Down-regulation of S100A1 protein in patients with metabolic syndrome and its association with zinc-α2-glycoprotein

Abstract

Objectives

It has been proposed that zinc-α2-glycoprotein and S100A1 are possibly linked to the development of lipogenesis and obesity. We aimed to measure serum levels of S100A1 and zinc-α2-glycoprotein in patients with metabolic syndrome and investigate any associations of these two novel peptides with each other or components of metabolic syndrome.

Methods

Forty-four patients with metabolic syndrome and the equivalent number of healthy controls participated in this study. The participants’ body mass index, waist circumference, systolic and diastolic blood pressure were measured. Serum levels of low- and high-density lipoprotein cholesterol, total cholesterol, triglyceride, fasting blood sugar, insulin, zinc-α2-glycoprotein and S100A1 protein were determined.

Results

Higher levels of anthropometric and lipid indices, metabolic factors and also SBP and DBP were observed in the metabolic syndrome group. Serum S100A1 levels were significantly lower in the metabolic syndrome group than the control group (P = 0.008). There was a strong positive correlation between serum zinc-α2-glycoprotein and S100A1 levels (r = 0.80, P < 0.0001). Serum levels of both S100A1 (P = 0.03) and zinc-α2-glycoprotein (P = 0.02) were potentially higher in subjects with hypertension than those with normal blood pressure, though these were found as part of multiple testing.

Conclusion

The results indicate that changes in the circulating level of S100A1 protein occur in metabolic syndrome patients. The strong correlation between serum zinc-α2-glycoprotein and S100A1 might suggest that production or release of these two proteins could be related mechanistically.

Keywords

Metabolic syndrome zinc-α2-glycoprotein S100A1

Introduction

The metabolic syndrome (MetS) is a multifactorial disease of the new world which comprises a combination of metabolic, anthropometric and blood circulation abnormalities. Based on the definition outlined by the Adult Treatment Panel III (ATPIII), anyone who has at least three of the five factors (central obesity, raised blood pressure, raised fasting triglyceride (TG), low high-density lipoprotein cholesterol (HDL-C) level and raised fasting blood glucose (FBG)) has MetS.^1,2 These patients are at high risk for coronary artery disease, type 2 diabetes mellitus and subsequent acute and chronic complications.^3,4 A quarter of the world’s adult population have MetS, with a higher risk of occurrence in females.^4,5 Although the aetiology of this syndrome is not clear, there are some triggers suggested, including obesity,⁶ ageing,⁷ sedentary life style,⁸ high calorie food and alcohol intake,^9,10 chronic stress,¹¹ sleep disorders¹² and dysregulation of adipokines and other biochemical markers.¹³

S100 calcium-binding protein A1 (S100A1) is a small peptide from the S100 family that has four platforms for binding calcium ions. This peptide is highly expressed in heart and skeletal muscle and is involved in the regulation of muscle contractility. Evidence indicates that S100A1 plays a major role in cardiac performance,¹⁴ blood pressure regulation^15,16 and skeletal muscle function.¹⁷ Olofsson et al. have also suggested S100 A1 gene as a potential susceptibility factor for obesity and linked its expression to resting energy expenditure. The suggestion was based on the observation that expression of the gene was low in obese subjects.¹⁸ However, evidence about the role of S100A1 in obesity-associated metabolic diseases is remarkably scarce.

Zinc-α2-glycoprotein (ZAG), a lipid-mobilizing factor, is expressed in adipocytes and has recently been identified as a novel adipokine and a marker of fat catabolism in humans.^19,20 Evidence indicates that insufficient production of ZAG could potentially be involved in metabolic diseases such as obesity and diabetes.^21–25 It has been demonstrated that ZAG-knockout mice are susceptible to increased body weight, whereas transgenic mice over-expressing ZAG display weight loss.²¹ Decreased ZAG messenger RNA (mRNA) and protein expression has been reported in adipose tissue, liver and plasma of obese mice²² and also in subcutaneous and visceral adipose tissue of obese patients.^23,24 An inverse association has also been documented between ZAG gene expression in adipose tissue with plasma insulin levels and homeostatic model assessment-insulin resistance (HOMA-IR).²⁵

In view of the involvement of S100A1 and ZAG in metabolic diseases such as obesity, diabetes and cardiovascular diseases, we hypothesised that there is possibly an interaction between these two peptides. However, studies of ZAG levels in patients with MetS, a major risk factor for metabolic diseases, are limited and inconsistent.^26,27 Further, to our knowledge, there has been no report addressing serum levels of S100A1 in these patients. Therefore, we aimed to investigate the serum levels of S100A1 and ZAG in patients with MetS and to find whether any association exists either between these two novel peptides or with the components of MetS.

