- Email: [email protected]
Plasma proANP1–98 levels are positively associated with central obesity: A cross-sectional study in a general population of China
Clinica Chimica Acta 469 (2017) 26–30
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/cca
Plasma proANP1–98 levels are positively associated with central obesity: A cross-sectional study in a general population of China
MARK
Zhengbao Zhua,b,1, Qiu Zhangc,1, Hao Penga,b, Chongke Zhonga,b, Yan Liua,b, Xinfeng Huangfua,b, Yunfan Tiana,b, Xiangqin Chaoc, Aili Wanga,b, Jianhua Jinc, Yonghong Zhanga,b,⁎ a b c
Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China. Center for Disease Prevention and Control of Gusu District, Suzhou, China.
A R T I C L E I N F O
A B S T R A C T
Keywords: Plasma proANP Waist circumference Central obesity Chinese Cross-sectional study
Background: Atrial natriuretic peptide (ANP) and its prohormone activating enzyme are associated with central obesity, suggesting there may be a potential relationship between proANP1–98 and central obesity. However, the association is still lack of population-based evidence. We explored the association in a general population of China. Methods: We measured plasma proANP1–98, waist circumference and other traditional biomarkers in 2203 participants aged ≥ 30 y. Multivariate logistic regression models were used to determine the association between plasma proANP1–98 and central obesity, and odds ratio (OR) and 95% confidence interval (CI) were calculated. Results: High proANP1–98 was significantly associated with increased risk of central obesity in participants, and the multivariate adjusted OR (95% CI) of central obesity associated with the second, third and fourth quartiles of proANP1–98 were 1.33 (1.03–1.72), 1.69 (1.31–2.19) and 1.76 (1.35–2.29), respectively, compared with the lowest quartile of proANP1–98. There was a dose-response relationship between proANP1–98 and risk of central obesity among the participants (Ptrend $AMP$lt; 0.001). Sensitivity analyses further confirmed these associations. Adding proANP1–98 to a model containing conventional risk factors improved discriminatory power of central obesity (as shown by significant improvement in continuous NRI and IDI). Conclusions: Contrary to known reduced ANP levels in central obesity, we found that plasma proANP1–98 was positively associated with central obesity, suggesting that elevated plasma proANP1–98 may be a marker or a risk factor for central obesity.
1. Introduction
extracellular fluid volume and normal blood pressure [8]. In the past decade, accumulating evidence has demonstrated that circulating ANP was reduced in individuals with central obesity [9–11]. As we all know, corin is the only activating enzyme of proANP1–126 which is the prohormone of ANP [12,13] and it has been suggested to be associated with central obesity in cell- and animal-based studies [14–16]. Furthermore, our previous epidemiological study found a higher serum soluble corin concentration in individuals with central obesity compared to those without central obesity [17]. Cleavage of proANP1–126 releases equimolar amounts of the biologically active peptide ANP and inactive proANP1–98 into the circulation [13,18]. These evidences suggest that there may be a potential association between plasma proANP1–98 and central obesity.
Obesity is a global pandemic and its prevalence has more than doubled in the last 30 y, resulting in a staggering disease burden around the world [1]. It is widely accepted that central obesity is more closely related to metabolic and cardiovascular complications than general obesity [2,3], and visceral adipose tissue is associated with a greater atherosclerotic risk profile than subcutaneous fat when present in excess [4–6]. Although existing strategies to prevent central obesity through lifestyle improvements and medical intervention have achieved some success, but there is still room for further improvement [7]. Some unknown risk factors for central obesity need to be studied to improve central obesity prevention and control. Atrial natriuretic peptide (ANP) plays a key role in maintaining
⁎
1
Corresponding author: Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, China. E-mail address: [email protected] (Y. Zhang). These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.cca.2017.03.019 Received 28 October 2016; Received in revised form 16 March 2017; Accepted 17 March 2017 Available online 19 March 2017 0009-8981/ © 2017 Published by Elsevier B.V.
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
2. Methods
tions of unknown samples were determined. Intra- and inter-assay coefficients of variation were $AMP$lt; 2% and $AMP$lt; 4%, respectively.
2.1. Study participants
2.3. Statistical analysis
We conducted a cross-sectional study in a traditional but economically developed district of Suzhou from January to May, 2010. The participants were selected via multiphase cluster random sampling. From the total 20 urban communities and 19 rural villages in the district, 4 urban communities, and 4 rural villages were randomly selected as the research fields. The residents aged ≥ 30 y living in the 4 urban communities and 4 rural villages were selected as subjects. The exclusion criteria were to meet one of the followings: (1) having clinical suspicion of diseases which may cause secondary hypertension (e.g., renal artery stenosis, coarctation, glomerulonephritis, pyelonephritis, phaeochromocytoma, Cushing's syndrome, Conn's syndrome), (2) selfreported history of coronary heart disease, stroke, or tumors, (3) selfreported thyroid or parathyroid diseases, (4) being pregnant. There were a total of 3061 eligible residents in the study fields, but only 2706 (participating rate: 88%) persons participated in this study. Among 2706 participants, 503 were excluded because they refused to offer blood samples, or some collected samples were hemolyzed in transport or storage, or failed to measure plasma proANP1–98 levels, a total of 2203 participants were finally included in current analysis. This study was approved by the Soochow University Ethics Committee. Written informed consent was obtained from all study participants.
Baseline characteristics were presented and compared between the participants with central obesity and those without central obesity. Comparisons in rates for categorical variables were performed by using the χ2 test. Comparisons in means of continuous variables (normal distribution) and in medians of continuous variables (skewed distribution) were analyzed by using Student's t-test and Wilcoxon rank-sum test, respectively. Multivariate non-conditional logistic regression models were used to assess the association of plasma proANP1–98 with central obesity. All participants were divided into 4 groups according to the quartiles of plasma proANP1–98 concentration in men and women, respectively. The quartile values of plasma proANP1–98 were 0.63, 1.04, and 1.51 nmol/l in men and 0.68, 1.15, and 1.69 nmol/l in women. Odds ratios (OR) and 95% confidence intervals (CI) of central obesity were calculated for upper quartiles of proANP1–98 with the lowest quartile as a reference. Trends for the ORs of central obesity across increasing proANP1–98 categories were determined, having proANP1–98 category as an ordinal variable. In addition, the potential covariates such as age, sex, current smoking, alcohol consumption, family history of hypertension, SBP, DBP, TC, TG, LDL-C, HDL-C and FPG were included in the multivariate models. We further used nonparametric restricted cubic splines to explore the shape of relationship between plasma proANP1–98 and central obesity, with 4 knots defined at the 5th, 35th, 65th, and 95th percentiles of proANP1–98 [24]. Some studies have found that hypertension, diabetes and dyslipidemia can affect the plasma proANP1–98 [25–27]. Therefore, in order to weaken or even eliminate the confounding effects of these diseases on the relationship between plasma proANP1–98 and central obesity, we performed sensitivity analyses which repeated the multivariate nonconditional logistic regression models after excluding the subjects with hypertension, diabetes and dyslipidemia, respectively. We also used the continuous net reclassification index (NRI) and integrated discrimination improvement (IDI) statistics [28] to assess whether inclusion of high plasma proANP1–98 concentration (alone or together) improved discriminatory abilities for risk of central obesity. A 2-tailed P $AMP $lt; 0.05 was considered statistically significant. SAS statistical software (ver 9.4) and R statistical software (ver 2.15) were used for data analysis.
