Literature DB >> 28272253

Association of body mass index, waist circumference, and metabolic syndrome with serum cystatin C in a Chinese population.

Xin Ying1, Yan Jiang, Guangming Qin, Yafang Qian, Xiaoru Shen, Zhenyan Jiang, Shu Zheng, Zhenya Song.   

Abstract

BACKGROUND: The aim of the study was to evaluate the association of body mass index (BMI), waist circumference (WC), and metabolic syndrome (MetS) with serum cystatin C (CysC) in a Chinese population.
METHODS: The population was composed of 5866 subjects. MetS was diagnosed using the American Heart Association/National Heart, Lung, and Blood Institute 2005 (NCEP-R) criteria. Covariates were analyzed using logistic regression and Spearman partial correlation.
RESULTS: In this population, triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), high sensitivity C-reactive protein (hs-CRP), BMI, WC, systolic blood pressure (SBP), diastolic blood pressure (DBP), serum creatinine (Scr), and CysC were significantly higher, and HDL-C and the estimated glomerular filtration rate (Chronic Kidney Disease Epidemiology Collaboration) (eGFRCKD-EPI) were significantly lower in the MetS than in the non-MetS group. TG, LDL-C, FPG, hs-CRP, BMI, WC, SBP, DBP, and Scr were significantly higher, and HDL-C and eGFRCKD-EPI were significantly lower in the 4th quartile than in the 1st quartile of CysC. Logistic regression analysis showed that sex, age, hs-CRP, and CysC were independently associated with the presence of MetS (OR = 3.732, 1.028, 1.051, and 3.334, respectively; P < 0.05). No significant association between the presence of MetS and either Scr or eGFRCKD-EPI was observed. After adjustment for age and sex, BMI, WC, hs-CRP, and Scr were all positively correlated, whereas eGFRCKD-EPI was negatively correlated with CysC (r = 0.029, 0.061, 0.189, 0.227, and -0.210, respectively; P < 0.05).
CONCLUSION: The present study revealed that the CysC was more closely associated with the presence of MetS, as compared Scr or eGFRCKD-EPI. CysC was positively correlated with BMI, and more strongly, positively correlated with WC and inflammation.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28272253      PMCID: PMC5348201          DOI: 10.1097/MD.0000000000006289

Source DB:  PubMed          Journal:  Medicine (Baltimore)        ISSN: 0025-7974            Impact factor:   1.889


Introduction

Cystatin C (CysC) is an extracellular inhibitor of cysteine proteases and is produced in all nucleated cells. CysC is freely filtered at the level of the renal glomeruli, and almost all of it is reabsorbed and metabolized in the proximal tubule.[ CysC can be used as a measure of kidney function. In recent years, multiple studies have shown that CysC may be used as a more accurate indicator of glomerular filtration rate (GFR) than creatinine.[ CysC has also served as a predictive marker of cardiovascular disease.[ Metabolic syndrome (MetS) is highly prevalent worldwide[ and is associated with an increased risk for cardiovascular disease and diabetes.[ Many studies on the treatment of MetS have recently been conducted, including studies examining complementary and alternative medicine (CAM) treatments and the use of berry fruits.[ Some researchers have found that low testosterone concentration and high serum ferritin level were risk factors for MetS.[ Others have demonstrated that CysC is associated with MetS[ and have reported a positive relationship between CysC, body mass index (BMI), and waist circumference (WC).[ To the best of our knowledge, research on the association between MetS and CysC is limited. In the present study, we assessed the association of BMI, WC, and MetS with serum CysC in a large Chinese population.

Methods

Study designs and population

A total of 6306 subjects visited our health care center for their regular checkup between January and December 2013. The medical history, including medications, of each subject was obtained. Subjects with thyroid dysfunction, pregnancy, malignant disease, cirrhosis, infectious disease, active liver disease, chronic kidney disease, missing a valid measurement for necessary indices, or less than 18 years old were excluded (n = 440). Of the total sample (N = 5866), none had a history of corticosteroid or cyclosporine use, hyperhomocysteinemia, or rheumatic diseases.

