Bioinformatic-driven search for metabolic biomarkers in disease

Abstract

The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data analysis and interpretation. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics, focusing on the problem of data preprocessing and consolidation, the data-driven search, verification, prioritization and biological interpretation of putative metabolic candidate biomarkers in disease. In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies, are reviewed and case examples of selected discovery steps are delineated in more detail. This review demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application.

Potential significance of telocytes in the pathogenesis of lung diseases

“…Telocytes may be a new target cell for the prevention and treatment of lung diseases, although there is still a need for further studies on the details of their biological functions during the pathologic status of the lung. It is important to characterize the protein profile of telocytes and explore the network of genes and proteins within telocytes by the application of proteomics and bioinformatics [29,[43][44][45][46]. Thus, it is believed that telocytes may play an important and critical role in the pathogenesis of lung diseases, and may be a potential therapeutic target for drug discovery and development.…”

Metabolic biomarkers for chronic kidney disease

“…In summary, a diverse range of metabolic alterations has been observed in individuals with impaired kidney function and in relevant animal models but, from a current perspective, it seems that only a limited set of these marker candidates has been substantiated by quality-controlled quantitative data Breier et al, 2014) analyzed using appropriate biostatistics (Baumgartner & Graber, 2008;Baumgartner et al, 2011;Baumgartner, 2013), diligent study design that allows to assess the specificity of the findings, and a mechanistic understanding often based on translational research and a detailed biochemical characterization of the involved pathways Enot et al, 2011;Breit et al, 2015). The markers fulfilling these criteria, however, certainly have a significant potential in clinical chemistry, particularly if they have been successfully replicated in independent clinical cohorts (Goek et al, 2012) …”

Mass-spectrometry-based metabolomics analysis for foodomics

“…Combined with bioinformatics, MS-based metabolomics holds promise for the discovery of potential biomarkers in relation to health and disease, helpful for personalized health and nutrition and the design of individualized interventions [103,104].…”