RESUMEN
Most of the variation in outcome following severe traumatic brain injury (TBI) remains unexplained by currently recognized prognostic factors. Neuroinflammation may account for some of this difference. We hypothesized that TBI generated variable autoantibody responses between individuals that would contribute to outcome. We developed a custom protein microarray to detect autoantibodies to both CNS and systemic Ags in serum from the acute-phase (the first 7 d), late (6-12 mo), and long-term (6-13 y) intervals after TBI in human patients. We identified two distinct patterns of immune response to TBI. The first was a broad response to the majority of Ags tested, predominantly IgM mediated in the acute phase, then IgG dominant at late and long-term time points. The second was responses to specific Ags, most frequently myelin-associated glycopeptide (MAG), which persisted for several months post-TBI but then subsequently resolved. Exploratory analyses suggested that patients with a greater acute IgM response experienced worse outcomes than predicted from current known risk factors, suggesting a direct or indirect role in worsening outcome. Furthermore, late persistence of anti-MAG IgM autoantibodies correlated with raised serum neurofilament light concentrations at these time points, suggesting an association with ongoing neurodegeneration over the first year postinjury. Our results show that autoantibody production occurs in some individuals following TBI, can persist for many years, and is associated with worse patient outcome. The complexity of responses means that conventional approaches based on measuring responses to single antigenic targets may be misleading.
Asunto(s)
Autoanticuerpos/inmunología , Lesiones Traumáticas del Encéfalo/inmunología , Adulto , Femenino , Humanos , Masculino , Persona de Mediana Edad , Adulto JovenRESUMEN
Recent developments in proteomics technology offer new opportunities for clinical applications in hospital or specialized laboratories including the identification of novel biomarkers, monitoring of disease, detecting adverse effects of drugs, and environmental hazards. Advanced spectrometry technologies and the development of new protein array formats have brought these analyses to a standard, which now has the potential to be used in clinical diagnostics. Besides standardization of methodologies and distribution of proteomic data into public databases, the nature of the human body fluid proteome with its high dynamic range in protein concentrations, its quantitation problems, and its extreme complexity present enormous challenges. Molecular cell biology (cytomics) with its link to proteomics is a new fast moving scientific field, which addresses functional cell analysis and bioinformatic approaches to search for novel cellular proteomic biomarkers or their release products into body fluids that provide better insight into the enormous biocomplexity of disease processes and are suitable for patient stratification, therapeutic monitoring, and prediction of prognosis. Experience from studies of in vitro diagnostics and especially in clinical chemistry showed that the majority of errors occurs in the preanalytical phase and the setup of the diagnostic strategy. This is also true for clinical proteomics where similar preanalytical variables such as inter- and intra-assay variability due to biological variations or proteolytical activities in the sample will most likely also influence the results of proteomics studies. However, before complex proteomic analysis can be introduced at a broader level into the clinic, standardization of the preanalytical phase including patient preparation, sample collection, sample preparation, sample storage, measurement, and data analysis is another issue which has to be improved. In this report, we discuss the recent advances and applications that fulfill the criteria for clinical proteomics with the focus on cellular proteomics (cytoproteomics) as related to preanalytical and analytical standardization and to quality control measures required for effective implementation of these technologies and analytes into routine laboratory testing to generate novel actionable health information. It will then be crucial to design and carry out clinical studies that can eventually identify novel clinical diagnostic strategies based on these techniques and validate their impact on clinical decision making.
Asunto(s)
Células/metabolismo , Proteómica/métodos , Proteómica/tendencias , Métodos Analíticos de la Preparación de la Muestra , Biología Computacional , Humanos , Proteómica/normas , Estadística como AsuntoRESUMEN
The field of clinical proteomics offers opportunities to identify new disease biomarkers in body fluids, cells and tissues. These biomarkers can be used in clinical applications for diagnosis, stratification of patients for specific treatment, or therapy monitoring. New protein array formats and improved spectrometry technologies have brought these analyses to a level with potential for use in clinical diagnostics. The nature of the human body fluid proteome with its large dynamic range of protein concentrations presents problems with quantitation. The extreme complexity of the proteome in body fluids presents enormous challenges and requires the establishment of standard operating procedures for handling of specimens, increasing sensitivity for detection and bioinformatical tools for distribution of proteomic data into the public domain. From studies of in vitro diagnostics, especially in clinical chemistry, it is evident that most errors occur in the preanalytical phase and during implementation of the diagnostic strategy. This is also true for clinical proteomics, and especially for fluid proteomics because of the multiple pretreatment processes. These processes include depletion of high-abundance proteins from plasma or enrichment processes for urine where biological variation or differences in proteolytic activities in the sample along with preanalytical variables such as inter- and intra-assay variability will likely influence the results of proteomics studies. However, before proteomic analysis can be introduced at a broader level into the clinical setting, standardization of the preanalytical phase including patient preparation, sample collection, sample preparation, sample storage, measurement and data analysis needs to be improved. In this review, we discuss the recent technological advances and applications that fulfil the criteria for clinical proteomics, with the focus on fluid proteomics. These advances relate to preanalytical factors, analytical standardization and quality-control measures required for effective implementation into routine laboratory testing in order to generate clinically useful information. With new disease biomarker candidates, it will be crucial to design and perform clinical studies that can identify novel diagnostic strategies based on these techniques, and to validate their impact on clinical decision-making.