ArticleHuman genomics2023
Analyzing the role of ACE2, AR, MX1 and TMPRSS2 genetic markers for COVID-19 severity.
Article in Human genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 9 citations in OpenAlex.
- DNAm landscape up to 4 months post SARS-CoV-2 infection: insights from four population-based cohorts.Clinical epigenetics · 2026Article
- A model including CD15, ACE2 and age efficiently predicts COVID-19 severity.Scientific reports · 2025Article
- Identification of aberrant interferon-stimulated gene associated host responses potentially linked to poor prognosis in COVID-19 during the Omicron wave.Virology journal · 2025Article
- Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.International journal of molecular sciences · 2025Article
- Dynamic Gene Attention Focus (DyGAF): Enhancing Biomarker Identification Through Dual-Model Attention Networks.Bioinformatics and biology insights · 2025Article
- Integration of T cell repertoire, CyTOF, genotyping and symptomatology data reveals subphenotypic variability in COVID-19 patients.Computational and structural biotechnology journal · 2025Article
- The T-cell repertoire of Spanish patients with COVID-19 as a strategy to link T-cell characteristics to the severity of the disease.Human genomics · 2024Article
- A Machine Learning-Based Web Tool for the Severity Prediction of COVID-19.Biotech (Basel (Switzerland)) · 2024Article
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Authors and funding
11 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe use of molecular biomarkers for COVID-19 remains unconclusive. The application of a molecular biomarker in combination with clinical ones that could help classifying aggressive patients in first steps of the disease could help clinician and sanitary system a better management of the disease. Here we characterize the role of ACE2, AR, MX1, ERG, ETV5 and TMPRSS2 for trying a better classification of COVID-19 through knowledge of the disease mechanisms.
methodsA total of 329 blood samples were genotyped in ACE2, MX1 and TMPRSS2. RNA analyses were also performed from 258 available samples using quantitative polymerase chain reaction for genes: ERG, ETV5, AR, MX1, ACE2, and TMPRSS2. Moreover, in silico analysis variant effect predictor, ClinVar, IPA, DAVID, GTEx, STRING and miRDB database was also performed. Clinical and demographic data were recruited from all participants following WHO classification criteria.
resultsWe confirm the use of ferritin (p < 0.001), D-dimer (p < 0.010), CRP (p < 0.001) and LDH (p < 0.001) as markers for distinguishing mild and severe cohorts. Expression studies showed that MX1 and AR are significantly higher expressed in mild vs severe patients (p < 0.05). ACE2 and TMPRSS2 are involved in the same molecular process of membrane fusion (p = 4.4 × 10
conclusionsIn addition to the key role of TMPSRSS2, we reported for the first time that higher expression levels of AR are related with a decreased risk of severe COVID-19 disease in females. Moreover, functional analysis demonstrates that ACE2, MX1 and TMPRSS2 are relevant markers in this disease.
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