2.2. Data collection Data on demographic information, lifestyle risk factors, and personal medical history were collected with standard questionnaires in Chinese language administered by trained staff. Cigarette smoking was defined as having smoked at least 1 cigarette per day for 1 year or more and reported current smoking. Alcohol consumption was defined as consuming any type of alcohol beverage at least once per week during the last three years. Body weight and height were measured using a regularly calibrated stadiometer and balance-beam scale with subjects wearing light clothing and no shoes. Waist circumference (WC) was measured at the level of 1 cm above the umbilicus. For this analysis, central obesity was defined as WC ≥ 85 cm for men and as WC ≥ 80 cm for women based on the recommendations of the Working Group on Obesity in China [19]. Three consecutive sitting blood pressure (BP) measurements (30 s interval between each) were measured by trained staff using a standard mercury sphygmomanometer according to a standard protocol [20], after the subjects had been resting for at least 5 min. The first and fifth Korotkoff sounds were recorded as systolic BP (SBP) and diastolic BP (DBP), respectively. The mean of the three records was used in analysis. Hypertension was defined as SBP ≥ 140 mm Hg or DBP ≥ 90 mm Hg or use of antihypertensive medication in the last 2 weeks [21]. Blood samples were collected in EDTA-containing tubes by venipuncture in the morning after a requested overnight fast (at least 8 h). All plasma and serum samples were frozen at −80 °C until laboratory testing. Total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol, low density lipoprotein cholesterol, and fasting plasma glucose (FPG) were measured for all participants. All the biochemical indexes were analyzed enzymatically on Hitachi 7020 automatic biochemical analyzer using commercial reagents. Intra- and inter-assay CVs were $AMP$lt; 2% and $AMP$lt; 4%, respectively. Diabetes was defined as FPG ≥ 7.0 mmol/l or use of hypoglycemic medication in the last 2 weeks [22]. Dyslipidemia was defined as TC ≥ 6.22 mmol/l or LDL-C ≥ 4.14 mmol/l or TG ≥ 2.26 mmol/l or HDL-C $AMP $lt; 1.04 mmol/l or use of lipid-lowering drugs in the last 2 weeks [23]. ProANP (1–98) ELISA No. BI-20892 kits (BIOMEDICA, AUSTRIA) was used to examine soluble proANP1–98 concentration in plasma samples. All the samples were processed in a duplicate assay. A standard curve was constructed and from which proANP1–98 concentra-
3. Results 3.1. Baseline characteristics of study participants A total of 2203 participants, including 842 males and 1361 females, were included in the present analysis and average age was 53 y (from 30 to 80 y). Among them, 1165 (52.88%) participants were central obesity. The baseline characteristics of study participants were presented in Table 1. Participants with central obesity were more likely to be older, males, hypertensive, have higher levels of SBP, DBP, TC, TG, LDL-C, and FPG, and have a lower level of HDL-C compared with those with a normal WC (all P values $AMP$lt; 0.05). The median concentration of plasma proANP1–98 was significantly higher in the participants with central obesity than that in those with normal WC (0.99 vs. 1.18 nmol/l, P $AMP$lt; 0.05). 3.2. Association between plasma proANP1–98 and central obesity The association between plasma proANP1–98 and central obesity was shown in Table 2. After adjustment for age, sex, current smoking, alcohol consumption, family history of hypertension, SBP, DBP, TC, TG, LDL-C, HDL-C and FPG, the participants in the second (OR = 1.33, 27
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
Table 1 Baseline characteristics of study participants. Characteristics
Normal WC
Central obesity
P-value
No. of participants Age, mean ± SD Male, n (%) Cigarette smoking, n (%) Alcohol consumption, n (%) FHH, n (%) HBP, n (%) SBP, mean ± SD DBP, mean ± SD TC, mmol/l TG, mmol/l LDL-C, mmol/l HDL-C, mmol/l FPG, mmol/l ProANP1–98, nmol/l
1038 50.75 ± 9.38 374 (36.03) 235 (22.64) 179 (17.24) 280 (26.97) 316 (30.44) 126.01 ± 15.85 82.68 ± 8.88 5.00 (4.46–5.61) 0.93 (0.69–1.34) 2.85 (2.44–3.31) 1.55 (1.33–1.82) 5.00 (4.60–5.50) 0.99 (0.58–1.51)
1165 54.35 ± 9.07 468 (40.17) 265 (22.75) 238 (20.43) 330 (28.33) 624 (53.56) 133.46 ± 16.81 86.50 ± 8.73 5.21 (4.63–5.79) 1.30 (0.91–1.79) 3.04 (2.59–3.48) 1.39 (1.18–1.64) 5.30 (4.80–5.90) 1.18 (0.72–1.72)
$AMP$lt; 0.001 0.046 0.952 0.057 0.479 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001
All values are expressed with median (inter-quartile range) unless otherwise noted. Normal WC was defined as WC $AMP$lt; 85 cm for men and WC $AMP$lt; 80 cm for women; and central obesity was defined as WC ≥ 85 cm for men and WC ≥ 80 cm for women. WC, waist circumference; FHH, family history of hypertension; HBP, diagnosis of hypertension; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; TG, triglycerides; LDL-C, low density lipoprotein cholesterol; HDL-C, high density lipoprotein cholesterol; FPG, fasting plasma glucose. Table 2 Odds ratio (ORs) and 95% confidence intervals (CIs) of central obesity according to quartiles of plasma proANP1–98. Variable
proANP1–98 (nmol/l)
Ptrend
Q1
Q2
Q3
Q4
No. of cases (%) Model 1
253 (45.50)
280 (50.27)
301 (55.43)
331 (60.51)
1.00
Model 2
1.00
1.19 (0.94–1.52) 1.33 (1.03–1.72)
1.42 (1.11–1.80) 1.69 (1.31–2.19)
1.49 (1.16–1.91) 1.76 (1.35–2.29)
$AMP $lt; 0.001 $AMP $lt; 0.001
1.17 (0.84–1.64) 1.21 (0.92–1.56) 1.22 (0.90–1.66)
1.54 (1.09–2.17) 1.58 (1.21–2.07) 1.82 (1.33–2.47)
1.71 (1.18–2.48) 1.68 (1.28–2.20) 1.52 (1.11–2.07)
0.001
Sensitivity analyses Model 3 1.00 Model 4
1.00
Model 5
1.00
$AMP $lt; 0.001 0.001
Fig. 1. Adjusted ORs of central obesity according to proANP1–98. Odds ratios and 95% confidence intervals derived from restricted cubic spline regression, with knots placed at the 5th, 35th, 65th, and 95th percentiles of proANP1–98. The reference point for proANP1–98 is the midpoint of the reference group (≤ 0.02 nmol/l). Panel adjusted for the same variables as model 2 in Table 2.
Q1: ≤ 0.63 nmol/l for men and ≤ 0.68 nmol/l for women; Q2: 0.64–1.04 nmol/l for men and 0.69–1.15 nmol/l for women; Q3: 1.05–1.51 nmol/l for men and 1.16–1.69 nmol/l for women; Q4: $AMP$gt; 1.51 nmol/l for men and $AMP$gt; 1.69 nmol/l for women. Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, current smoking, alcohol consumption, family history of hypertension, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low density lipoprotein cholesterol, high density lipoprotein cholesterol and fasting plasma glucose. Model 3: adjusted for Model 2 and further excluded subjects with hypertension. Model 4: adjusted for Model 2 and further excluded subjects with diabetes. Model 5: adjusted for Model 2 and further excluded subjects with dyslipidemia.
proANP1–98 levels after multivariate adjustment. 3.3. Incremental discriminatory ability of plasma proANP1–98 for central obesity We examined whether adding plasma proANP1–98 to the conditional logistic regression model consisting of conventional risk factors for obesity improved the discriminatory abilities for risk of central obesity among study participants. High levels of plasma proANP1–98 improved materially the discriminatory ability based on traditional risk factors for central obesity, as shown by significant improvement in continuous NRI and IDI statistics. Moreover, the incremental discriminatory ability of plasma proANP1–98 for central obesity remained stable in subjects without hypertension or diabetes or dyslipidemia (as described in Table 3).
