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Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?

ABSTRACT: GWAS involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have enabled the identification of numerous genomic biomarkers in various complex human diseases, including infectious ones. However, few of these studies are relevant for clinical practice or at the bedside. In this issue of the JCI, Nakanishi et al. characterized the clinical implications of a major genetic risk factor for COVID-19 severity and its age-dependent effect, using individual-level data in a large international multicenter consortium. This study indicates that a common COVID-19 genetic risk factor (rs10490770) associates with increased risks of morbidity and mortality, suggesting potential implications for future clinical risk management. How can the genomic biomarkers identified by GWAS be associated with the clinical outcomes of an infectious disease? In this Commentary, we evaluate the advantages and limitations of this approach.

SUBMITTER: Colona VL

PROVIDER: S-EPMC8631589 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?

Colona Vito Luigi VL Biancolella Michela M Novelli Antonio A Novelli Giuseppe G

The Journal of clinical investigation 20211201 23

GWAS involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have enabled the identification of numerous genomic biomarkers in various complex human diseases, including infectious ones. However, few of these studies are relevant for clinical practice or at the bedside. In this issue of the JCI, Nakanishi et al. characterized the clinical implications of a major genetic risk factor for COVID-19 severity and its age-dependent effect ...[more]

PMID: 34673571

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Project description:ObjectiveTo evaluate the association between common biomarkers, death and intensive care unit (ICU) admission in patients with COVID-19.DesignRetrospective cohort study. From electronic national registry data, we used Cox analysis and bootstrapping to evaluate associations between baseline levels of biomarkers and standardised absolute risks of death/ICU admission, adjusted for age and gender.SettingAll hospitals in Denmark.Participants1310 patients aged ≥18 years admitted to hospital with COVID-19 from 27th of February to 1st of May 2020, with available biochemistry data.Main outcome measuresA composite of death/ICU admission occurring within 30 days.ResultsOf the 1310 patients admitted to hospital (54.6% men; median age 73.6 years), 352 (26.9%) experienced the composite endpoint and 263 (20.1%) died. For the composite endpoint, the absolute risks for moderately and severely elevated C reactive protein (CRP) were significantly higher, 21.5% and 39.2%, respectively, compared with 5.0% for those with normal CRP. Moderately and severely elevated leucocytes were significantly higher, 34.5% and 46.6% risk, respectively, compared with 23.2% for those with normal leucocytes. Moderately and severely decreased estimated glomerular filtration rates (eGFR) were significantly higher, 41.5% and 45.9% risk, respectively, compared with 30.4% for those with normal/mildly decreased eGFR. Normal and elevated ureas were significantly higher, 22.3% and 40.6% risk, respectively, compared with 7.3% for those with low urea. Elevated D-dimer was significantly higher, 31.8% risk, compared with 17.5% for those with normal D-dimer. Moderately and severely elevated troponins were significantly higher, 27.7% and 57.3% risk, respectively, compared with 9.4% for those with normal troponin. Elevated procalcitonin was significantly higher, 52.1% risk, compared with 28.0% for those with normal procalcitonin.ConclusionIn this nationwide study of patients admitted with COVID-19, elevated levels of CRP, leucocytes, procalcitonin, urea, troponins and D-dimer, and low levels of eGFR were associated with higher standardised absolute risk of death/ICU admission within 30 days.

Project description: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.

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Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?

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Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?

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