ArticleBMC medical genomics2020
Identification of biological correlates associated with respiratory failure in COVID-19.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed, 13 citations in OpenAlex.
- Genetics of Long COVID: Exploring the Molecular Drivers of Persistent Pulmonary Vascular Disease Symptoms.Infectious disease reports · 2025Review
- Effects of Epitranscriptomic RNA Modifications on the Catalytic Activity of the SARS-CoV-2 Replication Complex.Chembiochem : a European journal of chemical biology · 2023Article
- SARS-CoV-2 Covid-19 Infection During Pregnancy and Differential DNA Methylation in Human Cord Blood Cells From Term Neonates.Epigenetics insights · 2023Article
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- Article
- Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing.Scientific reports · 2022Article
- Potential Genes Associated with COVID-19 and Comorbidity.International journal of medical sciences · 2022Article
- Article
- The Impact of IFNλ4 on the Adaptive Immune Response to SARS-CoV-2 Infection.Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research · 2021Article
- Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach.Saudi journal of biological sciences · 2021Article
- Update on human genetic susceptibility to COVID-19: susceptibility to virus and response.Human genomics · 2021Article
- COVID-19 one year into the pandemic: from genetics and genomics to therapy, vaccination, and policy.Human genomics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundCoronavirus disease 2019 (COVID-19) is a global public health concern. Recently, a genome-wide association study (GWAS) was performed with participants recruited from Italy and Spain by an international consortium group.
methodsSummary GWAS statistics for 1610 patients with COVID-19 respiratory failure and 2205 controls were downloaded. In the current study, we analyzed the summary statistics with the information of loci and p-values for 8,582,968 single-nucleotide polymorphisms (SNPs), using gene ontology analysis to determine the top biological processes implicated in respiratory failure in COVID-19 patients.
resultsWe considered the top 708 SNPs, using a p-value cutoff of 5 × 10
conclusionGene ontology and PPI analyses identified cardio-pulmonary processes that may partially explain the risk of respiratory failure in COVID-19 patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.