The Challenge to Search for New Nervous System Disease Biomarker Candidates: the Opportunity to Use the Proteogenomics Approach.
Thais Guimarães Martins NeryEsdras Matheus SilvaRaphael TavaresFabio PassettiPublished in: Journal of molecular neuroscience : MN (2018)
Alzheimer's disease, Parkinson's disease, prion diseases, schizophrenia, and multiple sclerosis are the most common nervous system diseases, affecting millions of people worldwide. The current scientific literature associates these pathological conditions to abnormal expression levels of certain proteins, which in turn improved the knowledge concerning normal and affected brains. However, there is no available cure or preventive therapy for any of these disorders. Proteogenomics is a recent approach defined as the data integration of both nucleotide high-throughput sequencing and protein mass spectrometry technologies. In the last years, proteogenomics studies in distinct diseases have emerged as a strategy for the identification of uncharacterized proteoforms, which are all the different protein forms derived from a single gene. For many of these diseases, at least one protein used as biomarker presents more than one proteoform, which fosters the analysis of publicly available data focusing proteoforms. Given this context, we describe the most important biomarkers for each neurodegenerative disease and how genomics, transcriptomics, and proteomics separately contributed to unveil them. Finally, we present a selection of proteogenomics studies in which the combination of nucleotide and proteome high-throughput data, from cell lines or brain tissue samples, is used to uncover proteoforms not previously described. We believe that this new approach may improve our knowledge about nervous system diseases and brain function and an opportunity to identify new biomarker candidates.
Keyphrases
- mass spectrometry
- multiple sclerosis
- high throughput
- healthcare
- single cell
- electronic health record
- white matter
- big data
- systematic review
- protein protein
- resting state
- transcription factor
- high throughput sequencing
- dna methylation
- amino acid
- high performance liquid chromatography
- ms ms
- cognitive decline
- sensitive detection
- gas chromatography
- quantum dots