663
Views
10
CrossRef citations to date
0
Altmetric
Clinical Study

Association of Inflammatory Biomarkers with Metabolic Syndrome in Hemodialysis Patients

, , , &
Pages 1109-1113 | Received 24 Apr 2012, Accepted 06 Jul 2012, Published online: 14 Aug 2012

Abstract

The relative importance of inflammatory markers in relation with metabolic syndrome (MeS) in hemodialysis (HD) patients is uncertain. This study investigated the association between MeS and high-sensitive C-reactive protein (hsCRP), hallmark of inflammation, and other inflammatory-related biomarkers. The study included 153 patients who were dialyzed at least for the last 3 months. The serum level of hsCRP was assessed by high-sensitive Enzyme-linked immunosorbent assay (ELISA). MeS was defined using the modified National Cholesterol Education Program Adult Treatment Panel III (ATP-III). Ninety-one HD patients (59.5%) were diagnosed as having MeS. Lower level of high-density lipoprotein-cholesterol (HDL-C) was the most prevalent MeS component (85.6%). The serum level of hsCRP in these patients was significantly higher than that in HD patients without MeS (2.3 ± 1.7 vs. 1.7 ± 1.6 mg/dL, p = 0.03). A significant linear increase in the hsCRP levels was found according to the number of MeS components (β = 0.09, p = 0.022). The study concluded that increasing inflammatory biomarkers, especially hsCRP, is associated with MeS in HD patients.

INTRODUCTION

A considerable proportion of hemodialysis (HD) patients have multiple metabolic abnormalities that may accelerate atherosclerosis along with other cardiovascular-related risk factors. Metabolic syndrome (MeS) is characterized by a combination of obesity, hypertension, dyslipidemia [with an elevated level of triglycerides (TG) and a lower level of high-density lipoprotein-cholesterol (HDL-C)], hyperglycemia, and insulin resistance. The prevalence of MeS in HD patients is reported from 40% to 60%.Citation1–5 This syndrome is considered as a significant risk factor for cardiovascular disease, mortality, and chronic kidney disease in the general population.Citation6–9 MeS also is a predictive parameter of mortality for HD patients,Citation10,11 and predicts hospitalization in these patients.Citation2

Although the fundamental mechanisms of pathophysiology of MeS are still not clear, contribution of low-grade systemic inflammation is considerable.Citation12 A substantial number of HD patients have chronic low-grade inflammation. Recently, chronic inflammation has been identified as a nonclassic risk factor of cardiovascular disease in end-stage renal disease (ESRD) patients.Citation13 Approximately 30–50% of patients with ESRD have elevated serum level of high-sensitive C-reactive protein (hsCRP), a marker of systemic inflammation.Citation14,15 The cardiovascular mortality in HD patients is directly related to high levels of CRP.Citation16

Several studies have also shown a strong relationship between elevated hsCRP levels and risk of MeS in general population.Citation12,17–23 However, the association between inflammatory biomarkers and MeS and its components in HD patients has not been examined extensively. This study investigated the relationships between the components of MeS and hsCRP, as hallmark of inflammation, and other inflammatory-related biomarkers including ferritin, albumin, transferrin, and uric acid in HD patients.

MATERIALS AND METHODS

A total of 202 patients with chronic renal failure, who were hemodialyzed at least for the last 3 months in three dialysis centers in Tehran, were included in the study. Patients older than 70; those with acute or chronic infective disorders; heart or brain attack, major trauma, or surgery in recent 3 months; or immunosuppressive therapy were excluded from this study. Finally, the study included 153 patients. All participants signed informed written consent. The study was approved by the ethical committee of Tehran University of Medical Sciences.

A standard questionnaire was used. Body weight (BW) was measured to the nearest half-kilogram with the patient in light clothing without shoes. Height was measured to the nearest half centimeter. Waist circumference (WC) was measured in a vertical plane, midway between the inferior margin of the ribs and the superior border of the iliac crest. Body mass index (BMI) was calculated as weight (kilograms) divided by height squared (meters). Blood pressure (BP) at baseline was measured with the patient in a sitting position before HD.

