Banyan Biomarkers, Inc. , Alachua, FL , USA.
Front Neurol. 2013 May 31;4:61. doi: 10.3389/fneur.2013.00061. eCollection 2013.
Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed.
创伤性脑损伤 (TBI) 是一场重大的医学危机，目前还没有经过美国食品和药物管理局 (FDA) 批准的能够改善功能预后的药物治疗方法。有人认为，发现与疾病相关的生物标志物可能有助于指导创伤性脑损伤的临床试验取得成功。质谱 (MS) 的重大进展彻底改变了蛋白质组学生物标志物发现领域，并促进了几个候选标志物的鉴定，这些标志物正在进一步评估其作为创伤性脑损伤生物标志物的疗效。然而，即使在发现阶段也存在许多障碍，这只是生物标志物开发漫长过程中的第一步。基于 MS 的蛋白质组学实验的高通量性质产生了大量的质谱数据，这在下游解释方面带来了巨大挑战。目前，有不同的生物信息学平台可用于 MS 生成的蛋白质组学数据的功能分析和数据挖掘。这些工具提供了一种将数据集转换为可生物解释的结果和功能结果的方法。一种有望推进生物标志物开发的策略涉及蛋白质组学、生物信息学和系统生物学的三联体。在这篇综述中，讨论了生物信息学和系统生物学工具如何分析、转换和解释复杂的 MS 数据集以获得生物学相关结果。此外，还介绍了蛋白质组学、生物信息学和系统生物学在创伤性脑损伤生物标志物发现中的挑战和局限性。还简要介绍了利用这三个重叠学科进行创伤性脑损伤生物标志物发现的研究。最后，讨论了创伤性脑损伤生物标志物及其应用的实例。
