Serum Uric Acid Is a Mediator of the Association Between Obesity and Incident Nonalcoholic Fatty Liver Disease: A Prospective Cohort Study

Triglycerides Mediate the Influence of Body Mass Index on Non-Alcoholic Fatty Liver Disease in a Non-Obese Chinese Population with Normal Low-Density Lipoprotein Cholesterol Levels

INTRODUCTION

Over 25% of the world's population has non-obese or lean non-alcoholic fatty liver disease (NAFLD), and the prevalence is higher than average in Asia. The present study focused on the relationship between body mass index (BMI) and non-obese NAFLD in non-overweight people in China, particularly the influence of triglycerides (TG) in the pathogenesis of non-obese NAFLD. The findings suggest new treatments for NAFLD patients with normal BMI, as well as provide an early warning system for the understanding and prevention of NAFLD in non-obese patients.

METHODS

This cross-sectional study enrolled 159,959 Chinese subjects with BMI <24 kg/m2 and normal levels of low-density lipoprotein cholesterol (LDL-c). The average age was 40.21 ± 13.88 years, and males accounted for 45.7%. A total of 15,907 (9.94%) patients with NAFLD were diagnosed by ultrasonography. Biochemical indicators were measured using an automated analyzer (Abbott AxSYM). The BMI (kg/m2) was calculated from the weight (kg)/height in square meters (m2). The BMI quartile was used as the column-stratified variable to determine the baseline distribution, and logistic regression analysis was used to assess the relationship between NAFLD and its risk factors, with multiple logistic regression used to assess the relationships between BMI or TG and NAFLD and multivariate linear regression used to analyze the association between BMI and TG, while mediation analysis was used to assess the mediation effect of TG.

RESULTS

After adjustment of all covariates, the odds ratios were 1.788 (95% CI: 1.749-1.829; p < 0.00001) and 1.491 (95% CI: 1.451-1.532; p < 0.00001) for the association between BMI and TG with NAFLD incidence. The multivariate linear regression coefficient of BMI and TG was β = 0.027 (95% CI: 0.023-0.030; p < 0.00001). Mediation analysis showed that BMI contributed to 10.81% of lean NAFLD with a mediation effect of 2.98%.

CONCLUSION

In a Chinese population with BMI <24 kg/m2 and normal LDL-c levels, BMI and TG were found to be independent predictors of NAFLD. The direct effect of BMI on non-obese NAFLD was 10.41%. The TG level was found to partially mediate the association.

Gout in an Obese Patient with Nonalcoholic Steatohepatitis on a Thiazide Diuretic and Association Between Hyperuricemia and Nonalcoholic Steatohepatitis: A Case Report

Gout is a common inflammatory arthritis caused by increased uric acid crystals in and around various joints, mainly the big toe in adults. It happens due to the increase of urate or uric acid levels either because of increased production or decreased excretion from the body. Uric acid is the final product of purine metabolism, and many patients with hyperuricemia may remain asymptomatic. We present a case of a 46-year-old male who presented to the ambulatory care unit with the clinical features of acute pharyngitis and left toe pain for the past three days. On further questioning, he added that he had pain in the left lumber region and left side of the toe for the past few months. He also had a known case of type 2 diabetes mellitus, hypertension, and gastritis, for which he has been taking the thiazide diuretic, angiotensin-converting enzyme (ACE) inhibitors, metformin, sitagliptin, aspirin, and atorvastatin. Laboratory tests showed elevated uric acid along with raised inflammatory markers. As a result, he was referred to the specialist for arthrocentesis in order to confirm the diagnosis, and the thiazide diuretic was replaced with calcium channel blockers. He also suffered from nonalcoholic steatohepatitis (NASH) based on his ultrasound abdomen. On the follow-up visit, his symptoms had resolved, and his uric acid level had normalized.

Mechanistic insights of soluble uric acid-induced insulin resistance: Insulin signaling and beyond

Hyperuricemia is a metabolic disease caused by purine nucleotide metabolism disorder. The prevalence of hyperuricemia is increasing worldwide, with a growing trend in the younger populations. Although numerous studies have indicated that hyperuricemia may be an independent risk factor for insulin resistance, the causal relationship between the two is controversial. There are few reviews, however, focusing on the relationship between uric acid (UA) and insulin resistance from experimental studies. In this review, we summarized the experimental models related to soluble UA-induced insulin resistance in pancreas and peripheral tissues, including skeletal muscles, adipose tissue, liver, heart/cardiomyocytes, vascular endothelial cells and macrophages. In addition, we summarized the research advances about the key mechanism of UA-induced insulin resistance. Moreover, we attempt to identify novel targets for the treatment of hyperuricemia-related insulin resistance. Lastly, we hope that the present review will encourage further researches to solve the chicken-and-egg dilemma between UA and insulin resistance, and provide strategies for the pathogenesis and treatment of hyperuricemia related metabolic diseases.

The relationship between serum uric acid and colorectal cancer: a prospective cohort study

Serum uric acid (SUA) may play an important role in the occurrence of colorectal cancer (CRC). This study aims to explore the association of SUA with the risk of CRC incidence by drawing data from the Kailuan Study. We prospectively examined the association between SUA and risk of CRC incidence among 93,356 Chinese. Eligible participants were divided into three groups based on their tertiles of SUA. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of CRC. During a median follow-up of 13.02 years, 583 new-onset CRC cases were identified. After adjustments were made for confounders, participants in the highest tertiles of SUA exhibited a 1.55-fold increased risk of CRC compared with patients with the lowest SUA levels (HR_{T3 vs. T1} = 1.55, 95% CI: 1.09-2.30). The associations of SUA with the risk of CRC were slightly reduced but remained substantial in the competing risk analyses when treating CRC unrelated death as the competing risk event. This study found a positive association of SUA with CRC incidence. Specific prevention efforts could be focused on the population with higher levels of SUA.

