Dataset Information

Venous hypertensive myelopathy LC-MS/MS

ABSTRACT: A major challenge in Spinal Dural Arteriovenous Fistula (SDAVF) was its timely diagnosis, but no specific predictive biomarkers were known. In the discovery cohort (case, n=8 vs. control, n=8), we used cerebrospinal fluid (CSF) and paired plasma samples to identify differentially expressed proteins by label-free quantitative proteomics. Further bioinformatics enrichment analyses were performed to screen target proteins. Finally, it was validated by ELISA experiment in two of the new cohort (case, n=17 vs. control, n=9).

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma, Cerebrospinal Fluid

DISEASE(S): Vascular Myelopathy

SUBMITTER: yinqing wang

LAB HEAD: China International Neuroscience Institute

PROVIDER: PXD030479 | Pride | 2022-08-11

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	MYJ_CSF_CONTROL_1_OTIT_180MIN_20200328.raw	Raw
	MYJ_CSF_CONTROL_2_OTIT_180MIN_20200328.raw	Raw
	MYJ_CSF_CONTROL_3_OTIT_180MIN_20200328.raw	Raw
	MYJ_CSF_CONTROL_4_OTIT_180MIN_20200328.raw	Raw
	MYJ_CSF_YOUCHUAN_1_OTIT_180MIN_20200328.raw	Raw

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Publications

Potential biomarkers of spinal dural arteriovenous fistula: C4BPA and C1QA.

Wang Yinqing Y Ma Yongjie Y Yang Chengbin C Huang Xiahe X Yang Kun K Lan Fei F Fu Jingxuan J Song Zihao Z Tian An A Feng Yueshan Y Tu Tianqi T Li Haifeng H Hong Tao T Wang Yingchun Y Zhang Hongqi H

Journal of neuroinflammation 20220622 1

<h4>Background and purpose</h4>A major challenge in spinal dural arteriovenous fistula (SDAVF) is timely diagnosis, but no specific predictive biomarkers are known.<h4>Methods</h4>In the discovery cohort (case, n = 8 vs. control, n = 8), we used cerebrospinal fluid (CSF) and paired plasma samples to identify differentially expressed proteins by label-free quantitative proteomics. Further bioinformatics enrichment analyses were performed to screen target proteins. Finally, it was validated by ELI ...[more]

PMID: 35733178

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Project description:The foundation for integrating mass spectrometry (MS)-based proteomics into systems medicine is to develop standardized start-to-finish and fit-for-purpose workflows for clinical specimens. An essential step in this pursuit is to highlight common ground in a diverse landscape of different sample preparation techniques and LC-MS setups with the aim to explore differences and potential confounding factors as well as to identify areas for improvement with a direct practical benefit. With the aim to benchmark and improve current best practices among the proteomics MS laboratories of the CLINSPECT-M consortium we performed two consecutive round robin studies with full freedom to operate in terms of sample preparation and MS measurements. The six participating study partners were provided with two clinically relevant sample matrices: plasma, and cerebrospinal fluid (CSF). In the first round each laboratory applied their current best practice protocol for the respective matrix, covering laboratory-specific sample proteolysis, liquid chromatography, and MS measurement procedure. All resulting MS files were analyzed centrally by a standardized pipeline. Based on the achieved results and following a fully transparent exchange of all lab-specific protocols within the consortium, each laboratory could improve their methods before measuring the same samples in a second acquisition round. The results of both measurement time points are compared with respect to identifications (IDs), data completeness, retention time and quantitative precision as well as inter-laboratory reproducibility. For instance, the number of identified protein groups was increased on average by 14% for CSF and 5% for plasma from first to second measurement round across participants resulting in a median overlap number of 579 protein groups for CSF and 246 IDs for plasma across setups. The individual performances of participating study centers and the inter-laboratory reproducibility were improved in the second measurement, emphasizing the effect and importance of expert-driven exchange of best practices. In total, the study not only clearly demonstrates the beneficial effect of sharing knowledge and expertise for direct practical improvements but also highlights tendencies such as common limits of detection or preferable preparation strategies.