Clinical and Laboratory Characteristics of Normal Weight and Obese Individuals with Non-Alcoholic Fatty Liver Disease

Update in lean metabolic dysfunction-associated steatotic liver disease

BACKGROUND

A new nomenclature consensus has emerged for liver diseases that were previously known as non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD). They are now defined as metabolic dysfunction-associated steatotic liver disease (MASLD), which includes cardiometabolic criteria in adults. This condition, extensively studied in obese or overweight patients, constitutes around 30% of the population, with a steady increase worldwide. Lean patients account for approximately 10%-15% of the MASLD population. However, the pathogenesis is complex and is not well understood.

AIM

To systematically review the literature on the diagnosis, pathogenesis, characteristics, and prognosis in lean MASLD patients and provide an interpretation of these new criteria.

METHODS

We conducted a comprehensive database search on PubMed and Google Scholar between January 2012 and September 2023, specifically focusing on lean NAFLD, MAFLD, or MASLD patients. We include original articles with patients aged 18 years or older, with a lean body mass index categorized according to the World Health Organization criteria, using a cutoff of 25 kg/m2 for the general population and 23 kg/m2 for the Asian population.

RESULTS

We include 85 studies in our analysis. Our findings revealed that, for lean NAFLD patients, the prevalence rate varied widely, ranging from 3.8% to 34.1%. The precise pathogenesis mechanism remained elusive, with associations found in genetic variants, epigenetic modifications, and adaptative metabolic response. Common risk factors included metabolic syndrome, hypertension, and type 2 diabetes mellitus, but their prevalence varied based on the comparison group involving lean patients. Regarding non-invasive tools, Fibrosis-4 index outperformed the NAFLD fibrosis score in lean patients. Lifestyle modifications aided in reducing hepatic steatosis and improving cardiometabolic profiles, with some medications showing efficacy to a lesser extent. However, lean NAFLD patients exhibited a worse prognosis compared to the obese or overweight counterpart.

CONCLUSION

MASLD is a complex disease comprising epigenetic, genetic, and metabolic factors in its pathogenesis. Results vary across populations, gender, and age. Limited data exists on clinical practice guidelines for lean patients. Future studies employing this new nomenclature can contribute to standardizing and generalizing results among lean patients with steatotic liver disease.

Global epidemiology of type 2 diabetes in patients with NAFLD or MAFLD: a systematic review and meta-analysis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) and metabolic-associated fatty liver disease (MAFLD) shares common pathophysiological mechanisms with type 2 diabetes, making them significant risk factors for type 2 diabetes. The present study aimed to assess the epidemiological feature of type 2 diabetes in patients with NAFLD or MAFLD at global levels.

METHODS

Published studies were searched for terms that included type 2 diabetes, and NAFLD or MAFLD using PubMed, EMBASE, MEDLINE, and Web of Science databases from their inception to December 2022. The pooled global and regional prevalence and incidence density of type 2 diabetes in patients with NAFLD or MAFLD were evaluated using random-effects meta-analysis. Potential sources of heterogeneity were investigated using stratified meta-analysis and meta-regression.

RESULTS

A total of 395 studies (6,878,568 participants with NAFLD; 1,172,637 participants with MAFLD) from 40 countries or areas were included in the meta-analysis. The pooled prevalence of type 2 diabetes among NAFLD or MAFLD patients was 28.3% (95% confidence interval 25.2-31.6%) and 26.2% (23.9-28.6%) globally. The incidence density of type 2 diabetes in NAFLD or MAFLD patients was 24.6 per 1000-person year (20.7 to 29.2) and 26.9 per 1000-person year (7.3 to 44.4), respectively.

CONCLUSIONS

The present study describes the global prevalence and incidence of type 2 diabetes in patients with NAFLD or MAFLD. The study findings serve as a valuable resource to assess the global clinical and economic impact of type 2 diabetes in patients with NAFLD or MAFLD.

Metabolic dysfunction and nonalcoholic fatty liver disease risk in individuals with a normal body mass index

PURPOSE OF REVIEW

Nonalcoholic fatty liver disease (NAFLD) is strongly associated with obesity, but is also common in individuals with a normal body mass index (BMI), who also experience the hepatic inflammation, fibrosis, and decompensated cirrhosis associated with NAFLD progression. The clinical evaluation and treatment of NAFLD in this patient population are challenging for the gastroenterologist. A better understanding of the epidemiology, natural history, and outcomes of NAFLD in individuals with normal BMI is emerging. This review examines the relationship between metabolic dysfunction and clinical characteristics associated with NAFLD in normal-weight individuals.

RECENT FINDINGS

Despite a more favorable metabolic profile, normal-weight NAFLD patients exhibit metabolic dysfunction. Visceral adiposity may be a critical risk factor for NAFLD in normal-weight individuals, and waist circumference may be better than BMI for assessing metabolic risk in these patients. Although screening for NAFLD is not presently recommended, recent guidelines may assist clinicians in the diagnosis, staging, and management of NAFLD in individuals with a normal BMI.

