Abstract
Background
Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD), and cardiovascular abnormalities are closely related in adulthood, but few studies were performed in childhood to prove this relationship, and its pathophysiologic mechanisms have not fully studied yet.
Objectives
This study aims to assess vascular endothelial dysfunction in children with obesity- related MAFLD and to investigate its relationship to the plasminogen activator inhibitor-1 (PAI-1) levels.
Methods
In this case-control study, we assessed both brachial flow-mediated dilation (FMD) and carotid intima-media thickness (CA-IMT), in addition to liver profile, lipid profile, glucose, insulin, insulin resistance, fasting C-peptide, high-sensitivity C-reactive protein (hs-CRP), and PAI-1 in 200 children with obesity, 80 with and 120 without MAFLD, respectively.
Results
Compared with non-MAFLD, children with MAFLD had lower brachial FMD% (3.94 ± 1.42 versus 8.16 ± 2.32 p = 0.001), similar CA-IMT (0.45 ± 0.06 versus 0.45 ± 0.07, p = 0.09) and higher PAI-1 (55.16 ± 14.42 versus 43.32 ± 10.34 p = 0.000). Moreover, FMD% was significantly correlated with PAI-1 ( r = −0.57, p = 0.001), hs-CRP ( r = −0.474, p = 0.001), Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) ( r = −0.306, p = 0.01) and CA-IMT ( r = −0.223, p <0.05). Using linear regression analysis, PAI-1 was the most significant independent predictor of FMD (p=0.001) in children with obesity-related MAFLD.
Conclusions
Children with obesity who have MAFLD showed impairment of FMD %, which was independently associated with elevated PAI-1 levels. Thus, the diagnosis of MAFLD in a child should raise urgent attention to its cardiovascular sequelae. In the management of MAFLD, the prevention of cardiovascular disease is crucial, along with the prevention of end-stage liver disease.
1
Introduction
With the rise of the obesity epidemic globally in both children and adults, metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD) has emerged as a common cause of chronic liver disease in the pediatric population [ ]. While cardiovascular changes have been more reported in adults with MAFLD, less is known about the strength of this association and the pathophysiologic mechanisms involved among children with MAFLD. [ ]. Accumulating evidence suggests that endothelial dysfunction is an early marker for atherosclerosis and can be detected before structural changes to the vessel wall are apparent on angiography or ultrasound [ ]. Measurement of flow-mediated dilatation (FMD) is considered a well-established noninvasive technique for assessing endothelial function. Briefly, endothelial-dependent vasodilatation in the brachial artery was measured through raised shear stress associated with increased blood flow. Moreover, measurement of peripheral circulation FMD has been proved to reflect that of the coronary arteries [ ]. Plasminogen Activator Inhibitor-1 (PAI-1) is a single-chain glycoprotein serine protease inhibitor secreted by megakaryocytes, smooth muscle cells, vascular endothelium, adipocytes, hepatocytes, and other cell types [ ]. It is the principal regulator of fibrinolysis and plays an important role in endogenous fibrinolytic activity [ ]. It has been shown that elevated PAI-1 activity was related to atherosclerosis and was an independent predictor of ischemic heart disease and myocardial infarction [ ]. However, the association of PAI-1 with vascular dysfunction in children with obesity-related MAFLD has not yet been validated. So, we designed this study to assess vascular endothelial dysfunction in children with obesity-related MAFLD and to study its association with PAI-1 levels.
2
Patients and methods
This case-control study included 200 children with simple obesity recruited from the Pediatric Outpatients Clinic, Children’s University Hospital, Assiut University, Assiut, Egypt. Child with obesity was defined as his body mass index (BMI) > 95th percentile [ ]. Simple obesity is characterized by a normal or increased linear growth rate with an acceleration of bone age maturation. Children with secondary causes of obesity (genetic, endocrine disorders, e.g., hypothyroidism, Cushing’s disease) and iatrogenic obesity, as well as children with active hepatotropic viral infections, autoimmune liver diseases, inherited inborn error of metabolism and genetic syndromes, were excluded from the study. Secondary causes of steatosis (familial or primary hypercholesterolemia or receiving drugs known to cause fatty liver) were excluded. There were 80 patients with obesity and MAFLD and 120 obese children, age and sex-matched without MAFLD according to hepatic ultrasound results. The Institutional Review Board approved this study, which was performed in accordance with “The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments in Human”. The legal guardians of cases and controls signed a written informed consent before enrollment in the study.
