Sex-specific metabolic risk factors and their trajectories towards the non-alcoholic fatty liver disease incidence

Sex Hormone: A Potential Target at Treating Female Metabolic Dysfunction-Associated Steatotic Liver Disease?

The global prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is rising due to rapid lifestyle changes. Although females may be less prone to MASLD than males, specific studies on MASLD in females should still be conducted. Previous research has shown that sex hormone levels are strongly linked to MASLD in females. By reviewing a large number of experimental and clinical studies, we summarized the pathophysiological mechanisms of estrogen, androgen, sex hormone-binding globulin, follicle-stimulating hormone, and prolactin involved in the development of MASLD. We also analyzed the role of these hormones in female MASLD patients with polycystic ovarian syndrome or menopause, and explored the potential of targeting sex hormones for the treatment of MASLD. We hope this will provide a reference for further exploration of mechanisms and treatments for female MASLD from the perspective of sex hormones.

Remnant cholesterol trajectory and subclinical arteriosclerosis: a 10-year longitudinal study of Chinese adults

We aimed to identify different trajectories of remnant cholesterol (RC) and investigate the association of RC trajectories with vascular endothelial function and atherosclerosis progression in a longitudinal cohort of the Chinese population. A total of 521 participants were included in the flow-mediated vasodilation (FMD) subcohort study, and 7775 participants were included in the brachial-ankle pulse wave velocity (baPWV) subcohort study. All participants had ≥ 3 medical examinations during the 10-year follow-up period. In the FMD subcohort study, three distinct RC trajectories were identified according to the RC range and changing pattern over time: "low" (57.58%), "moderate" (30.90%) and "high" (11.52%). The proportion of the three groups with vascular endothelial dysfunction (FMD < 7.0%) was 20.00%, 39.75% and 60.00% respectively. Taking the low group as a reference, participants in the moderate and high groups had over 1.88 and 2.94 times the odds of vascular endothelial dysfunction (P = 0.048). In the baPWV subcohort study, three distinct RC trajectories were also identified: "low" (54.29%), "moderate" (38.97%) and "high" (6.74%). The proportion of the three groups with atherosclerosis (baPWV > 1400 cm/s) was 38.79%, 51.26% and 59.01% respectively. Taking the low group as a reference, participants in the moderate and high groups had over 1.46 and 2.16 times the odds of atherosclerosis (P < 0.001). The findings indicated that distinct RC trajectories are significantly associated with vascular endothelial function and atherosclerosis. Regular monitoring to identify persistent increases in RC may be more helpful in identifying individuals with a high risk of cardiovascular disease.

Exploring the interplay of gut microbiota, inflammation, and LDL-cholesterol: a multiomics Mendelian randomization analysis of their causal relationship in acute pancreatitis and non-alcoholic fatty liver disease

BACKGROUND

Acute pancreatitis and non-alcoholic fatty liver disease are both serious diseases in the digestive system. The pathogenesis of both diseases is extremely complex closely and it related to gut microbiota, inflammation, and blood fat. There is a close relationship between gut microbiota and blood lipids.

METHODS

In this study, we used three types of exposure: 412 gut microbiota, 731 inflammatory cells, and 91 inflammatory proteins (pqtls), with LDL-C as an intermediary and acute pancreatitis and non-alcoholic fatty liver disease as outcomes. We mainly used MR-IVW, co-localization analysis, and reverse MR analysis methods for analysis.

RESULTS

7 gut microbiota, 21 inflammatory cells, and 3 inflammatory proteins can affect LDL-C levels. LDL-C is associated with acute pancreatitis and non-alcoholic fatty liver disease.

CONCLUSIONS

Three omics were used: 412 gut microbiota, 731 inflammatory cells, and 91 inflammatory proteins (pqtls). It explains the causal relationship between multiomics, LDL- cholesterol, acute pancreatitis, and non-alcoholic fatty liver disease.

Bidirectional relationship between nonalcoholic fatty liver disease and serum creatinine-to-body weight ratio as a proxy for skeletal muscle mass index

BACKGROUND AND AIM

Although an association between skeletal muscle mass index and nonalcoholic fatty liver disease (NAFLD) has previously been demonstrated, the causal direction remains unclear. Herein, we investigated the directional association between NAFLD and the serum creatinine-to-body weight ratio (sCr/bw), a surrogate marker of the muscle mass index, using longitudinal data.

METHODS

We recruited 9662 participants in 2017 and performed follow-up over 4 years. We evaluated whether sCr/bw was related to NAFLD development (Analysis I) and whether NAFLD was associated with a low sCr/bw incidence (Analysis II) using logistic regression models. Furthermore, a random intercept cross-lagged panel model was applied to evaluate the bidirectional association between sCr/bw ratio and NAFLD (Analysis III).

RESULTS

Analysis I demonstrated an association between sCr/bw and incident NAFLD (odds ratio [OR] = 0.160, 95% confidence interval [CI]:0.107-0.232). Analysis II indicated a relationship between NAFLD and subsequent low sCr/bw ratio (OR = 1.524, 95% CI: 1.258-1.846). Analysis III indicated that the standard regression coefficient from sCr/bw to subsequent hepatic steatosis (HS) was -0.053 for βsCr/bw2017 → HS2019 and -0.060 for βsCr/bw2019 → HS2021 and the coefficient from HS to subsequent sCr/bw was -0.093 for βHS2017 → sCr/bw2019 and -0.112 for βHS2019 → sCr/bw2021 (all P < 0.05).

