Liver Function Test Changes in Centrally Obese Youth with Metabolic Syndrome in a Serbian Population

Abstract

Objective:

The aim of this study was to investigate the association between metabolic syndrome and liver enzymes in overweight and obese adolescents and young adults.

Methods:

A total of 126 overweight and obese adolescents and young adults (age, 15–26 years), 55 (43.6%) with metabolic syndrome and 71 (56.4%) without metabolic syndrome, were studied.

Results:

Patients with metabolic syndrome had significantly higher alanine aminotransferase (ALT), γ-glutamyl transpeptidase (GGT), and alkaline phosphatase (ALP) levels compared to patients without metabolic syndrome [36.5±22.2 vs. 29.4±17.8 IU/L (P=0.043), 33.8±17.8 vs. 26.9±18.4 IU/L (P=0.002), and 84.3±32.2 vs. 75.7±29.5 IU/L (P=0.063)]. Aspartate aminotransferase (AST) levels were similar in both groups (24.1±9.8 vs. 23.3±9.0 IU/L, P=0.674). Elevated AST, ALT, GGT, and ALP levels were observed in 6, 15, 18, and 5 patients (11%, 27%, 14%, and 9%) with metabolic syndrome compared to 6, 17, 6, and 4 (8%, 24%, 8% and 5%) patients without metabolic syndrome (P=0.872, P=0.826, P<0.001, and P=0.035). In multivariate regression models adjusted for age and gender, metabolic syndrome was not a significant predictor of ALT (P=0.967), GGT (P=0.526), and ALP levels (P=0.221), but insulin resistance was a significant predictor for ALT and GGT levels (P=0.001, P=0.028).

Conclusion:

Changes in liver function tests were observed in obese patients with metabolic syndrome, compared to patients without metabolic syndrome, especially in ALT and GGT levels. Insulin resistance is an independent pathogenic mechanism in liver function test changes regardless of metabolic syndrome in nondiabetic centrally obese youth.

Introduction

T he prevalence of obesity in both pediatric and adult populations is increasing worldwide.^1,2 Apart from the obesity itself, findings of many studies have demonstrated that abdominal obesity is an independent risk factor for atherogenic and metabolic abnormalities in a young population.³ This issue is becoming more prominent with changes in lifestyle in youth, namely the decreased level of physical activity and increased intake of caloric, unhealthy food.⁴ Although metabolic syndrome is commonly associated with adulthood, during the last decade, findings of numerous studies suggested an increasing prevalence of metabolic syndrome in children and adolescents.¹ The US National Cholesterol Education Program Adult Treatment Panel (NCEP ATP III) criteria for metabolic syndrome are three of the following abnormalities: Waist circumference, blood pressure, triglycerides (TGs), high-density lipoproteins (HDL), and fasting glucose.⁵ An association between obesity (especially central obesity), a base criterion for diagnosis of metabolic syndrome, and liver steatosis in a young population was confirmed, especially due to changes in the quantity and composition of food.⁶ Hyperinsulinemia promotes hepatic de novo lipogenesis, which is increased in nonalcoholic fatty liver disease (NAFLD) patients compared with normal individuals. Also, a mild elevation of liver function enzymes is associated with features of metabolic syndrome.^7,8

The gold standard in the diagnosis of NAFLD is liver biopsy, but this method is invasive and unjustified, particularly in the initial stage of disease. Thus, findings of elevated alanine aminotransferase (ALT) and/or abnormal ultrasound imaging consistent with excess fat in the liver, including hepatomegaly and imaging consistent with excess fat in liver, are more frequently used in diagnosing NAFLD, especially in youth.⁹

It is important to state that the NAFLD develops as a continuum, and subtle changes in liver enzymes can be detected before the pathological findings are visible on ultrasound. Many studies suggested that metabolic syndrome is associated with elevated transaminases in adult population, but only a few studies have been conducted in the population of adolescents and young adults, where the disease is in its early stages and more likely to be missed on imaging. The aim of this study was to assess differences between obese adolescents and young adults with and without metabolic syndrome and its relationship with disturbance of liver enzymes.

