| dc.description.abstract | Reversible cerebral vasoconstriction syndromes (RCVS) are a group of central nerves system disorders that show reversible multifocal cerebral arteries narrowing, thunderclap headache and less commonly focal neurologic deficits. Due to limited knowledge about RCVS, the molecule mechanism are still unknown and the diagnosis tools remain to be developed. Revealing the cerebrospinal fluid (CSF) protein compositions and expression may provide an opportunity to advance our knowledge about the role of proteins in neurological disorders and to identify novel protein biomarkers for diagnosis and treatment purposes. In our previous study, we have analyzed 40 CSF sample with data dependent acquisition mass spectrometry (DDA-MS) method and revealed 18 candidate proteins.
In this thesis, we devolved a data independent acquisition mass spectrometry (DIA-MS) method for analyzing the CSF proteome. In the first part, we have generated a RCVS proteome mass spectral library by reversed phase stagetip fractionation strategies using DDA method together with LC-MS/MS analysis. Using CSF mixture sample (N=16), a library with precursor m/z, fragment m/z, fragment relative intensity, and relative retention time (iRT) information from 958 proteins were constructed, which provide higher proteome coverage compare to 475 proteins identified without fractionation method. Compared to the public CSF spectral library which had 1647 protein, our library can provide 744 proteins identification result which is more than 612 proteins from public CSF library, because of the own library is more specific to own CSF samples. We further optimized the DIA approach for quantitative proteomics by synthetic peptides and ALD4, and 5 peptides and 1 proteins were quantified additionally. The developed DIA-MS method was applied to quantitatively compare the CSF proteome of 12 non-RCVS controls and 13 RCVS patients. All the DIA-MS data were processed by generated DIA based spectral library, spectral library based identification and quantified by integrating the peak area of fragment alignment. Totally, we increased 48 proteins into the RCVS library and identified 762 proteins in 25 CSF samples, which revealed more RCVS proteome composition of 333 proteins from previous results of 40 CSF samples by data dependent acquisition mass spectrometry (DDA-MS) method. The DIA-MS method provides more identification and also more brain originated proteins based on human proteome map.
Further quantitation show that 117 proteins are differentially expressed between the RCVS and control individuals after two tailed t test (p<0.05). The biological enrichment analysis using IPA and DAVID of 117 differentially expressed proteins (DEPs) enrich functions related to inflammation, immune response, prothrombin, leukocyte and superoxide radicals degradation. 13 of 18 candidate proteins which are selected from previous results of 40 CSF samples are identified, and 3 of 13 identified candidate proteins including PRNP, THBS4 and CA1 are also DEPs. PRNP has the increase trend in previous and currently results and is associated with prion disease, response to oxidative stress and brain originated protein. These three proteins can be the confidence candidate portions for further investigation.
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