P = 0.03),third (OR = 1.69, P $AMP$lt; 0.001) and fourth (OR = 1.76, P $AMP$lt; 0.001) quartiles had significantly increased odds of central obesity compared to those in the lowest quartile. There was a dose-response relationship between proANP1–98 and risk of central obesity, namely, the ORs of central obesity positively increased with plasma proANP1–98 levels (Ptrend $AMP$lt; 0.001). Furthermore, we analyzed the association between plasma proANP1–98 levels and central obesity using restricted cubic splines. As shown in Fig. 1, with an increase of plasma proANP1–98 levels, the risk of central obesity increased among participants (Pnonlinearity = 0.163, Plinearity $AMP $lt; 0.001). After sensitivity analyses, the association of plasma proANP1–98 with central obesity remained. ORs of central obesity remained positively and significantly increased with elevated plasma
4. Discussion We conducted a cross-sectional study to examine the relationship between plasma proANP1–98 and prevalent central obesity in 2203 adults aged 30 years and above in Suzhou, China. In this study, we 28
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
terminal-pro-brain natriuretic peptide (NT-proBNP) in obesity. Similarly, the plasma levels of BNP which has lipolytic activity as ANP are decreased in obesity [36,37], but NT-proBNP is found to be increased in obesity [38,39] and weight loss could reduce the increased range of NTproBNP in the morbidly obese [40]. It is plausible to speculate that the synthesis of proANP1–98 and ANP might be elevated in response to visceral adipose accumulation as a counter-system against reduced ANP concentrations. This hypothesis was also supported by our previous study. We found that serum soluble concentration of corin which was the only activating enzyme of proANP1–126 was increased in individuals with central obesity [17], suggesting that the releases of the active ANP and inactive proANP1–98 into the circulation were increased. Interestingly, it is also reported that natriuretic peptide clearance receptors (NPR-C) expression is elevated in the adipose tissue of humans with obesity, which may contribute to the increased clearance of ANP and decreased ANP concentrations in obesity [38,41]. However, proANP1–98 is not cleared by NPR-C in adipose tissue [38,41], which may lead to the accumulation of proANP1–98 in obesity. Further studies are needed to clarify the mechanism of increased proANP1–98 levels in individuals with central obesity. This study includes a relatively large number of subjects, which enabled us to perform sensitivity analyses of this association. We excluded the participants who had a history of stroke, coronary heart disease, or tumors, which might affect the plasma proANP1–98 concentration. All data were collected with rigid quality control. We collected several important variables which could confound the observed association. These variables include cigarette smoking, alcohol consumption, blood glucose and blood lipids. After controlling these covariate variables, the finding still showed that plasma proANP1–98 was positively associated with central obesity; in sensitivity analyses, the associations persisted in all models. However, there are also some limitations that should be mentioned. A causal relationship between plasma proANP1–98 and central obesity cannot be inferred because this study is only a cross-sectional study. In addition, the measurement of adipocytokines was not performed as part of the study, thus we could not compare the role of proANP1–98 with that of adipocytokines in central obesity assessment among our study participants. Further studies are needed to compare the role of proANP1–98 with adipocytokines in central obesity.
Table 3 Reclassification and discrimination statistics (95% CI) for risk of central obesity by plasma proANP1–98 among study participants.
Model 2 Model 2 + proANP1–98 Model 3 Model 3 + proANP1–98 Model 4 Model 4 + proANP1–98 Model 5 Model 5 + proANP1–98
NRI
IDI
0.166 (0.083–0.249) (P $AMP$lt; 0.001)
0.009 (0.006–0.013) (P $AMP$lt; 0.001)
0.169 (0.058–0.280) (P = 0.003)
0.010 (0.005–0.015) (P $AMP$lt; 0.001)
0.161 (0.075–0.247) (P $AMP$lt; 0.001)
0.009 (0.005–0.013) (P $AMP$lt; 0.001)
0.129 (0.032–0.225) (P = 0.009)
0.006 (0.002–0.010) (P = 0.001)
Model 2: adjusted for age, sex, current smoking, alcohol consumption, family history of hypertension, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low density lipoprotein cholesterol, high density lipoprotein cholesterol and fasting plasma glucose. Model 3: adjusted for Model 2 and further excluded subjects with hypertension. Model 4: adjusted for Model 2 and further excluded subjects with diabetes. Model 5: adjusted for Model 2 and further excluded subjects with dyslipidemia.
observed that plasma proANP1–98 was significantly and positively associated with central obesity. What's more, adding proANP1–98 to a model containing conventional risk factors materially improved discriminatory power of central obesity. Sensitivity analyses further confirmed these findings. ANP is a member of the cardiac natriuretic peptide system (CNPS) and binds to the natriuretic peptide A receptor (NPRA) to stimulate the synthesis of intracellular cGMP and result in natriuresis, diuresis and vasodilating effects, thereby reducing blood volume, lowering BP and improving heart function [29]. A French-Czech group also found that natriuretic peptides were a specifically potent lipolytic hormone as strong as catecholamines in primates but not in rodents and other mammals [30], which implied that ANP had powerful lipomobilizing and lipolytic activity and its deficiency could be related to fat accumulation in humans. Recently, several cross-sectional studies have shown that plasma ANP concentration is decreased in individuals with obesity [9–11]. So far, there are few reports in regard to association between plasma proANP1–98 and central obesity in population. What epidemiological study face a great challenge is lack of a reliable detection methods for plasma ANP levels because of short half-life of 2 to 5 min [31], whereas proANP1–98 has a longer half-life and makes plasma measurement more feasible [32]. Therefore, plasma proANP1–98 may be a better biomarker of central obesity than ANP if there is a relationship between them. BMI is the most common anthropometric marker for assessing obesity. However, central obesity measurements such as waist circumference have been shown to be a more accurate marker of body fat distribution than BMI which cannot distinguish between muscle-related obesity and fat accumulation-related obesity [33]. Visceral adipose plays a key role in the cardiovascular and metabolic complications of obesity [6]. The pathophysiological link between cardiometabolic complications and visceral adiposity focuses on Renin-angiotensinaldosterone system, sympathetic nervous system, insulin sensitivity and CNPS recently suggested [34,35]. Natriuretic peptides are synthesized as an inactive precursor form and then pass through protein hydrolysis process to be the active form [12]. Cleavage of proANP1–126, which is the prohormone of ANP, releases equimolar amounts of the biologically active peptide ANP and inactive proANP1–98 into the circulation [13,18]. At first glance, the positive association between proANP1–98 and central obesity contradicted earlier studies which found that ANP was inversely correlated with central obesity [9–11]. However, this phenomenon is very similar to those previously reported for brain natriuretic peptide (BNP) and N-
5. Conclusions Contrary to known reduced ANP levels in central obesity, we found that plasma proANP1–98 was positively associated with central obesity. These findings suggest that elevated plasma proANP1–98 may be a marker or a risk factor for central obesity. Further studies conducted among participants with different social and culture backgrounds are needed to replicate our findings and to clarify the potential biological mechanisms. Acknowledgements We thank the participants in this study, and would like to thank all staffs of Center for Disease Prevention and Control of Gusu district for their support and assistance. The study is supported by a Project of the Priority Academic Program Development of Jiangsu Higher Education Institutions of China, and the Suzhou Science and Technology Project (SS0910 and SS201333). References [1] V.S. Malik, W.C. Willett, F.B. Hu, Global obesity: trends, risk factors and policy implications, Nat. Rev. Endocrinol. 9 (1) (2013) 13–27. [2] T. Pischon, H. Boeing, K. Hoffmann, M. Bergmann, M.B. Schulze, K. Overvad, et al., General and abdominal adiposity and risk of death in Europe, N. Engl. J. Med. 359 (20) (2008) 2105–2120. [3] D.B. Carr, K.M. Utzschneider, R.L. Hull, K. Kodama, B.M. Retzlaff, J.D. Brunzell,