Materials and methods

Participants

This cross-sectional study was carried out from January to June 2014. Consecutive sampling method was used to enrol participants from a medical weight loss centre. A power calculation²⁸ based on mean ± standard deviation (SD) of S100 protein from previously published data, with 5% significance level test (α = 0.05), power of 90% (β = 0.1), accounting 20% expected dropouts suggested a sample size of 44 in each group. Consecutive potential participants were assessed until these figures were obtained. Individuals who met the inclusion/exclusion criteria were eligible for the study. After biochemical tests, those who met MetS criteria were assigned to the MetS group; those who did not were considered for the control group. Once the MetS group reached 44 patients (20 male and 24 female), the search continued for ‘control’ patients until this also reached 44 (23 male and 21 female). Thus, eighty-eight adult volunteers (aged 30–50 years) participated in the study. Written informed consent was obtained from each subject. The study was approved by the Ethical Committee of Tabriz University of Medical Sciences, Tabriz, Iran.

Participants in the MetS group had at least three of five ATPIII criteria; abdominal obesity, given as waist circumference (WC) >88 cm (women) or >102 cm (men); TG ≥ 1.7 mmol/L; HDL-C < 1.29 mmol/L (women) or <1.03 mmol/L (men); systolic blood pressure (SBP) ≥130 mm Hg; diastolic blood pressure (DBP) ≥85 mm Hg and FBG ≥ 5.6 mmol/L. Exclusion criteria were body mass index (BMI) ≥ 40 kg/m², infectious and chronic inflammatory diseases, history of psychiatric diseases (such as depression, anxiety or psychosis), receiving anti-obesity, anti-inflammatory, anti-hypertensive treatments during the study period, thyroid disorders, endocrine diseases, smoking, excessive consumption of alcohol, pregnancy and breast-feeding, menopause and diet therapy during three months prior to the study.

Demographic data, including age, gender, physical activity, education level, smoking and drinking status, were recorded on a personal questionnaire by each participant.

Anthropometric and blood pressure assessments

Body weight was measured, with participant wearing light underwear and no shoes, by the SECA (SECA® Germany) pointer scale with 100 g accuracy. Height was measured with 0.5 cm precision while subject stood upright with feet together. We calculated BMI using metric units (kg/m²). Waist circumference was measured at the mid-point between the lower costal margin and iliac crest to the nearest 0.5 cm by a flexible tape-measure without making any pressure on body surface while participant was at the end of normal expiration. SBP and DBP were measured twice for each participant with at least 15 min rest before first measurement and 15 min interval before the second. Means of these two findings for SBP and DBP were recorded as the blood pressure.

Biochemical assessment

After an overnight fasting, 5 mL of venous blood was collected. Serum samples were separated by centrifugation at 3500 r/min for 15 min at 4℃. Aliquots were stored at −70℃ until analysis.

Levels of serum total cholesterol (TC), HDL-C and TG were measured by enzymatic colorimetric methods using a commercially available kit (Pars Azmone, Tehran, Iran) on an automatic analyzer (Abbott, model Alcyon 300, USA). Serum low-density lipoprotein cholesterol (LDL-C) was calculated by the Friedewald equation.²⁹ Fasting blood sugar (FBS) was determined by the glucose oxidase method. Insulin levels were determined by insulin ELISA kit (Monobind Inc, lake forest, California). To investigate insulin sensitivity, the HOMA-IR was calculated. S100A1 and ZAG levels were measured using a commercially available Enzyme-linked immunosorbent assay (ELISA) kit (Hangzhou Eastbiopharm Co. Ltd).

Statistical analyses

Demographic characteristics of the participants were summarized by either mean ± SD for continuous data, or frequency (%) for proportional data. Differences between two groups were assessed by independent sample t test for normally distributed data and Mann-Whitney U test for nonparametric variables. Spearman’s coefficient test was used to assess the correlation between the ZAG and S100A1 proteins together and also with MetS components. The multiple testing, the authors realise, does limit the significance of the results. Data analysis was performed by SPSS 16 software (IBM SPSS statistics, Chicago, Illinois) and P values less than 0.05 were considered statistically significant.

