Department of Twin Research and Genetic Epidemiology, St Thomas Hospital, King's College London, London, SE1 7EH, UK.
Estonian Genome Center, University of Tartu, Tartu, Estonia.
Eur J Nutr. 2017 Oct;56(7):2379-2391. doi: 10.1007/s00394-016-1278-x. Epub 2016 Jul 28.
Milk provides a significant source of calcium, protein, vitamins and other minerals to Western populations throughout life. Due to its widespread use, the metabolic and health impact of milk consumption warrants further investigation and biomarkers would aid epidemiological studies.
Milk intake assessed by a validated food frequency questionnaire was analyzed against fasting blood metabolomic profiles from two metabolomic platforms in females from the TwinsUK cohort (n = 3559). The top metabolites were then replicated in two independent populations (EGCUT, n = 1109 and KORA, n = 1593), and the results from all cohorts were meta-analyzed.
Four metabolites were significantly associated with milk intake in the TwinsUK cohort after adjustment for multiple testing (P < 8.08 × 10) and covariates (BMI, age, batch effects, family relatedness and dietary covariates) and replicated in the independent cohorts. Among the metabolites identified, the carnitine metabolite trimethyl-N-aminovalerate (β = 0.012, SE = 0.002, P = 2.98 × 10) and the nucleotide uridine (β = 0.004, SE = 0.001, P = 9.86 × 10) were the strongest novel predictive biomarkers from the non-targeted platform. Notably, the association between trimethyl-N-aminovalerate and milk intake was significant in a group of MZ twins discordant for milk intake (β = 0.050, SE = 0.015, P = 7.53 × 10) and validated in the urine of 236 UK twins (β = 0.091, SE = 0.032, P = 0.004). Two metabolites from the targeted platform, hydroxysphingomyelin C14:1 (β = 0.034, SE = 0.005, P = 9.75 × 10) and diacylphosphatidylcholine C28:1 (β = 0.034, SE = 0.004, P = 4.53 × 10), were also replicated.
We identified and replicated in independent populations four novel biomarkers of milk intake: trimethyl-N-aminovalerate, uridine, hydroxysphingomyelin C14:1 and diacylphosphatidylcholine C28:1. Together, these metabolites have potential to objectively examine and refine milk-disease associations.
牛奶为西方人群提供了大量的钙、蛋白质、维生素和其他矿物质,贯穿其一生。由于其广泛应用,牛奶消费的代谢和健康影响值得进一步研究,生物标志物将有助于开展流行病学研究。
通过验证过的食物频率问卷评估牛奶摄入量,然后分析来自 TwinsUK 队列的女性空腹血液代谢组学谱(n=3559)。使用两个代谢组学平台进行分析。从 TwinsUK 队列中鉴定出的前 4 种代谢物在经过多次测试(P<8.08×10)和协变量(BMI、年龄、批次效应、家族相关性和饮食协变量)调整后与牛奶摄入量相关,并在两个独立的队列中进行了复制。在鉴定出的代谢物中,肉碱代谢物三甲氨基丁酸(β=0.012,SE=0.002,P=2.98×10)和核苷酸尿嘧啶(β=0.004,SE=0.001,P=9.86×10)是来自非靶向平台的最强的新型预测生物标志物。值得注意的是,在牛奶摄入量不一致的 MZ 双胞胎中,三甲氨基丁酸与牛奶摄入量之间的关联具有统计学意义(β=0.050,SE=0.015,P=7.53×10),并在 236 名英国双胞胎的尿液中得到验证(β=0.091,SE=0.032,P=0.004)。靶向平台的两种代谢物,羟基神经酰胺 C14:1(β=0.034,SE=0.005,P=9.75×10)和二酰基磷脂酰胆碱 C28:1(β=0.034,SE=0.004,P=4.53×10)也得到了复制。
我们在独立人群中鉴定和复制了四个牛奶摄入量的新型生物标志物:三甲氨基丁酸、尿嘧啶、羟基神经酰胺 C14:1 和二酰基磷脂酰胆碱 C28:1。这些代谢物具有客观检查和完善牛奶疾病关联的潜力。