Risk factors of nonalcoholic fatty liver disease in lean body mass population: A systematic review and meta-analysis

Metabolic dysfunction-associated steatotic liver disease is associated with worse time in ranges in type 1 diabetes

AIM

To investigate the relationship between continuous glucose monitoring (CGM)-derived glucometrics and metabolic dysfunction-associated steatotic liver disease (MASLD) in type 1 diabetes (T1D).

METHODS

A cross-sectional study collecting data on anthropometrics, glucometrics and MASLD in adults with T1D using a CGM device was conducted. MASLD was assessed by abdominal ultrasound and the presence of at least one cardiometabolic criterion. Backward multivariable logistic regression models were applied to define variables independently associated with MASLD.

RESULTS

A total of 302 consecutive participants were included (median age 49 [34-61] years, male sex 58%, median diabetes duration 29 [17-38] years, mean time in range [TIR] 55% ± 16%). MASLD was present in 17% of cases, and 32% had metabolic syndrome (MetS). MetS was significantly more prevalent in the MASLD group (65% vs. 25%, P < .0001). TIR (P = .038) and time below range (TBR) (P = .032) were lower and time above range (TAR) was higher (P = .006), whereas HbA1c did not reach significance (P = .068). No differences were found for the glycaemia risk index. TIR (P = .028), TAR (P = .007), TBR (P = .036), waist circumference (P < .001) and systolic blood pressure (P = .029) were independently associated with MASLD, while sex, age, aspartate aminotransferase/alanine aminotransferase ratio, gamma-glutamyl transferase, high-density lipoprotein cholesterol and triglycerides were not.

CONCLUSIONS

TIR, TAR, TBR, waist circumference and systolic blood pressure were independently associated with MASLD.

Cardiovascular morbidity and mortality in lean vs. non-lean MASLD: A comprehensive meta-analysis

BACKGROUND

Lean metabolic dysfunction-associated steatotic liver disease (MASLD), characterized by a BMI < 25 kg/m² (or < 23 kg/m² in Asians), presents a challenging prognosis compared to non-lean MASLD. This study examines cardiovascular outcomes in both lean and non-lean MASLD cohorts.

METHODS

In this meta-analysis, pooled odds ratios (ORs) within 95 % confidence intervals (CIs) were calculated for primary outcomes (cardiovascular mortality and major adverse cardiovascular events [MACE]) and secondary outcomes (cardiovascular disease [CVD], all-cause mortality, hypertension, and dyslipidemia). Studies comparing lean and non-lean MASLD within the same cohorts were analyzed, prioritizing those with larger sample sizes or recent publication dates.

RESULTS

Twenty-one studies were identified, encompassing lean MASLD patients (n = 7153; mean age 52.9 ± 7.4; 56 % male) and non-lean MASLD patients (n = 23,514; mean age 53.2 ± 6.8; 63 % male). Lean MASLD exhibited a 50 % increase in cardiovascular mortality odds compared to non-lean MASLD (OR: 1.5, 95 % CI 1.2-1.8; p < 0.0001). MACE odds were 10 % lower in lean MASLD (OR: 0.9, 95 % CI 0.7-1.2; p = 0.7), while CVD odds were 40 % lower (p = 0.01). All-cause mortality showed a 40 % higher odds in lean MASLD versus non-lean MASLD (p = 0.06). Lean MASLD had 30 % lower odds for both hypertension (p = 0.01) and dyslipidemia (p = 0.02) compared to non-lean MASLD.

CONCLUSION

Despite a favorable cardiometabolic profile and comparable MACE rates, lean individuals with MASLD face elevated cardiovascular mortality risk.

Evaluation of risk factors for non-alcoholic fatty liver disease in India: A systematic review and meta-analysis

INTRODUCTION

NAFLD is emerging as an important cause of liver disease in India. It is estimated that 16-32% of general population in India (nearly 120 million) has NAFLD.

OBJECTIVE

This study aimed to identify the risk factors of NAFLD and to identify the association of lifestyle (dietary and physical activity), genetic, and environmental factors with NAFLD in India.

MATERIALS AND METHODS

A systematic literature search was conducted using an international electronic database: PubMed (MEDLINE) and Google Scholar from the date of inception 31st March 2021 to 28th September 2021. We included studies examining patients with NAFLD: Adults above 18 years of age. Studies with or without a control population were both eligible. The studies with a diagnosis of NAFLD based solely on abnormal liver tests were excluded. We tried to get unpublished data but they were not of the quality of inclusion. Meta-analysis was performed using the software STATA 14.2 (StataCorp, College Station, TX, USA). For each of the studies, the standard error was calculated using the reported number of outcomes and the sample size. A forest plot was used to graphically represent the study-specific and pooled prevalence estimates for overall and subgroup analysis.

