Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, Meckenheimer Allee 166a, 53115, Bonn, Germany.
Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), University Hospital Bonn, 53127, Bonn, Germany.
Sci Rep. 2023 Feb 25;13(1):3296. doi: 10.1038/s41598-023-30231-9.
Metabolomics-derived metabolites (henceforth metabolites) may mediate the relationship between modifiable risk factors and clinical biomarkers of metabolic health (henceforth clinical biomarkers). We set out to study the associations of metabolites with clinical biomarkers and a potential mediation effect in a population of young adults. First, we conducted a systematic literature review searching for metabolites associated with 11 clinical biomarkers (inflammation markers, glucose, blood pressure or blood lipids). Second, we replicated the identified associations in a study population of n = 218 (88 males and 130 females, average age of 18 years) participants of the DONALD Study. Sex-stratified linear regression models adjusted for age and BMI and corrected for multiple testing were calculated. Third, we investigated our previously reported metabolites associated with anthropometric and dietary factors mediators in sex-stratified causal mediation analysis. For all steps, both urine and blood metabolites were considered. We found 41 metabolites in the literature associated with clinical biomarkers meeting our inclusion criteria. We were able to replicate an inverse association of betaine with CRP in women, between body mass index and C-reactive protein (CRP) and between body fat and leptin. There was no evidence of mediation by lifestyle-related metabolites after correction for multiple testing. We were only able to partially replicate previous findings in our age group and did not find evidence of mediation. The complex interactions between lifestyle factors, the metabolome, and clinical biomarkers warrant further investigation.
代谢组学衍生的代谢物（以下简称代谢物）可能介导可改变的风险因素与代谢健康的临床生物标志物（以下简称临床生物标志物）之间的关系。我们旨在研究代谢物与临床生物标志物的关联以及在年轻成年人人群中的潜在中介效应。首先，我们进行了一项系统的文献综述，寻找与 11 种临床生物标志物（炎症标志物、葡萄糖、血压或血脂）相关的代谢物。其次，我们在 DONALD 研究的 218 名（男性 88 名，女性 130 名，平均年龄 18 岁）参与者的研究人群中复制了已确定的关联。计算了经过年龄和 BMI 调整并经多次检验校正的性别分层线性回归模型。第三，我们在性别分层因果中介分析中研究了我们之前报道的与人体测量和饮食因素相关的代谢物的中介作用。对于所有步骤，都考虑了尿液和血液代谢物。我们在文献中发现了 41 种与符合我们纳入标准的临床生物标志物相关的代谢物。我们能够复制甜菜碱与女性 CRP 之间、体重指数与 C 反应蛋白（CRP）之间以及体脂肪与瘦素之间的负相关。在经过多次检验校正后，没有证据表明生活方式相关代谢物存在中介作用。我们仅在我们的年龄组中部分复制了先前的发现，并且没有发现中介作用的证据。生活方式因素、代谢组学和临床生物标志物之间的复杂相互作用需要进一步研究。
