Background

It was found that thrombosis associated with obesity is mostly induced by inefficient fibrinolysis and chronic inflammation [1]. Plasmin is responsible for the instant breakage of any fibrin clot in a very important physiological process called fibrinolysis. Plasminogen activator inhibitor-1 (PAI-1) is the main regulator of fibrinolysis. It is a serine protease inhibitor which is secreted by the liver, adipose tissue, and vascular endothelium [2]. PAI-1 is responsible for the inhibition of the fibrin degradation process endogenously. It works through blockage of the action of tissue plasminogen activator and the urokinase-type activator, which consequently leads to the accumulation of fibrin in the interstitial tissues and the basement membranes [3,4,5]. Also, increased PAI-1 levels decrease normal fibrin degradation mechanisms and cause thrombosis [6]; it was believed that PAI-1 has a role in the development of the main components of the metabolic syndrome, and the increased PAI-1 levels are thought to be related positively to obesity and insulin resistance [7,8,9].

PAI-1 has been shown to be elevated in metabolic syndrome and generally is correlated with the number of components of metabolic syndrome present, such that the more severe the metabolic syndrome, the higher the PAI-1 levels [10, 11].

Aim of the work

The present study was done to investigate the impact of childhood obesity on circulating PAI-1 and its relationship to anthropometric measurements, insulin resistance, fasting blood sugar, and lipid profile. It also investigates the role of PAI-1 as a predictor for metabolic syndrome in the pediatric population.

Methods

The present work is a cross-sectional study conducted on 43 obese children recruited from Childrens’ Hospital. Cases were compared to 44 healthy children, age and sex matched; they had normal BMI according to the Egyptian growth charts (2002) [12], with no clinical evidence or family history of obesity or metabolic syndrome. Patients recruited in the study had simple exogenous obesity with ages from 7 to 12 years. Obesity is defined as BMI at or above the 95th percentile for children of the same age and sex according to the Egyptian growth curves [12, 13]. We meant by simple exogenous obesity, obesity not due to identified pathological cause, e.g., syndromic or endocrinological cause.

Patients excluded from the study were those with identified syndromes and chromosomal defects or endocrinal disorders causing obesity, those who were on medications like glucocorticoids or any affecting clotting profile, any diseases affecting fibrinolytic states (e.g., cardiovasular disease, hematological disease), and children with type 1diabetes.

Patients recruited in the study were subjected to detailed history taking, duration of obesity, history of any present or past illness (renal, hepatic, endocrinal), history of drug intake, and family history of obesity, and hypertension, and thorough physical examination, the data of the systolic and diastolic blood pressure were plotted on blood pressure tables for children and adolescents of the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children as in National High Blood Pressure Education Program [14].

Weight was measured using Seca scale Balance. Height was measured using a stadiometer. Body mass index was calculated as weight in kilograms divided by the square of height in meters (wt (kg)/Ht (m)2). Data obtained were plotted on the Egyptian Growth charts (2002) [12].

Waist circumference was measured at the end of gentle exhaling; a non-stretchable stain steal tape was held at a level midway between the lower rib margin and iliac crest all around the body in horizontal position parallel to the floor. Hip circumference is measured at the maximum protuberance of the buttock. Waist/hip ratio was then calculated [15].

Laboratory tests were done for all recruited subjects. Serum lipid profile {total serum cholesterol (TC), serum triglycerides (TG), high-density lipoprotein (HDL)} on a venous clotted sample type was centrifuged, and the serum was isolated by the device (Beckman, Synchron chemical system CK5). Assay of serum LDL cholesterol (LDL) was calculated from three primary measurements with the use of the Friedewald equation [16]. Fasting blood glucose was assayed using direct method by the device (Beckman, Synchron chemical system CK5) enzymatically, and fasting serum insulin was determined by immunoenzymometric assay using the Emmulite apparatus. Insulin resistance was estimated by using the homeostasis model assessment (HOMA) according to the following formula: HOMA = fasting serum insulin (IU/ml) × fasting serum glucose (mg/dL)/405 (insulin resistance being defined as a HOMA index > 3.16). The greater the HOMA value, the greater the level of insulin resistance [17].

