Evidence map›Paper›PMID 38354037›Full record

ArticleJMIR research protocols2024

Genomic, Proteomic, and Phenotypic Biomarkers of COVID-19 Severity: Protocol for a Retrospective Observational Study.

Andrew English, Darren McDaid, Seodhna M Lynch, Joseph McLaughlin, Eamonn Cooper, Benjamin Wingfield, Martin Kelly, Manav Bhavsar, Victoria McGilligan, Rachelle E Irwin and 8 more

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 3 institutions in 2 countries.

Andrew EnglishPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0003-1232-5585
Darren McDaidPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-5080-2090
Seodhna M LynchPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-5738-1129
Joseph McLaughlinPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0009-0002-7818-7226
Eamonn CooperPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0003-0432-016X
Benjamin WingfieldPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-2913-0779
Martin KellyWestern Health Social Care Trust, Londonderry, United Kingdom.ORCID https://orcid.org/0000-0003-1462-815X
Manav BhavsarWestern Health Social Care Trust, Londonderry, United Kingdom.ORCID https://orcid.org/0009-0005-5180-2075
Victoria McGilliganPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0003-1013-3504
Rachelle E IrwinPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-6137-1716
Magda BucholcPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-8417-1602
Shu-Dong ZhangPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-7721-0167
Priyank ShuklaPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-4985-9305
Taranjit Singh RaiPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-7276-7492
Anthony J BjoursonPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0002-1105-7147
Elaine MurrayPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0003-0170-6809
David S GibsonPersonalised Medicine Centre, School of Medicine, Ulster University, Derry/Londonderry, United Kingdom.ORCID https://orcid.org/0000-0003-3547-5551
Colum WalshDepartment of Biomedical and Clinical Sciences, Linköping University, Uppsala, Sweden.ORCID https://orcid.org/0000-0001-9921-7506
University of Ulster · GBWestern Health and Social Care Trust · GBLinköping University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth organizations and countries around the world have found it difficult to control the spread of COVID-19. To minimize the future impact on the UK National Health Service and improve patient care, there is a pressing need to identify individuals who are at a higher risk of being hospitalized because of severe COVID-19. Early targeted work was successful in identifying angiotensin-converting enzyme-2 receptors and type II transmembrane serine protease dependency as drivers of severe infection. Although a targeted approach highlights key pathways, a multiomics approach will provide a clearer and more comprehensive picture of severe COVID-19 etiology and progression.

objectiveThe COVID-19 Response Study aims to carry out an integrated multiomics analysis to identify biomarkers in blood and saliva that could contribute to host susceptibility to SARS-CoV-2 and the development of severe COVID-19.

methodsThe COVID-19 Response Study aims to recruit 1000 people who recovered from SARS-CoV-2 infection in both community and hospital settings on the island of Ireland. This protocol describes the retrospective observational study component carried out in Northern Ireland (NI; Cohort A); the Republic of Ireland cohort will be described separately. For all NI participants (n=519), SARS-CoV-2 infection has been confirmed by reverse transcription-quantitative polymerase chain reaction. A prospective Cohort B of 40 patients is also being followed up at 1, 3, 6, and 12 months postinfection to assess longitudinal symptom frequency and immune response. Data will be sourced from whole blood, saliva samples, and clinical data from the electronic care records, the general health questionnaire, and a 12-item general health questionnaire mental health survey. Saliva and blood samples were processed to extract DNA and RNA before whole-genome sequencing, RNA sequencing, DNA methylation analysis, microbiome analysis, 16S ribosomal RNA gene sequencing, and proteomic analysis were performed on the plasma. Multiomics data will be combined with clinical data to produce sensitive and specific prognostic models for severity risk.

resultsAn initial demographic and clinical profile of the NI Cohort A has been completed. A total of 249 hospitalized patients and 270 nonhospitalized patients were recruited, of whom 184 (64.3%) were female, and the mean age was 45.4 (SD 13) years. High levels of comorbidity were evident in the hospitalized cohort, with cardiovascular disease and metabolic and respiratory disorders being the most significant (P<.001), grouped according to the International Classification of Diseases 10 codes.

conclusionsThis study will provide a comprehensive opportunity to study the mechanisms of COVID-19 severity in recontactable participants. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50733.

Indexed as

clinical researchcomorbidityCOVID-19electronic health recordmultiomicsseverity

Identifiers

PMID38354037
PMCPMC10868637
OpenAlexW4388523918

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.