Abstract
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.
Highlights
Tremendous efforts have been put into the discovery of biomarkers that can diagnose disease or injury
Proteomics has led to the discovery of many candidate biomarkers and is becoming the method-of-choice for preliminary candidate marker selection
Systems biology coupled to data mining strategies has been applied to harness these large data sets into organized and interlinked databases that can be queried to identify non-redundant brain injury pathways
Summary
Tremendous efforts have been put into the discovery of biomarkers that can diagnose disease or injury. In traumatic brain injury (TBI), an interdisciplinary approach is employed by combining the methods and tools from three fields, namely, proteomics, bioinformatics, and systems biology. Protein biomarkers of TBI, induced by penetrating ballistic-like injury model (PBBI), were identified by the proteomics followed by systems biology analysis (Boutté et al, 2012). These proteins are ubiquitin carboxylterminal isozyme 1, tyrosine hydroxylase, and syntaxin-6. Three commercially available pathway analysis software include Pathway Studio (Ariadne Genomics, Rockville, MD, USA), Metacore (Thompson Reuters, New York City, NY, USA), and Ingenuity (Ingenuity Systems, Redwood City, CA, USA) These tools enable the identification of the relationship among proteins, small molecules, cell processes, and diseases. The obvious countermeasure to this problem is to measure the proteins right after injury; most mild TBI victims are not evaluated as soon as the injury occurs
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