Methods and Procedures

A cross-sectional study was conducted in the Clinic for Endocrinology, Diabetes and Metabolic Disorders, Clinical Center of Serbia, Belgrade, during the period from 2005 to 2011. The study included 126 overweight and obese patients. Inclusion criteria were the ages of 15–26, diet-induced obesity (based on interview for family history, degree of physical activity, type and quantity of food intake, and no presence of secondary obesity syndromes in medical records), and waist circumference over 80 cm for females and over 94 cm for males. Exclusion criteria were diabetes mellitus, alcohol intake (males >20 grams/day, females >10 grams/day), rapid weight loss, parenteral nutrition, rare metabolic disorders (M. Wilson, hemochromatosis), drug-induced steatosis, viral hepatitis, autoimmune hepatic diseases, polycystic ovarian syndrome (PCOS), hypopituitarism, hypothyroidism, corticosteroid therapy, and biliary obstruction.

All patients underwent physical examination, which included waist circumference (WC), measured in standing position with a nonelastic tape at the middle point between the upper point of the bilateral iliac crest and the inferior margin of the rib cage in the horizontal plane at the end of expiration. Body mass index (BMI) was calculated by dividing weight (kg) by the square of height (m²). Blood pressure was measured in sitting position at the end of the interview. Laboratory analyses were done in the morning after at least 12 h of fasting. Lipids, cholesterol, HDL, and TGs were measured by spectrophotometric method and low-density lipoprotein (LDL) was calculated indirectly by the formula LDL=Cholesterol−(TG/2.2+HDL). C-reactive protein (CRP) was measured by immunonephelometric method (Marburg, Germany) with detection from 0.175 mg/L and with no upper limit [coefficient of variation (CV) 3.1%–4.4% for intraassay and 2.5%–5.7% for interassay]. Fibrinogen was measured by the BCS coagulation analyzer with Multifibren U, a modification of the Clauss method (Marburg, Germany, measurement range is 0.8–12 g/L, CV within run 2.9% for control plasma N and 7.2% for control plasma P). Insulin-like growth factor-1 (IGF-1) was measured by the chemiluminescent microparticle assay (CMIA) method (Siemens Health Care Diagnostics, USA) with a precision of 2.3%–3.9% within run and linearity <37–916 ng/mL. Liver function tests included bilirubin, aspartate aminotransferase (AST), ALT, alkaline phosphatase (ALP), γ-glutamyl transpeptidase (GGT), albumin, total protein, and aminotransferase-to-platelet ratio index (APRI). The institutional normal upper limits (cutoff points are not specific for our population) of AST, ALT, ALP, and GGT were 37, 41, 120, and 55 IU/L, respectively. Other analyses included blood cell count (leukocytes and platelets) and uric acid.

To determine glucoregulation disorder and the degree of insulin sensitivity and secretion, a 2-h oral glucose tolerance test (OGTT) with a maximum of 75 grams of glucose was performed, and glucose and insulin levels were assessed at baseline, 30 and 120 min after glucose admission. Glycated hemoglobin (HbA1c) was measured as a parameter of long-term glucoregulation (3 months average amount of glucose). Insulin was measured by the chemiluminescent immune assay (CLIA) method (Siemens Health Care Diagnostic, USA) with a precision of 3.7%–5.5% within run and depending on dilution, linearity is from 19.9 to 269 mIU/L. Analytical sensitivity is 2 mIU/L and 8% is cross reactive with proinsulin. Insulin resistance was determined with the homeostatic model assessment of insulin resistance (HOMA-IR) index, calculated as a product of the fasting plasma insulin level (mIU/L) and the fasting plasma glucose level (mmol/L) divided by 22.5.¹⁰ Patients with HOMA-IR values >3.2 were considered as patients with insulin resistance.

Patients were divided in two groups, obese patients with metabolic syndrome and obese patients without metabolic syndrome. Patients with metabolic syndrome had three of five following abnormalities: Waist circumference over 102 cm for males and 88 cm for females (for adolescents waist over 90^th percentile, age and gender specific), elevated blood pressure [systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg for adults and for adolescents SBP or SBP over 90^th percentile specific for age and gender], TGs (≥1.7 mmol/L for adults and ≥1.25 for adolescents), HDL-C (in males <1.03 mmol/L and females <1.29 mmol/L for adults, and <1.03 mmol/L for both genders in adolescents), and fasting glucose (>6.1 mmol/L for adults and adolescents) were considered as obese patients with metabolic syndrome.^5,11 Patients with less than three of five of these components of metabolic syndrome were considered as patients without metabolic syndrome.