SUMMARY

Individuals with a normal BMI likely develop NAFLD as a result of different etiologies. Subclinical metabolic dysfunction may be a key component of NAFLD in these patients, and efforts to better understand this relationship in this patient population are needed.

Comparison of Machine Learning Models and the Fatty Liver Index in Predicting Lean Fatty Liver

The reported prevalence of non-alcoholic fatty liver disease in studies of lean individuals ranges from 7.6% to 19.3%. The aim of the study was to develop machine-learning models for the prediction of fatty liver disease in lean individuals. The present retrospective study included 12,191 lean subjects with a body mass index < 23 kg/m² who had undergone a health checkup from January 2009 to January 2019. Participants were divided into a training (70%, 8533 subjects) and a testing group (30%, 3568 subjects). A total of 27 clinical features were analyzed, except for medical history and history of alcohol or tobacco consumption. Among the 12,191 lean individuals included in the present study, 741 (6.1%) had fatty liver. The machine learning model comprising a two-class neural network using 10 features had the highest area under the receiver operating characteristic curve (AUROC) value (0.885) among all other algorithms. When applied to the testing group, we found the two-class neural network exhibited a slightly higher AUROC value for predicting fatty liver (0.868, 0.841-0.894) compared to the fatty liver index (FLI; 0.852, 0.824-0.81). In conclusion, the two-class neural network had greater predictive value for fatty liver than the FLI in lean individuals.

Non-Alcoholic Fatty Liver Disease or Type 2 Diabetes Mellitus—The Chicken or the Egg Dilemma

In clinical practice, we often deal with patients who suffer from non-alcoholic fatty liver disease (NAFLD) concurrent with type 2 diabetes mellitus (T2DM). The etiopathogenesis of NAFLD is mainly connected with insulin resistance (IR) and obesity. Similarly, the latter patients are in the process of developing T2DM. However, the mechanisms of NAFLD and T2DM coexistence have not been fully elucidated. Considering that both diseases and their complications are of epidemic proportions and significantly affect the length and quality of life, we aimed to answer which of these diseases appears first and thereby highlight the need for their diagnosis and treatment. To address this question, we present and discuss the epidemiological data, diagnoses, complications and pathomechanisms of these two coexisting metabolic diseases. This question is difficult to answer due to the lack of a uniform procedure for NAFLD diagnosis and the asymptomatic nature of both diseases, especially at their beginning stages. To conclude, most researchers suggest that NAFLD appears as the first disease and starts the sequence of circumstances leading ultimately to the development of T2DM. However, there are also data suggesting that T2DM develops before NAFLD. Despite the fact that we cannot definitively answer this question, it is very important to bring the attention of clinicians and researchers to the coexistence of NAFLD and T2DM in order to prevent their consequences.

Evaluation of ABCA1 gene polymorphism as a prognostic index of fibrosis progression in NAFLD patients

INTRODUCTION

It had been evident that non-alcoholic fatty liver disease (NAFLD) is the new era epidemic. Despite emergence of many drugs on the pipeline that considered candidates to cure NAFLD/NASH, the critical need for defining the cohort liable to fibrosis progression is yet unmet.

AIM

Evaluate ABCA1 (rs1800977) genotyping as a noninvasive predictor of liver fibrosis severity.

MATERIALS AND METHODS

This study included 118 liver biopsy-proven NAFLD-patients. According to Metavir-fibrosis-staging, cases were divided to early fibrosis (74 cases), and 44 cases with significant fibrosis (>F2), added to 49 healthy control subjects. All patients were subjected to liver function tests, lipids profile, triglyceride TG index, and hepatic steatosis index (HSI) and real-time PCR ABCA1 SNP (rs1800977).

RESULTS

Significant differences in transaminases (p > .05), albumin (p < .009), cholesterol (p0.03), low density lipoproteins (LDL) (0.006), triglycerides (p < .001), HSI (p < .001), FIB4 (p < .001) and APRI (p < .001) were reported in those with significant than early fibrosis and control groups. CC was the most prevalent in significant (36.4%) than early fibrosis (13.5%) and control groups (8.2%), with prevalence of C allele in significant fibrosis (p ≤ .003). Univariate analysis revealed that DM (p ≤ .001), TG index (p ≤ .022), cholesterol (p ≤ .03), HSI (p ≤ .006), LDL (p ≤ .02), HDL (p ≤ .01), APRI (p ≤ .02) and CC genotype (p ≤ .005) were the main factors affecting fibrosis progression in NAFLD. However multivariate analysis proved only the role of HSI (p ≤ .005), LDL (p ≤ .02), HDL (p ≤ .003) and CC genotype (p ≤ .03) in predicting fibrosis severity.

CONCLUSION

Dyslipidemias, hepatic steatosis index and ABCA1 (rs1800977) gene polymorphism CC genotype; were the only independent predictors of advanced fibrosis in NAFLD-patients.