Human Nutrition Unit, Faculty of Medicine and Health Sciences, Sant Joan Hospital, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201, Reus, Spain.
CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Mol Nutr Food Res. 2019 Sep;63(17):e1900140. doi: 10.1002/mnfr.201900140. Epub 2019 Jul 17.
The relationship between red wine (RW) consumption and metabolism is poorly understood. It is aimed to assess the systemic metabolomic profiles in relation to frequent RW consumption as well as the ability of a set of metabolites to discriminate RW consumers.
A cross-sectional analysis of 1157 participants is carried out. Subjects are divided as non-RW consumers versus RW consumers (>1 glass per day RW [100 mL per day]). Plasma metabolomics analysis is performed using LC-MS. Associations between 386 identified metabolites and RW consumption are assessed using elastic net regression analysis taking into consideration baseline significant covariates. Ten-cross-validation (CV) is performed and receiver operating characteristic curves are constructed in each of the validation datasets based on weighted models. A subset of 13 metabolites is consistently selected and RW consumers versus nonconsumers are discriminated. Based on the multi-metabolite model weighted with the regression coefficients of metabolites, the area under the curve is 0.83 (95% CI: 0.80-0.86). These metabolites mainly consisted of lipid species, some organic acids, and alkaloids.
A multi-metabolite model identified in a Mediterranean population appears useful to discriminate between frequent RW consumers and nonconsumers. Further studies are needed to assess the contribution of these metabolites in health and disease.
红酒(RW)消费与新陈代谢之间的关系尚未得到充分理解。本研究旨在评估与频繁 RW 消费相关的系统代谢组学特征,以及一组代谢物区分 RW 消费者的能力。
对 1157 名参与者进行了横断面分析。受试者分为非 RW 消费者与 RW 消费者(每天>1 杯 RW [每天 100 毫升])。使用 LC-MS 进行血浆代谢组学分析。采用弹性网络回归分析,考虑基线显著协变量,评估 386 种鉴定代谢物与 RW 消费之间的关联。在每个验证数据集中,基于加权模型进行十次交叉验证(CV)并构建接收者操作特征曲线。一组 13 种代谢物被一致选择,用于区分 RW 消费者与非消费者。基于代谢物回归系数加权的多代谢物模型,曲线下面积为 0.83(95%CI:0.80-0.86)。这些代谢物主要由脂质、一些有机酸和生物碱组成。
在地中海人群中确定的多代谢物模型似乎可用于区分频繁 RW 消费者和非消费者。需要进一步研究这些代谢物在健康和疾病中的作用。