Clinical indices and anthropometric measurements

Venous blood samples were drawn after a 10-hour fast for serum index measurements. Triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG), high-sensitivity C-reactive protein (hs-CRP), and serum creatinine (Scr) concentrations were measured using glycerol phosphate oxidase and peroxidase (GPO-POD), surfactant elution, selected inhibition, hexokinase, turbidimetric immunoassay, and sarcosine oxidase methods, respectively, using a Beckman Coulter AU 5400 machine. CysC concentrations were measured using the turbidimetric immunoassay method, specifically with a Beckman Coulter AU 5400 machine, at a reference range of less than 1.03 mg/L. Both the intra- and interassay coefficients of CysC were less than 10%. CysC levels were between 0.33 and 1.81 mg/L. Estimated glomerular filtration rate (Chronic Kidney Disease Epidemiology Collaboration) (eGFRCKD-EPI) equation[ was used. Blood pressure (BP) was measured after at least 5 minutes of rest. WC was measured on standing subjects with a measuring tape midway between the lowest rib and the iliac crest. Body weight was measured in kilograms (with light clothing), and height was measured in meters (without shoes). BMI was calculated by using the formula: Weight (kg)/[Height (m)]2. MetS was diagnosed according to the American Heart Association/National Heart, Lung, and Blood Institute 2005 (NCEP-R),[ which requires at least 3 of the following criteria to be met: WC ≥90 cm in males and ≥80 cm in females; TG ≥1.7 mmol/L (150 mg/dL) or a specific treatment for TG; HDL-C < 1.03 mmol/L (40 mg/dL) in males and <1.29 mmol/L (50 mg/dL) in females or a specific treatment for reduced HDL-C; systolic blood pressure (SBP) ≥130 mm Hg, diastolic blood pressure (DBP) ≥85 mm Hg, or antihypertensive treatment; and FPG ≥5.6 mmol/L (100 mg/dL) or drug treatment for elevated glucose.

Ethical issues

The ethical committee of the Second Affiliated Hospital, School of Medicine, Zhejiang University approved the study. All subjects provided informed consent.

Statistical analyses

SPSS software (version 13.0; SPSS Inc., Chicago, IL) was used for statistical analysis. Normal distribution data were expressed as the mean ± standard deviation. Skewed distribution data were expressed as the median with 25th and 75th percentiles (P25–P75). The Mann–Whitney U test was used to compare relevant data between non-MetS and MetS groups. The non-MetS group was defined as those subjects without MetS (2 or less MetS criteria). The Mann–Whitney U test was used to compare the data between the 1st and 4th quartiles of CysC. Logistic regression was performed to identify independent factors of MetS, and estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the factors. The following were considered covariates in the logistic regression analysis: age, sex, hs-CRP, Scr, eGFRCKD-EPI, and CysC. SAS software (Version 9.2; SAS Institute Inc., Cay, NC) was used to perform a Spearman partial correlation analysis, adjusting for age and sex, to determine the association of BMI, WC, hs-CRP, Scr, and eGFRCKD-EPI with CysC. P < 0.05 was considered statistically significant.

Results

Clinical characteristics

The clinical data on this cohort are shown in Table 1. A total of 5866 subjects were included in the study (females: 2081, males: 3785; age range: 18–84 years). Compared to the non-MetS group, the MetS group exhibited significantly higher levels of TG, LDL-C, FPG, hs-CRP, BMI, WC, SBP, DBP, Scr, and CysC, and lower levels of HDL-C and eGFRCKD-EPI.
Table 1

Relevant data according to the presence or the absence (non-MetS) of MetS.

Relevant data according to the presence or the absence (non-MetS) of MetS.

CysC and other indices

The data were divided into 4 groups according to the quartiles of serum CysC concentration (Table 2). Comparisons between the indices in the 1st and 4th quartiles showed significantly higher values for TG, LDL-C, FPG, hs-CRP, BMI, WC, SBP, DBP, and Scr, whereas both HDL-C and eGFRCKD-EPI were significantly lower in the 4th quartile.
Table 2

Comparison of data among the different quartiles of CysC.

Comparison of data among the different quartiles of CysC.

Logistic regression analysis

Logistic regression analysis revealed that sex, age, hs-CRP, and CysC were independently associated with the presence of MetS (OR = 3.732, 1.028, 1.051, and 3.334; 95% CI: 2.396–5.812, 1.004–1.053, 1.027–1.075, and 2.259–4.919; P < 0.001, 0.021, <0.001, and <0.001, respectively). No significant association was observed for presence of MetS and either Scr (P = 0.089) or eGFRCKD-EPI (P = 0.253) (Table 3).
Table 3

Association of CysC, hsCRP and the presence of MetS in logistic regression models.

Association of CysC, hsCRP and the presence of MetS in logistic regression models.

Partial correlation analysis

Spearman partial correlation coefficients of BMI, WC, hs-CRP, Scr, and eGFRCKD-EPI with CysC are summarized in Table 4. After adjustment for age and sex, the results indicated that BMI, WC, hs-CRP, and Scr were positively correlated with CysC, whereas eGFRCKD-EPI was negatively correlated with CysC (r = 0.029, 0.061, 0.189, 0.227, and −0.210; P = 0.0260, <0.0001, <0.0001, <0.0001, and <0.0001, respectively).
Table 4

Further partial correlation analysis between BMI, WC, hsCRP, Scr, and eGFR with CysC.