The current study used the following criteria for diagnosing metabolic syndrome (MetS). MetS was considered if three or more of the following criteria were present: abdominal obesity (WC ≥ 90th percentile for age and sex); fasting TG ≥ 110 mg/dl; HDL ≤ 40 mg/dl; systolic/diastolic BP ≥ 90th percentile for age, sex, and height; and fasting glucose ≥ 100 mg/dl [18,19,20].

Assessment of plasminogen activator inhibitor-1 was done by enzyme-linked immunoassay (ELISA); this assay recognizes recombinant and natural human PAI-1. No significant cross-reactivity or interference was observed. We calculated the mean value of the duplicate or triplicate readings for each standard and sample (from: Assaypro LLC, 30 Triad South Drive St. Charles, MO 63304.catalog No. EP11oo-1. Lot NO. o1491425).

Statistical methodology

Statistical analysis was performed using Statistical Package for Social Sciences (SPSS®) for Windows® version 16.0. Measured data was described as mean and standard deviation (for parametric variables), number, and percentage (for categorical variables). Difference between the two groups was measured using unpaired Student’s t test (for parametric variables). Association between variables was assessed using Pearson’s correlation coefficient (for parametric variables. *p value < 0.05 was considered significant.

Results

The study included 43 obese patients, and their mean age was 9.79 ± 1.90 ranged from 7 to 12 years; 53.4% (no. = 23) are males and 46.6% (no. = 20) are females. Forty-four normal healthy age- and sex-matched control subjects were included in this study, and their mean age was 9.17 ± 1.72 ranged from 7 to 11 years; 52.4% (no. = 22) are males and 47.6% (no. = 21) are females. Anthropometric and clinical data in the obese and control groups are illustrated in (Table 1).

Table 1 Anthropometric, clinical, and laboratory data in the obese and control groups
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The comparison between obese and control groups regarding their lab results showed statistically significant difference between both groups in cholesterol, triglycerides, LDL-c, fasting blood sugar, fasting insulin, and HOMA-IR, while there was no statistically significant difference in HDL-c (Table 1).

Our study showed a highly significant positive correlation between PAI-1 and weight (r = 0.6, p = 0.000), BMI (r = 0.6, p = 0.000) (Fig. 1), and waist/hip ratio (r = 0.7, p = 0.000) in the obese children. Also, there was statistically significant positive correlation between PAI-1 and the BMI SDS (r = 0.4, p = 0.01), biceps skinfold thickness (r = 0.4, p = 0.03), triceps skinfold thickness (r = 0.3, p = 0.04), and subscapular skinfold thickness (r = 0.3, p = 0.04). Regarding systolic and diastolic blood pressure, there was a significant positive correlation between PAI-1 and systolic BP (r = 0.7, p = 0.000) and diastolic BP (r = 0.3, p = 0.04) (Table 2).

Fig. 1
figure 1

Correlation between PAI-1 and BMI in obese group

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Table 2 Correlation between PAI-1 and the anthropometric measures and blood pressure measurements and the laboratory data in obese group
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There is a positive significant correlation between PAI-1 and cholesterol (r = 0.5, p = 0.000), triglycerides (r = 0.4, p = 0.02), LDL-c (r = 0.6, p = 0.000), insulin (r = 0.5, p = 0.000), and HOMA-IR (r = 0.5, p = 0.02) (Table 2).

Twelve obese children (27.9%) fulfilled the criteria for diagnosis of metabolic syndrome. WC is significantly higher in obese children with metabolic syndrome (p = 0.04) (Table 3).