3
Methods
Full medical history and physical examinations were performed on all participants. Anthropometrics were assessed, including weight (Wt), height (Ht), and calculation of body mass index (BMI). To measure weight accurately, we used a digital scale with the removal of heavy clothes and shoes, and it was recorded in kilograms and to the nearest decimal fraction (0.1 kg). Height was measured using a stadiometer without shoes and recorded to the nearest 0.1 cm. Body mass index (BMI) was calculated as follows: a child’s weight in kilograms divided by the square of height in meters (weight (kg)/height (m) 2 ) according to Cole [ ]. We applied the Egyptian Growth Reference Data to standardize BMI to age- and sex-specific percentiles [ ]. Waist circumference (WC) was measured midway between the lowest rib margin and the superior border of the iliac crest at the end of expiration with a flexible inextensible tape to the nearest 0.1 cm, and WC standard deviation scores [SDS] was calculated and compared to normal references for age and sex according to Schwandt et al. [ ]. Hip circumference (HC) was measured in a horizontal plane at the level of the greater trochanter at the widest part of the hip and HC SDS was calculated and compared to normal references for age and sex till the age of 11 years according to Schwandt et al. [ ] and above 11 years according to Moreno et al. [ ]. Waist/hip ratio (WHR) was calculated as the ratio of waist to hip circumference and compared to normal age and sex reference range together with calculation of WHR SDS for those 11 years or less according to Schwandt et al. [ ] and those above11 years according to Mederico et al. [ ]. We measured Blood pressure (BP) on three different occasions and compared the mean values to age-specific percentiles for BP [ ]. The pubertal development was assessed according to Tanner staging [ ].
3.1
Laboratory investigations
After an overnight fast, blood samples were collected from each patient. Fasting glucose was measured by YSI 2300 STAT Plus TM Glucose & Lactate Analyzer (Ohio, USA). Fasting insulin was measured using an insulin ELISA Kit (LDN, Nordhorn, Germany). Insulin resistance (IR) was estimated using the homeostasis model assessment (HOMA-IR) equation formula as follows: fasting plasma glucose (mmol/l) times fasting serum insulin (mU/l) divided by 22.5. A cut-off level for diagnosing insulin resistance was ≥2.6 [ ]. Fasting C-peptide was measured by human C-peptide enzyme-linked immunosorbent assay (ELISA) kit (DRG Instruments GmbH, Germany). Lipid profile, including total cholesterol, triglycerides (TG), high-density lipoprotein (HDL), and a low-density lipoprotein cholesterol (LDL-c) concentrations, were assessed by standard enzymatic methods and reagents (Boehringer Mannheim GmbH, Penzberg, Germany) with a fully automated analyzer. The liver function tests were assessed by auto-analyzer (Abbott AXSYM system-UK), including alanine aminotransferase (ALT), aspartate aminotransferase (AST), and Gamma-glutamyl transferase (GGT). The level of high- Sensitivity C-Reactive Protein (hs-CRP) was measured using the hs-CRP Enzyme Immunoassay Test (ELISA) kit for quantitative determination of the C-reactive protein concentration in human serum (Immunospec Corp., Canoga Park, CA, USA). Plasminogen activator inhibitor-1 estimation was done by enzyme-linked immunoassay (ELISA) [Assaypro LLC, 30 Triad South Drive St. Charles, MO 63304, USA].
3.2
Liver ultrasonography
Two radiologists who were uninformed about the laboratory findings and the aims of the study used ultrasound to diagnose fatty infiltrations of the liver. All ultrasonic instruments were high-end models from General Electric Company, Philips. Scanning was in the supine and left lateral decubitus position, utilizing subcostal and intercostal approaches. Diffuse fatty liver was diagnosed in patients who met two of the following three criteria in acoustic performances (16): (a) the liver’s near-field echo is diffusely enhanced, and its echo is stronger than the kidney’s; (b) the structure of the intrahepatic duct is unclear; (c) the liver’s far-field echo is gradually attenuated. The gold standard test for the detection of MAFLD is a liver biopsy. Performing a liver biopsy in younger children is invasive and has potentially life-threatening complications and was therefore not done in this study [ ].
3.3
FMD measurement
An ultrasound examination was performed in the morning after fasting for >4 h in the horizontal position. The site of ultrasound scanning was the brachial artery 5–10 cm above the cubital fossa with the child’s right arm fully extended and immobilized. Vessel images were recorded first, followed by inflation of a cuff to exceed systolic pressure (40–50 mmHg above systolic pressure) for 5 min. After occlusion, the subsequent rapid deflation led to reactive or flow-mediated hyperemia. Vasodilatation was then calculated as the percent change in diameter relative to the mean baseline value. The FMD was expressed as the percentage increase in artery diameter during hyperemia. FMD% = 100 x ([diameter after hyperemia – baseline diameter]/baseline diameter). [ ].