Fasting blood samples were taken before the start of the HD. The serum level of hsCRP and ferritin were assessed by high-sensitive Enzyme-linked immunosorbent assay (ELISA) (Pars Azmoon Inc., Tehran, Iran) and electrochemiluminescence methods, respectively. Transferrin, albumin, and uric acid levels were assessed with colorimetric methods. Plasma levels of glucose, total cholesterol, TG, and HDL-C were assessed with a conventional auto-analyzer. Low-density lipoprotein cholesterol (LDL-C) was calculated in those with TG < 350 mg/dL using Fridwald formula. Plasma levels of glycated hemoglobin A1c (HbA1c) was assessed with high-performance liquid chromatography.

MeS was defined using the modified National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP-III) criteria, having three or more of the following criteria: (1) abdominal obesity: WC ≥ 102 cm in men and ≥88 cm in women, (2) hyperglycemia: fasting plasma glucose levels (FPG) ≥100 mg/dL or on medication or previously diagnosed type 2 diabetes, (3) low HDL-C: <40 mg/dL in men or <50 mg/dL in women or on medication, (4) hypertriglyceridemia: TG ≥ 150 mg/dL or on drug treatment, and (5) hypertension: systolic BP (SBP) ≥ 130 mm Hg or diastolic BP (DBP) ≥ 85 mm Hg or under anti-hypertensive drug treatment.

SPSS 11.0 (SPSS Inc., Chicago, IL, USA) software was used for statistical analysis. Data were examined for normal distribution by Kolmogorov–Smirnov statistics. Student’s t-test and the Mann–Whitney U-test were used for independent normally and non-normally distributed continuous variables, respectively. One-way analysis of variance (ANOVA) was used when the grouping variable had more than two levels. Nominal variables were analyzed by means of chi-square test. Correlation between laboratory variables was evaluated by Spearman’s correlation analysis. Logistical regression analysis was used to evaluate the correlation between measured variables and the presence of MeS. All inflammatory biomarker analyses were adjusted for age and sex and ferritin analysis was adjusted for Venofer intake. Significance was defined at the level of p < 0.05.

RESULTS

Of the 153 HD patients included in this study, 84 (54.9%) were male and 69 (45.1%) were female. Etiologies of renal failure were hypertension (n = 42, 27.5%), diabetes mellitus (n = 33, 21.6%), diabetes and hypertension (n = 21, 13.7%), glomerulonephritis (n = 8, 5.2%), polycystic kidney (n = 8, 5.2%), unknown (n = 20, 13.1%), and others (n = 21, 13.7%). The levels of inflammatory biomarkers were not significantly different between the different etiologies of renal failure.

Ninety-one patients (59.5%) were diagnosed as having MeS as defined by the ATP-III. The clinical characteristics of the HD patients, with or without MeS, are presented in . Overall, 97.2% (n = 149) of HD patients had at least one MeS component. Of the patients with MeS, 43 (47.3%) had three components, 35 (38.4%) had four components, and 13 (14.3%) had five components of MeS. In HD patients, low HDL-C was the most prevalent MeS component (n = 131, 85.6%), followed by hypertension (n = 108, 71.1%), hyperglycemia (n = 86, 56.2%), hypertriglyceridemia (n = 57, 37.3%), and obesity (n = 44, 28.7%).

Table 1. The clinical characteristics of the HD patients with or without metabolic syndrome (MeS).

Table 2. Relationship between inflammation biomarkers and metabolic syndrome (MeS) components.

A significant linear increase in hsCRP levels was found according to the number of MeS components (). Also, an increase of 0.09 in hsCRP (95% CI 0.04–0.16, p = 0.022) was observed with increase in each component of MeS in linear regression analysis. However, this relation was not significant for other inflammatory biomarkers. The adjusted mean value of each inflammatory biomarker was compared between the HD subjects with or without each MeS component (). A significant difference in hsCRP and ferritin levels were observed in those with hyperglycemia (p = 0.02 and 0.04, respectively). In addition, decreased albumin level was observed in those with low HDL-C (p = 0.01).

Figure 1. Linear relation between increase in hsCRP levels and the number of metabolic syndrome (MeS) components.

Figure 1. Linear relation between increase in hsCRP levels and the number of metabolic syndrome (MeS) components.

The serum level of hsCRP was positively correlated with FPG (p = 0.01) and HbA1c (p = 0.016), and inversely correlated with HDL-C (p = 0.041). Serum albumin level had significant positive correlation with Hb1Ac (p = 0.049), total cholesterol (p = 0.007), and TG (p = 0.004), and negative correlation with HDL-C (p = 0.002). However, the absolute values of the all correlation coefficients were low. Serum levels of ferritin showed no significant correlation with characteristics of HD patients.