Results

Demographic characteristics

Demographic characteristics of the studied population are presented in Table 1. Mean age of MetS and control participants were 41.39 ± 7.08 and 38.64 ± 5.77 years, respectively (P = 0.05). The proportion of individuals with lower education was higher in the MetS group (P = 0.001). There was no significant difference in levels of physical activity.

Table 1.

Demographic characteristics of the studied population.

	MetS (n = 44)	Control (n = 44)	P value
Age^a (year)	41.39 ± 7.08	38.64 ± 5.77	0.05^b
Gender^c			0.53^b
Female	24 (54.5)	21 (47.7)
Male	20 (45.5)	23 (52.3)
Literacy level^c			0.001^d
Under diploma	7 (15.9)	0 (0)
Diploma	7 (15.9)	3 (6.8)
College	30 (68.2)	41 (93.2)
Physical activity^c			0.29^b
Low	23 (52.3)	28 (63.6)
Moderate	21 (47.7)	16 (36.4)
High	0	0

ANOVA: analysis of variance; MetS: metabolic syndrome; SD: standard deviation.

Expressed as mean (SD).

P value was reported based on independent samples t test.

Expressed as frequency (percent).

P value was reported based on ANOVA.

Anthropometric, blood pressure and metabolic parameters

As expected, mean body weight, WC, WHR and BMI were significantly higher in MetS group as compared with control group (Table 2; all P < 0.0001). DBP (P = 0.01) was higher in the MetS group.

Table 2.

Anthropometric parameters and blood pressure of the studied population.^a

	MetS (N = 44)	Controls (N = 44)	P ^b
Body weight (kg)	90.13 ± 12.93	76.34 ± 15.01	<0.0001
WC (cm)	109.10 ± 11.94	88.82 ± 11.65	<0.0001
WHR	0.95 ± 0.06	0.84 ± 0.05	<0.0001
BMI (kg/m²)	32.67 ± 4.02	26.47 ± 4.34	<0.0001
SBP (mm Hg)	124.27 ± 17.32	117.64 ± 14.86	0.06
DBP (mm Hg)	82.04 ± 12.07	77.20 ± 9.50	0.01

BMI: body mass index; DBP: diastolic blood pressure; MetS: metabolic syndrome; SBP: systolic blood pressure; SD: standard deviation; WC: waist circumference; WHR: waist/hip ratio.

Data were expressed as mean ± SD.

P values were reported based on independent samples t test.

Again as expected, participants with MetS had significantly higher levels of TC, TG, LDL-C, FBS, insulin, HOMA-IR and lower concentrations of HDL-C than controls (Table 3).

Table 3.

Parameters of MetS in the studied groups.

	MetS (N = 44)	Controls (N = 44)	P
TC^a (mg/dL)	204.50 ± 37.79	174.34 ± 39.04	<0.0001^b
TG^a (mg/dL)	234.20 ± 97.53	127.14 ± 62.67	<0.0001^b
LDL-C^a (mg/dL)	118.56 ± 32.40	104.11 ± 35.60	0.05^b
HDL-C^a (mg/dL)	39.09 ± 7.41	44.79 ± 11.15	0.006^b
FBS^a (mg/dL)	111.61 ± 26.26	87.95 ± 11.53	<0.0001^b
Insulin^c (mU/mL)	0.81 (0.74, 0.92)	0.74 (0.69, 0.77)	<0.0001^d
HOMA-IR^c	23.50 (21.25, 26.755)	21.00 (20.00, 22.00)	<0.0001^d

FBS: fasting blood sugar; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment-insulin resistance; MetS: metabolic syndrome; TC: total cholesterol; TG: triglyceride.

Data were expressed as mean ± SD.

P values were reported based on independent samples t test.

Data were expressed as median (percentile 25, 75).

P values were reported based on Mann-Whitney U test.

Serum levels and association of ZAG and S100A1 protein

As shown in Figure 1, subjects with MetS had significantly lower levels of S100A1 (955.50 (839.25, 1122.40) pg/mL) than controls (1214.20 (963.62, 3753.60) pg/mL) (P = 0.008).

