Dataset Information

Biomarker identification in hospitalised patients with COVID-19: a cohort study of acute infection and convalescence.

ABSTRACT: Pilot bottom-up depleted proteomic analysis of patients from the ManARTS COVID-19 cohort in early stages of the pandemic, for method development of high-throughput proteomics using small volumes of plasma and a 15-minute gradient. Demonstrates proof-of-concept for stratifying patients in an opportunistically collected cohort in a pandemic setting using available hospital data. Convalescent patients were used as an age and sex-matched comparator group against critically ill patients with a current infection.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

DISEASE(S): Covid-19

SUBMITTER: Shaufa Shareef

LAB HEAD: EN Clare Mills

PROVIDER: PXD061500 | Pride | 2026-06-08

REPOSITORIES: pride

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Dataset's files

Source:

			Action	DRS
	COVID_depleted_sample_pos_17_001.raw.zip	Raw
	COVID_depleted_sample_pos_17_002.raw.zip	Raw
	COVID_depleted_sample_pos_17_003.raw.zip	Raw
	COVID_depleted_sample_pos_18_001.raw.zip	Raw
	COVID_depleted_sample_pos_18_002.raw.zip	Raw

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Publications

Characterisation of a cohort of opportunistically recruited patients with COVID-19 and approaches to patient stratification.

Shareef Shaufa S Matthews Eleanor E Dodds Joseph J Silverberg Alasdair A Daly Matthew E ME Ahmed Waqar W Bannard-Smith Jonathan J Gethings Lee A LA King Adam A Hughes Chris C Fowler Stephen S Felton Timothy T Simpson Angela A Mills E N C ENC

BMC infectious diseases 20260331 1

Multiomic biomarker discovery generally uses well curated cohorts of patients and health individuals, although this can present challenges in validation and deployment of biomarkers for diagnosis in “real world” situations. An alternative approach is to use cohorts of patients in routine clinical care, but this necessitates identification of relevant comparator groups. In infectious disease one option is to compare patients with a current infection with those who are convalescent. This approach ...[more]

PMID: 41917819

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