All statistical analyses were performed in SPSS 12.0 (SPSS Inc., Chicago, IL). Results were presented as frequency, percent, mean±standard deviation (SD) and median (where appropriate). The chi-squared, Mann–Whitney U-test, general linear model, and t-test were used to compare the two groups. A linear regression model was performed to assess associations of liver enzymes and other variables. Variables with nonnormal data had to be transformed. Best results were obtained by logarithmic transformation. Transformed variables are ALT, GGT, fasting insulin, HOMA-IR, and CRP. All P values less than 0.05 were considered significant.

Results

Of 126 patients in our study, metabolic syndrome was present in 55 (43.6%). The mean age of all participants was 23.1±4.1 years; 47 participants (37.3%) were males and 79 (62.7%) were females.

We analyzed anthropometric parameters, lipid status, glucose regulation and insulin resistance, inflammation, and prothrombotic factors in both groups (Table 1). Patients with metabolic syndrome had significantly higher mean values of anthropometric parameters, inflammation (leukocytes, CRP), and lipid parameters (except cholesterol and LDL). Uric acid, HbA1c, HOMA-IR, glucose, and insulin mean levels were significantly higher in the metabolic syndrome group, but there was no influence of metabolic syndrome on glucose and insulin mean change (general linear model repeated measures for glucose P=0.476 and insulin P=0.302) during OGTT. Frequency of IGF and IGT was higher in the metabolic syndrome group, but no statistical difference was obtained. Insulin resistance (HOMA-IR >3.2) was present in 51 patients (92.7%) with metabolic syndrome and in 52 patients (73.2%) without metabolic syndrome (P=0.010).

Table 1.

Anthropometric Parameters, Lipid Status, Glucose Regulation, Prothrombotic, and Inflammation Factors

		Obesity with metabolic syndrome (n=55)	Obesity without metabolic syndrome (n=71)	p value
Gender male		21 (32.2)	26 (36.6)	0.857^a
Age (years)		23.4±4.2	23.3±4.2	0833^b
BMI (kg/m²)		37.3±7.1	31.5±5.5	<0.001^b
Waist circumference (cm)		115.0±17.4	100.3±14.1	<0.001^b
Waist/hip		0.92±0.09	0.86±0.08	<0.001^b
SBP (mmHg)		133.1±16.3	120.0±12.4	<0.001^b
DBP (mmHg)		86.7±11.2	79.4±9.9	<0.001^b
Cholesterol (mmol/L)		5.20±1.06	5.10±1.05	0.617^b
HDL-C (mmol/L)		0.96±0.16	1.23±0.24	<0.001^b
LDL-C (mmol/L)		3.19±0.87	3.26±0.87	0.701^b
Triglycerides (mmol/L)		2.54±2.27 (2.08)	1.31±.0.76 (1.21)	<0.001^c
Glucose minutes (mmol/L)	0	5.10±0.74	4.74±0.67	0.006^b
	30	7.82±1.61	7.41±1.38	0.136^b
	120	5.18±1.57	4.66±1.24	0.042^b
Insulin minutes (mIU/L)	0	61.83±80.69 (32.1)	23.91±15.69 (19.8)	<0.001^c
	30	160.14±110.44 (122.6)	112.71±88.13 (76.6)	0.022^c
	120	98.61±102.88 (41.2)	35.02±35.73 (20.4)	<0.001^c
IFG		11 (20.0)	8 (11.3)	0.174^a
IGT		5 (9.1)	2 (2.8)	0.257^a
HbA1c (%)		5.34±0.47	5.11±0.51	0.019^b
HOMA-IR		14.52±19.28 (6.85)	5.05±3.12 (4.24)	<0.001^c
Uric acid (μmol/L)		376.1±89.1	309.3±87.5	<0.001^b
Leukocytes (10⁹/L)		8.7±2.9	7.5±2.1	0.017^b
CRP (mg/L)		8.5±8.0 (6.4)	5.3±4.7 (4.1)	0.003^c
Fibrinogen (g/L)		4.21±0.89	4.08±0.94	0.430^b
Platelets (10⁹/L)		298.9±63.3 (297.0)	287.4±53.1 (276.0)	0.219^b

Results are shown as n (%) or mean±standard deviation (SD) (median).

Chi-squared test.

t-test.

Mann–Whitney U-test.

BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; CRP, C-reactive protein.

Table 2 shows liver function parameters. ALT, GGT, and ALP mean values and medians were higher in the metabolic syndrome group, but a significant difference was obtained in ALT and GGT levels. The difference between groups in ALP was near the conventional level of significance (0.05), so it can be considered nearly significant. A significant difference was obtained in frequency of patients with elevated GGT and ALP levels in the metabolic syndrome group compared to patients without metabolic syndrome. Although patients with elevated AST and ALT were frequent in the metabolic syndrome group, no statistical significance was found. In addition, IGF-1 and APRI were similar in both groups.

Table 2.

Liver Function Tests

	Obesity with metabolic syndrome (n=55)	Obesity without metabolic syndrome (n=71)	P value
Bilirubin (μmol/L)	11.73±5.27	11.31±5.14	0.667^b
AST (IU/L)	24.1±9.8 (21.0)	23.3±9.0 (21.0)	0.674^b
ALT (IU/L)	36.5±22.2 (28.0)	29.4±17.8 (24.0)	0.043^c
GGT (IU/L)	33.8±17.8(30.0)	26.9±18.4(20.0)	0.002^c
ALP (IU/L)	84.3±32.2 (77.0)	75.7±29.5 (69.0)	0.063^c
Total protein (g/L)	75.8±4.4	75.8±4.6	0.991^b
Albumin (g/L)	45.3±3.4	45.6±2.7	0.492^b
IGF-1 (ng/mL)	242.4±112.9 (228.5)	280.9±122.1(250.0)	0.199^c
APRI	0.228±0.101 (0.195)	0.227±0.095(0.203)	0.715^c
Elevated AST	6 (10.9)	6 (8.4)	0.872^a
Elevated ALT	15 (27.2)	17 (23.9)	0.826^a
Elevated GGT	18 (14.3)	6 (8.4)	0.001^a
Elevated ALT and GGT	6 (10.9)	4 (5.6)	0.450^a
Elevated ALP	5 (9.1)	4 (5.6)	0.035^a

Results are shown as mean±standard deviation (SD) (median) or n (%)

Chi-squared test.

t-test.

Mann–Whitney U-test.

AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, γ-glutamyl transpeptidase; ALP, alkaline phosphatase; IGF-1, insulin-like growth factor-1; APRI, aminotransferase-to-platelet ratio index.

Because ALT, GGT, and ALP mean values were significantly different in patients with metabolic syndrome and those without metabolic syndrome, we designed linear regression models to determine the influence of metabolic syndrome on enzyme variability and which predictor is associated with ALT, GGT, and ALP variability. The regression models are shown in Table 3.

Table 3.

Regression Models with ALT, GGT, and ALP as Dependent

	ALT			GGT			ALP
Regression models	R²	Stand. β	P ^*	R²	Stand. β	P ^*	R²	Stand. β	P ^*
Model 1. Age and gender
Age	0.220	0.217	0.001	0.211	0.303	0.001	0.114	−0.271	0.002
Gender		−0.428	<0.001		−0.360	<0.001		−0.186	0.034
Model 2. Metabolic syndrome adjusted for age and gender
Metabolic syndrome	0.243	0.149	0.065	0.270	0.244	0.005	0.145	0.177	0.041
Model 3. BMI adjusted for
Age and gender	0.265	0.213	0.008	0.303	0.308	<0.001	0.157	0.212	0.016
Age, gender, metabolic syndrome	0.270	0.185	0.039	0.321	0.250	0.007	0.167	0.166	0.083
Models 4. Metabolic syndrome adjusted for age, gender, and one of the following
BMI	0.270	0.074		0.321	0.148	0.100	0.167	0.110
Fibrinogen	0.268	0.152	0.063	0.311	0.269	0.002	0.189	0.161	0.063
Cholesterol	0.266	0.143	0.074	0.320	0.240	0.004	0.145	0.176	0.043
LDL-C	0.258	0.122		0.312	0.237	0.005	0.134	0.153	0.085
Leukocytes	0.249	0.107		0.291	0.211	0.016	0.134	0.158	0.080
Platelets	0.260	0.136		0.262	0.237	0.007	0.155	0.147	0.093
Uric acid	0.261	0.093		0.296	0.189	0.035	0.156	0.135
HbA1c	0.275	0.093		0.306	0.201	0.029	0.138	0.173	0.072
Fasting insulin	0.323	0.019		0.324	0.159	0.097	0.143	0.142
HOMA-IR	0.336	0.004		0.335	0.148		0.142	0.146
CRP	0.250	0.062		0.325	0.155	0.079	0.247	0.110
Model 5. Final model
Age	0.344	0.192	0.025	0.440	0.192	0.039	0.251	−0.354	0.001
Gender		−0.392	<0.001		−0.353	<0.001		−0.200	0.021
BMI		0.101	0.302		0.083	0.456		0.074	0.473
Metabolic syndrome		−0.029	0.764		0.021	0.833		0.089	0.346
HOMA-IR		0.285	0.004		0.282	0.007
CRP					0.250	0.015		0.294	0.003