29
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
[4]
[5]
[6]
[7]
[8] [9]
[10]
[11]
[12] [13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
Hypertension 22 (3) (1993) 392–403. [22] W. Kerner, J. Bruckel, Definition, classification and diagnosis of diabetes mellitus, Exp. Clin. Endocrinol. Diabetes 122 (7) (2014) 384–386. [23] Chinese guidelines on prevention and treatment of dyslipidemia in adults, Zhonghua Xin Xue Guan Bing Za Zhi 35 (5) (2007) 390–419. [24] S. Durrleman, R. Simon, Flexible regression models with cubic splines, Stat. Med. 8 (5) (1989) 551–561. [25] S. Tzikas, T. Keller, P.S. Wild, A. Schulz, I. Zwiener, T. Zeller, et al., Midregional pro-atrial natriuretic peptide in the general population/insights from the Gutenberg Health study, Clin. Chem. Lab. Med. 51 (5) (2013) 1125–1133. [26] C. Then, B. Kowall, A. Lechner, C. Meisinger, M. Heier, W. Koenig, et al., Plasma MR-proANP levels are associated with carotid intima-media thickness in the general community: the KORA F4 study, Atherosclerosis 230 (2) (2013) 235–241. [27] M. Magnusson, A. Jujic, B. Hedblad, G. Engstrom, M. Persson, J. Struck, et al., Low plasma level of atrial natriuretic peptide predicts development of diabetes: the prospective Malmo diet and cancer study, J. Clin. Endocrinol. Metab. 97 (2) (2012) 638–645. [28] M.J. Pencina, R.B. D'Agostino Sr., R.B. D'Agostino Jr., R.S. Vasan, Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond, Stat. Med. 27 (2) (2008) 157–172 (discussion 207-12). [29] L.R. Potter, S. Abbey-Hosch, D.M. Dickey, Natriuretic peptides, their receptors, and cyclic guanosine monophosphate-dependent signaling functions, Endocr. Rev. 27 (1) (2006) 47–72. [30] C. Sengenes, A. Zakaroff-Girard, A. Moulin, M. Berlan, A. Bouloumie, M. Lafontan, et al., Natriuretic peptide-dependent lipolysis in fat cells is a primate specificity, Am. J. Phys. Regul. Integr. Comp. Phys. 283 (1) (2002) R257–R265. [31] A. Rosenzweig, C.E. Seidman, Atrial natriuretic factor and related peptide hormones, Annu. Rev. Biochem. 60 (1991) 229–255. [32] H.K. Gaggin, J.L. Januzzi, Biomarkers and diagnostics in heart failure, Biochim. Biophys. Acta 1832 (12) (2013) 2442–2450. [33] P.K. Myint, C.S. Kwok, R.N. Luben, N.J. Wareham, K.T. Khaw, Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease, Heart 100 (20) (2014) 1613–1619. [34] S. Engeli, A.M. Sharma, The renin-angiotensin system and natriuretic peptides in obesity-associated hypertension, J. Mol. Med. (Berlin, Germany) 79 (1) (2001) 21–29. [35] H.E. Lebovitz, M.A. Banerji, Point: visceral adiposity is causally related to insulin resistance, Diabetes Care 28 (9) (2005) 2322–2325. [36] T. Sugisawa, I. Kishimoto, Y. Kokubo, H. Makino, Y. Miyamoto, Y. Yoshimasa, Association of plasma B-type natriuretic peptide levels with obesity in a general urban Japanese population: the Suita study, Endocr. J. 57 (8) (2010) 727–733. [37] C. Sengenes, M. Berlan, I. De Glisezinski, M. Lafontan, J. Galitzky, Natriuretic peptides: a new lipolytic pathway in human adipocytes, FASEB J. 14 (10) (2000) 1345–1351. [38] F. Fernandes, F.J. Ramires, P.C. Buck, I.J. Almeida, R. Rabelo, S.A. Dantas, et al., Nterminal-pro-brain natriuretic peptide, but not brain natriuretic peptide, is increased in patients with severe obesity, Braz. J. Med. Biol. Res. 40 (2) (2007) 153–158. [39] K.M. Hermann-Arnhof, U. Hanusch-Enserer, T. Kaestenbauer, T. Publig, A. Dunky, H.R. Rosen, et al., N-terminal pro-B-type natriuretic peptide as an indicator of possible cardiovascular disease in severely obese individuals: comparison with patients in different stages of heart failure, Clin. Chem. 51 (1) (2005) 138–143. [40] U. Hanusch-Enserer, K.M. Hermann, E. Cauza, M. Spak, B. Mahr, A. Dunky, et al., Effect of gastric banding on aminoterminal pro-brain natriuretic peptide in the morbidly obese, Obes. Res. 11 (6) (2003) 695–698. [41] P. Dessi-Fulgheri, R. Sarzani, P. Tamburrini, A. Moraca, E. Espinosa, G. Cola, et al., Plasma atrial natriuretic peptide and natriuretic peptide receptor gene expression in adipose tissue of normotensive and hypertensive obese patients, J. Hypertens. 15 (12 Pt 2) (1997) 1695–1699.
et al., Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome, Diabetes 53 (8) (2004) 2087–2094. J.N. Fain, A.K. Madan, M.L. Hiler, P. Cheema, S.W. Bahouth, Comparison of the release of adipokines by adipose tissue, adipose tissue matrix, and adipocytes from visceral and subcutaneous abdominal adipose tissues of obese humans, Endocrinology 145 (5) (2004) 2273–2282. T. McLaughlin, C. Lamendola, A. Liu, F. Abbasi, Preferential fat deposition in subcutaneous versus visceral depots is associated with insulin sensitivity, J. Clin. Endocrinol. Metab. 96 (11) (2011) E1756–E1760. I.J. Neeland, C.R. Ayers, A.K. Rohatgi, A.T. Turer, J.D. Berry, S.R. Das, et al., Associations of visceral and abdominal subcutaneous adipose tissue with markers of cardiac and metabolic risk in obese adults, Obesity (Silver Spring, Md) 21 (9) (2013) E439–E447. G.W. Kim, J.E. Lin, E.S. Blomain, S.A. Waldman, New advances in models and strategies for developing anti-obesity drugs, Expert Opin. Drug Discovery 8 (6) (2013) 655–671. M.A. Silver, The natriuretic peptide system: kidney and cardiovascular effects, Curr. Opin. Nephrol. Hypertens. 15 (1) (2006) 14–21. J.H. Wang, C.J. Lee, J.C. Hsieh, Y.C. Chen, B.G. Hsu, Serum atrial natriuretic peptide level inversely associates with metabolic syndrome in older adults, Geriatr. Gerontol. Int. 14 (3) (2014) 640–646. J.C. Hsieh, J.H. Wang, C.J. Lee, Y.C. Chen, H.H. Liou, B.G. Hsu, Low serum longacting natriuretic peptide level correlates with metabolic syndrome in hypertensive patients: a cross-sectional study, Arch. Med. Res. 44 (3) (2013) 215–220. R. Sarzani, F. Salvi, P. Dessi-Fulgheri, A. Rappelli, Renin-angiotensin system, natriuretic peptides, obesity, metabolic syndrome, and hypertension: an integrated view in humans, J. Hypertens. 26 (5) (2008) 831–843. F. Wu, W. Yan, J. Pan, J. Morser, Q. Wu, Processing of pro-atrial natriuretic peptide by corin in cardiac myocytes, J. Biol. Chem. 277 (19) (2002) 16900–16905. J. Mair, B. Lindahl, E. Giannitsis, K. Huber, K. Thygesen, M. Plebani, et al., Will sacubitril-valsartan diminish the clinical utility of B-type natriuretic peptide testing in acute cardiac care? Eur. Heart J. Acute Cardiovasc. Care (2016). J.C. Chan, O. Knudson, F. Wu, J. Morser, W.P. Dole, Q. Wu, Hypertension in mice lacking the proatrial natriuretic peptide convertase corin, Proc. Natl. Acad. Sci. U. S. A. 102 (3) (2005) 785–790. D.K. Mayfield, A.M. Brown, G.P. Page, W.T. Garvey, M.D. Shriver, G. Argyropoulos, A role for the Agouti-Related Protein promoter in obesity and type 2 diabetes, Biochem. Biophys. Res. Commun. 287 (2) (2001) 568–573. D. Enshell-Seijffers, C. Lindon, B.A. Morgan, The serine protease Corin is a novel modifier of the Agouti pathway, Development (Cambridge, England) 135 (2) (2008) 217–225. H. Peng, Q. Zhang, H. Shen, Y. Liu, X. Chao, H. Tian, et al., Association between serum soluble corin and obesity in Chinese adults: a cross-sectional study, Obesity (Silver Spring, Md) 23 (4) (2015) 856–861. A. Clerico, F.A. Recchia, C. Passino, M. Emdin, Cardiac endocrine function is an essential component of the homeostatic regulation network: physiological and clinical implications, Am. J. Physiol. Heart Circ. Physiol. 290 (1) (2006) H17–H29. Zhou Bei-Fan, Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults: study on optimal cut-off points of body mass index and waist circumference in Chinese adults, Asia Pac. J. Clin. Nutr. 11 (Suppl. 8) (2002) (S685–S93). M.A. Weber, E.L. Schiffrin, W.B. White, S. Mann, L.H. Lindholm, J.G. Kenerson, et al., Clinical practice guidelines for the management of hypertension in the community: a statement by the American Society of Hypertension and the International Society of Hypertension, J. Clin. Hypertens. (Greenwich) 16 (1) (2014) 14–26. 1993 guidelines for the management of mild hypertension. Memorandum from a World Health Organization/International Society of Hypertension meeting. Guidelines subcommittee of the WHO/ISH Mild hypertension Liaison committee,
30
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/cca
Plasma proANP1–98 levels are positively associated with central obesity: A cross-sectional study in a general population of China
MARK
Zhengbao Zhua,b,1, Qiu Zhangc,1, Hao Penga,b, Chongke Zhonga,b, Yan Liua,b, Xinfeng Huangfua,b, Yunfan Tiana,b, Xiangqin Chaoc, Aili Wanga,b, Jianhua Jinc, Yonghong Zhanga,b,⁎ a b c
Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China. Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China. Center for Disease Prevention and Control of Gusu District, Suzhou, China.
