Annika Blümlhuber, Dennis Freuer, Nina Wawro, Florian Rohm, Christine Meisinger, Jakob Linseisen
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引用次数: 0
Abstract
Background: Chronic non-communicable diseases (NCDs) are a major global health challenge, with unhealthy diets contributing significantly to their burden. Metabolomics data offer new possibilities for identifying nutritional biomarkers, as demonstrated in short-term intervention studies. This study investigated associations between habitual dietary intake and urinary metabolites, a not well-studied area.
Methods: Data were available from 496 participants of the population-based MEIA study. Linear and median regression models examined associations between habitual dietary intake and metabolites, adjusted for possible confounders. K-means clustering identified urinary metabolite clusters, and multinomial regression models were applied to analyze associations between food intake and metabolite clusters.
Results: Using linear regression models, previously reported associations could be replicated, including citrus intake with proline betaine, protein intake with urea, and fiber intake with hippurate. Novel findings include positive associations of poultry intake with taurine, indoxyl sulfate, 1-methylnicotinamide, and trimethylamine-N-oxide. Milk substitutes were positively associated with urinary uracil, pseudouridine, 4-hydroxyhippurate, and 3-hydroxyhippurate, and inversely associated with quinic acid. Dietary fiber intake showed a positive association with 3-(3-hydroxyphenyl)-3-hydroxypropionic acid and a negative association with indoxyl sulfate. We identified sucrose and taurine as key metabolites differentiating metabolite clusters. Multinomial regression analysis confirmed significantly different dietary associations across clusters, particularly for fruits, processed meat, poultry, and alcoholic beverages.
Conclusions: This study highlights established and novel food-metabolite associations, demonstrating the potential of urinary metabolomics for use as nutritional biomarkers in individuals from the general population.
背景:慢性非传染性疾病(NCDs)是一项重大的全球健康挑战,不健康的饮食在很大程度上加重了它们的负担。正如短期干预研究所证明的那样,代谢组学数据为识别营养生物标志物提供了新的可能性。这项研究调查了习惯饮食摄入和尿液代谢物之间的关系,这是一个尚未得到充分研究的领域。方法:数据来自496名以人群为基础的MEIA研究参与者。线性和中位数回归模型检验了习惯饮食摄入和代谢物之间的关系,并对可能的混杂因素进行了调整。K-means聚类识别尿液代谢物簇,并应用多项回归模型分析食物摄入与代谢物簇之间的关系。结果:使用线性回归模型,先前报道的关联可以重复,包括柑橘摄入量与脯氨酸甜菜碱,蛋白质摄入量与尿素,纤维摄入量与希波尿酸。新的发现包括家禽摄入量与牛磺酸、硫酸吲哚酚、1-甲基烟酰胺和三甲胺- n -氧化物呈正相关。牛奶替代品与尿嘧啶、假尿嘧啶、4-羟基马嘌呤和3-羟基马嘌呤呈正相关,与奎宁酸呈负相关。膳食纤维摄入量与3-(3-羟基苯基)-3-羟基丙酸呈正相关,与硫酸吲哚酚呈负相关。我们确定蔗糖和牛磺酸是区分代谢物簇的关键代谢物。多项回归分析证实了不同群体的饮食关联存在显著差异,尤其是水果、加工肉类、家禽和酒精饮料。结论:本研究强调了已建立的和新的食物代谢物关联,证明了尿代谢组学在普通人群中作为营养生物标志物的潜力。
MetabolitesBiochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
5.70
自引率
7.30%
发文量
1070
审稿时长
17.17 days
期刊介绍:
Metabolites (ISSN 2218-1989) is an international, peer-reviewed open access journal of metabolism and metabolomics. Metabolites publishes original research articles and review articles in all molecular aspects of metabolism relevant to the fields of metabolomics, metabolic biochemistry, computational and systems biology, biotechnology and medicine, with a particular focus on the biological roles of metabolites and small molecule biomarkers. Metabolites encourages scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on article length. Sufficient experimental details must be provided to enable the results to be accurately reproduced. Electronic material representing additional figures, materials and methods explanation, or supporting results and evidence can be submitted with the main manuscript as supplementary material.