Only P values less than 0.1 are shown.

ALT, alanine aminotransferase; GGT, γ-glutamyl transpeptidase; ALP, alkaline phosphatase; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; CRP, C-reactive protein.

Model 1 is a multivariate model with age and gender as independent variables. Model 2 represents a linear regression with metabolic syndrome as an independent predictor, but adjusted for age and gender. Model 3 is a model with BMI as the dependent variable and age and gender or age, gender, and metabolic syndrome as independent variables. In model 4, metabolic syndrome is adjusted for age, gender, and one of all other variables except metabolic syndrome components. In the final model, age, gender, metabolic syndrome, and BMI are forced entry variables, and significant variables in Table 1 (except metabolic syndrome components) are entered in next block by the forward method.

In model 1, ALT and GGT have similar R ² values and both predictors (age and gender) are significant. R ² values in the ALP model as dependent is lower than in ALT and GGT models. In model 2, metabolic syndrome was a significant predictor of GGT and ALP variability. In the ALT model as dependent, it was near the conventional level of significance so we can consider it nearly significant. In model 3, BMI is a significant predictor for all three enzymes when adjusted for age and gender and all but ALP when adjusted for age, gender, and metabolic syndrome. In model 4, metabolic syndrome was a still significant predictor for GGT and ALP variability in nearly all models, but no significance was found in ALT as dependent models. In the final model (Model 5), R ² is the highest in GGT as dependent model, than in ALT and the lowest in the ALP model. In all models but ALP, HOMA-IR is a significant predictor.

Discussion

In our study, all metabolic syndrome parameters, BMI, lipids, glucose, and insulin were significantly higher in the metabolic syndrome group, as expected. Other studies on children, adolescents, and adult populations showed similar results.^12
–14 Numerous studies indicate that insulin resistance is a central feature of metabolic syndrome; even the link between insulin resistance and most of the components of metabolic syndrome is not completely revealed. Insulin resistance is strongly associated with atherogenic dyslipidemia and proinflammatory parameters but less associated with hypertension and prothrombotic parameters.¹⁵ In our study, HOMA-IR and CRP were significantly higher in the metabolic syndrome group. A study on healthy subjects reports a strong relationship between inflammatory markers and metabolic syndrome.¹⁶ Florez et al. found that abdominal obesity (waist circumference) was the most important component of the metabolic syndrome associated with increased CRP levels, followed by female gender and HOMA-IR.¹⁷ In our study, both groups have abdominal obesity, but waist circumference is significantly higher in the metabolic syndrome group so it could be a cause of higher CRP.

Metabolic syndrome is an important additional cause of elevated liver enzymes in obese (particularly central) adolescents and young adults.^18
–20 In our study, ALT, GGT, and ALP were significantly higher in the metabolic syndrome group. Distribution of patients with elevated liver enzymes was frequent in the metabolic syndrome group, but there was a significant difference only in distribution of patients with elevated GGT and ALP. Cutoff values in our study were much higher than in most studies on adolescents and adults. That could be a possible explanation of a lower percentage of patients with elevated enzymes in our study compared to other studies.^21,22

Other studies on adults report a significant difference of ALT, AST, and GGT between patients with or without metabolic syndrome.²³ Average levels of ALT and AST in our study in patients with metabolic syndrome were similar to the Di Bonito et al. study.²⁴ In their study, nonobese subjects were examined together with those that were obese, and results revealed a higher difference between patients with and without metabolic syndrome. Because only patients with central obesity were included in our study, mean differences were expected to be lower, and our results revealed a higher prevalence of discrete, subclinical changes in liver function tests in patients with metabolic syndrome.