A R T I C L E I N F O
A B S T R A C T
Keywords: Plasma proANP Waist circumference Central obesity Chinese Cross-sectional study
Background: Atrial natriuretic peptide (ANP) and its prohormone activating enzyme are associated with central obesity, suggesting there may be a potential relationship between proANP1–98 and central obesity. However, the association is still lack of population-based evidence. We explored the association in a general population of China. Methods: We measured plasma proANP1–98, waist circumference and other traditional biomarkers in 2203 participants aged ≥ 30 y. Multivariate logistic regression models were used to determine the association between plasma proANP1–98 and central obesity, and odds ratio (OR) and 95% confidence interval (CI) were calculated. Results: High proANP1–98 was significantly associated with increased risk of central obesity in participants, and the multivariate adjusted OR (95% CI) of central obesity associated with the second, third and fourth quartiles of proANP1–98 were 1.33 (1.03–1.72), 1.69 (1.31–2.19) and 1.76 (1.35–2.29), respectively, compared with the lowest quartile of proANP1–98. There was a dose-response relationship between proANP1–98 and risk of central obesity among the participants (Ptrend $AMP$lt; 0.001). Sensitivity analyses further confirmed these associations. Adding proANP1–98 to a model containing conventional risk factors improved discriminatory power of central obesity (as shown by significant improvement in continuous NRI and IDI). Conclusions: Contrary to known reduced ANP levels in central obesity, we found that plasma proANP1–98 was positively associated with central obesity, suggesting that elevated plasma proANP1–98 may be a marker or a risk factor for central obesity.
1. Introduction
extracellular fluid volume and normal blood pressure [8]. In the past decade, accumulating evidence has demonstrated that circulating ANP was reduced in individuals with central obesity [9–11]. As we all know, corin is the only activating enzyme of proANP1–126 which is the prohormone of ANP [12,13] and it has been suggested to be associated with central obesity in cell- and animal-based studies [14–16]. Furthermore, our previous epidemiological study found a higher serum soluble corin concentration in individuals with central obesity compared to those without central obesity [17]. Cleavage of proANP1–126 releases equimolar amounts of the biologically active peptide ANP and inactive proANP1–98 into the circulation [13,18]. These evidences suggest that there may be a potential association between plasma proANP1–98 and central obesity.
Obesity is a global pandemic and its prevalence has more than doubled in the last 30 y, resulting in a staggering disease burden around the world [1]. It is widely accepted that central obesity is more closely related to metabolic and cardiovascular complications than general obesity [2,3], and visceral adipose tissue is associated with a greater atherosclerotic risk profile than subcutaneous fat when present in excess [4–6]. Although existing strategies to prevent central obesity through lifestyle improvements and medical intervention have achieved some success, but there is still room for further improvement [7]. Some unknown risk factors for central obesity need to be studied to improve central obesity prevention and control. Atrial natriuretic peptide (ANP) plays a key role in maintaining
⁎
1
Corresponding author: Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, China. E-mail address: [email protected] (Y. Zhang). These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.cca.2017.03.019 Received 28 October 2016; Received in revised form 16 March 2017; Accepted 17 March 2017 Available online 19 March 2017 0009-8981/ © 2017 Published by Elsevier B.V.
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
2. Methods
tions of unknown samples were determined. Intra- and inter-assay coefficients of variation were $AMP$lt; 2% and $AMP$lt; 4%, respectively.
2.1. Study participants
2.3. Statistical analysis
We conducted a cross-sectional study in a traditional but economically developed district of Suzhou from January to May, 2010. The participants were selected via multiphase cluster random sampling. From the total 20 urban communities and 19 rural villages in the district, 4 urban communities, and 4 rural villages were randomly selected as the research fields. The residents aged ≥ 30 y living in the 4 urban communities and 4 rural villages were selected as subjects. The exclusion criteria were to meet one of the followings: (1) having clinical suspicion of diseases which may cause secondary hypertension (e.g., renal artery stenosis, coarctation, glomerulonephritis, pyelonephritis, phaeochromocytoma, Cushing's syndrome, Conn's syndrome), (2) selfreported history of coronary heart disease, stroke, or tumors, (3) selfreported thyroid or parathyroid diseases, (4) being pregnant. There were a total of 3061 eligible residents in the study fields, but only 2706 (participating rate: 88%) persons participated in this study. Among 2706 participants, 503 were excluded because they refused to offer blood samples, or some collected samples were hemolyzed in transport or storage, or failed to measure plasma proANP1–98 levels, a total of 2203 participants were finally included in current analysis. This study was approved by the Soochow University Ethics Committee. Written informed consent was obtained from all study participants.
Baseline characteristics were presented and compared between the participants with central obesity and those without central obesity. Comparisons in rates for categorical variables were performed by using the χ2 test. Comparisons in means of continuous variables (normal distribution) and in medians of continuous variables (skewed distribution) were analyzed by using Student's t-test and Wilcoxon rank-sum test, respectively. Multivariate non-conditional logistic regression models were used to assess the association of plasma proANP1–98 with central obesity. All participants were divided into 4 groups according to the quartiles of plasma proANP1–98 concentration in men and women, respectively. The quartile values of plasma proANP1–98 were 0.63, 1.04, and 1.51 nmol/l in men and 0.68, 1.15, and 1.69 nmol/l in women. Odds ratios (OR) and 95% confidence intervals (CI) of central obesity were calculated for upper quartiles of proANP1–98 with the lowest quartile as a reference. Trends for the ORs of central obesity across increasing proANP1–98 categories were determined, having proANP1–98 category as an ordinal variable. In addition, the potential covariates such as age, sex, current smoking, alcohol consumption, family history of hypertension, SBP, DBP, TC, TG, LDL-C, HDL-C and FPG were included in the multivariate models. We further used nonparametric restricted cubic splines to explore the shape of relationship between plasma proANP1–98 and central obesity, with 4 knots defined at the 5th, 35th, 65th, and 95th percentiles of proANP1–98 [24]. Some studies have found that hypertension, diabetes and dyslipidemia can affect the plasma proANP1–98 [25–27]. Therefore, in order to weaken or even eliminate the confounding effects of these diseases on the relationship between plasma proANP1–98 and central obesity, we performed sensitivity analyses which repeated the multivariate nonconditional logistic regression models after excluding the subjects with hypertension, diabetes and dyslipidemia, respectively. We also used the continuous net reclassification index (NRI) and integrated discrimination improvement (IDI) statistics [28] to assess whether inclusion of high plasma proANP1–98 concentration (alone or together) improved discriminatory abilities for risk of central obesity. A 2-tailed P $AMP $lt; 0.05 was considered statistically significant. SAS statistical software (ver 9.4) and R statistical software (ver 2.15) were used for data analysis.