3.4
Measurement of carotid IMT
Carotid scanning was carried out using a color duplex flow imaging system operating in multiple modes: real-time B, color Doppler, and spectral Doppler modes (Acuson 128 XP; Acuson Corporation, Mountain View, CA, USA). The time of measurement was in the morning after overnight fasting between 7:00 and 9:00 a.m. The position of the examined child was supine, with neck slightly extended and the heads turned 450 away from the side of the examination. Starting on the right side of the neck, the probe was put longitudinally in the anterolateral position. Then, the procedure was repeated on the left side. One cm below the carotid bifurcation, the right CA-IMT was measured. The thickness of the intima-media was estimated as the distance between the echogenicity of the lumen-intima interface and the adventitia-media interface [ ]. The calculation of CA-IMT was performed as a mean of three independent measurements at 3-mm intervals from each side of the neck [ ]. A single cardiologist measured and analyzed CA-IMT and FMD in all cases and controls using the same equipment. He was unaware of the clinical and laboratory findings of the study subjects.
3.5
Statistical analysis
All statistical analyses were carried out using SPSS 21.0 software version for Windows (IBM Corporation, Armonk, NY, USA). Continuous variables were presented as mean ± SD when normally distributed, and categorical variables were presented as frequency and percentages (%). Normality in the distribution of data was assessed using the Kolmogorov-Smirnov test. The t- test was used for comparison of normal variables, while Mann-Whitney U test was used for non-parametric variables. Chi-square test with Fisher’s exact method was used for comparing Categorical variables. Pearson test was used for correlation assessment. To determine the factors significantly associated with FMD%, linear regression analysis using the stepwise method was used. P < 0.05 was considered statistically significant.
4
Results
Demographic, anthropometric, and clinical data on the studied groups [ Table 1 ] shows that children with obesity-related MAFLD had significantly higher BMI SD, WC SDS, TC, TG, LDL-C, fasting insulin, fasting C peptide, HOMA-IR, and ALT compared to those with non- MAFLD. The difference was statistically significant ( p < 0.05). Moreover, PAI-1, hs-CRP, and FMD% were significantly different, p = 0.001 for each, while CA-IMT was not statistically different [ Table 2 ]. Moreover, FMD% correlated significantly with PAI-1 ( r = −0.57, p = 0.001), hs-CRP ( r = − 0.474, p = 0.001), HOMA-IR ( r = −0.306, p = 0.01) and CA-IMT ( r = −0.223, p < 0.05), [ Table 3 ]. By linear regression analysis, the significant independent predictors of FMD% were PAI-1 (standardized β coefficient – 0.516, p = 0.001), hs-CRP (standardized β coefficient − 0.329, p = 0.01), MAFLD (standardized β coefficient – 0.471, p = 0.01), and HOMA-IR (standardized β coefficient – 0.236, p = 0.05) [ Table 4 ].
| Variable | MAFLD ( n = 80) | Non-MAFLD ) n = 120) | P value |
|---|---|---|---|
| Age (year) | 11.35 ± 2.54 | 11.43 ± 2.23 | 0.081 |
| Male/female | 56/24 | 78/42 | 0.072 |
| Obesity duration (year) | 5.8 ± 4.5 | 5.7 ± 4.6 | 0.059 |
| BMI SDS | 3.3 ± 1.1 | 2.9 ± 0.06 | 0.01 |
| WC SDS | 4.12 ± 1.9 | 3.4. ± 1.8 | 0.01 |
| Hip SDS | 3.21 ± 1.7 | 3.01 ± 1.2 | 0.08 |
| Waist/hip SDS | 2.3 ± 1.5 | 2.2 ± 1.4 | 0.17 |
| SBP (mmHg) | 118.0 ± 7.0 | 105.0 ± 5.0 | 0.001 |
| DBP (mmHg) | 76.0 ± 8.0 | 64.0 ± 6.0 | 0.001 |
| ALT (U/L) | 39.5 ± 5.1 | 18.8 ± 6.8 | 0.001 |
| AST (U/L) | 28.1 ± 5.7 | 22.5 ± 3.7 | 0.001 |
| GGT (U/L) | 20.6 ± 4.3 | 13.2 ± 3. 5 | 0.05 |
| TC, mg/dL | 176.2 ± 45.5 | 166.3 ± 22.1 | 0.01 |
| TG, mg/dL | 153.5 ± 43.1 | 121.1 ± 13.5 | 0.01 |
| LDL-c, mg/dL | 115.5 ± 34.2 | 99.6 ± 11.2 | 0,01 |
| HDL-c, mg/dL | 44.1 ± 6.8 | 50.2 ± 5.8 | 0.02 |
| Fasting blood glucose, mg/dL | 87.3 ± 8.7 | 84.6 ± 9.7 | 0.862 |
| Fasting insulin (mU/l) | 15.6 ± 3.23 | 11.6 ± 2.21 | 0.001 |
| HOMA-IR | 3.45 ± 1.3 | 2.53 ± 1.4 | 0.001 |
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