Relationship between body composition and the histology of non-alcoholic fatty liver disease: a cross-sectional study

Association between cardiometabolic index and hepatic steatosis and liver fibrosis: a population-based study

BACKGROUND

The cardiometabolic index (CMI) is a new type of obesity index that is based on a combination of lipid levels and abdominal obesity indicators. It is closely correlated with the occurrence of diabetes mellitus, atherosclerosis, hypertension, and other diseases, thus playing an important role in the screening of metabolic diseases. This is coupled with hepatic steatosis and fibrosis which are characterized by excessive liver fat deposition. The aim of this study was to investigate the possible association between CMI and hepatic steatosis and liver fibrosis.

METHODS

A cross-sectional investigation was conducted using the 2017-2020 National Health and Nutrition Examination Survey (NHANES) dataset to probe the relationship between CMI and hepatic steatosis and liver fibrosis, while multiple linear regression models were used to test the linear association between CMI and controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Smooth-fit curves and threshold effects analysis were used to describe the nonlinear relationships. Subgroup analyses were performed according to gender, age, body mass index (BMI), hypertension, diabetes, cardiovascular disease, and smoking status.

RESULTS

A total of 3084 adults aged 18-80 years were included in this analysis, and after controlling for a variety of variables, there was a significant positive correlation between CMI and CAP [20.38 (16.27,24.49)]. When subgroups were analyzed, this positive correlation was found to be stronger in the female population than in the male (P for interaction = 0.0303). Furthermore, the association between CMI and CAP was nonlinear. Using multiple regression analysis, it was shown that the linear relationship between CMI and liver fibrosis was not significant [-0.09 (-0.47,0.29)].

CONCLUSIONS

The findings suggest that elevated CMI levels are associated with hepatic steatosis, but that CMI is not linked to liver fibrosis. Larger prospective investigations are needed to confirm our findings.

The relative contributions of soft tissue mass components as risk or protective factors of non-alcoholic fatty liver disease in children

BACKGROUND/OBJECTIVE

Several body components are known to be associated with non-alcoholic fatty liver disease (NAFLD) in children. However, the relative contributions of soft tissue mass components as risk or protective factors of NAFLD are largely unknown because measurements of these components are often highly correlated. Therefore, we aimed to estimate levels of association between soft tissue mass components and NAFLD.

SUBJECTS/METHODS

We collected the medical records of 555 Chinese children (aged 3-18 years). Five mutually exclusive and exhaustive components of soft tissue mass were measured using dual energy X-ray absorptiometry. NAFLD was diagnosed with abdominal B-ultrasound scan. We fit Dirichlet regression and multivariate linear regression models wherein age and NAFLD were used as predictors of the proportional measurements of soft tissue mass components.

RESULTS

The proportion of android fat was significantly higher in children with NAFLD than in those without NAFLD (ratio of proportions ranged from 1.18 to 1.30), whereas proportions of trunk lean and limb lean were significantly lower (ratio of proportions ranged from 0.87 to 0.92 for trunk lean and from 0.82 to 0.91 for limb lean). The proportion of gynoid fat was slightly higher in boys with NAFLD than in those without NAFLD (ratio = 1.05), but this proportion was not significantly higher in girls. The association between the proportion of android fat and NAFLD appeared to be somewhat greater than the associations between proportions of trunk lean or limb lean components and NAFLD.

CONCLUSION

Our findings suggest that lowering fat mass and increasing lean mass can both be used to combat NAFLD in children and that more studies are needed to determine the association between gynoid fat and NAFLD.