Table 3 Comparison between anthropometric and laboratory data in MetS and non-MetS obese patients
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PAI-1 was significantly higher in obese patients with MetS (p = 0.02). Obese patients with MetS showed significantly higher serum TG (p = 0.000) and fasting blood glucose (p = 0.000) (Table 3).

Discussion

The current study shows that obese children have dysregulation of fibrinolytic system. The evidence is that the mean PAI-1 was significantly higher in obese children than the control subject (47.98 ± 17.42 vs 28.00 ± 11.35) p value < 0.001.

Plasminogen activators are responsible for the conversion of plasminogen to plasmin which accelerates fibrinolysis. These plasminogen activators are strongly and irreversibly inhibited by PAI-1. It was found that PAI-1 expression is markedly increased in visceral adipose tissue in obese individuals, and those with central adiposity have increased levels of PAI-1 [2].

There are several studies which observed positive correlations between PAI-1 and weight, weight standard deviation, height, BMI, BMI standard deviation, waist circumference, hip circumference, and waist to hip ratio in obese children [21,22,23,24,25].

Also, PAI-1 levels are observed to be high in patients with metabolic syndrome (MetS) [26]. Elevated levels of PAI-1 found in obese patients can be decreased by changing lifestyle and following intensive programs for weight loss [27, 28].

In the current study, total cholesterol, triglycerides, LDL-c, fasting blood glucose, fasting insulin, and HOMA-IR were significantly increased in obese children in comparison with controls (p value 0.000, 0.000, 0.03, 0.01, 0.00, and 0.00 respectively). These findings were consistent with the findings of others [22, 29,30,31].

Significant positive correlations between PAI-1 and fasting insulin concentrations may give us an idea about the role of insulin in stimulating PAI-1 synthesis in adipose tissue sites and how it is the cause of relating high levels of PAI-1 to fatness [32].

Also, Akanji et al. [31] found that PAI-1 is associated with insulin resistance found in obese subjects, and Al-Daghri et al. [30] found that PAI-1 levels were correlated with HOMA-IR and fasting serum insulin. Many earlier reports had suggested associations between PAI-1 with insulin sensitivity, WC, and BMI in obese children and adolescents [33, 34]; this is in agreement with the current results as PAI-1 was found to be correlated with BMI, HOMA-IR, and insulin in obese children.

So we can conclude from the data above that the presence of insulin resistance found in obese children is a risk factor for atherothrombosis that increases the possibilities of cardiovascular disease later on. Despite the answer to the question why levels of PAI-1 are increased in obese individuals is not agreed upon yet, it has been found that the fat cell itself can produce PAI-1 that possibly explain the high levels found in obese patients [35]. Fatness does not directly enhance PAI-1 synthesis. But likely, it exaggerates the response of the fat cell to the inducers of PAI-1 [36].

In the present study, we found that obese children with MetS had significantly higher levels of PAI-1 than their counterparts without MetS (p = 0.02). This coincides with the results of Valle et al. [37] and Galli-Tsinopoulou et al. work [38], which showed that PAI-1 levels are directly associated with MetS among children and adolescents. The increased percentage of visceral fat tissue may be the linkage between MetS and elevated plasminogen activator inhibitor-1 (PAI-1). This might be explained by the metabolic derangements found in MetS such as hypertension, dyslipidemia, hyperinsulinemia, and hyperglycemia could all induce PAI-1 synthesis and release from different cell types [39]. However, Mantovani et al. [25] found that triglycerides, insulin, and HOMA-IR have no direct relation to fibrinolytic disorders in childhood and the pathogenesis explaining the elevation of PAI-1 levels in obese patients remains to be elucidated.

Conclusions

We concluded that PAI-1 is a good predictive test for metabolic syndrome in obese children and it is correlated significantly to other metabolic risk factors such as waist circumference, systolic blood pressure, and fasting blood pressure. Using multiple biomarkers for diagnosis and early detection of metabolic syndrome, and hence customized treatment and risk management, is an upcoming field with much room for research.