CONCLUSIONS

This study indicated mutual causality between sCr/bw and NAFLD. Considering that sCr/bw is a surrogate marker of muscle mass index, the findings emphasize that NAFLD and low muscle mass form a vicious cycle, which should be taken seriously in clinical practice.

Shift in prevalence and systemic inflammation levels from NAFLD to MAFLD: a population-based cross-sectional study

BACKGROUND

Variations in the prevalence and systemic inflammatory (SI) status between non-alcoholic fatty liver disease (NAFLD) and newly defined metabolic dysfunction-associated fatty liver disease (MAFLD) have only been reported by few studies. Hence, this study aimed to compile data on the prevalence and the systemic inflammation levels of MAFLD and NAFLD in a general population from Southeast China was summarized to explore the potential effect of the transformation of disease definition.

METHODS

A total of 6718 general population participants aged 35-75 were enrolled. Logistic regression and restricted cubic spline (RCS) models were used to examine the relationship between 15 SI indicators and NAFLD and MAFLD. The predicted values of MAFLD and NAFLD were analyzed using the receiver operating characteristic (ROC) curve.

RESULTS

The prevalence of MAFLD and NAFLD was 34.7% and 32.4%, respectively. Their overlapping rate was 89.7%, while only 8.3% and 1.9% of participants were MAFLD-only and NAFLD-only. Among three FLD groups, the MAFLD-only group had the highest levels of 8 SI indicators, including CRP, WBC, LYMPH, NEUT, MONO, ALB, NLR, and SIRI. The non-FLD group had the lower levels of all 15 SI indicators compared with all FLD subgroups. The odds ratios (ORs) of 10 SI indicators were significant in both multivariable-adjusted logistic regression and RCS analyses of MAFLD or NAFLD, including CRP, WBC, LYMPH, NEUT, MONO, ALB, PLR, LMR, ALI and CA. ROC analysis showed that the AUC values of all SI were lower than 0.7 in both MAFLD and NAFLD.

CONCLUSIONS

MAFLD could cover more FLD than NAFLD, and the MAFLD-only group had a more severe inflammation status, whereas the NAFLD-only exhibited lower levels. Moreover, there was not a high AUC and a high sensitivity of SI indicators, suggesting that SI indicators are not good indicators to diagnose NAFLD/MAFLD.

Impact renaming non-alcoholic fatty liver disease to metabolic associated fatty liver disease in prevalence, characteristics and risk factors

BACKGROUND

Recently, a group of hepatologists proposed to rename non-alcoholic fatty liver disease (NAFLD) as metabolic associated fatty liver disease (MAFLD) with modified diagnostic criteria. It is important to note, however, that there are some differences between the diagnostic criteria used for NAFLD and MAFLD. Since the research on MAFLD is just beginning, however, evidence on its incidence and prevalence in the general population and in specific subpopulations remains limited.

AIM

To assess epidemiology of fatty liver in new definition and compare MAFLD with NAFLD. Exploring risk factors of MAFLD individuals.

METHODS

This was a retrospective, cross-sectional study. A total of 85242 adults were selected from the Chinese health management database in 2017-2022. The data of general information, laboratory indicators, lifestyle management and psychological status were obtained. MAFLD was diagnosed as ultrasound diagnosis of fatty liver and at least one between these three conditions: Overweight/obesity, type 2 diabetes mellitus (T2DM) or metabolic dysregulation. Metabolic factors were not considered in NAFLD diagnosis standard. The clinical characteristics of MAFLD and NAFLD were analysed using descriptive statistics. Continuous variables normally distributed were expressed as means ± SD. Categorical variables were expressed as frequencies and proportions. Binary logistic regression was used to determine risk factors of the MAFLD.

RESULTS

The prevalence of MAFLD and NAFLD was 40.5% and 31.0%, respectively. The MAFLD or NAFLD population is more likely to be older (M: 47.19 ± 10.82 vs 43.43 ± 11.96; N: 47.72 ± 11.17 vs 43.71 ± 11.66), male (M: 77.21% vs 44.43%; N: 67.90% vs 53.12%) and high body mass index (M: 26.79 ± 2.69 vs 22.44 ± 2.48; N: 26.29 ± 2.84 vs 23.29 ± 3.12) than the non-MAFLD or non-MAFLD population. In multivariate analysis, general information (e.g., ≥ 2 metabolic abnormalities OR = 3.38, (95%CI: 2.99-3.81), P < 0.001; diastolic blood pressure OR = 1.01, (95%CI: 1.00-1.01), P = 0.002), laboratory results [e.g.,total bilirubin (TBIL) OR = 0.98, (95%CI: 0.98-0.99), P < 0.001; serum uric acid(SUA) OR = 1.01, (95%CI: 1.01-1.01), P < 0.001], and lifestyle factors [e.g., drink beverage OR = 0.32, (95%CI: 0.17-0.63), P = 0.001] were influence factors for MAFLD. Our study results offer new insight into potential risk factors associated with fatty liver disease, including SUA, TBIL and creatinine, all of which are related to chronic renal disease (CKD).

CONCLUSION

MAFLD is more prevalent than NAFLD, with two-fifths of individuals meeting the diagnosis criteria. MAFLD and NAFLD populations have different clinical characteristics. CKD may be related with MAFLD.