The Role of Aspartate Transaminase to Platelet Ratio Index (APRI) for the Prediction of Non-Alcoholic Fatty Liver Disease (NAFLD) in Severely Obese Children and Adolescents

Reference intervals of biochemical parameters in Chilean adults

Background

Establishing reference intervals (RIs) in clinical laboratories is essential, as these can vary due to inter-individual variability as well as the analytical methods used. The purpose of this study was to determine RIs for markers and ratios biochemical in apparently healthy Chilean adults.

Methods

A sample of 1,143 data was selected from the Universidad Católica de Temuco, Clinical Laboratory database, La Araucanía Region, Chile, which were analysed by sex. The Tukey's Fences was used to detect outliers and the RIs were established using the non-parametric method.

The role of platelets in non-alcoholic fatty liver disease: From pathophysiology to therapeutics

Platelets are one of the key mediators in thrombosis as well as in the progression of many diseases. An increase in platelet activation and a decrease in platelet count is associated with a plethora of liver diseases. In non-alcoholic fatty liver disease (NAFLD), platelets are highly activated and participate in the disease progression by enhancing the pro-thrombotic and pro-inflammatory state. Some altered platelet parameters such as mean platelet volume, plateletcrits, and platelet distribution width, aspartate transaminase to platelet ratio index, liver stiffness to platelet ratio and red cell distribution width to platelet ratio were found to be associated with NAFLD disease. Further, platelet contributes to the progression of cardiovascular complications in NAFLD is gaining the researcher's attention. An elevated mean platelet volume is known to enhance the risk of stroke, atherosclerosis, thrombosis, and myocardial infarction in NAFLD. Evidence also suggested that modulation in platelet function using aspirin, ticlopidine, and cilostazol help in controlling the NAFLD progression. Future research should focus on antiplatelet therapy as a treatment strategy that can control platelet activation in NAFLD as well as its cardiovascular risk. In the present review, we have detailed the role of platelets in NAFLD and its cardiovascular complications. We further aimed to highlight the growing need for antiplatelet therapy in NAFLD.

Combi-Elasto Evaluation of the Degree of Liver Fibrosis in Children with Cholestatic Liver Disease

Cholestatic liver disease is a common liver disease in infants and young children. Liver fibrosis is a key factor affecting the prognosis, and liver transplantation is the only treatment option for liver cirrhosis. This study aimed to explore the efficacy of Combi-elasto for diagnosing liver fibrosis in children affected by cholestatic liver disease. A total of 64 children with S1-S4-grade liver fibrosis were enrolled. The general data, routine ultrasound, Combi-elasto, aspartate aminotransferase-to-platelet ratio index (APRI) and Fibrosis-4 (FIB-4) score were compared among children with different grades of liver fibrosis, and the efficacy of the above indexes for evaluating the degree of liver fibrosis was reported. There were remarkable differences in liver size, liver echogenicity, Young's modulus (E), fibrosis index (FI), activity index (AI) and FIB-4 score among the groups (all p < 0.05). E and liver echogenicity were the independent impact factors of liver fibrosis. The areas under the curve of E, APRI, FIB-4 score and the combined model (E+ liver echogenicity) in the evaluation of liver fibrosis were 0.84, 0.61, 0.66 and 0.90, respectively. Ultimately, we concluded that CE is an effective method to evaluate liver fibrosis in children with cholestatic liver disease.

Diagnostic Performance of Biomarker-Based Scores as Predictors of Metabolic Dysfunction-Associated Fatty Liver Disease Risk in Healthy Children

INTRODUCTION

Metabolic dysfunction-associated fatty liver disease (MAFLD)-a new definition for non-alcoholic fatty liver disease-reflects the impact of metabolic abnormalities on liver function. We assessed the diagnostic accuracy of biomarker-based scores for prediction of MAFLD in apparently healthy children.

METHODS

This study included 144 children aged 9-11. MAFLD was recognized in 14 girls and 29 boys. Anthropometric indices, glycemia, insulin resistance, lipid profile, enzymes (ALT, AST, GGT, ALP), CRP, N-terminal propeptide of type I procollagen (P1NP) and collagen type I C-telopeptide (CTX-1) levels were measured. Fatty liver and hepatic steatosis index (FLI, HSI) and potential indicators of liver fibrogenesis: P1NP/ALP, P1NP/ALPxALT, P1NP/ALPxCRP were calculated.