Combined Effect of Body Mass Index and Waist Circumference in Predicting Nonalcoholic Fatty Liver Disease

Background: Body mass index (BMI) and waist circumference (WC) are the most widely used anthropometric indices for identifying obesity. This study aimed to compare and clarify the usefulness of BMI, WC, and the combination of these two indicators in predicting nonalcoholic fatty liver disease (NAFLD). Methods: This cross-sectional study included 15,267 Korean adults. We defined four obesity categories using BMI and WC as follows: BMI nonobese and WC nonobese (BNWN); BMI obese and WC nonobese (BOWN); BMI nonobese and WC obese (BNWO); and BMI obese and WC obese (BOWO). Analysis of variance was used to compare fatty liver severity across each category. The odds ratios (ORs) and 95% confidence intervals (CIs) for NAFLD were calculated using multiple logistic regression. Results: Compared with BNWN, participants with BNWO were 3.235 (95% CI: 2.774-3.773) times more likely and participants with BOWN were 2.344 (95% CI: 2.045-2.687) times more likely to have NAFLD. Participants with BNWO had higher OR for NAFLD than those with BOWN. Moreover, BOWO participants had the highest OR of 4.788 (95% CI: 4.350-5.270) for NAFLD among all obesity categories. Conclusion: Combined obesity classification by BOWO is the most reliable indicator for NAFLD presence in Korean adults.

A genetic basis of mitochondrial DNAJA3 in nonalcoholic steatohepatitis-related hepatocellular carcinoma

BACKGROUND AND AIMS

NAFLD is the most common form of liver disease worldwide, but only a subset of individuals with NAFLD may progress to NASH. While NASH is an important etiology of HCC, the underlying mechanisms responsible for the conversion of NAFLD to NASH and then to HCC are poorly understood. We aimed to identify genetic risk genes that drive NASH and NASH-related HCC.

APPROACH AND RESULTS

We searched genetic alleles among the 24 most significant alleles associated with body fat distribution from a genome-wide association study of 344,369 individuals and validated the top allele in 3 independent cohorts of American and European patients (N=1380) with NAFLD/NASH/HCC. We identified an rs3747579-TT variant significantly associated with NASH-related HCC and demonstrated that rs3747579 is expression quantitative trait loci of a mitochondrial DnaJ Heat Shock Protein Family (Hsp40) Member A3 ( DNAJA3 ). We also found that rs3747579-TT and a previously identified PNPLA3 as a functional variant of NAFLD to have significant additional interactions with NASH/HCC risk. Patients with HCC with rs3747579-TT had a reduced expression of DNAJA3 and had an unfavorable prognosis. Furthermore, mice with hepatocyte-specific Dnaja3 depletion developed NASH-dependent HCC either spontaneously under a normal diet or enhanced by diethylnitrosamine. Dnaja3 -deficient mice developed NASH/HCC characterized by significant mitochondrial dysfunction, which was accompanied by excessive lipid accumulation and inflammatory responses. The molecular features of NASH/HCC in the Dnaja3 -deficient mice were closely associated with human NASH/HCC.

CONCLUSIONS

We uncovered a genetic basis of DNAJA3 as a key player of NASH-related HCC.

LEARN algorithm: a novel option for predicting non-alcoholic steatohepatitis

Background

There is an unmet need for accurate non-invasive methods to diagnose non-alcoholic steatohepatitis (NASH). Since impedance-based measurements of body composition are simple, repeatable and have a strong association with non-alcoholic fatty liver disease (NAFLD) severity, we aimed to develop a novel and fully automatic machine learning algorithm, consisting of a deep neural network based on impedance-based measurements of body composition to identify NASH [the bioeLectrical impEdance Analysis foR Nash (LEARN) algorithm].

Methods

A total of 1,259 consecutive subjects with suspected NAFLD were screened from six medical centers across China, of which 766 patients with biopsy-proven NAFLD were included in final analysis. These patients were randomly subdivided into the training and validation groups, in a ratio of 4:1. The LEARN algorithm was developed in the training group to identify NASH, and subsequently, tested in the validation group.