Using logistic regression, abdominal obesity (p = 0.043), hypertriglyceridemia (p = 0.021), LDL-C (p = 0.035), low HDL-C (p = 0.002), and hyperglycemia (p = 0.035) were found to be independent predictors of MeS in HD patients.

DISCUSSION

This study has shown that the HD patients with MeS have significantly higher hsCRP and ferritin levels, as inflammatory biomarkers, in comparison with HD patients without MeS. In addition, a significant linear relation was found between hsCRP levels and the number of components of MeS. Moreover, WC, TG, LDL-C, HDL-C, and DM were independent predictors of MeS in HD patients.

Previous studies reported MeS in 40–60% of HD patients.Citation1–5 In this study, the prevalence was 59.5%, which is consistent with high prevalence of MeS in general Iranian population (50.8%).Citation24 Relatively little is known about the precise causes of such a high prevalence. This may have been the result of greater altering in the diets of the Iranian population and a greater reduction in physical activity.Citation25 According to the results of other investigators, hypertension usually was the most common component of MeS in HD patients.Citation26–28 However, our results showed that low HDL-C (85.6%) is the most prevalent MeS element in these patients, followed by hypertension (71.1%), which is in agreement with recent investigation in Iranian general population.Citation24 Similar to previous studies, MeS was prevalent among diabetics and female, and HD patients had higher age, WC, BMI, SBP, DBP, FPG, HbA1c, TG, and lower HDL-C levelsCitation3,26–33 and are just beginning the dialysis process.Citation29

Serum level of hsCRP, a marker of systemic inflammation, was more strongly related with MeS than other inflammatory biomarkers in regard not only to the number of components but also to their clustering, in agreement with previous reports in general population.Citation34,35 However, another study did not found significant relation between hsCRP and incidence of MeS in HD patients, may be due to lower sample size.Citation3

Serum level of hsCRP was significantly positively correlated with FPG and HbA1c, and negatively with HDL-C levels. Our results confirm the concept that inflammatory states play a primary role in the initiation of insulin resistance, and hence MeS.Citation12,36,37 The mechanisms responsible for insulin resistance due to inflammation might be related to the activation of serine/threonine phosphorylation cascades that lead to the activation of nuclear factor and to the serine phosphorylation of elements of insulin receptor signaling system.Citation38 On the other hand, adipose tissue is not only the energy storage, but also now recognized as an immune organ that releases various peptides and inflammatory cytokines, such as hsCRP, that cause disturbance to the insulin-signaling pathway.Citation36,37,39 Abdominal obesity, defined using WC, had a major role for the elevation of hsCRP levels and considered as independent predictor of MeS.Citation12

A number of studies reported that chronic inflammatory diseases, particularly renal failure, are associated with an increase in ferritin levels Citation40,Citation41 and a high ferritin level in these patients represents an inflammatory marker.Citation42 We also showed that the serum ferritin levels were associated with the presence of MeS in HD patients. One previous study found no significant difference in the level of ferritin in HD patients with and without MeS, but reported an increasing serum iron level in HD patients with MeS.Citation3

Serum albumin level had significant positive correlation with Hb1Ac, total cholesterol, and TG, and negative correlation with HDL-C.

The major limitation of this study is the cross-sectional nature, which does not allow us for inferring causality from the present results. In addition, some medication, such as statins and angiotensin II modulators, could decrease hsCRP level,Citation43,44 which had not been considered in this study.

In conclusion, inflammatory biomarkers, especially hsCRP, had correlation with MeS in HD patients. As hsCRP has been practically established as a cardiovascular disease predictor, which is considered as the most common cause of mortality in HD patients,Citation45–47 reducing serum level of inflammatory biomarkers, particularly hsCRP and ferritin, should be considered for the prevention of MeS, cardiovascular disease, and finally mortality in HD patients.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