RESULTS

P1NP/ALPxALT and P1NP/ALPxCRP were significantly higher in subjects with MAFLD. FLI was a good, significant predictor of MAFLD occurrence, regardless of sex. In boys, P1NP/ALPxCRP was a comparable predictor as CRP (OR 1.14 vs. 1.17; p < 0.001). P1NP/ALPxCRP had better discrimination capability in boys (AUC = 0.79; p < 0.001). However, the use of this algorithm did not improve discriminatory power in comparison to CRP (AUC = 0.81; p < 0.001), but gave a better sensitivity for MAFLD prediction (86% vs. 59%).

CONCLUSIONS

We suggest that P1NP/ALPXCRP is a reliable tool for MAFLD prediction in routine pediatric practice.

A dynamic machine learning model for prediction of NAFLD in a health checkup population: A longitudinal study

Background

Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide. Currently, most NAFLD prediction models are diagnostic models based on cross-sectional data, which failed to provide early identification or clarify causal relationships. We aimed to use time-series deep learning models with longitudinal health checkup records to predict the onset of NAFLD in the future, and update the model stepwise by incorporating new checkup records to achieve dynamic prediction.

Methods

10,493 participants with over 6 health checkup records from Beijing MJ Health Screening Center were included to conduct a retrospective cohort study, in which the constantly updated initial 5 checkup data were incorporated stepwise to predict the risk of NAFLD at and after their sixth health checkups. A total of 33 variables were considered, consisting of demographic characteristics, medical history, lifestyle, physical examinations, and laboratory tests. L1-penalized logistic regression (LR) was used for feature selection. The long short-term memory (LSTM) algorithm was introduced for model development, and five-fold cross-validation was conducted to tune and choose optimal hyperparameters. Both internal validation and external validation were conducted, using the 20% randomly divided holdout test dataset and previously unseen data from Shanghai MJ Health Screening Center, respectively, to evaluate model performance. The evaluation metrics included area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, Brier score, and decision curve. Bootstrap sampling was implemented to generate 95% confidence intervals of all the metrics. Finally, the Shapley additive explanations (SHAP) algorithm was applied in the holdout test dataset for model interpretability to obtain time-specific and sample-specific contributions of each feature.

Results

Among the 10,493 participants, 1662 (15.84%) were diagnosed with NAFLD at and after their sixth health checkups. The predictive performance of the deep learning model in the internal validation dataset improved over the incorporation of the checkups, with AUROC increasing from 0.729 (95% CI: 0.698,0.760) at baseline to 0.818 (95% CI: 0.798,0.844) when consecutive 5 checkups were included. The external validation dataset, containing 1728 participants, was used to verify the results, in which AUROC increased from 0.700 (95% CI: 0.657,0.740) with only the first checkups to 0.792 (95% CI: 0.758,0.825) with all five. The results of feature significance showed that body fat percentage, alanine transaminase (ALT), and uric acid owned the greatest impact on the outcome, time-specific, individual-specific and dynamic feature contributions were also produced for model interpretability.

Conclusion

A dynamic prediction model was successfully established in our study, and the prediction capability kept improving with the renewal of the latest checkup records. In addition, we identified key features associated with the onset of NAFLD, making it possible to optimize the prevention and control strategies of the disease in the general population.

A Metabolomics-Based Investigation of the Effects of a Short-Term Body Weight Reduction Program in a Cohort of Adolescents with Obesity: A Prospective Interventional Clinical Study

Metabolomics applied to assess the response to a body weight reduction program (BWRP) may generate valuable information concerning the biochemical mechanisms/pathways underlying the BWRP-induced cardiometabolic benefits. The aim of the present study was to establish the BWRP-induced changes in the metabolomic profile that characterizes the obese condition. In particular, a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted metabolomic approach was used to determine a total of 188 endogenous metabolites in the plasma samples of a cohort of 42 adolescents with obesity (female/male = 32/10; age = 15.94 ± 1.33 year; body mass index standard deviation score (BMI SDS) = 2.96 ± 0.46) who underwent a 3-week BWRP, including hypocaloric diet, physical exercise, nutritional education, and psychological support. The BWRP was capable of significantly improving body composition (e.g., BMI SDS, p < 0.0001), glucometabolic homeostasis (e.g., glucose, p < 0.0001), and cardiovascular function (e.g., diastolic blood pressure, p = 0.016). A total of 64 metabolites were significantly reduced after the intervention (at least p < 0.05), including 53 glycerophospholipids (23 PCs ae, 21 PCs aa, and 9 lysoPCs), 7 amino acids (tyrosine, phenylalanine, arginine, citrulline, tryptophan, glutamic acid, and leucine), the biogenic amine kynurenine, 2 sphingomyelins, and (free) carnitine (C0). On the contrary, three metabolites were significantly increased after the intervention (at least p < 0.05)-in particular, glutamine, trans-4-hydroxyproline, and the octadecenoyl-carnitine (C18:1). In conclusion, when administered to adolescents with obesity, a short-term BWRP is capable of changing the metabolomic profile in the plasma.