2.2. Data collection Data on demographic information, lifestyle risk factors, and personal medical history were collected with standard questionnaires in Chinese language administered by trained staff. Cigarette smoking was defined as having smoked at least 1 cigarette per day for 1 year or more and reported current smoking. Alcohol consumption was defined as consuming any type of alcohol beverage at least once per week during the last three years. Body weight and height were measured using a regularly calibrated stadiometer and balance-beam scale with subjects wearing light clothing and no shoes. Waist circumference (WC) was measured at the level of 1 cm above the umbilicus. For this analysis, central obesity was defined as WC ≥ 85 cm for men and as WC ≥ 80 cm for women based on the recommendations of the Working Group on Obesity in China [19]. Three consecutive sitting blood pressure (BP) measurements (30 s interval between each) were measured by trained staff using a standard mercury sphygmomanometer according to a standard protocol [20], after the subjects had been resting for at least 5 min. The first and fifth Korotkoff sounds were recorded as systolic BP (SBP) and diastolic BP (DBP), respectively. The mean of the three records was used in analysis. Hypertension was defined as SBP ≥ 140 mm Hg or DBP ≥ 90 mm Hg or use of antihypertensive medication in the last 2 weeks [21]. Blood samples were collected in EDTA-containing tubes by venipuncture in the morning after a requested overnight fast (at least 8 h). All plasma and serum samples were frozen at −80 °C until laboratory testing. Total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol, low density lipoprotein cholesterol, and fasting plasma glucose (FPG) were measured for all participants. All the biochemical indexes were analyzed enzymatically on Hitachi 7020 automatic biochemical analyzer using commercial reagents. Intra- and inter-assay CVs were $AMP$lt; 2% and $AMP$lt; 4%, respectively. Diabetes was defined as FPG ≥ 7.0 mmol/l or use of hypoglycemic medication in the last 2 weeks [22]. Dyslipidemia was defined as TC ≥ 6.22 mmol/l or LDL-C ≥ 4.14 mmol/l or TG ≥ 2.26 mmol/l or HDL-C $AMP $lt; 1.04 mmol/l or use of lipid-lowering drugs in the last 2 weeks [23]. ProANP (1–98) ELISA No. BI-20892 kits (BIOMEDICA, AUSTRIA) was used to examine soluble proANP1–98 concentration in plasma samples. All the samples were processed in a duplicate assay. A standard curve was constructed and from which proANP1–98 concentra-
3. Results 3.1. Baseline characteristics of study participants A total of 2203 participants, including 842 males and 1361 females, were included in the present analysis and average age was 53 y (from 30 to 80 y). Among them, 1165 (52.88%) participants were central obesity. The baseline characteristics of study participants were presented in Table 1. Participants with central obesity were more likely to be older, males, hypertensive, have higher levels of SBP, DBP, TC, TG, LDL-C, and FPG, and have a lower level of HDL-C compared with those with a normal WC (all P values $AMP$lt; 0.05). The median concentration of plasma proANP1–98 was significantly higher in the participants with central obesity than that in those with normal WC (0.99 vs. 1.18 nmol/l, P $AMP$lt; 0.05). 3.2. Association between plasma proANP1–98 and central obesity The association between plasma proANP1–98 and central obesity was shown in Table 2. After adjustment for age, sex, current smoking, alcohol consumption, family history of hypertension, SBP, DBP, TC, TG, LDL-C, HDL-C and FPG, the participants in the second (OR = 1.33, 27
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
Table 1 Baseline characteristics of study participants. Characteristics
Normal WC
Central obesity
P-value
No. of participants Age, mean ± SD Male, n (%) Cigarette smoking, n (%) Alcohol consumption, n (%) FHH, n (%) HBP, n (%) SBP, mean ± SD DBP, mean ± SD TC, mmol/l TG, mmol/l LDL-C, mmol/l HDL-C, mmol/l FPG, mmol/l ProANP1–98, nmol/l
1038 50.75 ± 9.38 374 (36.03) 235 (22.64) 179 (17.24) 280 (26.97) 316 (30.44) 126.01 ± 15.85 82.68 ± 8.88 5.00 (4.46–5.61) 0.93 (0.69–1.34) 2.85 (2.44–3.31) 1.55 (1.33–1.82) 5.00 (4.60–5.50) 0.99 (0.58–1.51)
1165 54.35 ± 9.07 468 (40.17) 265 (22.75) 238 (20.43) 330 (28.33) 624 (53.56) 133.46 ± 16.81 86.50 ± 8.73 5.21 (4.63–5.79) 1.30 (0.91–1.79) 3.04 (2.59–3.48) 1.39 (1.18–1.64) 5.30 (4.80–5.90) 1.18 (0.72–1.72)
$AMP$lt; 0.001 0.046 0.952 0.057 0.479 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001 $AMP$lt; 0.001
All values are expressed with median (inter-quartile range) unless otherwise noted. Normal WC was defined as WC $AMP$lt; 85 cm for men and WC $AMP$lt; 80 cm for women; and central obesity was defined as WC ≥ 85 cm for men and WC ≥ 80 cm for women. WC, waist circumference; FHH, family history of hypertension; HBP, diagnosis of hypertension; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; TG, triglycerides; LDL-C, low density lipoprotein cholesterol; HDL-C, high density lipoprotein cholesterol; FPG, fasting plasma glucose. Table 2 Odds ratio (ORs) and 95% confidence intervals (CIs) of central obesity according to quartiles of plasma proANP1–98. Variable
proANP1–98 (nmol/l)
Ptrend
Q1
Q2
Q3
Q4
No. of cases (%) Model 1
253 (45.50)
280 (50.27)
301 (55.43)
331 (60.51)
1.00
Model 2
1.00
1.19 (0.94–1.52) 1.33 (1.03–1.72)
1.42 (1.11–1.80) 1.69 (1.31–2.19)
1.49 (1.16–1.91) 1.76 (1.35–2.29)
$AMP $lt; 0.001 $AMP $lt; 0.001
1.17 (0.84–1.64) 1.21 (0.92–1.56) 1.22 (0.90–1.66)
1.54 (1.09–2.17) 1.58 (1.21–2.07) 1.82 (1.33–2.47)
1.71 (1.18–2.48) 1.68 (1.28–2.20) 1.52 (1.11–2.07)
0.001
Sensitivity analyses Model 3 1.00 Model 4
1.00
Model 5
1.00
$AMP $lt; 0.001 0.001
Fig. 1. Adjusted ORs of central obesity according to proANP1–98. Odds ratios and 95% confidence intervals derived from restricted cubic spline regression, with knots placed at the 5th, 35th, 65th, and 95th percentiles of proANP1–98. The reference point for proANP1–98 is the midpoint of the reference group (≤ 0.02 nmol/l). Panel adjusted for the same variables as model 2 in Table 2.
Q1: ≤ 0.63 nmol/l for men and ≤ 0.68 nmol/l for women; Q2: 0.64–1.04 nmol/l for men and 0.69–1.15 nmol/l for women; Q3: 1.05–1.51 nmol/l for men and 1.16–1.69 nmol/l for women; Q4: $AMP$gt; 1.51 nmol/l for men and $AMP$gt; 1.69 nmol/l for women. Model 1: adjusted for age and sex. Model 2: adjusted for age, sex, current smoking, alcohol consumption, family history of hypertension, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low density lipoprotein cholesterol, high density lipoprotein cholesterol and fasting plasma glucose. Model 3: adjusted for Model 2 and further excluded subjects with hypertension. Model 4: adjusted for Model 2 and further excluded subjects with diabetes. Model 5: adjusted for Model 2 and further excluded subjects with dyslipidemia.
proANP1–98 levels after multivariate adjustment. 3.3. Incremental discriminatory ability of plasma proANP1–98 for central obesity We examined whether adding plasma proANP1–98 to the conditional logistic regression model consisting of conventional risk factors for obesity improved the discriminatory abilities for risk of central obesity among study participants. High levels of plasma proANP1–98 improved materially the discriminatory ability based on traditional risk factors for central obesity, as shown by significant improvement in continuous NRI and IDI statistics. Moreover, the incremental discriminatory ability of plasma proANP1–98 for central obesity remained stable in subjects without hypertension or diabetes or dyslipidemia (as described in Table 3).
