Development and validation study of a non-alcoholic fatty liver disease risk scoring model among adults in China

Diagnostic accuracy of blood biomarkers and non-invasive scores for the diagnosis of NAFLD and NASH: Systematic review and meta-analysis

INTRODUCTION AND OBJECTIVES

Fatty liver disease is an important public health problem. Early diagnosis is critical to lower its rate of progression to irreversible/terminal stages. This study aimed to evaluate the accuracy of non-invasive prediction scores for fatty liver disease (NAFLD and NASH) diagnosis in adults.

MATERIALS AND METHODS

A search was conducted in 10 databases, a qualitative synthesis of 45 studies, and quantitative analysis of the six most common scores. There were 23 risk scores found for NAFLD diagnosis and 32 for NASH diagnosis. The most used were Fatty Liver Index (FLI), aspartate aminotransferase (AST) to Platelet Ratio Index, Fibrosis-4 Index (FIB-4), AST/alanine aminotransferase (ALT) ratio, BARD score, and NAFLD fibrosis score (NFS).

RESULTS

The results from the meta-analysis for FLI: Area under the curve (AUC) of 0.76 (95% Confidence Interval [CI] 0.73, 0.80), sensitivity 0.67 (CI 95% 0.62, 0.72) and specificity 0.78 (CI 95% 0.74, 0.83). The AST to Platelet Ratio Index: AUC 0.83 (CI 95% 0.80, 0.86), sensitivity 0.45 (95% CI 0.29, 0.62), and specificity of 0.89 (95% CI 0.83, 0.92). The NFS: AUC of 0.82 (CI 95% 0.78, 0.85), sensitivity 0.30 (CI 95% 0.27, 0.33) and specificity 0.96 (CI 95% 0.95,0.96).

CONCLUSIONS

The FLI for NAFLD and AST to Platelet Ratio Index for NASH were the risk scores with the highest prognostic value in the included studies. Further research is needed for the application of new diagnostic risk scores for NAFLD and NASH.

2019 Global NAFLD Prevalence: A Systematic Review and Meta-analysis

BACKGROUND & AIMS

The increasing rates of obesity and type 2 diabetes mellitus may lead to increased prevalence of nonalcoholic fatty liver disease (NAFLD). We aimed to determine the current and recent trends on the global and regional prevalence of NAFLD.

METHODS

Systematic search from inception to March 26, 2020 was performed without language restrictions. Two authors independently performed screening and data extraction. We performed meta-regression to determine trends in NAFLD prevalence.

RESULTS

We identified 17,244 articles from literature search and included 245 eligible studies involving 5,399,254 individuals. The pooled global prevalence of NAFLD was 29.8% (95% confidence interval [CI], 28.6%-31.1%); of these, 82.5% of included articles used ultrasound to diagnose NAFLD, with prevalence of 30.6% (95% CI, 29.2%-32.0%). South America (3 studies, 5716 individuals) and North America (4 studies, 18,236 individuals) had the highest NAFLD prevalence at 35.7% (95% CI, 34.0%-37.5%) and 35.3% (95% CI, 25.4%-45.9%), respectively. From 1991 to 2019, trend analysis showed NAFLD increased from 21.9% to 37.3% (yearly increase of 0.7%, P < .0001), with South America showing the most rapid change of 2.7% per year, followed by Europe at 1.1%.

CONCLUSIONS

Despite regional variation, the global prevalence of NAFLD is increasing overall. Policy makers must work toward reversing the current trends by increasing awareness of NAFLD and promoting healthy lifestyle environments.

Adiposity, metabolomic biomarkers, and risk of nonalcoholic fatty liver disease: a case-cohort study

BACKGROUND

Globally, the burden of obesity and associated nonalcoholic fatty liver disease (NAFLD) are rising, but little is known about the role that circulating metabolomic biomarkers play in mediating their association.

OBJECTIVES

We aimed to examine the observational and genetic associations of adiposity with metabolomic biomarkers and the observational associations of metabolomic biomarkers with incident NAFLD.

METHODS

A case-subcohort study within the prospective China Kadoorie Biobank included 176 NAFLD cases and 180 subcohort individuals and measured 1208 metabolites in stored baseline plasma using a Metabolon assay. In the subcohort the observational and genetic associations of BMI with biomarkers were assessed using linear regression, with adjustment for multiple testing. Cox regression was used to estimate adjusted HRs for NAFLD associated with biomarkers.

