What is the appropriate strategy for diagnosing NAFLD using ultrasonography in obese children?

Establish a noninvasive model to screen metabolic dysfunction-associated steatotic liver disease in children aged 6-14 years in China and its applications in high-obesity-risk countries and regions

Background

The prevalence of metabolic-associated steatotic liver disease (MASLD) is rising precipitously among children, particularly in regions or countries burdened with high prevalence of obesity. However, identifying those at high risk remains a significant challenge, as the majority do not exhibit distinct symptoms of MASLD. There is an urgent need for a widely accepted non-invasive predictor to facilitate early disease diagnosis and management of the disease. Our study aims to 1) evaluate and compare existing predictors of MASLD, and 2) develop a practical screening strategy for children, tailored to local prevalence of obesity.

Methods

We utilized a school-based cross-sectional survey in Beijing as the training dataset to establish predictive models for screening MASLD in children. An independent school-based study in Ningbo was used to validate the models. We selected the optimal non-invasive MASLD predictor by comparing logistic regression model, random forest model, decision tree model, and support vector machine model using both the Beijing and Ningbo datasets. This was followed by serial testing using the best performance index we identified and indices from previous studies. Finally, we calculated the potential MASLD screening recommendation categories and corresponding profits based on national and subnational obesity prevalence, and applied those three categories to 200 countries according to their obesity prevalence from 1990 to 2022.

Findings

A total of 1018 children were included (NBeijing = 596, NNingbo = 422). The logistic regression model demonstrated the best performance, identifying the waist-to-height ratio (WHtR, cutoff value ≥0.48) as the optimal noninvasive index for predicting MASLD, with strong performance in both training and validation set. Additionally, the combination of WHtR and lipid accumulation product (LAP) was selected as an optimal serial test to improve the positive predictive value, with a LAP cutoff value of ≥668.22 cm × mg/dL. Based on the obesity prevalence among 30 provinces, three MASLD screening recommendations were proposed: 1) "Population-screening-recommended": For regions with an obesity prevalence ≥12.0%, where MASLD prevalence ranged from 5.0% to 21.5%; 2) "Resources-permitted": For regions with an obesity prevalence between 8.4% and 12.0%, where MASLD prevalence ranged from 2.3% to 4.4%; 3) "Population-screening-not-recommended": For regions with an obesity prevalence <8.4%, where MASLD prevalence is difficult to detect using our tool. Using our proposed cutoff for screening MASLD, the number of countries classified into the "Population-screening-recommended" and "Resources-permitted" categories increased from one and 11 in 1990 to 95 and 28 in 2022, respectively.

Interpretation

WHtR might serve as a practical and accessible index for predicting pediatric MASLD. A WHtR value ≥0.48 could facilitate early identification and management of MASLD in areas with obesity prevalence ≥12.0%. Furthermore, combining WHtR ≥0.48 with LAP ≥668.22 cm × mg/dL is recommended for individual MASLD screening. Moreover, linking these measures with population obesity prevalence not only helps estimate MASLD prevalence but also indicates potential screening profits in regions at varying levels of obesity risk.

Funding

This study was supported by grants from Capital's Funds for Health Improvement and Research (Grant No. 2022-1G-4251), National Natural Science Foundation of China (Grant No. 82273654), Major Science and Technology Projects for Health of Zhejiang Province (Grant No. WKJ-ZJ-2216), Cyrus Tang Foundation for Young Scholar 2022 (2022-B126) and Sino-German Mobility Programme (M-0015).

