Journal List > Korean Diabetes J > v.32(5) > 1002245

Kim, Song, Jeon, Kim, Bae, Kim, Lee, Son, Kim, Kim, and Kang: Association of Serum Cystatin C with Metabolic Syndrome and Its Related Components in Korean Adults

Abstract

Background

Serum cystatin C has been reported as a better marker than serum creatinine for estimation of kidney function and may be associated with cardiovascular disease. The aim of this study was to elucidate the association of serum cystatin C with metabolic syndrome (MS), a constellation of cardiovascular risk factors, and its related components and the usefulness of serum cystatin C for the cardiovascular risk assessment.

Methods

1,468 healthy subjects (814 men and 655 women), who visited health promotion center of Pusan National University Hospital for routine medical checkup were included. MS was defined by modified, revised National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III criteria.

Results

Mean serum cystatin C value was 0.87 ± 0.17 mg/L. In partial correlation analysis adjusted by age, sex and Glomerular Filtration Rate (GFR), cystatin C was associated with most of metabolic parameters and especially had significant positive correlation with waist circumference (r = 0.215), triglyceride (TG) (r = 0.141), diastolic blood pressure (BP) (r = 0.116), and correlated negatively with high density lipoprotein (HDL) cholesterol (r = -0.152) (all P < 0.001). There were increasing trends of prevalence of MS with the increase of quartiles of cystatin C and as the number of MS components increased, cystatin C values significantly increased. Serum cystatin C was also significantly increased in MS (0.90 ± 0.19 mg/L vs. 0.86 ± 0.16 mg/L). In stepwise multiple regression analysis including the components of MS, Waist circumference, diastolic BP, triglyceride, and HDL cholesterol were independent determinants of serum cystatin C, but with creatinine, only waist circumference was independent determinant.

Conclusions

Serum cystatin C was closely associated with MS and its related cardiovascular risk factors and might be useful as a tool of cardiovascular risk assessment.

Figures and Tables

Fig. 1
Associations of serum cystatin C with metabolic syndrome. Prevalence of metabolic syndrome according to the quartiles of serum cystatin C (A) and mean serum cystatin C levels according to the increase of the number of metabolic syndrome components (B). MS, metabolic syndrome; *P < 0.001.
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Table 1
Characteristics of metabolic and laboratory parameters in total subjects
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Data are expressed as mean ± standard deviation, unless otherwise indicated. P values by independent samples t-test and chi-squire test*. AST, aspartate aminotransferase; ALT, alanine aminotransferase; BMI, body mass index; DBP, diastolic blood pressure; FBS, fasting blood sugar; GFR, glomerular filtration rate; GGT, gamma glutamyltransferase; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; hs-CRP, high sensitivity C-reactive protein; MDRD, modification of diet in renal disease; MS, metabolic syndrome; SBP, systolic blood pressure; TG, triglyceride; WBC, white blood cell; WC, Waist circumference.

Table 2
Partial correlation analyses of serum cystatin C with metabolic syndrome related parameters after adjustment for age, sex and GFR
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BMI, body mass index; DBP, diastolic blood pressure; FBS, fasting blood sugar; GFR, glomerular filtration rate; GGT, gamma glutamyltransferase; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; hs-CRP, high sensitivity C-reactive protein; SBP, systolic blood pressure; TG, triglyceride; WC, Waist circumference.

Table 3
Difference of serum cystatin C levels according to the age, metabolic syndrome, and metabolic syndrome related disorders
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Data are expressed as mean ± standard deviation, P values by independent samples t-test. BP, blood pressure; HDL-C, high-density lipoprotein cholesterol; IFG: Impaired fasting glucose; MS, metabolic syndrome; TG, triglyceride.

Table 4
Stepwise multiple regression analyses using the individual components of metabolic syndrome with or without serum creatinine as the independent variables and serum cystatin C as the dependent variable
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DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride.

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