RESULTS

In observational analyses, BMI (kg/m2; mean: 23.9 in the subcohort) was associated with 199 metabolites at a 5% false discovery rate. The effects of genetically elevated BMI with specific metabolites were directionally consistent with the observational associations. Overall, 35 metabolites were associated with NAFLD risk, of which 15 were also associated with BMI, including glutamate (HR per 1-SD higher metabolite: 1.95; 95% CI: 1.48, 2.56), cysteine-glutathione disulfide (0.44; 0.31, 0.62), diaclyglycerol (C32:1) (1.71; 1.24, 2.35), behenoyl dihydrosphingomyelin (C40:0) (1.92; 1.42, 2.59), butyrylcarnitine (C4) (1.91; 1.38, 2.35), 2-hydroxybehenate (1.81; 1.34, 2.45), and 4-cholesten-3-one (1.79; 1.27, 2.54). The discriminatory performance of known risk factors was increased when 28 metabolites were also considered simultaneously in the model (weighted C-statistic: 0.84 to 0.90; P  < 0.001).

CONCLUSIONS

Among relatively lean Chinese adults, a range of metabolomic biomarkers are associated with NAFLD risk and these biomarkers may lie on the pathway between adiposity and NAFLD.

Systematic review on the prevalence of nonalcoholic fatty liver disease in South Korea

AIMS

We aimed to conduct a systematic review and a meta-analysis to estimate NAFLD prevalence and its change in Korea.

METHODS

We searched the literature involving NAFLD prevalence in Korea in PubMed, RISS, and KMBASE from inception to June 2017. Studies with subjects with certain disorders, population limitations, or subjects who consume alcohol were excluded. Analysis was stratified by publication year, age, gender, severity, body mass index (BMI), and diagnostic technique. Random-effects models were used to provide point estimates (95% confidence interval) of prevalence with subgroup analysis to account for heterogeneity.

RESULTS

A total of 61 studies (837,897 participants) were included. The overall NAFLD prevalence in Korea was 30.3% (men: 41.1%, women: 20.3%), with a slight increase from 29.0% to 31.0% over an approximately 10-year period. BMI significantly affected NAFLD prevalence (≤ or > 25 kg/m², 12.3% vs. 41.7%, p < 0.001), while women were significantly affected by aging (< or ≥ 50 years, 17.0% vs. 25.8%, p < 0.01). The prevalence of steatosis by severity was 22.6% for mild, 9.8% for moderate to severe and 2.2% for nonalcoholic steatohepatitis (NASH), with different patterns by gender.

CONCLUSION

The current study is the first systematic analysis on NAFLD prevalence in Korea and found a change in NAFLD prevalence during the recent decade.

Associations between Phase Angle Values Obtained by Bioelectrical Impedance Analysis and Nonalcoholic Fatty Liver Disease in an Overweight Population

OBJECTIVE

There is a limited diagnosis of nonalcoholic fatty liver disease (NAFLD). Thus, the noninvasive assessments are worth exploring. We determined the associations of phase angles (PhAs) obtained from bioelectric impedance analysis (BIA) with the risk of NAFLD in an overweight population.

METHODS

A study involving 953 overweight participants was conducted in Wuhan city, China. The associations between PhAs (right arm, left arm, body trunk, right leg, left leg, and whole body) and the risk of NAFLD were conducted using multivariate logistic regression analyses. The associations of PhAs with the controlled attenuation parameter (CAP), a noninvasive assessment of liver steatosis and fibrosis, were also evaluated by both linear and logistic regression analyses.

RESULTS

The PhA values of the whole body, trunk, and legs were significantly lower (P < 0.05) in the NAFLD group than the non-NAFLD group. After adjustment for BMI, gender, education, income/year, hyperlipidemia, hypertension, diabetes, smoking, passive smoking, and drinking, significant associations of PhA values of the right leg, left leg, and whole body with the risk of NAFLD were observed. In addition, the PhA of the right leg, left leg, and whole body were significantly related to the CAP values. Further stratified analyses indicated that these associations were significant in the participants with BMI <30, but not in the participants with BMI ≥30.

CONCLUSIONS

PhAs might be effective indicators in the management of NAFLD among overweight people.