Vitamin D improves hepatic alterations in ACE1 and ACE2 expression in experimentally induced metabolic syndrome

Metabolic Syndrome (MetS) is a term used to describe a cluster of pathophysiological, biochemical, and metabolic criteria; including high Blood Pressure (BP), high cholesterol, dyslipidaemia, central obesity and Insulin Resistance (IR). The Renin Angiotensin System (RAS) has a regulatory function in BP, hydroelectrolyte balance, and cardiovascular function. RAS is composed of angiotensinogen (AGT), (Ang I), (Ang II), (ACE1), (ACE2), (AT1R), (AT2R), and (Ang 1-7). Vitamin D had been proved to act as a protective factor against MetS. Therefore, the study is pursued to explore vitamin D supplementation roles on hepatic RAS in MetS experimental model. At first, 36 males Albino rats were separated into 4 groups and induced to MetS under controlled circumstances for 3 months. Then, data were collected from blood samples, whereas RNA extracted from liver were analyzed using biochemical and statistical analysis tests. As a result, the major finding was proving that vitamin D can balance the expression of ACE1 and ACE2. Also, confirming that it can improve MetS components by elevating HDL and insulin levels while reducing the levels of BP, cholesterol, LDL, TG, GLU, ALT, AST, and IR. These outcomes may give a new insight into the RAS pathways associated with MetS.

Optimum non-invasive predictive indicators for metabolic dysfunction-associated fatty liver disease and its subgroups in the Chinese population: A retrospective case-control study

OBJECTIVE

Metabolic dysfunction-associated fatty liver disease (MAFLD) affects 25% of the population without approved drug therapy. According to the latest consensus, MAFLD is divided into three subgroups based on different diagnostic modalities, including Obesity, Lean, and Type 2 diabetes mellitus (T₂DM) MAFLD subgroups. This study aimed to find out the optimum non-invasive metabolism-related indicators to respectively predict MAFLD and its subgroups.

DESIGN

1058 Chinese participants were enrolled in this study. Anthropometric measurements, laboratory data, and ultrasonography features were collected. 22 metabolism-related indexes were calculated, including fatty liver index (FLI), lipid accumulation product (LAP), waist circumference-triglyceride index (WTI), etc. Logistic regression analyzed the correlation between indexes and MAFLD. Receiver operating characteristics were conducted to compare predictive values among 22 indicators for screening the best indicators to predict MAFLD in different subgroups.

RESULTS

FLI was the best predictor with the maximum odds ratio (OR) values of overall MAFLD (OR: 6.712, 95%CI: 4.766-9.452, area under the curve (AUC): 0.879, P < 0.05) and T₂DM MAFLD subgroup (OR: 14.725, 95%CI: 3.712-58.420, AUC: 0.958, P < 0.05). LAP was the best predictor with the maximum OR value of Obesity MAFLD subgroup (OR: 2.689, 95%CI: 2.182-3.313, AUC: 0.796, P < 0.05). WTI was the best predictor with the maximum OR values of Lean MAFLD subgroup (OR: 3.512, 95%CI: 2.286-5.395, AUC: 0.920, P < 0.05).

CONCLUSION

The best predictors of overall MAFLD, Obesity, Lean, and T₂DM MAFLD subgroups were respectively FLI, LAP, WTI, and FLI.

Lipid accumulation product is a predictor of nonalcoholic fatty liver disease in childhood obesity

Background

Lipid accumulation product (LAP) is associated with the presence and severity of nonalcoholic fatty liver disease (NAFLD) in adults.

Purpose

Here we evaluated the ability of LAP to predict NAFLD in obese children.

Methods

Eighty obese children (38 girls; age 6–18 years) were included. Anthropometric measurements and biochemical values were obtained from the patients’ medical records. LAP was calculated as [waist circumference (WC) (cm) – 58]×triglycerides (mmol/L) in girls; [WC (cm) – 65]×triglycerides (mmol/ L) in boys. The minLAP and adjLAP were described (3% and 50% of WC values, respectively) and the total/high-density lipoprotein cholesterol index (TC/HDL-C) was calculated. NAFLD was observed on ultrasound, and patients were divided into 3 groups by steatosis grade (normal, grade 0; mild, grade 1; moderate-severe, grade 2–3). The area under the curve (AUC) and appropriate index cutoff points were calculated by receiver operator characteristic analysis.