REFERENCES

  • Ucar E, Huzmeli C, Guven O, . Frequency of metabolic syndrome among hemodialysis patients according to NCEP-ATP III and IDF definitions. Ren Fail. 2009;31:221–228.
  • Yang SY, Chiang CK, Hsu SP, . Metabolic syndrome predicts hospitalization in hemodialysis patients: A prospective Asian cohort study. Blood Purif. 2007;25:252–259.
  • Rasic-Milutinovic Z, Perunicic G, Pljesa S, . Metabolic syndrome in HD patients: Association with body composition, nutritional status, inflammation and serum iron. Intern Med. 2007;46:945–951.
  • Tsangalis G, Papaconstantinou S, Kosmadakis G, . Prevalence of the metabolic syndrome in hemodialysis. Int J Artif Organs. 2007;30:118–123.
  • Lee CC, Lee RP, Subeq YM, . Fasting serum total ghrelin level inversely correlates with metabolic syndrome in hemodialysis patients. Arch Med Res. 2008;39:785–790.
  • Alberti KG, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A consensus statement from the international diabetes federation. Diabetes Med. 2006;23:469–480.
  • Isomaa B, Almgren P, Tuomi T, . Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care. 2001;24:683–689.
  • Grundy SM, Cleeman JI, Daniels SR, . Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation. 2005;112:2735–2752.
  • Peralta CA, Kurella M, Lo JC, Chertow GM. The metabolic syndrome and chronic kidney disease. Curr Opin Nephrol Hypertens. 2006;15:361–365.
  • Shinohara K, Shoji T, Emoto M, . Insulin resistance as an independent predictor of cardiovascular mortality in patients with endstage renal disease. J Am Soc Nephrol. 2002;13: 1894–1900.
  • Stolic R, Trajkovic G, Jovanovic A, . Association of metabolic changes with mortality of patients treated by peritoneal dialysis or hemodialysis. Ren Fail. 2010;32(7):778–783.
  • Mahajan A, Jaiswal A, Tabassum R, . Elevated levels of C-reactive protein as a risk factor for metabolic syndrome in Indians. Atherosclerosis. 2012;220(1):275–281.
  • Sarnak MJ, Levey AS. Cardiovascular disease and chronic renal disease: A new paradigm. Am J Kidney Dis. 2000;35(4 Suppl. 1):S117–S131.
  • Engström G, Lind P, Hedblad B, . Lung function and cardiovascular risk: Relationship with inflammation-sensitive plasma proteins. Circulation. 2002;106(20):2555–2560.
  • Razeghi E, Parkhideh S, Ahmadi F. Khashayar 2, serum CRP levels in pre- dialysis, patient. Ren Fail. 2008;30:193–198.
  • Varghese K, Cherian G, Abraham UT, Hayat NJ, Johny KV. Predictors of coronary disease in patients with end stage renal disease. Ren Fail. 2001;23(6):797–806.
  • Rutter MK, Meigs JB, Sullivan LM, . C-reactive protein, the metabolic syndrome, and prediction of cardiovascular events in the Framingham offspring study. Circulation. 2004;110(4): 380–385.
  • Wilson PWF, D’Agostino RB, Parise H, . Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation. 2005;112(20):3066–3072.
  • Ye X, Yu Z, Li H, . Distributions of C-reactive protein and its association with metabolic syndrome in middle-aged and older Chinese people. J Am Coll Cardiol. 2007;49(17):798–805.
  • Mahadik SR, Deo SS, Mehtalia SD. Relation of C-reactive protein with the components of metabolic syndrome in Asian Indian subjects. Diabetes Metab Syndr Res Rev. 2008;2(1):29–35.
  • Forouhi NG, Sattar N, McKeigue PM. Relation of C-reactive protein to body fat distribution and features of the metabolic syndrome in Europeans and South Asians. Int J Obes Relat Metab Disord. 2001;25(9):1327–1331.
  • Festa A, DÁgostino Jr R, Howard G, . Chronic subclinical inflammation as a part of the insulin resistance syndrome: The Insulin Resistance Atherosclerosis Study (IRAS). Circulation. 2000;102(1):42–47.
  • Frohlich M, Imhof A, Berg G, . Association of C-reactive protein and features of metabolic syndrome: A population based study. Diabetes Care. 2000;23(12):1835–1839.
  • Esmaillzadeh A, Mirmiran P, Azadbakht L, Etemadi A, Azizi F. High prevalence of the metabolic syndrome in Iranian adolescents. Obesity. 2006;14(3):377–382.