Figure 1.

Box-plot graphs of serum S100A1 (pg/mL) and ZAG (µg/mL) levels in MetS (n = 44) and control (n = 44) groups. Medians (quartiles 25 and 75) of S100A1 for MetS and controls were 955.50 (839.25, 1122.40) and 1214.20 (963.62, 3753.60), respectively. Medians (quartiles 25 and 75) of ZAG for MetS and controls were 357.56 (311.62, 443.81) and 369.75 (302.56, 1213.20), respectively. MetS: metabolic syndrome; ZAG: zinc-α2-glycoprotein.

Serum levels of ZAG were significantly higher in all subjects with hypertension (n = 67) vs. those with normal blood pressure (n = 21) (391.62 (311.62, 827.25) vs. 314.12 (281.31, 418.50) µg/mL) (P = 0.02). Levels of S100A1 were also higher in the hypertension group (1078.00 (910.50, 2910.50) vs. 855.50 (770.50, 1226.80) pg/mL) (P = 0.03).

Figure 2 shows the strong positive correlation between serum ZAG and S100A1 protein levels in the entire population (r = 0.80, P < 0.0001). This was also observed separately in both MetS patients (r = 0.77, P < 0.0001) and controls (r = 0.89, P < 0.0001). Age did not appear to influence serum levels of ZAG (r = 0.13, P = 0.22) and S100A1 (r = 0.11, P = 0.33).

Figure 2.

Spearman’s rank correlation test between serum S100A1 (pg/mL) and ZAG (µg/mL) levels in studied population (n = 88). ZAG: zinc-α2-glycoprotein.

Correlation of serum levels of ZAG and S100A1 protein with measured variables

As shown in Table 4, serum levels of ZAG positively associated with DBP pressure (r = 0.26, P = 0.01). Serum levels of S100A1 negatively correlated with TG (r = −0.23, P = 0.03). However, as multiple possible correlations were tested, these results cannot be presumed as significant. There was no suggested correlation between serum ZAG and S100A1 levels with any other component of MetS, age or BMI.

Table 4.

Correlation of serum levels of ZAG and S100A1 protein with measured variables.

	ZAG			S100A1
	r	P ^a	P ^b	r	P ^a	P ^b
Age	0.13	0.22	1.00	0.11	0.33	1.00
BMI	−0.05	0.64	1.00	−0.13	0.22	1.00
WC	−0.07	0.53	1.00	−0.19	0.07	0.91
WHR	−0.03	0.75	1.00	−0.07	0.49	1.00
SBP	0.14	0.19	1.00	0.11	0.30	1.00
DBP	0.26	0.01	0.13	0.19	0.08	1.00
TC	−0.02	0.82	1.00	−0.04	0.71	1.00
TG	−0.09	0.42	1.00	−0.23	0.03	0.39
LDL-C	0.02	0.86	1.00	−0.04	0.69	1.00
HDL-C	−0.02	0.88	1.00	0.16	0.15	1.00
FBS	−0.06	0.56	1.00	−0.15	0.17	1.00
Insulin	−0.09	0.40	1.00	−0.16	0.13	1.00
HOMA-IR	−0.11	0.32	1.00	−0.18	0.10	1.00

BMI: body mass index; DBP: diastolic blood pressure; FBS: fasting blood sugar; HDL-C: high-density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment-insulin resistance; LDL-C: low-density lipoprotein cholesterol; SBP: systolic blood pressure; TC: total cholesterol; TG: triglyceride; WC: waist circumference; WHR: waist/hip ratio; ZAG: zinc-α2-glycoprotein.

Expressed based on spearman’s coefficient test.

Expressed based on multiple statistical tests.

Discussion

The present study determined that serum S100A1 level was significantly lower in the MetS group compared with control group. To our knowledge, this is the first report describing S100A1 levels in MetS. S100A1 has been abundantly researched in patients with heart failure and is identified as a crucial controller of cardiac performance.^14,30 Evidence using an animal model of post-ischaemic heart failure indicates that S100A1 levels are reduced in failing cardiomyocytes³¹ and this contributes to loss of contractile performance of the diseased heart.³⁰ MetS is a major risk factor for cardiovascular diseases. It is possible that reduction of S100A1 level might be an early marker for cardiovascular disease in this condition.

