The association between dietary consumption of amino acids and the risk of non-alcoholic fatty liver disease: a case-control study.

IF 4.1 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2025-10-09 DOI:10.1186/s12986-025-00992-3

Asieh Mansour, Mohammad Abdollahi, Maryam Mirahmad, Soudabe Motamed, Atie Sadat Khorasanian, Seyed Hossein Mirlohi, Hossein Poustchi, Elaheh Amini, Farnaz Tavakoli, Mohammad Reza Mohajeri-Tehrani, Sayed Mahmoud Sajjadi-Jazi, Azita Hekmatdoost

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引用次数: 0

Abstract

Background: Few studies, with inconsistent results, have been conducted to examine the effect of protein and amino acid consumption on non-alcoholic fatty liver disease (NAFLD). Therefore, this study aimed to assess the relationship between dietary intake of amino acids or groups of amino acids and the risk of NAFLD.

Methods: This case-control study included 171 participants with NAFLD and 730 controls from Tehran, Iran. A validated Food frequency questionnaire (FFQ) with 168 items, was used to evaluate dietary information. Odds ratios (ORs) and corresponding confidence intervals (CIs) were calculated by regression models, adjusted for potential confounders including age, sex, body mass index (BMI), smoking status, physical activity, history of diabetes mellitus, and total energy intake.

Results: The mean ± standard deviation (SD) age of participants was 43.26 ± 13.9 years. Intake of total protein and all amino acids was significantly higher in patients with NAFLD than in the control group (P < 0.001). Increased risk of developing NAFLD compared to the reference quartile was observed in the highest quartiles of dietary isoleucine (OR, 4.72; 95%CI, 1.57-14.19), tyrosine (OR, 5.11, 95%CI, 1.73-15.05), threonine (OR, 3.47; 95%CI, 1.16-10.33), and valine (OR, 4.51; 95%CI, 1.45-14.02) intake. Subgroup analysis by sex revealed that in the females, the OR for NAFLD were 0.36 (95%CI, 0.13-0.98) among those with the highest intake of non-essential amino acids, and 2.78 (95%CI, 1.02-7.50) among those with the highest intake of essential amino acids compared to those in the first quartile. However, there was no significant trend among male cases.

Conclusion: Consumption of specific amino acids might be associated with odds of NAFLD.

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膳食氨基酸摄入与非酒精性脂肪性肝病风险之间的关系：一项病例对照研究

背景：关于蛋白质和氨基酸摄入对非酒精性脂肪性肝病（NAFLD）影响的研究很少，结果也不一致。因此，本研究旨在评估膳食中氨基酸或氨基酸群的摄入与NAFLD风险之间的关系。方法：本病例对照研究包括来自伊朗德黑兰的171名NAFLD患者和730名对照组。采用经验证的食物频率问卷（FFQ）对饮食信息进行评估，问卷共有168个条目。通过回归模型计算优势比（ORs）和相应的置信区间（ci），并对潜在混杂因素进行校正，包括年龄、性别、体重指数（BMI）、吸烟状况、身体活动、糖尿病史和总能量摄入。结果：参与者的平均±标准差（SD）年龄为43.26±13.9岁。NAFLD患者总蛋白和所有氨基酸的摄取量明显高于对照组(P结论：特定氨基酸的摄取量可能与NAFLD的发病几率有关。

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.