Results

The LEARN algorithm utilizing impedance-based measurements of body composition along with age, sex, pre-existing hypertension and diabetes, was able to predict the likelihood of having NASH. This algorithm showed good discriminatory ability for identifying NASH in both the training and validation groups [area under the receiver operating characteristics (AUROC): 0.81, 95% CI: 0.77-0.84 and AUROC: 0.80, 95% CI: 0.73-0.87, respectively]. This algorithm also performed better than serum cytokeratin-18 neoepitope M30 (CK-18 M30) level or other non-invasive NASH scores (including HAIR, ION, NICE) for identifying NASH (P value <0.001). Additionally, the LEARN algorithm performed well in identifying NASH in different patient subgroups, as well as in subjects with partial missing body composition data.

Conclusions

The LEARN algorithm, utilizing simple easily obtained measures, provides a fully automated, simple, non-invasive method for identifying NASH.

Association between Body Composition Contents and Hepatic Fibrosis in Sarcopenic Obesity

It is well established that sarcopenic obesity (SO) is linked to many diseases such as metabolic and non-alcoholic fatty liver diseases, but there is little known about the relationship between SO and hepatic fibrosis progression in chronic liver disease. This study compared body composition contents in patients with non-obesity (NOb) and SO using abdominal magnetic resonance imaging and investigated the relationship between hepatic fibrosis and SO factors. This retrospective study enrolled 60 patients (28 NOb; 32 SO) from June 2014 to December 2020. Patients underwent histopathologic investigation where they classified fibrosis stages based on the Meta-analysis of Histological Data in Viral Hepatitis fibrosis scoring system. Muscle and fat areas at the third lumber vertebra level were assessed. The variation in the areas of muscle (MA), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) among fibrosis stages, and associations between hepatic fibrosis and SO factors, were analyzed. There were significant differences in SAT and VAT (p < 0.001), whereas there was no difference in MA (p = 0.064). There were significant differences in MA/SAT (p = 0.009), MA/VAT (p < 0.001), and MA/(SAT+VAT) (p < 0.001). In all the patients, hepatic fibrosis positively correlated with serum aspartate aminotransferase level (AST, R = 0.324; p = 0.025). Especially in SO patients, hepatic fibrosis closely correlated with body mass index (BMI, R = 0.443; p = 0.011), AST (R = 0.415; p = 0.044), VAT (R = 0.653; p < 0.001), MA/VAT (R = -0.605; p < 0.001), and MA/(SAT+VAT) (R = -0.416; p = 0.018). However, there was no association in NOb patients. This study demonstrated that SO patients had larger SAT and VAT than NOb patients. Hepatic fibrosis in SO positively correlated with body visceral fat composition in combination with BMI and AST level. These findings will be useful for understanding the relationship between the hepatic manifestation of fibrosis and body fat composition in sarcopenia and SO.

Association of Hepatic Steatosis with Adipose and Muscle Mass and Distribution in Children

Background: Pediatric studies have shown associations between hepatic steatosis and total body fat, visceral fat, and lean mass. However, these associations have not been assessed simultaneously, leaving their relative importance unknown. Objective: To evaluate associations between hepatic steatosis and total-body adiposity, visceral adiposity, and lean mass in children. Method: In children at risk for fatty liver, hepatic steatosis, adipose, and lean mass were estimated with magnetic resonance imaging and dual-energy X-ray absorptiometry. Results: Two hundred twenty-seven children with mean age 12.1 years had mean percent body fat of 38.9% and mean liver fat of 8.4%. Liver fat was positively associated with total-body adiposity, visceral adiposity, and lean mass (P < 0.001), and negatively associated with lean mass percentage (P < 0.001). After weight adjustment, liver fat was only positively associated with measures of central adiposity (P < 0.001). Visceral adiposity also had the strongest association with liver fat (P < 0.001). Conclusions: In children, hepatic steatosis is more strongly associated with visceral adiposity than total adiposity, and the association of lean mass is not independent of weight or fat mass. These relationships may help guide the choice of future interventions to target hepatic steatosis.