Results

LAP was positively correlated with puberty stage (rho=0.409; P<0.001), fasting insulin (rho= 0.507; P<0.001), homeostasis model assessment of insulin resistance (rho=0.470; P<0.001), uric acid (rho=0.522; P<0.001), and TC/HDL-C (rho=0.494; P<0.001) and negatively correlated with HDL-C (rho=-3.833; P<0.001). LAP values could be used to diagnose hepatosteatosis (AUC=0.698; P=0.002). The LAP, adjLAP, and minLAP cutoff values were 42.7 (P=0.002), 40.05 (P=0.003), and 53.47 (P= 0.08), respectively. For LAP, the differences between the normal and mild groups (P=0.035) and the normal and moderate-severe groups were statistically significant (P=0.037), whereas the difference between the mild and moderate-severe groups was not (P>0.005). There was a statistically significant difference between the normal and mild groups for adjLAP (P=0.043) but not between the other groups (P>0.005). There was no significant intergroup difference in minLAP (P>0.005).

Conclusion

LAP is a powerful and easy tool to predict NAFLD in childhood. If LAP is ≥42.7, NAFLD should be suspected. This is the first study to assess LAP diagnostic accuracy for childhood obesity.

Relationship between Vitamin D Level and Lipid Profile in Non-Obese Children

Vitamin D deficiency is associated with not only cardiovascular disease itself but also cardiovascular risk factors, including obesity, hypertension, diabetes, hyperglycemia, and dyslipidemia. This study aimed to investigate the relationship between vitamin D level and lipid profile in non-obese children. A total of 243 non-obese healthy volunteers, aged 9-18 years, were enrolled from March to May 2017. Their height and weight were measured, and body mass index was calculated. Subjects underwent blood tests, including measurements of vitamin D (25(OH)D) level and lipid panels, and were divided into either the vitamin D-deficient group (<20 ng/mL) or normal group. The student's t-test and a simple linear regression analysis were used to estimate the association between vitamin D level and lipid profile. Overall, 69.5% of non-obese children (n = 169) had a 25(OH)D level of less than 20 ng/mL. The vitamin D-deficient group showed higher triglyceride (TG) level and TG/high-density lipoprotein cholesterol (HDL-C) ratio than the normal group (TG level: 90.27 vs. 74.74 mmol/L, p = 0.003; TG/HDL-C ratio: 1.753 vs. 1.358, p = 0.003). Vitamin D level seems to affect the lipid profile, even in non-obese children, and a low vitamin D level may progress to dyslipidemia or obesity in non-obese children.

The Liver in Children With Metabolic Syndrome

Non-alcoholic fatty liver disease (NAFLD) is recognized as an emerging health risk in obese children and adolescents. NAFLD represents a wide spectrum of liver conditions, ranging from asymptomatic steatosis to steatohepatitis. The growing prevalence of fatty liver disease in children is associated with an increased risk of metabolic and cardiovascular complications. NAFLD is considered the hepatic manifestation of Metabolic Syndrome (MetS) and several lines of evidence have reported that children with NAFLD present one or more features of MetS. The pathogenetic mechanisms explaining the interrelationships between fatty liver disease and MetS are not clearly understood. Altough central obesity and insulin resistance seem to represent the core of the pathophysiology in both diseases, genetic susceptibility and enviromental triggers are emerging as crucial components promoting the development of NAFLD and MetS in children. In the present review we have identified and summarizied studies discussing current pathogenetic data of the association between NAFLD and MetS in children.

Atherogenic index of plasma is a novel predictor of non-alcoholic fatty liver disease in obese participants: a cross-sectional study

Background

The atherogenic index of plasma showed to be related with some chronic disease like cardiovascular diseases and atherosclerosis. Body mass index which was commonly used in clinical practice is not an accurate index to predict non-alcoholic fatty liver disease. The aim of this study is to investigate the relationship between atherogenic index of plasma and non-alcoholic fatty liver disease in obese participants.

