Key Laboratory of Trace Element Nutrition of National Health Commission of China, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, China.
Nutrients. 2021 Dec 20;13(12):4567. doi: 10.3390/nu13124567.
Red meat (RM) consumption is correlated with multiple health outcomes. This study aims to identify potential biomarkers of RM consumption in the Chinese population and evaluate their predictive ability. We selected 500 adults who participated in the 2015 China Health and Nutrition Survey and examined their overall metabolome differences by RM consumption by using elastic-net regression, then evaluate the predictivity of a combination of filtered metabolites; 1108 metabolites were detected. In the long-term RM consumption analysis 12,13-DiHOME, androstenediol (3α, 17α) monosulfate 2, and gamma-Glutamyl-2-aminobutyrate were positively associated, 2-naphthol sulfate and S-methylcysteine were negatively associated with long-term high RM consumption, the combination of metabolites prediction model evaluated by area under the receiver operating characteristic curve (AUC) was 70.4% (95% CI: 59.9-80.9%). In the short-term RM consumption analysis, asparagine, 4-hydroxyproline, and 3-hydroxyisobutyrate were positively associated, behenoyl sphingomyelin (d18:1/22:0) was negatively associated with short-term high RM consumption. Combination prediction model AUC was 75.6% (95% CI: 65.5-85.6%). We identified 10 and 11 serum metabolites that differed according to LT and ST RM consumption which mainly involved branch-chained amino acids, arginine and proline, urea cycle and polyunsaturated fatty acid metabolism. These metabolites may become a mediator of some chronic diseases among high RM consumers and provide new evidence for RM biomarkers.
红肉(RM)的消费与多种健康结果相关。本研究旨在鉴定中国人群中 RM 消费的潜在生物标志物,并评估其预测能力。我们选择了 500 名参加 2015 年中国健康与营养调查的成年人,通过弹性网络回归法根据 RM 消费情况检测他们的整体代谢组差异,然后评估过滤代谢物组合的预测能力;共检测到 1108 种代谢物。在长期 RM 消费分析中,12,13-DiHOME、雄烯二酮(3α,17α)单硫酸盐 2 和γ-谷氨酰-2-氨基丁酸呈正相关,2-萘酚硫酸盐和 S-甲基半胱氨酸与长期高 RM 消费呈负相关,经受试者工作特征曲线(AUC)评估的代谢物组合预测模型为 70.4%(95%CI:59.9-80.9%)。在短期 RM 消费分析中,天冬酰胺、4-羟脯氨酸和 3-羟基异丁酸呈正相关,二十二碳二烯酰基鞘氨醇(d18:1/22:0)与短期高 RM 消费呈负相关。组合预测模型 AUC 为 75.6%(95%CI:65.5-85.6%)。我们根据 LT 和 ST RM 消费鉴定了 10 种和 11 种血清代谢物,主要涉及支链氨基酸、精氨酸和脯氨酸、尿素循环和多不饱和脂肪酸代谢。这些代谢物可能成为高 RM 消费者中某些慢性疾病的中介,并为 RM 生物标志物提供新的证据。