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Identification of Serum Metabolites Associated With Incident Hypertension in the European Prospective Investigation into Cancer and Nutrition-Potsdam Study

机译:在癌症和营养-波茨坦研究的欧洲前瞻性研究中确定与高血压相关的血清代谢物

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Metabolomics is a promising tool to gain new insights into early metabolic alterations preceding the development of hypertension in humans. We therefore aimed to identify metabolites associated with incident hypertension using measured data of serum metabolites of the European Prospective Investigation Into Cancer and Nutrition (EPIC)-Potsdam study. Targeted metabolic profiling was conducted on serum blood samples of a randomly drawn EPIC-Potsdam subcohort consisting of 135 cases and 981 noncases of incident hypertension, all of them being free of hypertension and not on antihypertensive therapy at the time of blood sampling. Mean follow-up was 9.9 years. A validated set of 127 metabolites was statistically analyzed with a random survival forest backward selection algorithm to identify predictive metabolites of incident hypertension taking into account important epidemiological hypertension risk markers. Six metabolites were identified to be most predictive for the development of hypertension. Higher concentrations of serine, glycine, and acyl-alkyl-phosphatidylcholines C42:4 and C44:3 tended to be associated with higher and diacyl-phosphatidylcholines C38:4 and C38:3 with lower predicted 10-year hypertension-free survival, although visualization by partial plots revealed some nonlinearity in the above associations. The identified metabolites improved prediction of incident hypertension when used together with known risk markers of hypertension. In conclusion, these findings indicate that metabolic alterations occur early in the development of hypertension. However, these alterations are confined to a few members of the amino acid or phosphatidylcholine metabolism, respectively.
机译:代谢组学是一种有前途的工具,可在人类高血压发展之前获得有关早期代谢变化的新见解。因此,我们旨在使用欧洲癌症与营养前瞻性调查(EPIC)-波茨坦研究的血清代谢物的测定数据来鉴定与高血压相关的代谢物。在随机抽取的EPIC-Potsdam亚人群的血清样本中进行了目标代谢谱分析,该人群包括135例和981例非高血压事件,所有患者均无高血压,并且在采血时未进行降压治疗。平均随访时间为9。9年。使用随机生存森林向后选择算法对经过验证的127种代谢物进行统计分析,以考虑到重要的流行病学高血压风险标记物,确定突发性高血压的预测代谢物。确定了六种代谢物最能预测高血压的发展。较高浓度的丝氨酸​​,甘氨酸和酰基烷基磷脂酰胆碱C42:4和C44:3往往与较高的和二酰基磷脂酰胆碱C38:4和C38:3相关联,但预测的10年无高血压生存期较低,通过局部绘图揭示了上述关联中的一些非线性。与已知的高血压危险标志物一起使用时,鉴定出的代谢物可改善对高血压的预测。总之,这些发现表明代谢改变发生在高血压的发展早期。然而,这些改变分别局限于氨基酸或磷脂酰胆碱代谢的几个成员。

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