RESULTS

In a systematic review and meta-analysis of 8 studies including data from over 1800 individuals, we found that among components of lipid profile, LDL and HDL had a negative effects on NAFLD while triglycerides had a positive effect on NAFLD.

CONCLUSION

Type 2 Diabetes Mellitus, Hypertension, and Obesity were the potential risk factors for NAFLD but the evidence generated was only from single studies.

Lean Indian patients with non-alcoholic fatty liver disease (NAFLD) have less metabolic risk factors but similar liver disease severity as non-lean patients with NAFLD

INTRODUCTION

Although most patients with NAFLD are obese or overweight, some are lean with normal BMI. Our aim was to assess differences in clinicopathological profile and liver disease severity among lean and non-lean NAFLD.

METHODS

Data of 1040 NAFLD patients over last 10 years was analysed. BMI < 23 kg/m2 categorised lean patients. Non-invasive assessment of steatosis was done by ultrasound and controlled attenuation parameter (CAP) while fibrosis was assessed with FIB-4 and liver stiffness measurement (LSM). FibroScan-AST (FAST) score was used for non-invasive prediction of NASH with significant fibrosis. Histology was reported using NASH-CRN system.

RESULTS

149 (14.3%) patients were lean while 891 (85.7%) patients were non-lean. Diabetes mellitus [25 (16.7%) vs 152 (17.05%), p > 0.99], elevated triglycerides [81 (54.3%) vs 525 (58.9%), p = 0.33] and low HDL [71(47.6%) vs 479(53.7%), p = 0.18] were observed in a similar proportion. Lean patients were less likely to have central obesity [72 (48.3%) vs 788 (88.4%), p < 0.001], hypertension [16 (10.7%) vs 239(26.8%), p < 0.001] and metabolic syndrome [21 (14.09%) vs 290 (32.5%), p < 0.001]. No difference in steatosis assessment was noted using ultrasound (p = 0.55) or CAP (0.11). FAST [0.38 (0.18-0.66) vs 0.39 (0.27-0.73), p = 0.53], FIB-4 [1.08 (0.65-1.91) vs 1.09 (0.66-1.94), p = 0.94] and LSM [6.1 (4.8-7.9) vs 6.2 (4.7-8.6), p = 0.19) were similar. Liver biopsy was available in 149 patients [lean: 19 (12.7%), non-lean: 130 (87.3%)]. There was no difference in the number of patients with NASH [4 (21.05%) vs 20 (15.3%), p = 0.51], significant fibrosis [2 (10.5%) vs 32 (24.6%), p = 0.25] or advanced fibrosis [1 (5.26%) vs 18 (13.84%), p = 0.47].

CONCLUSION

Although metabolic co-morbidities are less common, there is no difference in liver disease severity among both groups.

Metabolic characteristics of non-obese and obese metabolic dysfunction-associated fatty liver disease in type 2 diabetes mellitus and its association with diabetic peripheral neuropathy and diabetic retinopathy

Aim

To assess the metabolic characteristics of non-obese metabolic dysfunction-associated fatty liver disease (MAFLD) compared with obese MAFLD and the relationship of MAFLD with diabetic peripheral neuropathy and diabetic retinopathy in patients with Type 2 diabetes mellitus (T2DM).

Methods

Data were obtained from 536 T2DM patients (355 women, 181 men; age 58.2 ± 12.0 years). We explored the difference in clinical characteristics between obese MAFLD (body mass index ≥25 kg/m2) and non-obese MAFLD (body mass index <25 kg/m2) in T2DM patients. One-way analysis of variance (ANOVA) was used to compare the means of continuous variables, and the Chi-squared test was used to compare the differences in frequencies of categorical variables. Logistic regression models were adopted to calculate odds ratios.

Results

The prevalence of MAFLD in hospitalized Chinese T2DM patients was calculated to be 42.7%. Both obese and non-obese MAFLD patients had higher levels of body mass index (BMI), waist circumfere nce, triglyceride, alanine aminotransferase, aspar tate aminotransferase, γ-glutamyltransferase, you nger age, higher prevalence of hyperlipidemia and shorter duration of T2DM and lower incidence of diabetic retinopathy, compared with participants with out MAFLD in the same weight group. Uric acid levels were positively correlated with the risk of MAFLD only in non-obese subjects but not in obese subjects. In non-obese patients with T2DM, a negative correlation was found between the prevalence of MAFLD and diabetic retinopathy.

Conclusion

Even in non-obese patients with T2DM, BMI was found to be an independent risk factor for MAFLD. These findings support a more structured, risk-factor-based approach to MAFLD management, particularly in patients with T2DM. Non-obese MAFLD has unique results in metabolic characteristics and the correlation with diabetic retinopathy and diabetic peripheral neuropathy, which should be further explored.