Methods

538 obese subjects were included in this cross sectional study. Non-alcoholic fatty liver disease was diagnosed by B-ultrasonography after excluding participants with other liver diseases. The atherogenic index of plasma was classified into three groups: the low (< 0.11), the intermediate (0.11–0.21) and the high (> 0.21) risk. The participants were separated into groups according to their atherogenic index of plasma levels. The area under receiver operating characteristic curve of the atherogenic index of plasma for predicting non-alcoholic fatty liver disease was calculated.

Results

There were concordances between increased atherogenic index of plasma and significant increase in the value of body mass index, waist circumference, alanine aminotransferase, glutamyl transpeptidase and lipid profile. The atherogenic index of plasma is strongly associated with non-alcoholic fatty liver disease. Compared to the low risk group, the high risk group had a 5.37 folds risk after adjustment for covariates. Results of receiver operating characteristic curves showed that the area under the curve (95% confidence intervals) was 0.718 (0.670–0.766).

Conclusion

These data suggest that atherogenic index of plasma might be a method which can be used in the auxiliary diagnosis of non-alcoholic fatty liver disease.

Prevalence and risk factors for non-alcoholic fatty liver in children and youth with obesity

Background

Non- Alcoholic Fatty Liver (NAFL) is a spectrum of liver diseases (LD) that ranges from benign fatty infiltration of the liver to cirrhosis and hepatic failure. Hepatic ultrasound (US) and serum alanine aminotransferase (ALT) are often used as markers of NAFL. Our aim is to describe prevalence of NAFL and associated findings on ultrasound (US) and biochemical parameters in a population of children and adolescents with obesity at the Children’s Hospital of Eastern Ontario.

Methods

Children with Obesity (BMI >95th percentile) ages 8–17 years presenting to the Endocrinology and Gastroenterology clinics, without underlying LD were prospectively recruited from 2009 to 2012. Fasting lipid profile, HOMA IR) and serum adiponectin levels were measured. NAFL was defined as ALT > 25 and >22 IU/mL (males and females respectively) and/or evidence of fatty infiltration by US. Logistic regression was performed to assess associations.

Results

97 children with obesity included in the study (Male 43%). Mean age was 12.9 ± 3.2 years (84% were older than 10 y). Mean BMI-Z score was 3.8 ± 1.4. NAFL was identified in 85%(82/97) of participants. ALT was elevated in 61% of patients. Median triglyceride (TG) level was higher in children with NAFL(1.5 ± 0.9 vs. 1.1 ± 0.5 mmol/L, p = 0.01). Total cholesterol, HDL, LDL and Non HDL cholesterol were similar in both groups(p = 0.63, p = 0.98, p = 0.72 and p = 0.37 respectively). HOMA IR was ≥3.16 in 53% of children(55% in those with NAFL and 40% in those without NAFL). Median serum adiponectin was 11.2 μg/ml(IQR 7.3–18.3) in children with NAFL vs. 16.1 μg/ml(IQR 9.0–21.9) in those without NAFL(p = 0.23). Liver US was reported as normal in 30%, mild fatty infiltration in 38%, moderate in 20% and severe in 12%. TG were significantly higher(1.5 mmol/L vs. 1.0 mmol/L, p < 0.01) and HDL-C was lower(1.0 mmol/L vs. 1.1 mmol/L, p = 0.05) in children with moderate and severe NAFL by US. BMI-Z score, HOMA IR, serum adiponectin and HDL levels were not associated with NAFL, however TG were significantly associated(OR = 3.22 (95% CI: 1.01–10.25, p = 0.04)).

Conclusion

NAFL is highly prevalent in obese children and youth. Elevated TG levels are associated with NAFL; these findings may serve as a noninvasive screening tool to help clinicians identify children with obesity needing liver biopsy and/or more aggressive therapeutic interventions.