Further partial correlation analysis between BMI, WC, hsCRP, Scr, and eGFR with CysC.

Discussion

MetS is characterized by high fasting blood glucose, TG, BP levels, elevated WC, and low HDL-C levels. The worldwide prevalence of MetS has recently been acknowledged as an important public health challenge.[ MetS was present in 26.1% of the current study subjects, identical to that found in the literature.[ Furthermore, CysC concentrations were significantly higher in the MetS group than in the non-MetS group. Similar to our findings, Liu et al[ demonstrated higher serum CysC levels were positively and independently associated with the presence of MetS in a sample of Chinese premenopausal and postmenopausal women. Based on group-stratified CysC values, MetS significantly differed in the lowest CysC quartile compared to the highest quartile. Last, our data reflected a correlation between CysC and MetS. The association between inflammation and MetS has been well documented.[ A previous report suggested that chronic subclinical inflammation may be partly influenced by MetS.[ Some studies have suggested a significant association between CysC and CRP,[ and CysC may be considered as a potential inflammatory biomarker.[ Our data showed that CysC and hs-CRP were independent covariates of MetS. Partial correlation analysis indicated a positive correlation between CysC and hs-CRP, after adjusting for age and sex. Therefore, our data suggest an association between CysC and inflammation. Logistic regression analysis showed that the CysC was more closely associated with the presence of MetS, as compared Scr or eGFRCKD-EPI. Previous studies demonstrated that CysC was considered as a “preclinical” state of renal disease, which was not detected with Scr or eGFR.[ Thus, CysC is considered to be an accurate glomerular marker for early renal insufficiency.[ After adjusting for age and sex, the results indicated that, besides hs-CRP, BMI and WC were also positively correlated with CysC. Although both r-values were low, CysC was more strongly correlated with WC than with BMI. Previous studies have shown associations between BMI, WC, and CysC.[ CysC is an endogenous inhibitor of cathepsin proteases. A recent report has shown that CysC affects adipose tissue and vascular homeostasis through the inhibition of cathepsins.[ This particular study indicated that WC is more closely related to CysC than BMI. Magnusson et al[ showed that abdominal obesity is the only component of MetS that is significantly associated with increased baseline levels of CysC. Another study illustrated a stronger correlation between CysC and WC compared to BMI.[ These data indicate that the close association between CysC and MetS may be mediated by visceral fat. A limitation of our study is that it only included subjects who visited our center for a checkup. The analysis was also limited by the cross-sectional design. In conclusion, we found the CysC was more closely associated with the presence of MetS, as compared Scr or eGFRCKD-EPI.. CysC was positively correlated with BMI, and more strongly, positively correlated with WC and inflammation.

Acknowledgments

The authors thank Zhejiang Medical Scientific and Technological Projects (2012KYA100 and 2012KYA091), China for the support.
  39 in total

1.  Serum cystatin C concentration as a marker of renal dysfunction in the elderly.

Authors:  D Fliser; E Ritz
Journal:  Am J Kidney Dis       Date:  2001-01       Impact factor: 8.860

Review 2.  Current evidence on the health-beneficial effects of berry fruits in the prevention and treatment of metabolic syndrome.

Authors:  Katarzyna Kowalska; Anna Olejnik
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2016-11       Impact factor: 4.294

3.  Cystatin-C and mortality in elderly persons with heart failure.

Authors:  Michael G Shlipak; Ronit Katz; Linda F Fried; Nancy Swords Jenny; Catherine O Stehman-Breen; Anne B Newman; David Siscovick; Bruce M Psaty; Mark J Sarnak
Journal:  J Am Coll Cardiol       Date:  2005-01-18       Impact factor: 24.094

4.  Cystatin C is associated with the metabolic syndrome and other cardiovascular risk factors in a hypertensive population.

Authors:  Luis Vigil; Manuel Lopez; Emilia Condés; Manuel Varela; Dulce Lorence; Rafael Garcia-Carretero; Julian Ruiz
Journal:  J Am Soc Hypertens       Date:  2009-03-09

5.  Plasma concentrations of cystatin C in patients with coronary heart disease and risk for secondary cardiovascular events: more than simply a marker of glomerular filtration rate.

Authors:  Wolfgang Koenig; Dorothee Twardella; Hermann Brenner; Dietrich Rothenbacher
Journal:  Clin Chem       Date:  2004-11-24       Impact factor: 8.327

6.  Is serum cystatin-C a reliable marker for metabolic syndrome?

Authors:  Aude Servais; Philippe Giral; Maguy Bernard; Eric Bruckert; Gilbert Deray; Corinne Isnard Bagnis
Journal:  Am J Med       Date:  2008-05       Impact factor: 4.965

Review 7.  Metabolic syndrome: connecting and reconciling cardiovascular and diabetes worlds.

