Human cerebrospinal fluid data for use as spectral library, for biomarker research
Lukas M. Schilde,
Simone Steinbach,
Bettina Serschnitzki,
Fabian Maass,
Mathias Bähr,
Paul Lingor,
Katrin Marcus,
Caroline May
Affiliations
Lukas M. Schilde
Ruhr-University Bochum, Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Germany; Ruhr-University Bochum, Medical Faculty, Medizinisches Proteom-Center, Germany
Simone Steinbach
Ruhr-University Bochum, Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Germany; Ruhr-University Bochum, Medical Faculty, Medizinisches Proteom-Center, Germany
Bettina Serschnitzki
Ruhr-University Bochum, Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Germany; Ruhr-University Bochum, Medical Faculty, Medizinisches Proteom-Center, Germany
Fabian Maass
Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
Mathias Bähr
Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
Paul Lingor
Department of Neurology, University Medical Center Göttingen, Göttingen, Germany; Center for Biostructural Imaging of Neurodegeneration (BIN), University of Göttingen Medical Center, Göttingen, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, München, Germany
Katrin Marcus
Ruhr-University Bochum, Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Germany; Ruhr-University Bochum, Medical Faculty, Medizinisches Proteom-Center, Germany; Corresponding authors.
Caroline May
Ruhr-University Bochum, Center for Protein Diagnostics (PRODI), Medical Proteome Analysis, Germany; Ruhr-University Bochum, Medical Faculty, Medizinisches Proteom-Center, Germany; Corresponding authors.
Spectral libraries generated by data dependent acquisition (DDA) are a useful tool for the analysis of data created by data independent acquisition (DIA) in mass spectrometry. The quality of DIA analysis is dependent on the quality of the spectral library. We used cerebrospinal fluid (CSF) of patients with Parkinson's disease and healthy controls to create a spectral library of human CSF proteome. To this date, there is no validated CSF biomarker for Parkinson's disease. This data set may therefore be valuable for the future analysis of CSF proteins. Part of the samples consisted of fractions that were separated by gel electrophoresis. After tryptic digestion, all samples were spiked with indexed retention time (iRT) peptides and were measured using a DDA mass spectrometry approach. The here provided data set can be used as a CSF-specific spectral library. Data files generated from the described workflow are hosted in the public repository ProteomeXchange under the identifier PXD013487.