Lean nonalcoholic fatty liver disease: Age-dependent differences in pathology, prognosis, and liver-related events

AIM

This study aimed to evaluate the age-specific characteristics, prognosis, and complications of patients with lean nonalcoholic fatty liver disease (NAFLD).

METHODS

Background factors (age, sex, diabetes, dyslipidemia, hypertension, and PNPLA3 gene polymorphism), blood test results, liver histology findings, muscle mass, and grip strength were investigated in 782 patients with NAFLD who underwent liver biopsy. Prognosis and complications were compared among 549 patients with nonlean or lean NAFLD who were followed up for 6.5 years. Additionally, background factors, blood test results, liver histology findings, prognosis, and complications were compared according to age (≥60 years vs. <60 years) in patients with lean NAFLD.

RESULTS

Lean NAFLD patients showed lower aspartate aminotransferase, alanine aminotransferase, homeostasis model assessment-insulin resistance, high-sensitivity C-reactive protein, ferritin, and leptin but higher adiponectin and hemoglobin A1c (HbA1c) levels than patients with nonlean NAFLD. Furthermore, lean NAFLD patients showed less liver fibrosis, inflammation, steatosis, and ballooning. Among lean NAFLD patients, those aged 60 years and older were more frequently female, showed higher rates of hypertension, diabetes, and dyslipidemia, had higher HbA1c and type IV collagen 7S levels, lower platelet count, higher liver fibrosis and inflammation grades, and lower muscle mass and grip strength. Lean NAFLD was associated with a worse prognosis in patients aged 60 years and over than in those younger than 60 years of age and with a higher incidence of liver-related disease, cerebrocardiovascular events, and nonliver cancer.

CONCLUSIONS

Age is an important consideration in patients with lean NAFLD. Compared with nonlean NAFLD, lean NAFLD was associated with a worse prognosis and higher risk of complications in patients aged 60 years and older.

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.

Prevalence, characteristics, and mortality outcomes of obese and nonobese MAFLD in the United States

BACKGROUND AND AIMS

Metabolic dysfunction-associated fatty liver disease (MAFLD) establishes new criteria for diagnosis of fatty liver disease independent of alcohol intake. We aimed to describe the prevalence and compare characteristics and mortality outcomes of persons with nonobese and obese MAFLD.

METHODS

Using data from 13,640 participants from the third National Health and Nutrition Examination Survey (NHANES III) 1988-1994, we identified participants with fatty liver on ultrasound who had MAFLD and analyzed them by the presence of obesity.

RESULTS

Overall prevalence of MAFLD was 19%; amongst those, 54% were obese and 46% were nonobese. Nonobese MAFLD was more common in participants older than 65 than in younger participants (56.8% vs. 43.2%, p < 0.0001). Nonobese MAFLD was more common in males (63.2% vs. 48.3%, p < 0.0001). Obese MAFLD was more common in females (51.7% vs. 48.3%, p < 0.0001). After adjusting for several demographic factors and alcohol use, older age [adjusted odds ratio (aOR) 1.02, 95% CI 1.00-1.02, p = 0.003] and being male (aOR: 1.65, 95% CI 1.25-2.17, p = 0.001) were independent risk factors for nonobese MAFLD. Nonobese MAFLD participants had a higher 20-year cumulative incidence for all-cause mortality compared to obese MAFLD participants (33.2% vs. 28.8%, p = 0.0137). However, nonobese MAFLD was not independently associated with mortality after adjusting for relevant confounders, while FIB-4 > 1.3 and cardiovascular disease were the strongest risk factors associated with increased mortality [adjusted hazard ratio (aHR)  > 2.7 for both, p < 0.0001 for both].

CONCLUSIONS

Nonobese MAFLD constitutes about half of the MAFLD in the United States, especially among males and the elderly. Notably, nonobese MAFLD carries higher mortality than obese MAFLD. Screening and diagnosis of MAFLD should be considered in nonobese populations.