Correlation between CT Abdominal Anthropometric Measurements and Liver Density in Individuals with Non-Alcoholic Fatty Liver Disease

Background: With a growing frequency, nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. NAFLD has a strong correlation with other metabolic disorders, such as obesity, particularly abdominal obesity, even though the underlying causes or risk factors are not entirely understood. This study aims to investigate correlations between abdominal anthropometric measurements and the presence and intensity of liver steatosis as assessed by unenhanced computed tomography (CT). Methods: One hundred and nineteen patients (male/female, 66/53; mean age 54.54 +/− 12.90 years) underwent abdominal non–contrast-enhanced CT. CT images were examined to determine the attenuation of liver parenchyma, subcutaneous fat depth, and waist circumference (WC). Results: Among all patients, WC (r = −0.78, p < 0.0001), infraumbilical subcutaneous fat thicknesses (r = −0.51, p < 0.0001), right paraumbilical subcutaneous fat thicknesses (r = −0.62, p < 0.0001), and left paraumbilical subcutaneous fat thicknesses (r = −0.53, p < 0.0001) had a high inverse correlation with the liver attenuation values. The presence of T2D (OR: 2.40, p = 0.04), WC (OR: 11.45, p < 0.001), right paraumbilical (OR: 10.09, p < 0.001), left paraumbilical (OR: 2.81, p = 0.01), and infraumbilical (OR: 3.06, p = 0.007) were strongly independent predictors of NAFLD risk. Moreover, regarding the laboratory parameters, only the higher value of GGT (OR: 2.84, p = 0.009) is a predictor of NAFLD risk. Conclusions: Our data show that higher baseline values of all abdominal anthropometric measurements are correlated with liver attenuation and act as predictors of NAFLD risk.

Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions

CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high speed and accuracy for extracting body composition metrics from CT scans. These may inform preoperative interventions and guide treatment planning. This review aims to discuss the clinical applications of CT body composition in clinical practice, as it moves towards widespread clinical implementation.

NAFLD as the metabolic hallmark of obesity

Non-alcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease worldwide, associated with a high risk of progression to NASH, liver cirrhosis and hepatocarcinoma. Its prevalence is closely related to obesity (understood as adipose-based disease and insulin resistance), which makes that at present NAFLD can be considered a metabolic dysfunction hallmark, regardless of the body mass index. Despite being such a prevalent condition, with such severe consequences, at present there are no reliable biomarkers for its diagnosis or specific treatment. Significant and sustained weight loss, as well as some antidiabetic treatments, has shown promising results for NAFLD but data needs confirmation in larger clinical trials and longer follow-up. Efforts should be made for a better and more accurate baseline diagnosis (including large-scale genetics), identification of patients at higher risk for progression to NASH as well as adequate treatment, to allow us to offer a personalized approach in NAFLD in the context of precision medicine.

Cutoff Points of Waist Circumference for Predicting Incident Non-Alcoholic Fatty Liver Disease in Middle-Aged and Older Korean Adults

This study aimed to determine the optimal cutoff value of waist circumference (WC) for predicting incident NAFLD. In this community-based prospective cohort study, we analyzed data from 5400 participants without NAFLD at baseline aged 40−69 years. NAFLD was defined as a NAFLD-liver fat score >−0.640. A Cox proportional hazards regression model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for an association between body composition and NAFLD incidence. The predictive power of each body composition indicator was assessed by Harrell’s concordance index for Cox models. During a mean follow-up period of 12 years, there were 2366 new-onset NAFLD events. Compared with men with WC < 81 cm, the adjusted HR (95% CI) for incident NAFLD in those with WC ≥ 81 cm was 2.44 (2.23−2.67). Compared with women with WC < 78.5 cm, the adjusted HR (95% CI) for incident NAFLD in those with WC ≥ 78.5 cm was 2.54 (2.25−2.87). WC was the most significant risk factor for predicting incident NAFLD among body composition indicators in middle-aged and older Korean adults. The optimal WC cutoff point for predicting incident NALFD was 81 cm in men and 78.5 cm in women, which might assist in the early detection and prevention of NAFLD.

