Identification of biological correlates associated with respiratory failure in COVID-19
Abstract Background Coronavirus 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. Methods Summary GWAS statistics for 1610 patients with COVI...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-12-01
|
Series: | BMC Medical Genomics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12920-020-00839-1 |
id |
doaj-1d76d07640694a3ca928d24b69eed13e |
---|---|
record_format |
Article |
spelling |
doaj-1d76d07640694a3ca928d24b69eed13e2021-04-02T20:45:28ZengBMCBMC Medical Genomics1755-87942020-12-011311610.1186/s12920-020-00839-1Identification of biological correlates associated with respiratory failure in COVID-19Jung Hun Oh0Allen Tannenbaum1Joseph O. Deasy2Department of Medical Physics, Memorial Sloan Kettering Cancer CenterDepartments of Computer Science and Applied Mathematics & Statistics, Stony Brook UniversityDepartment of Medical Physics, Memorial Sloan Kettering Cancer CenterAbstract Background Coronavirus 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. Methods Summary 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. Results We considered the top 708 SNPs, using a p-value cutoff of 5 × 10− 5, which were mapped to the nearest genes, leading to 144 unique genes. The list of genes was input into a curated database to conduct gene ontology and protein-protein interaction (PPI) analyses. The top ranked biological processes were wound healing, epithelial structure maintenance, muscle system processes, and cardiac-relevant biological processes with a false discovery rate < 0.05. In the PPI analysis, the largest connected network consisted of 8 genes. Through a literature search, 7 out of the 8 gene products were found to be implicated in both pulmonary and cardiac diseases. Conclusion Gene ontology and PPI analyses identified cardio-pulmonary processes that may partially explain the risk of respiratory failure in COVID-19 patients.https://doi.org/10.1186/s12920-020-00839-1COVID-19SARS-CoV-2Single-nucleotide polymorphismsGenome-wide association studyRespiratory failureBioinformatics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jung Hun Oh Allen Tannenbaum Joseph O. Deasy |
spellingShingle |
Jung Hun Oh Allen Tannenbaum Joseph O. Deasy Identification of biological correlates associated with respiratory failure in COVID-19 BMC Medical Genomics COVID-19 SARS-CoV-2 Single-nucleotide polymorphisms Genome-wide association study Respiratory failure Bioinformatics |
author_facet |
Jung Hun Oh Allen Tannenbaum Joseph O. Deasy |
author_sort |
Jung Hun Oh |
title |
Identification of biological correlates associated with respiratory failure in COVID-19 |
title_short |
Identification of biological correlates associated with respiratory failure in COVID-19 |
title_full |
Identification of biological correlates associated with respiratory failure in COVID-19 |
title_fullStr |
Identification of biological correlates associated with respiratory failure in COVID-19 |
title_full_unstemmed |
Identification of biological correlates associated with respiratory failure in COVID-19 |
title_sort |
identification of biological correlates associated with respiratory failure in covid-19 |
publisher |
BMC |
series |
BMC Medical Genomics |
issn |
1755-8794 |
publishDate |
2020-12-01 |
description |
Abstract Background Coronavirus 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. Methods Summary 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. Results We considered the top 708 SNPs, using a p-value cutoff of 5 × 10− 5, which were mapped to the nearest genes, leading to 144 unique genes. The list of genes was input into a curated database to conduct gene ontology and protein-protein interaction (PPI) analyses. The top ranked biological processes were wound healing, epithelial structure maintenance, muscle system processes, and cardiac-relevant biological processes with a false discovery rate < 0.05. In the PPI analysis, the largest connected network consisted of 8 genes. Through a literature search, 7 out of the 8 gene products were found to be implicated in both pulmonary and cardiac diseases. Conclusion Gene ontology and PPI analyses identified cardio-pulmonary processes that may partially explain the risk of respiratory failure in COVID-19 patients. |
topic |
COVID-19 SARS-CoV-2 Single-nucleotide polymorphisms Genome-wide association study Respiratory failure Bioinformatics |
url |
https://doi.org/10.1186/s12920-020-00839-1 |
work_keys_str_mv |
AT junghunoh identificationofbiologicalcorrelatesassociatedwithrespiratoryfailureincovid19 AT allentannenbaum identificationofbiologicalcorrelatesassociatedwithrespiratoryfailureincovid19 AT josephodeasy identificationofbiologicalcorrelatesassociatedwithrespiratoryfailureincovid19 |
_version_ |
1721546456259624960 |