The current study does not provide any mechanistic data on the reduction of S100A1 in MetS patients. However, it is possible that high activity of endothelin (ET)-1 system in MetS patients may contribute to the reduced levels of S100A1. ET-1 is a powerful vasoconstrictor peptide with a crucial role in the regulation of vascular tone. Up-regulated ET-1 system activity is related to the development of some metabolic-related diseases including hypertension, type 2 diabetes, coronary artery disease and chronic heart failure. Ferri et al. have indicated that venous plasma ET-1 levels were significantly higher in obese men with MetS than in controls.³² In addition, it has been shown that ET-1 activation reduces both cardiac S100A1 mRNA and protein levels.³⁰ However, further studies are required to establish the exact cause of the reduction.

Despite the correlation of ZAG with S100A levels, serum levels of ZAG in the current study did not significantly differ between MetS and control participants. The limited reports available show similar results, with no significant differences.^27,33 One study showed that circulating ZAG levels did not differ according to BMI or MetS classification; however, ZAG expression in adipose tissue was significantly lower in overweight and obese individuals.³³ Lower serum ZAG levels have been reported in obese patients^34,24 and its reduced expression shown in adipose tissue and liver of genetically²² or high-fat diet-induced obese animals³⁴ and also in adipose tissue of obese humans.^23,24 The inconsistent results from various investigations on serum ZAG level in humans may be related to diverse production sites of ZAG (liver, prostate, kidney, salivary glands, mammary glands and sweat glands),³⁵ food intake and energy balance²⁷and intervening factors with ZAG synthesis and expression from adipose tissue such as lipolytic genes, hormonal interactions (such as adiponectin) and possibly proteins such as S100A1. However, this warrants further researches to elucidate the exact regulatory mechanisms that determine circulating ZAG level.

An interesting finding of the current study is the strong positive association between serum levels of S100A1 and ZAG. Separate reports may suggest that the two peptides act in a same direction. Zoico et al. using mouse 3T3-L1 cells showed that S100A1 expression was highest during differentiation of the adipocytes.³⁶ Meanwhile, Bing et al. found that ZAG mRNA was present in 3T3-L1 cells and its level increased gradually after the differentiation process.³⁷ Thus, we speculate that production or release of these two proteins might be related mechanistically.

In this study, ZAG serum levels were possibly correlated with DBP. Stepan et al. in a study on patients with preeclampsia demonstrated that increased circulating ZAG was positively associated with SBP and DBP.³⁸ Kurita et al. suggested that ZAG may lead to enhancement of vascular tone through the activation of RhoA and contribute to increased blood pressure.³⁹ However, there is little further evidence to support the speculation.

We observed, for the first time, a possible inverse association between serum levels of S100A1 and TG (P = 0.03). Allowing for multiple testing, the significance of this finding is uncertain. It can thus only be a basis for speculation, but it may make intuitive sense. S100A1 is a regulator of calcium homeostasis in cardiac muscle. It directly increases sarcoplasmic reticulum calcium uptake. Any defect may lead to Ca²⁺ leakage from sarcoplasmic reticulum into the cytosol of muscle cells, with accumulation in the extracellular compartment.⁴⁰ Increased serum Ca²⁺ is reportedly associated with cardiovascular risk factors including increased SBP and DBP, and dyslipidemia⁴¹ and separately with high TG and glucose.⁴² Indeed, higher serum calcium levels have been observed in MetS patients.⁴²

In conclusion, levels of S100A1 – a peptide involved with cardiac muscle function – were lower in subjects with MetS than healthy participants. Those of ZAG – a lipid-mobilizing factor – and S100A1– a cardiac Ca²⁺ regulator – were strongly and positively correlated. Further studies may show whether production or release of these two proteins might be related mechanistically.

Limitations of the study

The present study did not provide any mechanistic data to explain down regulation of S100A1 in patients with MetS. Future investigations are needed to clarify role of ET-1 system in down regulation of S100A1 in patients with MetS and key mechanisms connecting the protein with the disease. The correlation between S100A1 with TG and ZAG with DBP should be interpreted with caution in view of the multiple statistical testing.

Footnotes

Authors’ contributions

SK conceptualized the research proposal. MA assisted in designing and facilitating inter-sectoral collaboration. EE participated in data collection. All authors contributed in analysis and interpretation and manuscript writing. All authors read and approved the final manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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