5.5 [+ or -] 2.1
Serum creatinine (mg/dL)                      1.1 [+ or -] 0.9
eGFR (mL/min/1.73 [m.sup.2])                 56.0 [+ or -] 20.2
CKD stage (1 + 2/3a/3b/4), %                 51.5/21.2/14.5/12.8
Serum bilirubin (mg/dL)                         0.7 (0.5-1.0)
Cardiovascular disease (%)                          40.1

Data are presented as means [+ or -] standard deviation.
HDL: high-density lipoprotein; LDL: low-density lipoprotein;
eGFR: estimated glomerular filtration rate. ([dagger]) Body
mass index was calculated using weight in kilograms divided
by the square of the height in meters. ([double dagger])
Smoking status: daily consumption (pack) x duration of
smoking (year) {never, light (<20 pack-year), moderate (20-
39 pack x year), and heavy ([greater than or equal to] 40
pack-year)}. Data for triglycerides, fasting plasma glucose,
and serum bilirubin were skewed and are presented as median
(interquartile range) values.

Table 2: Relationship between various risk factors including
serum bilirubin and estimated glomerular filtration rate.

                                                   Multiple linear
                                                   regression analysis

                      Pearson's          Forced          Stepwise
Characteristic       correlation     method [beta]    method [beta]
(N = 509)            r (P value)       (P value)        (P value)

Gender              -0.08 (0.059)    -0.11 (0.006)    -0.07 (0.032)
  (male = 0,
  female = 1)
Age                 -0.35 (<0.001)   -0.29 (<0.001)   -0.27 (<0.001)
Body mass index     -0.02 (0.645)    -0.03 (0.397)          --
Smoking status       0.02 (0.738)    -0.06 (0.129)          --
Systolic blood       0.05 (0.260)          --               --
  pressure
Diastolic blood     0.21 (<0.001)     0.05 (0.174)          --
  pressure
antihypertensive    -0.18 (<0.001)   -0.08 (0.026)    -0.09 (0.004)
  medication
Triglycerides       -0.17 (<0.001)   -0.06 (0.152)          --
HDL cholesterol      0.14 (0.002)     0.06 (0.077)     0.09 (0.008)
LDL cholesterol      0.11 (0.017)     0.07 (0.057)          --
Antidyslipidemic     0.00 (0.974)    -0.02 (0.573)          --
  medication
Fasting blood        0.03 (0.501)     0.01 (0.736)          --
  glucose
Antidiabetic         0.00 (0.983)    -0.04 (0.233)          --
  medication
Serum uric acid     -0.59 (<0.001)   -0.53 (<0.001)   -0.56 (<0.001)
Serum bilirubin     0.22 (<0.001)    0.12 (<0.001)    0.13 (<0.001)
[R.sup.2]                 --         0.50 (<0.001)    0.49 (<0.001)

r: Pearson's correlation coefficient; [beta]: standardized
coefficient; [R.sup.2]: multiple coefficient of
determination. Data for triglycerides, fasting plasma
glucose, and serum bilirubin were skewed and log-
transformed for analysis.

Table 3: Relationship between serum bilirubin categories and
risk for reduced eGFR.

                       Quartiles of serum bilirubin (mg/dL)

                            Q-4                  Q-3
Characteristic           1.01-1.97            0.71-1.00
N = 509                   N = 125               N= 125

eGFR (mL/min/1.73    59.5 [+ or -] 17.9   60.2 [+ or -] 18.8
  [m.sup.2])
Prevalence of            51 (40.8)            54 (43.2)
    eGFR
    <60, N (%)
  Nonadjusted OR            1.00           1.10 (0.67-1.82)
    (95% CI)
  Age and gender            1.00           1.23 (0.72-2.09)
    adjusted
    OR (95% CI)
  Multivariate              1.00           1.30 (0.70-2.41)
    adjusted
    OR (95% CI)
Prevalence of            22 (17.6)            27 (21.6)
    eGFR
    <45, N (%)
  Nonadjusted OR            1.00           1.29 (0.69-2.42)
    (95% CI)
  Age and gender            1.00           1.33 (0.70-2.54)
    adjusted
    OR (95% CI)
  Multivariate              1.00           1.68 (0.78-3.64)
    adjusted OR
    (95% CI)
    ([section])

                               Quartiies of serum bilirubin (mg/dL)

                            Q-2                  Q-1           P value
Characteristic           0.51-0.70            0.13-0.50
N = 509                   N = 135              N = 124

eGFR (mL/min/1.73    56.0 [+ or -] 18.9   48.1 [+ or -] 22.9   <0.001
  [m.sup.2])
Prevalence of            69 (51.1)            73 (58.9)         0.018
    eGFR
    <60, N (%)
  Nonadjusted OR      1.52 (0.93-2.48)     2.08 (1.25-3.44)     0.018
    (95% CI)
  Age and gender      1.52 (0.91-2.54)     1.82 (1.07-3.09)     0.133
    adjusted
    OR (95% CI)
  Multivariate        1.48 (0.81-2.72)     1.53 (0.83-2.81)     0.514
    adjusted
    OR (95% CI)
Prevalence of            37 (27.4)            53 (42.7)        <0.001
    eGFR
    <45, N (%)
  Nonadjusted OR      1.77 (0.97-3.21)     3.50 (1.95-6.25)    <0.001
    (95% CI)
  Age and gender      1.71 (0.93-3.14)     3.12 (1.72-5.65)     0.001
    adjusted
    OR (95% CI)
  Multivariate        1.74 (0.83-3.65)     3.53 (1.71-7.26)     0.004
    adjusted OR
    (95% CI)
    ([section])

CKD: chronic kidney disease: OR: odds ratio; CI: confidence
interval. ([section]) Adjusted for all confounding factors
in the stepwise method in Table 2 by multiple logistic
regression analysis. Data for triglycerides were skewed and
log-transformed for analysis.

Table 4: Relationship between serum bilirubin and estimated
glomerular filtration rate within selected subgroups.

Characteristics (N = 509)    N    [beta] (P value)   P-interaction

Gender
  Men                       230     0.13 (0.013)         0.923
  Women                     279     0.14 (0.001)
Age
  < 80 years                200     0.21 (0.001)         0.075
  [greater than or          279     0.10 (0.028)
    equal to] 80 years
Medication
  Absence                   141     0.12 (0.047)         0.670
  Presence                  368    0.14 (<0.001)
Serum uric acid
  First-second tertiles     319    0.18 (<0.001)         0.830
  Third tertile             190    0.13 (<0.001)
Cardiovascular disease
  Absence                   305     0.05 (0.210)         0.020
  Presence                  204    0.21 (<0.001)

[beta]: standardized coefficient. Medication included
antihypertensive, antidyslipidemic, and antidiabetic agents.
([section]) Adjusted for all confounding factors in the
stepwise method in Table 2 by multiple linear regression
analysis.
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Title Annotation:Research Article
Author:Katoh, Takeaki; Kawamoto, Ryuichi; Kohara, Katsuhiko; Miki, Tetsuro
Publication:International Scholarly Research Notices
Date:Jan 1, 2015
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