  • Ghassemi H, Harrison G, Mohammad K. An accelerated nutrition transition in Iran. Public Health Nutr. 2002;5:149–155.
  • Hsu CY, McCulloch CE, Iribarren C, . Body mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144:21–28.
  • Williams JD, Woods HF. Insulin resistance, the metabolic syndrome and renal failure – Is there a special problem for patients treated with peritoneal dialysis? Eur Endocrine Rev. 2006;15:54–59.
  • Bakker SL, Gansevoort RT, Zeeuw DD. Metabolic syndrome: A fata morgana? Nephro Dial Transplant. 2007;22:15–20.
  • Young DO, Lund RJ, Haynatzki G, Dunlay RW. Prevalence of the metabolic syndrome in an incident dialysis population. Hemodial Int. 2007;11:86–95.
  • Armstrong KA, Hiremagalur B, Haluska BA, . Free fatty acids are associated with obesity, insulin resistance, and atherosclerosis in renal transplant recipients. Transplantation. 2005;80:937–944.
  • Armstrong KA, Campbell SB, Hawley CM, Nicol DL, Johnson DW, Isbel NM. Obesity is associated with worsening cardiovascular risk factor profiles and proteinuria progression in renal transplant recipients. Am J Transplant. 2005;5:2710–2718.
  • Elsaid SA, Hamada MA, Alsaran KA. Obesity and metabolic syndrome in Saudi hemodialysis patients. JNRT. 2009;2:18–27.
  • Stoli R, Trajkovi G, Peri V, . Frequency and characteristics of metabolic disorders in patients on hemodialysis. Vojnosanit Pregl. 2008;65:205–209.
  • Salmenniemi U, Ruotsalainen E, Pihlajamäki J, . Multiple abnormalities in glucose and energy metabolism and coordinated changes in levels of adiponectin, cytokines, and adhesion molecules in subjects with metabolic syndrome. Circulation. 2004;110:3842–3848.
  • Choi KM, Lee J, Lee KW, . Comparison of serum concentrations of C-reactive protein, TNF-alpha, and IL 6 between elderly Korean women with normal and impaired glucose tolerance. Diabetes Res Clin Pract. 2004;64:1.
  • Wisse BE. Inflammatory syndrome: The role of adipose tissue cytokines in metabolic disorders link to obesity. J Am Soc Nephrol. 2004;15:2792–2800.
  • Garg R, Tripathy D, Dandona P. Insulin resistance as a proinflammatory state: Mechanisms, mediators, and therapeutic interventions. Curr Drug Targets. 2003;4:487–492.
  • Collins T, Cybulsky MI. NF-kB: Pivotal mediator or innocent bystander in atherogenesis? J Clin Invest. 2001;107:255–264.
  • Dressner A. Insulin mediated glucose uptake in muscle, in the absence of fatty acids and in the presence of LCFACoA. J Clin Invest. 1999;103:253–259.
  • Feldman HI, Santana J, Guo W, . Iron administration and clinical outcome in hemodialysis patients. J Am Soc Nephrol. 2002;13:734–744.
  • Kalantar-Zadeh K, Rodrigez RA, Humphreys MH. Association between serum ferritin and measures of inflammation, nutrition and iron in hemodialysis patients. Nephrol Dial Transplant. 2004;19:141–149.
  • Vozarova B, Weyer C, Hanson K, Tataranni PA, Bogardus C, Partley RE. Circulating interleukin-6 in relation to adiposity, insulin action, and insulin secretion. Obes Res. 2001;9:414–417.
  • Takeda T, Hoshida S, Nishino M, Tanouchi J, Otsu K, Hori M. Relationship between effects of statins, aspirin and angiotensin II modulators on high-sensitive C-reactive protein levels. Atherosclerosis. 2003;169:155–158.
  • Maeda N, Takahashi M, Funahashi T, . PPARγ ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes. 2001;50:2094–2099.
  • Pearson TA, Mensah GA, Alexander RW, . Markers of inflammation and cardiovascular disease. Application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation. 2003;107:499–511.
  • Hwang SJ, Yang WC, Chen HH, . National dialysis surveillance in Taiwan. Acta Nephrol. 1999;14:139–228.
  • Torres JL, Ridker PM. Clinical use of high sensitivity C-reactive protein for the prediction of adverse cardiovascular events. Curr Opin Cardiol. 2003;18:471–478.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.