AST is not a specific marker of hepatocellular injury because it occurs in liver, heart, skeletal muscle, kidney, brain, pancreas, and blood cells.²⁵ Although multiple sources for ALT are recognized, the highest concentrations of ALT are found in the liver.²⁶ Many studies have shown that elevations in ALT, including values in reference range, are associated with metabolic syndrome.^13,27 IGF-1 levels and APRI were similar in both groups and ALT and GGT levels differed, thus we may conclude that the liver synthetic function was not compromised and patients had no liver fibrosis; however, enzymes elevation is expressed more in the metabolic syndrome group compared to patients without metabolic syndrome.^28,29

Multiple regression models indicate that metabolic syndrome is a significant predictor of ALT variation when adjusting for age and gender. But in model 4, metabolic syndrome is not significant in any of its models when adjusted for age, gender, and all other variables that are related to metabolic syndrome but are not its components. However, in final model, HOMA-IR is significantly correlated with ALT, whereas metabolic syndrome is not. This confirms that insulin resistance, excessive TG accumulation in hepatocytes, oxidative stress, and inflammatory cytokines are key players in the development and progression of liver damage in obese patients.^30,31 In fact, common underlying abnormalities present in these conditions, such as insulin resistance and oxidative stress, may be a potential basis of NAFLD co-morbidity with metabolic syndrome.¹³

As with AST, GGT is also a nonspecific marker found in different tissues.³² In our study, metabolic syndrome significantly correlated with GGT in age- and gender-adjusted models. Compared to the ALT model, the correlation of metabolic syndrome and GGT was significant or nearly significant when adjusted for age, gender, and all other variables that are related to metabolic syndrome but are not its components, except for HOMA-IR and CRP.

In the final model, HOMA-IR and CRP (adjusted for age and gender) were correlated with GGT but metabolic syndrome was not. Wessel et al. showed in their study that CRP highly correlates with GGT and is associated with multiple features of the metabolic syndrome.³³ Also, GGT and HOMA-IR correlation in nondiabetic patients is confirmed in other studies.³⁴ Elevated GGT levels are significantly associated with reduced insulin sensitivity and increased hepatic lipid contents.³⁵

Loomba et al. confirmed that plasma GGT is a marker of fatty liver disease and metabolic syndrome traits such as insulin resistance, increased TGs, uric acid, and blood pressure.³⁶ Hseih et al. showed that elevation of AST, ALT, and GGT is strongly related with metabolic syndrome and that GGT might be the most representative liver enzyme that is related to metabolic syndrome.²³

In obese individuals, increased supply of free fatty acids to the liver from diet, adipose tissue, and increased de novo lipogenesis all serve to promote hepatic steatosis. In liver, insulin inhibits glucose production and promotes fatty acid synthesis. With the development of hepatic insulin resistance, the inhibitory effect of insulin on glucose production is diminished, whereas the stimulatory effect of insulin on lipogenesis is retained. Insulin resistance is strongly correlated with steatosis, and interventions that ameliorate insulin resistance lead to lower insulin levels and decreased liver fat content.⁷ When analyzing these models and comparing literature facts with our results, we can conclude that metabolic syndrome and particularly insulin resistance are highly associated with ALT and GGT levels.

All our patients are adolescents or young adults, so it is questionable whether elevation of ALP is due to bone growth, obesity or metabolic syndrome.²⁶ In the final model, metabolic syndrome and HOMA-IR do not correlate with ALP, but CRP does. A possible explanation is that proinflammatory cytokines from adipose tissue (central obesity) enter directly into the portal circulation and cause inflammation of liver tissue that then causes increased synthesis of ALP and GGT.

In conclusion, we documented a significant association between liver function tests and metabolic syndrome. Changes in liver function tests are observed in centrally obese patients with metabolic syndrome, compared to centrally obese patients without metabolic syndrome, especially in ALT and GGT levels. Insulin resistance is an independent pathogenic mechanism in liver function test changes regardless of metabolic syndrome in nondiabetic centrally obese youth. It plays a key role in pathogenesis of metabolic syndrome and liver function test changes and is probably the most important mediator between these two disorders.

Footnotes

Acknowledgment

No funding was received for this study.

Author Disclosure Statement

The authors declare no conflicts of interest.

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