瘦肉型和非瘦肉型非酒精性脂肪肝的临床特征：一项横断面研究

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2025-05-12 DOI:10.1186/s12986-025-00927-y

Mengyan Xu, Rui Gong, Jiao Xie, Sanping Xu, Shi Wang

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引用次数: 0

摘要

简介：非酒精性脂肪性肝病（NAFLD）影响着全球四分之一以上的人口，已成为世界头号慢性肝病，严重危害着公众的生命和健康。尽管提出了代谢功能障碍相关脂肪性肝病（MASLD）的新术语，但非酒精性脂肪性肝病（NAFLD） BMI分层异质性的机制仍不清楚。本研究的目的是揭示亚洲人群中瘦（BMI 2）和非瘦NAFLD之间代谢和纤维化特征的差异。方法：本研究从体检人群中收集NAFLD患者。将患者按BMI分为两组，比较其临床参数，包括瘦（BMI 2）和非瘦（BMI≥23 kg/m2）和纤维化亚组（LSM阈值= 8 kPa），并通过logistic回归模型分析危险因素。结果：参与研究的11,577名NAFLD患者中，有916名瘦患者和10,661名非瘦患者。非瘦组比瘦组更年轻（中位年龄50岁vs. 52岁）。结论：非瘦NAFLD患者表现出更明显的代谢紊乱和肝纤维化风险。尽管代谢指标（TyG、FIB-4）对肝纤维化的预测价值有限，但它们与MASLD的代谢风险密切相关。

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Clinical characteristics of lean and non-lean non-alcoholic fatty liver disease: a cross-sectional study.

Introduction: Non-alcoholic fatty liver disease (NAFLD) affects more than a quarter of the global population and has become the world's number one chronic liver disease, seriously jeopardizing public life and health. Despite the new terminology of metabolic dysfunction-associated steatotic liver disease (MASLD) has been proposed, the mechanisms underlying the heterogeneity across BMI stratification in non-alcoholic fatty liver disease (NAFLD) remain unclear. The aim of this study was to reveal the differences in metabolic and fibrotic characteristics between lean (BMI < 23 kg/m²) and non-lean NAFLD in an Asian population.

Methods: The current study collected NAFLD patients from the physical examination population. Patients were divided into two groups by BMI to compare their clinical parameters, including lean (BMI < 23 kg/m²) and non-lean (BMI ≥ 23 kg/m²) and fibrosis subgroups (with a threshold of LSM = 8 kPa) and analyzed for risk factors by logistic regression models.

Results: Of the 11,577 NAFLD patients who participated in the study, there were 916 lean and 10,661 non-lean. The non-lean group was younger than the lean group (median age 50 vs. 52 years, P < 0.001) and had a significantly higher prevalence of hypertension (28.0% vs. 18.3%), diabetes mellitus (10.1% vs. 6.1%), and liver fibrosis (9.1% vs. 5.1%) (all P < 0.001). Analysis of metabolic indexes showed that TyG, TyG-BMI, TG/HDL-C and APRI were higher in the non-lean group (all P < 0.001). Gender stratification revealed that ALT was significantly higher in the male non-lean group, while HDL-C was lower in the female non-lean group (1.35 vs. 1.47 mmol/L). Multiple regression suggested that the risk of fibrosis was independently associated with CAP values and fasting glucose, BMI, direct bilirubin, globulin, and age in the non-lean group, whereas the risk was mainly driven by GGT and ALP in the lean group.

Conclusions: Non-lean NAFLD patients showed more significant metabolic disturbances and risk of liver fibrosis. Although metabolic indicators (TyG, FIB-4) have limited predictive value for liver fibrosis, they are strongly associated with metabolic risk in MASLD.

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.