Authors:  Scott M Grundy
Journal:  J Am Coll Cardiol       Date:  2006-02-23       Impact factor: 24.094

8.  All-cause mortality associated with specific combinations of the metabolic syndrome according to recent definitions.

Authors:  Louis Guize; Frédérique Thomas; Bruno Pannier; Kathy Bean; Bertrand Jego; Athanase Benetos
Journal:  Diabetes Care       Date:  2007-06-11       Impact factor: 19.112

9.  Potential contribution of adipose tissue to elevated serum cystatin C in human obesity.

Authors:  Nadia Naour; Soraya Fellahi; Jean-François Renucci; Christine Poitou; Christine Rouault; Arnaud Basdevant; Anne Dutour; Marie-Christine Alessi; Jean-Philippe Bastard; Karine Clément; Michèle Guerre-Millo
Journal:  Obesity (Silver Spring)       Date:  2009-04-09       Impact factor: 5.002

10.  A new equation to estimate glomerular filtration rate.

Authors:  Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh
Journal:  Ann Intern Med       Date:  2009-05-05       Impact factor: 25.391

View more
  8 in total

1.  Indices calculated by serum creatinine and cystatin C as predictors of liver damage, muscle strength and sarcopenia in liver disease.

Authors:  Tatsuki Ichikawa; Hisamitsu Miyaaki; Satoshi Miuma; Yasuhide Motoyoshi; Mio Yamashima; Shinobu Yamamichi; Makiko Koike; Youichi Takahashi; Tetsurou Honda; Hiroyuki Yajima; Ryouhei Uehara; Naoyuki Hino; Ryousuke Hirata; Naota Taura; Kazuhiko Nakao
Journal:  Biomed Rep       Date:  2020-01-24

2.  Genomic Heritabilities and Correlations of 17 Traits Related to Obesity and Associated Conditions in the Japanese Population.

Authors:  Olivier Gervais; Kazuko Ueno; Yosuke Kawai; Yuki Hitomi; Kazuharu Misawa; Shunsuke Teraguchi; Yen-Yen Wang; Katsushi Tokunaga; Masao Nagasaki
Journal:  G3 (Bethesda)       Date:  2020-07-07       Impact factor: 3.154

Review 3.  Metabolic Syndrome: Findings from 20 Years of the Tehran Lipid and Glucose Study.

Authors:  Firoozeh Hosseini-Esfahani; Zahra Bahadoran; Nazanin Moslehi; Golaleh Asghari; Emad Yuzbashian; Somayeh Hosseinpour-Niazi; Parvin Mirmiran; Fereidoun Azizi
Journal:  Int J Endocrinol Metab       Date:  2018-10-21

4.  Serum Uric Acid in Roma and Non-Roma-Its Correlation with Metabolic Syndrome and Other Variables.

Authors:  Jana Petrikova; Martin Janicko; Jan Fedacko; Sylvia Drazilova; Andrea Madarasova Geckova; Maria Marekova; Daniel Pella; Peter Jarcuska
Journal:  Int J Environ Res Public Health       Date:  2018-07-04       Impact factor: 3.390

5.  Is neck circumference an appropriate tool to predict cardiovascular risk in clinical practice? A cross-sectional study in Chilean population.

Authors:  Patricia Caro; Ximena Guerra; Andrea Canals; Gerardo Weisstaub; Carlos Sandaña
Journal:  BMJ Open       Date:  2019-11-07       Impact factor: 2.692

6.  Association of cystatin C levels with metabolic syndrome incidence: a nested case-control study with propensity score matching.

Authors:  Tengfei Yang; Dongmei Pei
Journal:  J Int Med Res       Date:  2021-01       Impact factor: 1.671

7.  Serum Cystatin-C is linked to increased prevalence of diabetes and higher risk of mortality in diverse middle-aged and older adults.

Authors:  Kevin A González; Ariana M Stickel; Sonya S Kaur; Alberto R Ramos; Hector M González; Wassim Tarraf
Journal:  PLoS One       Date:  2022-09-12       Impact factor: 3.752

8.  Diagnostic Power of Circulatory Metabolic Biomarkers as Metabolic Syndrome Risk Predictors in Community-Dwelling Older Adults in Northwest of England (A Feasibility Study).

Authors:  Razieh Hassannejad; Hamsa Sharrouf; Fahimeh Haghighatdoost; Ben Kirk; Farzad Amirabdollahian
Journal:  Nutrients       Date:  2021-06-30       Impact factor: 5.717

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.