P = 0.03),third (OR = 1.69, P $AMP$lt; 0.001) and fourth (OR = 1.76, P $AMP$lt; 0.001) quartiles had significantly increased odds of central obesity compared to those in the lowest quartile. There was a dose-response relationship between proANP1–98 and risk of central obesity, namely, the ORs of central obesity positively increased with plasma proANP1–98 levels (Ptrend $AMP$lt; 0.001). Furthermore, we analyzed the association between plasma proANP1–98 levels and central obesity using restricted cubic splines. As shown in Fig. 1, with an increase of plasma proANP1–98 levels, the risk of central obesity increased among participants (Pnonlinearity = 0.163, Plinearity $AMP $lt; 0.001). After sensitivity analyses, the association of plasma proANP1–98 with central obesity remained. ORs of central obesity remained positively and significantly increased with elevated plasma
4. Discussion We conducted a cross-sectional study to examine the relationship between plasma proANP1–98 and prevalent central obesity in 2203 adults aged 30 years and above in Suzhou, China. In this study, we 28
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
terminal-pro-brain natriuretic peptide (NT-proBNP) in obesity. Similarly, the plasma levels of BNP which has lipolytic activity as ANP are decreased in obesity [36,37], but NT-proBNP is found to be increased in obesity [38,39] and weight loss could reduce the increased range of NTproBNP in the morbidly obese [40]. It is plausible to speculate that the synthesis of proANP1–98 and ANP might be elevated in response to visceral adipose accumulation as a counter-system against reduced ANP concentrations. This hypothesis was also supported by our previous study. We found that serum soluble concentration of corin which was the only activating enzyme of proANP1–126 was increased in individuals with central obesity [17], suggesting that the releases of the active ANP and inactive proANP1–98 into the circulation were increased. Interestingly, it is also reported that natriuretic peptide clearance receptors (NPR-C) expression is elevated in the adipose tissue of humans with obesity, which may contribute to the increased clearance of ANP and decreased ANP concentrations in obesity [38,41]. However, proANP1–98 is not cleared by NPR-C in adipose tissue [38,41], which may lead to the accumulation of proANP1–98 in obesity. Further studies are needed to clarify the mechanism of increased proANP1–98 levels in individuals with central obesity. This study includes a relatively large number of subjects, which enabled us to perform sensitivity analyses of this association. We excluded the participants who had a history of stroke, coronary heart disease, or tumors, which might affect the plasma proANP1–98 concentration. All data were collected with rigid quality control. We collected several important variables which could confound the observed association. These variables include cigarette smoking, alcohol consumption, blood glucose and blood lipids. After controlling these covariate variables, the finding still showed that plasma proANP1–98 was positively associated with central obesity; in sensitivity analyses, the associations persisted in all models. However, there are also some limitations that should be mentioned. A causal relationship between plasma proANP1–98 and central obesity cannot be inferred because this study is only a cross-sectional study. In addition, the measurement of adipocytokines was not performed as part of the study, thus we could not compare the role of proANP1–98 with that of adipocytokines in central obesity assessment among our study participants. Further studies are needed to compare the role of proANP1–98 with adipocytokines in central obesity.
Table 3 Reclassification and discrimination statistics (95% CI) for risk of central obesity by plasma proANP1–98 among study participants.
Model 2 Model 2 + proANP1–98 Model 3 Model 3 + proANP1–98 Model 4 Model 4 + proANP1–98 Model 5 Model 5 + proANP1–98
NRI
IDI
0.166 (0.083–0.249) (P $AMP$lt; 0.001)
0.009 (0.006–0.013) (P $AMP$lt; 0.001)
0.169 (0.058–0.280) (P = 0.003)
0.010 (0.005–0.015) (P $AMP$lt; 0.001)
0.161 (0.075–0.247) (P $AMP$lt; 0.001)
0.009 (0.005–0.013) (P $AMP$lt; 0.001)
0.129 (0.032–0.225) (P = 0.009)
0.006 (0.002–0.010) (P = 0.001)
Model 2: adjusted for age, sex, current smoking, alcohol consumption, family history of hypertension, systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides, low density lipoprotein cholesterol, high density lipoprotein cholesterol and fasting plasma glucose. Model 3: adjusted for Model 2 and further excluded subjects with hypertension. Model 4: adjusted for Model 2 and further excluded subjects with diabetes. Model 5: adjusted for Model 2 and further excluded subjects with dyslipidemia.
observed that plasma proANP1–98 was significantly and positively associated with central obesity. What's more, adding proANP1–98 to a model containing conventional risk factors materially improved discriminatory power of central obesity. Sensitivity analyses further confirmed these findings. ANP is a member of the cardiac natriuretic peptide system (CNPS) and binds to the natriuretic peptide A receptor (NPRA) to stimulate the synthesis of intracellular cGMP and result in natriuresis, diuresis and vasodilating effects, thereby reducing blood volume, lowering BP and improving heart function [29]. A French-Czech group also found that natriuretic peptides were a specifically potent lipolytic hormone as strong as catecholamines in primates but not in rodents and other mammals [30], which implied that ANP had powerful lipomobilizing and lipolytic activity and its deficiency could be related to fat accumulation in humans. Recently, several cross-sectional studies have shown that plasma ANP concentration is decreased in individuals with obesity [9–11]. So far, there are few reports in regard to association between plasma proANP1–98 and central obesity in population. What epidemiological study face a great challenge is lack of a reliable detection methods for plasma ANP levels because of short half-life of 2 to 5 min [31], whereas proANP1–98 has a longer half-life and makes plasma measurement more feasible [32]. Therefore, plasma proANP1–98 may be a better biomarker of central obesity than ANP if there is a relationship between them. BMI is the most common anthropometric marker for assessing obesity. However, central obesity measurements such as waist circumference have been shown to be a more accurate marker of body fat distribution than BMI which cannot distinguish between muscle-related obesity and fat accumulation-related obesity [33]. Visceral adipose plays a key role in the cardiovascular and metabolic complications of obesity [6]. The pathophysiological link between cardiometabolic complications and visceral adiposity focuses on Renin-angiotensinaldosterone system, sympathetic nervous system, insulin sensitivity and CNPS recently suggested [34,35]. Natriuretic peptides are synthesized as an inactive precursor form and then pass through protein hydrolysis process to be the active form [12]. Cleavage of proANP1–126, which is the prohormone of ANP, releases equimolar amounts of the biologically active peptide ANP and inactive proANP1–98 into the circulation [13,18]. At first glance, the positive association between proANP1–98 and central obesity contradicted earlier studies which found that ANP was inversely correlated with central obesity [9–11]. However, this phenomenon is very similar to those previously reported for brain natriuretic peptide (BNP) and N-
5. Conclusions Contrary to known reduced ANP levels in central obesity, we found that plasma proANP1–98 was positively associated with central obesity. These findings suggest that elevated plasma proANP1–98 may be a marker or a risk factor for central obesity. Further studies conducted among participants with different social and culture backgrounds are needed to replicate our findings and to clarify the potential biological mechanisms. Acknowledgements We thank the participants in this study, and would like to thank all staffs of Center for Disease Prevention and Control of Gusu district for their support and assistance. The study is supported by a Project of the Priority Academic Program Development of Jiangsu Higher Education Institutions of China, and the Suzhou Science and Technology Project (SS0910 and SS201333). References [1] V.S. Malik, W.C. Willett, F.B. Hu, Global obesity: trends, risk factors and policy implications, Nat. Rev. Endocrinol. 9 (1) (2013) 13–27. [2] T. Pischon, H. Boeing, K. Hoffmann, M. Bergmann, M.B. Schulze, K. Overvad, et al., General and abdominal adiposity and risk of death in Europe, N. Engl. J. Med. 359 (20) (2008) 2105–2120. [3] D.B. Carr, K.M. Utzschneider, R.L. Hull, K. Kodama, B.M. Retzlaff, J.D. Brunzell,
