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关于代谢谱分析以提高对呼吸道感染疾病病理生理学理解和结局预测的系统评价。

Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections.

作者信息

Nickler Manuela, Ottiger Manuel, Steuer Christian, Huber Andreas, Anderson Janet Byron, Müller Beat, Schuetz Philipp

机构信息

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.

出版信息

Respir Res. 2015 Oct 15;16:125. doi: 10.1186/s12931-015-0283-6.

Abstract

Metabolic profiling through targeted quantification of a predefined subset of metabolites, performed by mass spectrometric analytical techniques, allows detailed investigation of biological pathways and thus may provide information about the interaction of different organic systems, ultimately improving understanding of disease risk and prognosis in a variety of diseases. Early risk assessment, in turn, may improve patient management in regard to cite-of-care decisions and treatment modalities. Within this review, we focus on the potential of metabolic profiling to improve our pathophysiological understanding of disease and management of patients. We focus thereby on lower respiratory tract infections (LRTI) including community-acquired pneumonia (CAP) and chronic obstructive pulmonary disease (COPD), an important disease responsible for high mortality, morbidity and costs worldwide. Observational data from numerous clinical and experimental studies have provided convincing data linking metabolic blood biomarkers such as lactate, glucose or cortisol to patient outcomes. Also, identified through metabolomic studies, novel innovative metabolic markers such as steroid hormones, biogenic amines, members of the oxidative status, sphingo- and glycerophospholipids, and trimethylamine-N-oxide (TMAO) have shown promising results. Since many uncertainties remain in predicting mortality in these patients, further prospective and retrospective observational studies are needed to uncover metabolic pathways responsible for mortality associated with LRTI. Improved understanding of outcome-specific metabolite signatures in LRTIs may optimize patient management strategies, provide potential new targets for future individual therapy, and thereby improve patients' chances for survival.

摘要

通过质谱分析技术对预定义的代谢物子集进行靶向定量分析来进行代谢谱分析,能够详细研究生物途径,从而可能提供有关不同有机系统相互作用的信息,最终增进对多种疾病的疾病风险和预后的理解。反过来,早期风险评估可能会改善患者在护理地点决策和治疗方式方面的管理。在本综述中,我们重点关注代谢谱分析在增进我们对疾病的病理生理学理解和患者管理方面的潜力。我们特别关注下呼吸道感染(LRTI),包括社区获得性肺炎(CAP)和慢性阻塞性肺疾病(COPD),这是一种在全球范围内导致高死亡率、高发病率和高成本的重要疾病。来自众多临床和实验研究的观察数据提供了令人信服的数据,将代谢血液生物标志物如乳酸、葡萄糖或皮质醇与患者预后联系起来。此外,通过代谢组学研究确定的新型创新代谢标志物,如类固醇激素、生物胺、氧化状态成员、鞘脂和甘油磷脂以及氧化三甲胺(TMAO),已显示出有前景的结果。由于在预测这些患者的死亡率方面仍存在许多不确定性,因此需要进一步开展前瞻性和回顾性观察研究,以揭示与LRTI相关的死亡率所涉及的代谢途径。更好地理解LRTIs中特定结局的代谢物特征可能会优化患者管理策略,为未来的个体化治疗提供潜在的新靶点,从而提高患者的生存机会。

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