Association of behavioral factors, liver function and NAFLD: Bayesian Mendelian randomization.

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2025-06-23 DOI:10.1186/s12986-025-00961-w

Lei Pu, Cheng Pu, Xiaoyan Zhang

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引用次数: 0

Abstract

Background: The causal associations between behavioral factors (BFs) and the risk of non-alcoholic fatty liver disease (NAFLD), and whether liver function mediates these associations, remain unclear. Therefore, this study aimed to assess these associations.

Methods: We performed two-sample Mendelian randomization (2SMR) and multivariable MR (MVMR) analysis using summary-level data to assess the associations between BFs and NAFLD. The linkage disequilibrium score regression (LDSC) was used for genetic correlation analysis. Additionally, we utilized NHANES database to assess dose-response relationships. Furthermore, we applied two-sample MVMR approach based on Bayesian model averaging (MR-BMA) to identify the most influential liver function index as a mediating factor, and performed mediation analysis.

Results: 2SMR results showed that leisure screen time (ST, β = 0.414, P = 5.91e-6) and smoking initiation (SI, β = 0.164, P = 0.012) were associated with NAFLD risk with no reverse causality. LDSC supported these associations (SI: rg = 0.291, P = 1.04e-8; ST: 0.518, P = 5.41e-21). However, MVMR showed that only ST was independently associated with NAFLD (β = 0.334, P = 4.6e-5). There was a linear relationship between ST and NAFLD, and NAFLD risk increased significantly after 5 h of ST. Alanine transaminase level was the most influential index (ALT, MIP = 0.452) and mediated 54% of the ST-NAFLD association.

Conclusion: ST is independently associated with an increased risk of NAFLD. It is recommended to avoid more than 5 h of ST per day. ALT is the most influential liver function index associated with NAFLD and mediates the ST-NAFLD association.

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行为因素、肝功能和NAFLD的关联：贝叶斯孟德尔随机化。

背景：行为因素（BFs）与非酒精性脂肪性肝病（NAFLD）风险之间的因果关系，以及肝功能是否介导了这些关联，目前尚不清楚。因此，本研究旨在评估这些关联。方法：我们采用双样本孟德尔随机化（2SMR）和多变量磁共振（MVMR）分析，利用汇总数据评估bf与NAFLD之间的关系。遗传相关分析采用连锁不平衡评分回归（LDSC）。此外，我们利用NHANES数据库来评估剂量-反应关系。此外，我们采用基于贝叶斯模型平均（MR-BMA）的双样本MVMR方法，确定最具影响力的肝功能指数作为中介因素，并进行中介分析。结果：2SMR结果显示，休闲屏幕时间（ST, β = 0.414, P = 5.91e-6）和开始吸烟（SI, β = 0.164, P = 0.012）与NAFLD风险相关，无反向因果关系。LDSC支持这些关联(SI: rg = 0.291, P = 1.04e-8；ST: 0.518, P = 5.41e-21)。然而，MVMR显示只有ST与NAFLD独立相关（β = 0.334, P = 4.6e-5）。ST与NAFLD呈线性关系，且ST后5 h NAFLD风险显著升高，丙氨酸转氨酶水平是影响最大的指标（ALT, MIP = 0.452），介导了54%的ST-NAFLD关联。结论：ST与NAFLD风险增加独立相关。建议每天ST时间不要超过5小时。ALT是与NAFLD相关的最具影响力的肝功能指标，并介导ST-NAFLD的关联。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.