Correction: Rigamonti et al. The Role of Aspartate Transaminase to Platelet Ratio Index (APRI) for the Prediction of Non-Alcoholic Fatty Liver Disease (NAFLD) in Severely Obese Children and Adolescents. Metabolites 2022, 12, 155

In the original publication [...].

Comparison of the Modified TyG Indices and Other Parameters to Predict Non-Alcoholic Fatty Liver Disease in Youth

Simple Summary

Non-alcoholic fatty liver disease (NAFLD) is associated with cardio-metabolic risk factors, including obesity, dyslipidemia, insulin resistance, and hepatic cirrhosis. The increasing prevalence of NAFLD among youths has become a public health concern. However, studies about reliable markers for assessing NAFLD in youths are limited. Thus, we investigated the markers including the triglycerides-glucose (TyG) index, modified TyG indices, hepatic steatosis index (HSI), aspartate transaminase-to-platelet ratio index (APRI), and modified APRIs for the prediction of NAFLD. This study demonstrated that the modified TyG indices, APRI-body mass index standard deviation score, and HSI are strongly associated with NAFLD in children and adolescents. Thus, these markers may be useful for identifying youths who require hepatic ultrasonography and early treatment.

Abstract

We investigated the modified triglycerides-glucose (TyG) indices and other markers for non-alcoholic fatty liver disease (NAFLD) in 225 participants aged 10–19 years, and the participants were divided into subgroups according to their NAFLD grade. We performed logistic regression analysis and calculated the odds ratios (ORs) with 95% confidence intervals (CIs) of tertiles 2 and 3 for each parameter, with those of tertile 1 as a reference. The area under the receiver operating characteristic (ROC) curve was calculated to compare the parameters for identifying NAFLD. TyG and modified indices, aspartate transaminase-to-platelet ratio index (APRI)-body mass index (BMI), APRI-BMI standard deviation score (SDS), APRI waist-to-hip ratio, fibrosis-4 index (FIB)-4, and hepatic steatosis index (HSI) were higher in participants with NAFLD than in those without NAFLD. The ORs and 95% CIs for NAFLD progressively increased across tertiles of each parameter. TyG and modified TyG indices, FIB-4, HSI, and modified APRIs, except APRI waist-to-height ratio, predicted NAFLD significantly through ROC curves. Modified TyG indices, APRI-BMI SDS, and HSI were superior to the other markers for NAFLD prediction. Modified TyG indices, APRI-BMI SDS, and HSI appear to be useful for assessing NAFLD in youths.

Non-Invasive Diagnostic Test for Advanced Fibrosis in Adolescents With Non-Alcoholic Fatty Liver Disease

INTRODUCTION

Non-alcoholic fatty liver disease (NAFLD) is a multifaceted disease that includes a wide spectrum of liver damage. The presence and the degree of fibrosis are considered important factors for the prognosis of NAFLD and in predicting the risk of developing cirrhosis. Our aim was to evaluate the usefulness of four fibrosis scores (aspartate aminotransferase/Platelet Index [APRI], FIB-4, NAFLD Fibrosis Score [NFS], and Hepamet) in predicting different degrees of fibrosis among children with biopsy-proven NAFLD.

METHODS

About 286 adolescents [mean age 14.3 years ± 2.5; 154 (53.6%) males], referred between January 2014 and December 2019, with biopsy-proven NAFLD were enrolled.

RESULTS

About 173 (60.4%) patients presented fibrosis at histological analysis. In particular: 140 (49.3%) patients had F = 1, 31 (10.8%), had F = 2 and 2 (0.66%) had F = 3. APRI (AUROC 0.619, 95% CI 0.556-0.679) and Hepamet (AUROC 0.778, 95% CI 0.722-0.828) scores had significant (p < 0.001) accuracy to distinguish subjects with fibrosis; while NFS and FIB-4 had not. APRI had a positive predictive value (PPV) of 62.77% (95% CI 57.96-67.35) and an negative predictive value (NPV) of 52.01% (95% CI 46.54-57.43); Hepamet a PPV of 63.24% (95% CI 59.95-66.41) and an NPV of 61.29% (52.9-69.01).

CONCLUSIONS

Our study showed that Hepamet and APRI perform better than NFS and FIB-4 for identifying fibrosis in patients with NAFLD, but do not have PPVs so high to be considered diagnostic. Therefore, they cannot be employed, in children, for a certain diagnosis of fibrosis or its progression and cannot replace liver biopsy as the gold diagnostic standard. It is, therefore, necessary to continue to research and develop new markers of exclusive fibrosis.