29
Clinica Chimica Acta 469 (2017) 26–30
Z. Zhu et al.
[4]
[5]
[6]
[7]
[8] [9]
[10]
[11]
[12] [13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
Hypertension 22 (3) (1993) 392–403. [22] W. Kerner, J. Bruckel, Definition, classification and diagnosis of diabetes mellitus, Exp. Clin. Endocrinol. Diabetes 122 (7) (2014) 384–386. [23] Chinese guidelines on prevention and treatment of dyslipidemia in adults, Zhonghua Xin Xue Guan Bing Za Zhi 35 (5) (2007) 390–419. [24] S. Durrleman, R. Simon, Flexible regression models with cubic splines, Stat. Med. 8 (5) (1989) 551–561. [25] S. Tzikas, T. Keller, P.S. Wild, A. Schulz, I. Zwiener, T. Zeller, et al., Midregional pro-atrial natriuretic peptide in the general population/insights from the Gutenberg Health study, Clin. Chem. Lab. Med. 51 (5) (2013) 1125–1133. [26] C. Then, B. Kowall, A. Lechner, C. Meisinger, M. Heier, W. Koenig, et al., Plasma MR-proANP levels are associated with carotid intima-media thickness in the general community: the KORA F4 study, Atherosclerosis 230 (2) (2013) 235–241. [27] M. Magnusson, A. Jujic, B. Hedblad, G. Engstrom, M. Persson, J. Struck, et al., Low plasma level of atrial natriuretic peptide predicts development of diabetes: the prospective Malmo diet and cancer study, J. Clin. Endocrinol. Metab. 97 (2) (2012) 638–645. [28] M.J. Pencina, R.B. D'Agostino Sr., R.B. D'Agostino Jr., R.S. Vasan, Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond, Stat. Med. 27 (2) (2008) 157–172 (discussion 207-12). [29] L.R. Potter, S. Abbey-Hosch, D.M. Dickey, Natriuretic peptides, their receptors, and cyclic guanosine monophosphate-dependent signaling functions, Endocr. Rev. 27 (1) (2006) 47–72. [30] C. Sengenes, A. Zakaroff-Girard, A. Moulin, M. Berlan, A. Bouloumie, M. Lafontan, et al., Natriuretic peptide-dependent lipolysis in fat cells is a primate specificity, Am. J. Phys. Regul. Integr. Comp. Phys. 283 (1) (2002) R257–R265. [31] A. Rosenzweig, C.E. Seidman, Atrial natriuretic factor and related peptide hormones, Annu. Rev. Biochem. 60 (1991) 229–255. [32] H.K. Gaggin, J.L. Januzzi, Biomarkers and diagnostics in heart failure, Biochim. Biophys. Acta 1832 (12) (2013) 2442–2450. [33] P.K. Myint, C.S. Kwok, R.N. Luben, N.J. Wareham, K.T. Khaw, Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease, Heart 100 (20) (2014) 1613–1619. [34] S. Engeli, A.M. Sharma, The renin-angiotensin system and natriuretic peptides in obesity-associated hypertension, J. Mol. Med. (Berlin, Germany) 79 (1) (2001) 21–29. [35] H.E. Lebovitz, M.A. Banerji, Point: visceral adiposity is causally related to insulin resistance, Diabetes Care 28 (9) (2005) 2322–2325. [36] T. Sugisawa, I. Kishimoto, Y. Kokubo, H. Makino, Y. Miyamoto, Y. Yoshimasa, Association of plasma B-type natriuretic peptide levels with obesity in a general urban Japanese population: the Suita study, Endocr. J. 57 (8) (2010) 727–733. [37] C. Sengenes, M. Berlan, I. De Glisezinski, M. Lafontan, J. Galitzky, Natriuretic peptides: a new lipolytic pathway in human adipocytes, FASEB J. 14 (10) (2000) 1345–1351. [38] F. Fernandes, F.J. Ramires, P.C. Buck, I.J. Almeida, R. Rabelo, S.A. Dantas, et al., Nterminal-pro-brain natriuretic peptide, but not brain natriuretic peptide, is increased in patients with severe obesity, Braz. J. Med. Biol. Res. 40 (2) (2007) 153–158. [39] K.M. Hermann-Arnhof, U. Hanusch-Enserer, T. Kaestenbauer, T. Publig, A. Dunky, H.R. Rosen, et al., N-terminal pro-B-type natriuretic peptide as an indicator of possible cardiovascular disease in severely obese individuals: comparison with patients in different stages of heart failure, Clin. Chem. 51 (1) (2005) 138–143. [40] U. Hanusch-Enserer, K.M. Hermann, E. Cauza, M. Spak, B. Mahr, A. Dunky, et al., Effect of gastric banding on aminoterminal pro-brain natriuretic peptide in the morbidly obese, Obes. Res. 11 (6) (2003) 695–698. [41] P. Dessi-Fulgheri, R. Sarzani, P. Tamburrini, A. Moraca, E. Espinosa, G. Cola, et al., Plasma atrial natriuretic peptide and natriuretic peptide receptor gene expression in adipose tissue of normotensive and hypertensive obese patients, J. Hypertens. 15 (12 Pt 2) (1997) 1695–1699.
et al., Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome, Diabetes 53 (8) (2004) 2087–2094. J.N. Fain, A.K. Madan, M.L. Hiler, P. Cheema, S.W. Bahouth, Comparison of the release of adipokines by adipose tissue, adipose tissue matrix, and adipocytes from visceral and subcutaneous abdominal adipose tissues of obese humans, Endocrinology 145 (5) (2004) 2273–2282. T. McLaughlin, C. Lamendola, A. Liu, F. Abbasi, Preferential fat deposition in subcutaneous versus visceral depots is associated with insulin sensitivity, J. Clin. Endocrinol. Metab. 96 (11) (2011) E1756–E1760. I.J. Neeland, C.R. Ayers, A.K. Rohatgi, A.T. Turer, J.D. Berry, S.R. Das, et al., Associations of visceral and abdominal subcutaneous adipose tissue with markers of cardiac and metabolic risk in obese adults, Obesity (Silver Spring, Md) 21 (9) (2013) E439–E447. G.W. Kim, J.E. Lin, E.S. Blomain, S.A. Waldman, New advances in models and strategies for developing anti-obesity drugs, Expert Opin. Drug Discovery 8 (6) (2013) 655–671. M.A. Silver, The natriuretic peptide system: kidney and cardiovascular effects, Curr. Opin. Nephrol. Hypertens. 15 (1) (2006) 14–21. J.H. Wang, C.J. Lee, J.C. Hsieh, Y.C. Chen, B.G. Hsu, Serum atrial natriuretic peptide level inversely associates with metabolic syndrome in older adults, Geriatr. Gerontol. Int. 14 (3) (2014) 640–646. J.C. Hsieh, J.H. Wang, C.J. Lee, Y.C. Chen, H.H. Liou, B.G. Hsu, Low serum longacting natriuretic peptide level correlates with metabolic syndrome in hypertensive patients: a cross-sectional study, Arch. Med. Res. 44 (3) (2013) 215–220. R. Sarzani, F. Salvi, P. Dessi-Fulgheri, A. Rappelli, Renin-angiotensin system, natriuretic peptides, obesity, metabolic syndrome, and hypertension: an integrated view in humans, J. Hypertens. 26 (5) (2008) 831–843. F. Wu, W. Yan, J. Pan, J. Morser, Q. Wu, Processing of pro-atrial natriuretic peptide by corin in cardiac myocytes, J. Biol. Chem. 277 (19) (2002) 16900–16905. J. Mair, B. Lindahl, E. Giannitsis, K. Huber, K. Thygesen, M. Plebani, et al., Will sacubitril-valsartan diminish the clinical utility of B-type natriuretic peptide testing in acute cardiac care? Eur. Heart J. Acute Cardiovasc. Care (2016). J.C. Chan, O. Knudson, F. Wu, J. Morser, W.P. Dole, Q. Wu, Hypertension in mice lacking the proatrial natriuretic peptide convertase corin, Proc. Natl. Acad. Sci. U. S. A. 102 (3) (2005) 785–790. D.K. Mayfield, A.M. Brown, G.P. Page, W.T. Garvey, M.D. Shriver, G. Argyropoulos, A role for the Agouti-Related Protein promoter in obesity and type 2 diabetes, Biochem. Biophys. Res. Commun. 287 (2) (2001) 568–573. D. Enshell-Seijffers, C. Lindon, B.A. Morgan, The serine protease Corin is a novel modifier of the Agouti pathway, Development (Cambridge, England) 135 (2) (2008) 217–225. H. Peng, Q. Zhang, H. Shen, Y. Liu, X. Chao, H. Tian, et al., Association between serum soluble corin and obesity in Chinese adults: a cross-sectional study, Obesity (Silver Spring, Md) 23 (4) (2015) 856–861. A. Clerico, F.A. Recchia, C. Passino, M. Emdin, Cardiac endocrine function is an essential component of the homeostatic regulation network: physiological and clinical implications, Am. J. Physiol. Heart Circ. Physiol. 290 (1) (2006) H17–H29. Zhou Bei-Fan, Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults: study on optimal cut-off points of body mass index and waist circumference in Chinese adults, Asia Pac. J. Clin. Nutr. 11 (Suppl. 8) (2002) (S685–S93). M.A. Weber, E.L. Schiffrin, W.B. White, S. Mann, L.H. Lindholm, J.G. Kenerson, et al., Clinical practice guidelines for the management of hypertension in the community: a statement by the American Society of Hypertension and the International Society of Hypertension, J. Clin. Hypertens. (Greenwich) 16 (1) (2014) 14–26. 1993 guidelines for the management of mild hypertension. Memorandum from a World Health Organization/International Society of Hypertension meeting. Guidelines subcommittee of the WHO/ISH Mild hypertension Liaison committee,
30