协同使用 NMR 和 HRMS 的个性化代谢谱。

Personalized Metabolic Profile by Synergic Use of NMR and HRMS.

机构信息

Department of Chemical Science and Technology, University of Rome "Tor Vergata", 00133 Rome, Italy.

Chemistry Department, University of Rome "Sapienza", 00185 Rome, Italy.

出版信息

Molecules. 2021 Jul 8;26(14):4167. doi: 10.3390/molecules26144167.

A new strategy that takes advantage of the synergism between NMR and UHPLC-HRMS yields accurate concentrations of a high number of compounds in biofluids to delineate a personalized metabolic profile (SYNHMET). Metabolite identification and quantification by this method result in a higher accuracy compared to the use of the two techniques separately, even in urine, one of the most challenging biofluids to characterize due to its complexity and variability. We quantified a total of 165 metabolites in the urine of healthy subjects, patients with chronic cystitis, and patients with bladder cancer, with a minimum number of missing values. This result was achieved without the use of analytical standards and calibration curves. A patient's personalized profile can be mapped out from the final dataset's concentrations by comparing them with known normal ranges. This detailed picture has potential applications in clinical practice to monitor a patient's health status and disease progression.

一种新策略利用 NMR 和 UHPLC-HRMS 之间的协同作用，可在生物流体中准确测定大量化合物的浓度，从而描绘出个性化的代谢谱（SYNHMET）。与单独使用两种技术相比，这种方法在代谢物的鉴定和定量方面具有更高的准确性，即使在尿液中也是如此，由于其复杂性和可变性，尿液是最具挑战性的生物流体之一。我们对健康受试者、慢性膀胱炎患者和膀胱癌患者的尿液进行了总共 165 种代谢物的定量分析，且数据缺失值最小。该结果是在不使用分析标准品和校准曲线的情况下实现的。通过将患者的个人资料与已知的正常范围进行比较，可以从最终数据集的浓度中描绘出患者的个性化图谱。这种详细的图谱在临床实践中有应用潜力，可以用于监测患者的健康状况和疾病进展。