Challenges and opportunities for discovery of disease biomarkers using urine proteomics.
Challenges and opportunities for discovery of disease biomarkers using urine proteomics.
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DOI：
10.1111/j.1442-200x.2010.03253.x
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发表时间：
2011-02
期刊：
影响因子：
--
通讯作者：
Kentsis A
中科院分区：
文献类型：
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作者：
Kentsis A
现代医学经历了疾病病理生理学知识的巨大爆炸，这些知识主要来自对人类疾病的分子生物学的了解。质谱和蛋白质组学的最新进展现在可以同时识别和定量复杂生物组织和液体中的数千种独特的蛋白质和肽。特别是，与血清和组织相比，尿液的蛋白质组学研究受益于尿液的成分不太复杂，并且已成功用于发现各种感染、自身免疫、肿瘤和外科疾病的新标记物。这种观点讨论了此类研究的挑战，这些挑战源于人类尿液的成分变异性和复杂性，以及仪器采样的局限性以及噪音和选择偏差的影响。概述了观察性临床试验的设计、尿液样本的物理和化学分离、质谱分析和功能数据注释的策略。使用尿液蛋白质组学进行严格的转化研究可能会发现罕见和常见疾病的新颖且准确的标记物。这应该有助于诊断，改善治疗分层，并确定各种儿童和成人疾病的新治疗靶点，所有这些对于未来个性化和预测医学的发展至关重要。
Modern medicine has experienced a tremendous explosion in knowledge about disease pathophysiology, gained largely from understanding the molecular biology of human disease. Recent advances in mass spectrometry and proteomics now allow for simultaneous identification and quantification of thousands of unique proteins and peptides in complex biological tissues and fluids. In particular, proteomic studies of urine benefit from urine’s less complex composition as compared to serum and tissues, and have been used successfully to discover novel markers of a variety of infectious, autoimmune, oncological, and surgical conditions. This perspective discusses the challenges of such studies that stem from the compositional variability and complexity of human urine, as well as instrumental sampling limitations and the effects of noise and selection bias. Strategies for the design of observational clinical trials, physical and chemical fractionation of urine specimens, mass spectrometry analysis, and functional data annotation are outlined. Rigorous translational investigations using urine proteomics are likely to discover novel and accurate markers of both rare and common diseases. This should aid the diagnosis, improve stratification of therapy, and identify novel therapeutic targets for a variety of childhood and adult diseases, all of which will be essential for the development of personalized and predictive medicine of the future.