ArticleiScience2021
Phenome-wide and expression quantitative trait locus associations of coronavirus disease 2019 genetic risk loci.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Widespread gene-environment interactions shape the immune response to SARS-CoV-2 infection in hospitalized COVID-19 patients.Nature communications · 2026Article
- Genome-wide association study for Kleiber ratio and growth efficiency traits in Lori-Bakhtiari sheep.Tropical animal health and production · 2025Article
- The multifunctional regulatory post-proline protease dipeptidyl peptidase 9 and its inhibitors: new opportunities for therapeutics.Cellular and molecular life sciences : CMLS · 2025Review
- Comprehensive analysis of genetic associations and single-cell expression profiles reveals potential links between migraine and multiple diseases: a phenome-wide association study.Frontiers in neurology · 2024Article
- Cis-meQTL for cocaine use-associated DNA methylation in an HIV-positive cohort show pleiotropic effects on multiple traits.BMC genomics · 2023Article
- Computational network analysis of host genetic risk variants of severe COVID-19.Human genomics · 2023Article
- Morphometric similarity network alterations in COVID-19 survivors correlate with behavioral features and transcriptional signatures.NeuroImage. Clinical · 2023Article
- COVID-19: impact on Public Health and hypothesis-driven investigations on genetic susceptibility and severity.Immunogenetics · 2022Review
- Prevalence of genetically defined familial hypercholesterolemia and the impact on acute myocardial infarction in Taiwanese population: A hospital-based study.Frontiers in cardiovascular medicine · 2022Article
- Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?The Journal of clinical investigation · 2021Article
- Update on human genetic susceptibility to COVID-19: susceptibility to virus and response.Human genomics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
While several genes and clinical traits have been associated with higher risk of severe coronavirus disease 2019 (COVID-19), how host genetic variants may interact with these parameters and contribute to severe disease is still unclear. Herein, we performed phenome-wide association study, tissue and immune-cell-specific expression quantitative trait locus (eQTL)/splicing quantitative trait locus, and colocalization analyses for genetic risk loci suggestively associated with severe COVID-19 with respiratory failure. Thirteen phenotypes/traits were associated with the severe COVID-19-associated loci at the genome-wide significance threshold, including monocyte counts, fat metabolism traits, and fibrotic idiopathic interstitial pneumonia. In addition, we identified tissue and immune subtype-specific eQTL associations affecting 48 genes, including several ones that may directly impact host immune responses, colocalized with the severe COVID-19 genome-wide association study associations, and showed altered expression in single-cell transcriptomes. Collectively, our work demonstrates that host genetic variations associated with multiple genes and traits show genetic pleiotropy with severe COVID-19 and may inform disease etiology.
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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 Socratic graph.