Nonalcoholic fatty liver disease experiences accumulation of hepatic liquid crystal associated with increasing lipophagy

Background

In the past 30 years, incidences of non-alcoholic fatty liver disease (NAFLD) has risen by 30%. However, there is still no clear mechanism or accurate method of anticipating liver failure. Here we reveal the phase transitions of liquid crystalline qualities in hepatic lipid droplets (HLDs) as a novel method of anticipating prognosis.

Methods

NAFLD was induced by feeding C57BL/6J mice on a high-fat (HiF) diet. These NAFLD livers were then evaluated under polarized microscopy, X-ray diffraction and small-angle scattering, lipid component chromatography analysis and protein expression analysis. Optically active HLDs from mouse model and patient samples were both then confirmed to have liquid crystal characteristics. Liver MAP1LC3A expression was then evaluated to determine the role of autophagy in liquid crystal HLD (LC-HLD) formation.

Results

Unlike the normal diet cohort, HiF diet mice developed NAFLD livers containing HLDs exhibiting Maltese cross birefringence, phase transition, and fluidity signature to liquid crystals. These LC-HLDs transitioned to anisotropic crystal at 0 °C and remain crystalline. Temperature increase to 42 °C causes both liquid crystal and crystal HLDs to convert to isotropic droplet form. These isotropic HLDs successfully transition to anisotropic LC with fast temperature decrease and anisotropic crystal with slow temperature decrease. These findings were duplicated in patient liver. Patient LC-HLDs with no inner optical activity were discovered, hinting at lipid saturation as the mechanism through which HLD acquire LC characteristics. Downregulation of MAP1LC3A in conjunction with increased LC-HLD also implicated autophagy in NAFLD LC-HLD formation.

Conclusions

Increasing concentrations of amphiphilic lipids in HLDs favors organization into alternating hydrophilic and hydrophobic layers, which present as LC-HLDs. Thus, evaluating the extent of liquid crystallization with phase transition in HLDs of NAFLD patients may reveal disease severity and predict impending liver damage.

Identification of Potential Type II Diabetes in a Chinese Population with a Sensitive Decision Tree Approach

BACKGROUND

Diabetes mellitus is a chronic disease with a steadfast increase in prevalence. Due to the chronic course of the disease combining with devastating complications, this disorder could easily carry a financial burden. The early diagnosis of diabetes remains as one of the major challenges medical providers are facing, and the satisfactory screening tools or methods are still required, especially a population- or community-based tool.

METHODS

This is a retrospective cross-sectional study involving 15,323 subjects who underwent the annual check-up in the Department of Family Medicine of Shengjing Hospital of China Medical University from January 2017 to June 2017. With a strict data filtration, 10,436 records from the eligible participants were utilized to develop a prediction model using the J48 decision tree algorithm. Nine variables, including age, gender, body mass index (BMI), hypertension, history of cardiovascular disease or stroke, family history of diabetes, physical activity, work-related stress, and salty food preference, were considered.

RESULTS

The accuracy, precision, recall, and area under the receiver operating characteristic curve (AUC) value for identifying potential diabetes were 94.2%, 94.0%, 94.2%, and 94.8%, respectively. The structure of the decision tree shows that age is the most significant feature. The decision tree demonstrated that among those participants with age ≤ 49, 5497 participants (97%) of the individuals were identified as nondiabetic, while age > 49, 771 participants (50%) of the individuals were identified as nondiabetic. In the subgroup where people were 34 < age ≤ 49 and BMI ≥ 25, when with positive family history of diabetes, 89 (92%) out of 97 individuals were identified as diabetic and, when without family history of diabetes, 576 (58%) of the individuals were identified as nondiabetic. Work-related stress was identified as being associated with diabetes. In individuals with 34 < age ≤ 49 and BMI ≥ 25 and without family history of diabetes, 22 (51%) of the individuals with high work-related stress were identified as nondiabetic while 349 (88%) of the individuals with low or moderate work-related stress were identified as not having diabetes.

CONCLUSIONS

We proposed a classifier based on a decision tree which used nine features of patients which are easily obtained and noninvasive as predictor variables to identify potential incidents of diabetes. The classifier indicates that a decision tree analysis can be successfully applied to screen diabetes, which will support clinical practitioners for rapid diabetes identification. The model provides a means to target the prevention of diabetes which could reduce the burden on the health system through effective case management.