Crosstalk between dietary patterns, obesity and nonalcoholic fatty liver disease

The prevalence of nonalcoholic fatty liver disease (NAFLD) is rising worldwide, paralleling the epidemic of obesity. The liver is a key organ for the metabolism of proteins, fats and carbohydrates. Various types of fats and carbohydrates in isocaloric diets differently influence fat accumulation in the liver parenchyma. Therefore, nutrition can manage hepatic and cardiometabolic complications of NAFLD. Even moderately reduced caloric intake, which leads to a weight loss of 5%-10% of initial body weight, is effective in improving liver steatosis and surrogate markers of liver disease status. Among dietary patterns, the Mediterranean diet mostly prevents the onset of NAFLD. Furthermore, this diet is also the most recommended for the treatment of NAFLD patients. However, clinical trials based on the dietary interventions in NAFLD patients are sparse. Since there are only a few studies examining dietary interventions in clinically advanced stages of NAFLD, such as active and fibrotic steatohepatitis, the optimal diet for patients in these stages of the disease must still be determined. In this narrative review, we aimed to critically summarize the associations between different dietary patterns, obesity and prevention/risk for NAFLD, to describe specific dietary interventions’ impacts on liver steatosis in adults with NAFLD and to provide an updated overview of dietary recommendations that clinicians potentially need to apply in their daily practice.

Clinical spectrum transition and prediction model of nonalcoholic fatty liver disease in children with obesity

OBJECTIVE

This study aims to outline the clinical characteristics of pediatric NAFLD, as well as establish and validate a prediction model for the disease.

MATERIALS AND METHODS

The retrospective study enrolled 3216 children with obesity from January 2003 to May 2021. They were divided into obese without NAFLD, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH) groups. Clinical data were retrieved, and gender and chronologic characteristics were compared between groups. Data from the training set (3036) were assessed using univariate analyses and stepwise multivariate logistic regression, by which a nomogram was developed to estimate the probability of NAFLD. Another 180 cases received additional liver hydrogen proton magnetic resonance spectroscopy (1H-MRS) as a validation set.

RESULTS

The prevalence of NAFLD was higher in males than in females and has increased over the last 19 years. In total, 1915 cases were NAFLD, and the peak onset age was 10-12 years old. Hyperuricemia ranked first in childhood NAFLD comorbidities, followed by dyslipidemia, hypertension, metabolic syndrome (MetS), and dysglycemia. The AUROC of the eight-parameter nomogram, including waist-to-height ratio (WHtR), hip circumference (HC), triglyceride glucose-waist circumference (TyG-WC), alanine aminotransferase (ALT), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1(ApoA1), insulin sensitivity index [ISI (composite)], and gender, for predicting NAFLD was 0.913 (sensitivity 80.70%, specificity 90.10%). Calibration curves demonstrated a great calibration ability of the model.

CONCLUSION AND RELEVANCE

NAFLD is the most common complication in children with obesity. The nomogram based on anthropometric and laboratory indicators performed well in predicting NAFLD. This can be used as a quick screening tool to assess pediatric NAFLD in children with obesity.

Associations of Uric Acid With Liver Steatosis and Fibrosis Applying Vibration Controlled Transient Elastography in the United States: A Nationwide Cross-Section Study

BACKGROUND AND OBJECTIVE

Serum uric acid (UA) is related to many metabolic diseases. However, the association of UA with liver diseases was not very clear. The objective of this study is to clarify the relationship of UA with liver steatosis and fibrosis.

METHODS

This is a cross-sectional study of 4364 people of National Health and Nutrition Examination Survey (NHANES) 2017-2018. Liver steatosis and fibrosis were assessed by controlled attenuation parameter (CAP) and liver stiffness measurements (LSM) using Vibration-controlled transient elastography (VCTE). Linear and logistic regressions were performed.

RESULTS

After adjusting for potential confounders, UA levels were associated with the prevalence of liver steatosis [OR=2.097 (95%CI: 1.245, 3.534)] and liver fibrosis [OR=2.983 (95%CI: 1.797, 4.952)]. Furthermore, the results were consistent in the subgroup analyses of males and females.

CONCLUSIONS

UA levels were positively associated with the prevalence of liver steatosis and fibrosis.

Muscle Fat Content Is Strongly Associated With Hyperuricemia: A Cross-Sectional Study in Chinese Adults

Studies have indicated that the skeletal muscle mass and strength was related to serum uric acid (UA), but there is a lack of research on the association of skeletal muscle fat content with UA. The purpose of this cross-sectional study is to investigate the correlation of skeletal muscle fat index (SMFI) and hyperuricemia (HUA) in Chinese adults. 500 subjects (306 men and 194 women) were included in the study. The participants were divided into four groups according to SMFI quartiles. Pearson's correlations between SMFI and metabolic variables were calculated. Logistic regression analysis was used to estimate the association between the quartiles of SMFI and risk of hyperuricemia. UA showed a positive association with SMFI after adjusted for BMI, age and gender. A significant association between the SMFI and risk of HUA was found, the OR for HUA was 2.79 (95% CI 1.18-6.59, p<0.05) in Q2, 2.41(95% CI 1.00-5.81, p<0.05) in Q3, and 2.63 (95% CI 1.03-6.72, p<0.05) in Q4, after adjusted for BMI. In conclusion, the SMFI was significantly associated with the level of serum UA, and the higher SMFI may indicate a higher risk of HUA, independent of BMI.