Association Between Skeletal Muscle Mass and Severity of Steatosis and Fibrosis in Non-alcoholic Fatty Liver Disease

Background

Sarcopenia is known to be the risk factor of non-alcoholic fatty liver disease (NAFLD). However, studies evaluating the association of skeletal muscle mass (SMM) with liver fibrosis by transient elastography are limited. Here, we investigated the association of SMM with hepatic steatosis and fibrosis assessed in Chinese adults.

Methods

Patients who underwent liver ultrasonography at the Health Promotion Center of the First Affiliated Hospital of Nanjing Medical University between January 2020 to June 2021 were enrolled. We used transient elastography to evaluate the degree of hepatic fat and liver stiffness. Appendicular skeletal muscle mass was determined by bioelectrical impedance and was adjusted for body weight to derive the skeletal muscle mass index (SMI).

Results

Of 3,602 finally enrolled individuals, 1,830 had NAFLD and 1,772 did not have NAFLD. SMI gradually decreased as the severity of hepatic steatosis increased (40.47 ± 3.94% vs. 39.89 ± 3.57% vs. 39.22 ± 3.46% vs. 37.81 ± 2.84%, P < 0.001). Individuals with F3-F4 and F2 liver fibrosis groups had significantly lower SMI than individuals with F0-F1 stages (37.51 ± 3.19% vs. 38.06 ± 3.51% vs. 39.36 ± 3.38%, P < 0.001). As the SMI increased, the percentages of subjects with mild and severe NAFLD, and the percentages of subjects in F2 and F3-F4 stage were gradually decreased. SMI was independently associated with the severity of hepatic steatosis and fibrosis by logistic regression analysis. Moreover, decreased SMI was an independent risk factor for NAFLD and fibrosis.

Conclusion

SMI is closely associated with liver fat content and liver fibrosis in Chinese adults with NAFLD.

Gender differences in the association of body composition and biopsy-proved nonalcoholic steatohepatitis

BACKGROUND AND AIM

Body composition was associated with nonalcoholic steatohepatitis (NASH), but results were controversial probably due to gender differences. Hence, we aim to explore the association of body composition and NASH in males and females.

METHODS

We conducted a cross-sectional analysis of obese subjects undergone liver biopsy. According to NASH Clinical Research Network system, subjects were categorized as Normal Control (NC), non-NASH or NASH. Body composition was accessed by dual-energy X-ray absorptiometry.

RESULTS

This study enrolled 336 subjects (mean age 32.0 years, mean BMI 39.15 kg/m², female, 64.0%). Males have lower relative muscle mass (RMM 55.21 ± 4.07%) and females have higher android to gynoid ratio (AGR, 0.82 ± 0.21) in NASH when compared with non-NASH (RMM 57.49 ± 4.75%; AGR 0.7 ± 0.15) and NC (RMM 58.69 ± 4.09%; AGR 0.66 ± 0.19, p < 0.05 for each). After adjusting for confounding factors, low RMM was the independent risk factor for NASH in males (odds ratio [OR] 0.550; 95% confidence interval [CI] 0.312-0.970), high AGR was the independent risk factor for NASH in females (OR 1.694; 95% CI 1.073-2.674). Further, RMM in males and AGR in females, respectively, was associated with liver steatosis and activity, but not with fibrosis. ROC curve revealed that the optimal cutoff value of RMM was 58.09% in males and AGR was 0.92 in females for predicting NASH.

CONCLUSIONS

We firstly revealed that low RMM and high AGR were the independent risk factors for NASH in males and females, respectively, indicating that sex-specific interventions for improving body composition may reduce the risk of NASH in obese subjects.