The Impact of Post-Genomics Approaches in Neurodegenerative Demyelinating Diseases: The Case of Guillain-Barré Syndrome.

BACKGROUND

Why an autoimmune disease that is the main cause of the acute neuromuscular paralysis worldwide does not have a well-characterized cause or an effective treatment yet? The existence of different clinical variants for the Guillain-Barré syndrome (GBS) coupled with the fact that a high number of pathogens can cause an infection that sometimes, but not always, precedes the development of the syndrome, confers a high degree of uncertainty for both prognosis and treatment. In the post-genomic era, the development of omics technologies for the high-throughput analysis of biological molecules is allowing the characterization of biological systems in a degree of depth unimaginable before. In this context, this work summarizes the application of post-genomics technologies to the study of GBS.

METHODS

We performed a structured search of bibliographic databases for peer-reviewed research literature to outline the state of the art with regard the application of post-genomics technologies to the study of GBS. The quality of retrieved papers was assessed using standard tools and thirty-four were included in the review. To date, transcriptomics and proteomics have been the unique post-genomics approaches applied to GBS study. Most of these studies have been performed on cerebrospinal fluid samples and only a few studies have been conducted with other samples such as serum, Schwann cells and human peripheral nerve.

RESULTS AND CONCLUSION

In the post-genomics era, transcriptomics and proteomics have shown the possibilities that omics technologies can offer for a better understanding of the immunological and pathological mechanisms involved in GBS and the identification of potential biomarkers, but these results have only shown the tip of the iceberg and there is still a long way to exploit the full potential that post-genomics approaches could offer to the study of the GBS. The integration of different omics datasets through a systems biology approach could allow network-based analyses to describe the complexity and functionality of the molecular mechanisms involved in the course of disease facilitating the discovery of novel biomarkers that could be used to improve the diagnosis, predict the disease progression, improve our understanding of the pathology, and serve as therapeutic targets for GBS.