NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
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DOI：
10.1093/ije/dyx271
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发表时间：
2018-04-01
影响因子：
7.7
通讯作者：
Touvier, Mathilde
中科院分区：
文献类型：
--
作者：
Lecuyer, Lucie;Bala, Agnes Victor;Touvier, Mathilde
背景：代谢组学和流行病学方法的结合为突破性发现开辟了新的视角。本研究的目的是首次调查从健康女性的简单抽血中建立的血浆非靶向代谢组学特征是否有助于预测未来十年内患乳腺癌的风险，并更好地了解这种复杂疾病的病因。方法：在补充维生素和矿物质抗氧化剂（SU. VI. MAX）队列中建立了一项前瞻性巢式病例对照研究，其中包括206例在13年随访期间诊断的乳腺癌病例和396例匹配对照。从基线血浆样本中建立非靶向核磁共振（NMR）代谢组学图谱。为每个单独的核磁共振变量和主成分分析得出的变量组合计算了多变量条件逻辑回归模型。结果：1D核磁共振光谱的几个代谢组学变量与乳腺癌风险相关。空腹血浆中缬氨酸、赖氨酸、精氨酸、谷氨酰胺、肌酸、肌酐和葡萄糖水平较高，血浆中脂蛋白、脂质、糖蛋白、丙酮、甘油衍生化合物和不饱和脂质水平较低的女性患乳腺癌的风险较高。p值范围从0.00007[甘油衍生化合物的比值比（OR）(T3vsT1) = 0.37(0.23-0.61)]到0.04[谷氨酰胺的ORT3vsT1 = 1.61(1.02-2.55)]。结论：本研究强调了基线核磁共振血浆代谢组学特征与长期乳腺癌风险之间的关联。这些结果为更好地理解乳腺癌发生的复杂机制和诱发有利于癌变起始的血浆代谢紊乱提供了有趣的见解。这项研究可能有助于制定筛查策略，以便在症状出现之前识别有乳腺癌风险的妇女。
Background: Combination of metabolomics and epidemiological approaches opens new perspectives for ground-breaking discoveries. The aim of the present study was to investigate for the first time whether plasma untargeted metabolomic profiles, established from a simple blood draw from healthy women, could contribute to predict the risk of developing breast cancer within the following decade and to better understand the aetiology of this complex disease.Methods: A prospective nested case-control study was set up in the Supplementation en Vitamines et Mineraux Antioxydants (SU. VI. MAX) cohort, including 206 breast cancer cases diagnosed during a 13-year follow-up and 396 matched controls. Untargeted nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples. Multivariable conditional logistic regression models were computed for each individual NMR variable and for combinations of variables derived by principal component analysis.Results: Several metabolomic variables from 1D NMR spectroscopy were associated with breast cancer risk. Women characterized by higher fasting plasma levels of valine, lysine, arginine, glutamine, creatine, creatinine and glucose, and lower plasma levels of lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds and unsaturated lipids had a higher risk of developing breast cancer. P-values ranged from 0.00007 [odds ratio (OR)(T3vsT1) = 0.37 (0.23-0.61) for glycerol-derived compounds] to 0.04 [ORT3vsT1 = 1.61 (1.02-2.55) for glutamine].Conclusion: This study highlighted associations between baseline NMR plasma metabolomic signatures and long-term breast cancer risk. These results provide interesting insights to better understand complex mechanisms involved in breast carcinogenesis and evoke plasma metabolic disorders favourable for carcinogenesis initiation. This study may contribute to develop screening strategies for the identification of at-risk women for breast cancer well before symptoms appear.