Unique genetic variants of lean nonalcoholic fatty liver disease: a retrospective cohort study

We investigated the prevalence and clinical metabolic characteristics of lean nonalcoholic fatty liver disease (NAFLD) in an elderly Chinese population and assessed the relevance of lipid markers and genetic variation. All 5,338 community subjects underwent detailed clinical and laboratory examinations and were divided into three groups: lean (Body mass index (BMI) < 23 kg/m², n = 2,012), overweight (BMI = 23-24.9 kg/m², n = 1,354), and obese (BMI ≥ 25 kg/m², n = 1,972). Single nucleotide polymorphisms were selected based on those reported in previous NAFLD or obesity genome-wide association studies. The frequencies of alleles and genotypes were calculated and statistically analyzed with Pearson's χ² tests. One-way ANCOVA was used to test the association between positive SNPs and metabolic parameters in lean NAFLD individuals. Our results showed that the C allele frequency of rs2279026, the G allele of rs2279028, the C allele of rs780093, and the C allele frequency of rs1260326 were higher in obese NAFLD than in lean NAFLD (P < 0.05). In addition, we observed an association between the CC of rs1421085, TT of rs3751812, AA of rs8050136, and AA of rs9939609 genotypes in the FTO gene and low-density lipoprotein levels (P < 0.05). In conclusion, our findings provide a unique perspective on the prevalence, genetic characteristics, and metabolic profile of NAFLD in older lean individuals in China. This is the first study to examine the association between genetic variants in the FTO, TFAP2B and GCKR genes and NAFLD in a cohort of lean individuals.

Impact on Prevalence of the Application of NAFLD/MAFLD Criteria in Overweight and Normal Weight Patients

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is considered the hepatic manifestation of metabolic syndrome. Recently, the term metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed and adapted to body mass index (BMI). This study describes the impact on prevalence of the application of both criteria in overweight and lean patients.

METHODS

Patients who were evaluated for liver steatosis by transient elastography were included and divided according to BMI (≥25 kg/m² and <25 kg/m²) and classified as NAFLD or MAFLD, according to metabolic abnormalities. Differences in prevalence were evaluated applying both criteria. A multivariate analysis was performed to evaluate independent associations of metabolic abnormalities and liver steatosis in lean patients.

RESULTS

3847 patients were included. In overweight patients (61%), the prevalence NAFLD was 63.6% and 65.3% for MAFLD (p = 0.22). In contrast, the prevalence of MAFLD was lower (7.9% vs. 18.3%, p ≤ 0.001) in lean patients. In this group, higher age, fasting glucose, triglycerides, and waist circumference showed independent association with liver steatosis.

CONCLUSION

The application of NAFLD/MAFLD criteria did not show prevalence differences in overweight patients. With MAFLD criteria, the prevalence is lower in lean patients, but patients with high risk of progression of liver disease for steatosis were identified, according to their metabolic abnormalities.

Clinical Differences and Non-Alcoholic Fatty Liver Disease-Related Factors of Lean and Non-Lean Patients with Metabolic Syndrome

This study investigated differences in the clinical data and prevalence of lean and non-lean patients with non-alcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS). Data on patients with MetS who had results of ultrasonography or transient elastography were collected from a Thai university hospital database. Patients with exclusion criteria for NAFLD diagnosis were excluded. Patients’ clinical characteristic and the performances of three non-invasive scoring systems (fatty liver index [FLI], fibrosis-4 [FIB-4] index, and NAFLD fibrosis score [NFS]) were evaluated. The 743 subjects were classified into two groups: lean MetS (131 patients) and non-lean MetS (612 patients). The NAFLD prevalence in the non-lean group (62.6%) was higher than that in the lean group (31.3%). The age-adjusted odds ratio was 3.43. Advanced fibrosis was detected in 7.6% of lean patients and 10.8% of non-lean patients. FLI was not sensitive enough to detect NAFLD in the lean group at a high cutoff, but it performed acceptably at a low cutoff. FIB-4 performed better than NFS in determining advanced fibrosis. NAFLD was more common in non-lean than lean patients. Lean patients with MetS had a relatively higher risk of NAFLD than the general population. FLI and FIB-4 index performed acceptably in both groups.

NAFLD in normal weight individuals

Nonalcoholic fatty liver disease (NAFLD) can develop in lean individuals. Despite a better metabolic profile, the risk of disease progression to hepatic inflammation, fibrosis, and decompensated cirrhosis in the lean is similar to that in obesity-related NAFLD and lean individuals may experience more severe hepatic consequences and higher mortality relative to those with a higher body mass index (BMI). In the absence of early symptoms and abnormal laboratory findings, lean individuals are not likely to be screened for NAFLD or related comorbidities; however, given the progressive nature of the disease and the increased risk of morbidity and mortality, a clearer understanding of the natural history of NAFLD in lean individuals, as well as efforts to raise awareness of the potential health risks of NAFLD in lean individuals, are warranted. In this review, we summarize available data on NAFLD prevalence, clinical characteristics, outcomes, and mortality in lean individuals and discuss factors that may contribute to the development of NAFLD in this population, including links between dietary and genetic factors, menopausal status, and ethnicity. We also highlight the need for greater representation of lean individuals in NAFLD-related clinical trials, as well as more studies to better characterize lean NAFLD, develop improved screening algorithms, and determine specific treatment strategies based on underlying etiology.