D03 Quality control for plasma and cerebrospinal fluid samples using mass spectrometry. (September 2018)

• Record Type: Journal Article
• Authors: Skotte, Niels H; Geyer, Phillip E; Steger, Martin; Treit, Peter V; Voytik, Eugenia; Hellem, Marie NN; Nielsen, Jørgen E; Mann, Matthias
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 89(2018)Supplement 1
• Page Start: A31
• Page End: A32
• Publication Date: 2018-09
• Subjects: Biomarker -- Plasma -- Cerebrospinal fluid -- Quality control -- mass spectrometry -- proteomics; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2018-EHDN.85
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Identification and quantification of disease-associated proteins in human biofluids is much needed for monitoring disease progression in HD gene expression carriers as well as providing means for monitoring therapeutic intervention. We believe studying biofluids with cutting-edge proteomics tools will help these unmet needs and provide novel leads for further validation and use in the clinic. To this end, the cerebrospinal fluid (CSF) is an accessible source enriched for brain derived peptides as well as proteins, which allows us to investigate changes in the CNS physiology. Similarly, plasma is of great importance for evaluating systemic changes in protein secretion and can act as a secondary source of CSF proteins drained into and found in blood circulation. High-throughput quantitative analysis of plasma and CSF is challenging because of the high dynamic range of protein abundances. However, dramatic improvements in mass spectrometry (MS)-based proteomics and advances biofluid proteome profiling have recently been achieved, which have rekindled the interest and the hope for new biomarker discoveries. Here, we describe our robust and streamlined shotgun proteomics pipeline that allows rapid and unbiased analysis of hundreds of proteins in plasma and CSF and introduce sample quality control criteria that may provide valuable insights in understanding preanalytical variables as well as forming the foundation for sample inclusion/exclusion for future biomarker studies.