JPED Journal

Introduction

Over the last decade, the rising prevalence and adverse outcomes of hepatic steatosis, to be referred as non-alcoholic fatty liver (NAFL), have been at the epicenter of global public health both in adult and pediatric populations. NAFL is of multifactorial etiology and is associated with obesity, insulin resistance, diabetes type 2, dyslipidaemia and hypertension [1,2]. Surrogate laboratory indices including elevated transaminases, abnormal lipid profile and markers of insulin resistance. Liver steatosis is found on ultrasonographic or magnetic resonance imaging. Progression to NAFL disease (NAFLD) may occur in a number of patients with NAFL [3-5], where hepatic steatosis is complicated by lobular inflammation, hepatocellular injury, and less frequently to non- alcoholic steatohepatitis (NASH) with ballooning hepatocyte injury and fibrosis, potentially leading to end stage liver disease. Disease pathogenesis, risk and protective factors of event sequence are not completely understood [6].

According to published guidelines by the expert committees of the North American Society of Paediatric Gastroenterology, Hepatology and Nutrition and The American Association for the Study of Liver Diseases, the diagnosis of NAFL and NAFLD largely depends on clinical history, biochemical, imaging and less on histological criteria; these are reserved for more complex cases of NAFLD staging and diagnosis of NASH or cirrhosis, where liver biopsy is warranted [7].  Most patients with suspected NAFL/ NAFLD are referred due to incidental radiological finding of hepatic steatosis [8].

Rising prevalence rates of NAFL/NAFLD parallels the sharp rise in childhood obesity over the past decades [9]. Available epidemiologic data from Europe demonstrate that NAFL in childhood and adolescence is a problem of global scale [10]. The central role of obesity as risk factor for pediatric NAFLD is underscored by cohort studies in children and adolescents, where reported prevalence rates range from 10% to 77% [11-16].  The mechanisms of progression of NAFL to NAFLD are incompletely understood. 

Paediatric studies focusing on values of surrogate markers of liver function, such as serum alanine aminotransferase (ALT), are scarce in children with obesity and severe obesity; current evidence is largely extrapolated from adult studies [11].  NAFL prevalence is reported to be up to 30% in obese children and adolescents [17], therefore liver enzyme screening is recommended in children and adolescents with body mass index ≥95^th percentile [18,19]. Elevated liver enzymes per se are not included in the adult NAFL/

NAFLD diagnostic criteria, because individuals with normal ALT may have NAFL/NAFLD or NASH [20,21]. According to the recommendations of the pediatric SAFETY study, elevated ALT yields an estimate of hepatic steatosis similar to a paediatric population-based autopsy NAFLD prevalence, therefore ALT may be used as a screening tool in the general population [12, 22].

Insulin resistance in peripheral tissues is a putative pathogenetic mechanism which contributes to visceral adipose tissue expansion in obesity.  Bile acids activate nuclear transcription receptors, such as the farnesoid X receptor, which regulate hepatic gluconeogenesis, glycogen synthesis and insulin resistance; impaired signaling therefore may be implicated in NAFL pathogenesis [23].  Ethnicity, sex, age, genetic, hormonal, metabolic, nutritional and environmental parameters including gut microbiota profiling, have been reported to have diverse effects on the hepatocyte metabolic milieu [24-28].

Thyroid hormone status is a key regulator of energy metabolism, while adverse alterations of body composition, lipid status, cardiac function, arterial blood pressure and various non-traditional cardiovascular risk factors are associated with various degrees of thyroid dysfunction, ranging from subclinical to overt hypothyroidism [16].  According to Marzullo et al. [29], in euthyroid obese subjects, FT4 appears more closely related than TSH levels, to parameters of cardio-metabolic risk. Hypothyroidism may possibly contribute to NAFL development, through its important role in lipid metabolism, fatty acid oxidation, hepatic lipid peroxidation [15,30]. The actual mechanism is presumed to be mediated by hepatokines, which are liver derived molecules, upregulated in hepatic steatosis and linked to metabolic dysfunction by impacting on glucose homeostasis through interorgan communication [31]. Thyroid hormone receptors crosstalk with nuclear transcription factors in target tissues such as the liver, resulting in under-utilization of fatty acids, esterification and ectopic accumulation of triglycerides. Hypothyroidism is therefore associated with dyslipidaemia due to impaired insulin mediated lipolysis suppression in adipose tissue [32]. It therefore seems plausible to hypothesize a role for thyroid dysfunction in the pathogenesis of NAFL and NAFLD [30].  Furthermore, a potential link between altered thyroid function test and NAFLD has recently been reported in children [33,34].

The purpose of this manuscript is to present and discuss the findings of a single pediatric tertiary center cross-sectional study comparing ALT values in children and adolescents with obesity and severe obesity and their association with thyroid function tests.

Material and Methods

This is a cross-sectional retrospective study of Greek children and adolescents, without known history of liver disease, who attended our obesity clinics accepting nationwide referrals at one of the two major tertiary children’s hospitals in Athens. Patient data had been collected over a ten-year period from 1^st January 2010 until 31^st December 2020. The study protocol was approved by the P. & A. Kyriakou Tertiary Children’s Hospital ethics committee (Approval number 11482/29-06-2022) as per standard regional process. Written consent was waivered, because this study was observational and retrospective, data were derived from anonymized password protected clinical database of patients with obesity and severe obesity, who had attended clinic over the aforementioned time period.

