Discovery and longitudinal evaluation of candidate biomarkers for ischaemic stroke by mass spectrometry-based proteomics
Dagonnier, Marie, Cooke, Ira Robin, Faou, Pierre, Sidon, Tara Kate, Dewey, Helen Margaret, Donnan, Geoffrey Alan, and Howells, David William (2017) Discovery and longitudinal evaluation of candidate biomarkers for ischaemic stroke by mass spectrometry-based proteomics. Biomarker Insights, 12.
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Abstract
Application of acute therapies such as thrombolysis for ischaemic stroke (IS) is constrained because of diagnostic uncertainty and the dynamic nature of stroke biology. To investigate changes in blood proteins after stroke and as a result of thrombolysis treatment we performed label-free quantitative proteomics on serum samples using high-resolution mass spectrometry and long high-performance liquid chromatography gradient (5 hours) combined with a 50-cm column to optimise the peptide separation. We identified (false discovery rate [FDR]: 1%) and quantified a total of 574 protein groups from a total of 92 samples from 30 patients. Ten patients were treated by thrombolysis as part of a randomised placebo-controlled trial and up to 5 samples were collected from each individual at different time points after stroke. We identified 26 proteins differently expressed by treatment group (FDR: 5%) and significant changes of expression over time for 23 proteins (FDR: 10%). Molecules such as fibrinogen and C-reactive protein showed expression profiles with a high-potential clinical utility in the acute stroke setting. Protein expression profiles vary acutely in the blood after stroke and have the potential to allow the construction of a stroke clock and to have an impact on IS treatment decision making.
| Item ID: | 53245 |
|---|---|
| Item Type: | Article (Research - C1) |
| ISSN: | 1177-2719 |
| Keywords: | stroke; biomarker; protein expression; mass spectrometry |
| Additional Information: | This Open Access article is distributed under CC BY-NC which permits non-commercial use of the work without further permission provided the work is fully attributed. |
| Date Deposited: | 23 Apr 2018 05:17 |
| FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3205 Medical biochemistry and metabolomics > 320506 Medical biochemistry - proteins and peptides (incl. medical proteomics) @ 70% 31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310205 Proteomics and metabolomics @ 30% |
| SEO Codes: | 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920103 Cardiovascular System and Diseases @ 50% 97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 50% |
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