Dataset Information

Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection

ABSTRACT: The majority of those infected by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during the first wave did not require hospitalisation. Most had a short-lived mild or asymptomatic infection, while others had symptoms that persisted for weeks or months. We performed a longitudinal targeted analysis of the plasma proteome of 156 healthcare workers (HCW) with and without lab confirmed SARS-CoV-2 infection. We hypothesized that the plasma proteome would reflect differences in the inflammatory response that linked to symptom severity and duration. We showed that perturbation of the proteome persisted for over six weeks, tracking symptom severity and antibody responses. Additionally, we identified a prognostic signature at the time of seroconversion that identified individuals likely to suffer from persistent symptoms related to SARS-CoV-2 infection.

INSTRUMENT(S): 6410 Triple Quadrupole LC/MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood Plasma

DISEASE(S): Covid-19

SUBMITTER: Gaby Captur

LAB HEAD: Dr Kevin Mills

PROVIDER: PXD036590 | Pride | 2022-10-11

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	Barts_COVID_Inflamm_panel_Plate_1_Inject_1_peakpickDONE_YE_IS.sky	Other
	Barts_COVID_Inflamm_panel_Plate_1_Inject_1_peakpickDONE_YE_IS.sky.view	Other
	Barts_COVID_Inflamm_panel_Plate_1_Inject_1_peakpickDONE_YE_IS.skyd	Other
	Barts_COVID_Inflamm_panel_Plate_1_Inject_1_peakpickDONE_YE_IS.skyl	Other
	Barts_COVID_Inflamm_panel_Plate_1_Inject_2_peakpickDONE_YE_IS.sky	Other

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Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection.

Captur Gabriella G Moon James C JC Topriceanu Constantin-Cristian CC Joy George G Swadling Leo L Hallqvist Jenny J Doykov Ivan I Patel Nina N Spiewak Justyna J Baldwin Tomas T Hamblin Matt M Menacho Katia K Fontana Marianna M Treibel Thomas A TA Manisty Charlotte C O'Brien Ben B Gibbons Joseph M JM Pade Corrina C Brooks Tim T Altmann Daniel M DM Boyton Rosemary J RJ McKnight Áine Á Maini Mala K MK Noursadeghi Mahdad M Mills Kevin K Heywood Wendy E WE

EBioMedicine 20220928

<h4>Background</h4>The majority of those infected by ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during the UK first wave (starting March 2020) did not require hospitalisation. Most had a short-lived mild or asymptomatic infection, while others had symptoms that persisted for weeks or months. We hypothesized that the plasma proteome at the time of first infection would reflect differences in the inflammatory response that linked to symptom severity and duration.<h4>Met ...[more]

PMID: 36182629

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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.