For definition of obesity in children older than 2 years of age, BMI and BMI percentiles were used, as defined by the Centre for Disease Control and Prevention (CDC).  In detail, obesity is defined as ΒΜΙ ≥95^th percentile and severe obesity as ΒΜΙ ≥99^th percentile for age and sex, according to the expert committee recommendations [35]. Demographic, anthropometric and laboratory data were collected, including age, sex, pubertal status, BMI, ALT, fasting lipid profile, fasting serum glucose and insulin, thyroxine stimulating hormone (TSH) and free thyroxine (FT4) levels. Insulin resistance was defined as homeostasis model assessment of insulin resistance (HOMA-IR) ≥ 3.0 [36]. 

Elevated values of ALT ≥ 22 mg/dl for females and ≥ 25.8 mg/dl for males were used as biomarkers of possible liver dysfunction [22].  Suboptimal thyroid function was defined by low normal 0.7 ng/dl 2). Children with syndromic obesity (such as Prader Willi, LaurenceMoon-Bardet-Biedl syndrome), Cushing’s syndrome or primary hypothyroidism were excluded from the analysis.  Subjects with systemic conditions, including cystic fibrosis, inflammatory bowel disease, coeliac disease, infectious or autoimmune hepatitis, Wilson’s disease, personal history of parenteral nutrition administration, cigarette, drug and alcohol use, family history of hereditary hyperlipidemia and/or premature atherosclerosis were also excluded.  All participants were Caucasian.

Fasting blood glucose was measured by glucose oxidase technique (Siemens Advia 1800, USA) and insulin levels were analyzed by direct chemiluminescence technique (Siemens Centaur, USA). Insulin resistance was defined as homeostasis model assessment of insulin resistance (HOMA-IR) ≥ 3.0 [36].  HOMA-IR values were calculated from fasting plasma measurements with the use of the formula [insulin (mU/L) x glucose (mmol/L)/22.5].    Elevated values of ALT ≥ 22 mg/dl for females and ≥ 25.8 mg/dl for males were used as biomarkers of possible liver dysfunction [22].  Suboptimal thyroid function was defined by low normal 0.7 ng/dl

Two hundred and seventy-nine (279 children) with obesity (47.3%) and severe obesity (56.7%), aged between 4 and 16 years old were included in the analysis (51.3% females), and were divided in two groups, as follows; Group 1 included subjects with obesity (95^th percentile ≤ΒΜΙ ≤99^th percentile for age and sex), and Group 2 included subjects with severe obesity (ΒΜΙ≥99^th percentile for age and sex). 

Statistical analysis

All continuous variables were tested for normal distribution using Kolmogorov-Smirnov statistic.  Since they deviated from normality, they are described as median and Interquartile range (75^th – 25^th percentile) (IQR), therefore non-parametric tests were used.  Categorical data are shown as absolute (N) and relative (%) frequencies.  Any differences in the distribution of study participants’ categorical characteristics compared across subgroups were evaluated using Pearson’s χ² test or Fisher’s exact test.  The comparison of the distribution of continuous variables was performed using Mann-Whitney U statistic.  The ALT values (gender dependent) that were described in the Methods section were used as the cut off points in order to construct the surrogate marker of liver dysfunction which was further used as the dependent variable of interest in both univariate and multiple logistic regression analysis.  Due to the relatively small number of comparisons, no adjustment for inflation of type I error was applied.  All tests were two-sided at a significance level of p<0.05. IBM® SPSS® software version 25.0 was used for the analysis.

Post hocpower analysis showed that in order to detect significantly higher differences in the proportion of the variables of interest (higher than 15%) at a significance level lower than 0.05, at the same time achieving statistical power equal to 70%, 137 subjects would be required for each study (obesity) group.

Results

Sex and pubertal status were comparable between the two groups of participants.  The pairwise comparisons revealed that children with severe obesity (Group 2) were much younger (9.9 ± 5.4 vs. 11.3 ± 2.6 years old respectively, p: 0.003) and had higher BMI (p: <0.001).  ALT median values were higher in children with severe obesity compared to their peers with obesity (21 ± 11 vs. 20 ± 8 respectively, p: 0.001).  This finding was further supported when implementing ALT cut off values for categorization as ‘normal vs abnormal liver function’ as per Schwimmer et al. Higher percentage of children with severe obesity had elevated ALT, compared to children with obesity (41.9 % vs. 26.1% respectively, p=0.008). 

Table 1: Descriptive statistics of the study population: demographic, clinical and laboratory characteristics.

The results of univariate logistic regression are shown in (Table 2) The odds of having elevated ALT values were 2.05 times higher among children with severe obesity than among children with obesity; the same trend (OR=2.54) was demonstrated in children with HOMA-IR ≥3 when compared to children with HOMA-IR<3 (p:0.008, 0.001 respectively).  In addition, the odds of having elevated ALT was almost four times higher among children with fT4<1 than among children with fT4≥1 (p: 0.011).  Both LDL<130 and TG<100 reduced significantly and close to 50% the odds of elevated ALT (p=0.037 and p=0.003 respectively).

Table 2: Univariate logistic regression. Elevated ALT as surrogate marker of liver dysfunction is the dependent variable.

Multiple logistic regression modeling (Table 3) showed that the significant effects of severe obesity, low normal 0.7 ng/dl

Table 3: Multiple logistic regression analysis. Elevated ALT as surrogate marker of liver dysfunction is the dependent variable.