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HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort
BACKGROUND: The Human Leukocyte Antigen (HLA) gene locus plays a fundamental role in human immunity, and it is established that certain HLA alleles are disease determinants. Previously, we have identified prevalent HLA class I and class II alleles, including DPA1*02:02, in two small patient cohorts...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522641/ https://www.ncbi.nlm.nih.gov/pubmed/34722002 http://dx.doi.org/10.7717/peerj.12368 |
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author | Warren, René L. Birol, Inanc |
author_facet | Warren, René L. Birol, Inanc |
author_sort | Warren, René L. |
collection | PubMed |
description | BACKGROUND: The Human Leukocyte Antigen (HLA) gene locus plays a fundamental role in human immunity, and it is established that certain HLA alleles are disease determinants. Previously, we have identified prevalent HLA class I and class II alleles, including DPA1*02:02, in two small patient cohorts at the COVID-19 pandemic onset. METHODS: We have since analyzed a larger public patient cohort data (n = 126 patients) with controls, associated demographic and clinical data. By combining the predictive power of multiple in silico HLA predictors, we report on HLA-I and HLA-II alleles, along with their associated risk significance. RESULTS: We observe HLA-II DPA1*02:02 at a higher frequency in the COVID-19 positive cohort (29%) when compared to the COVID-negative control group (Fisher’s exact test [FET] p = 0.0174). Having this allele, however, does not appear to put this cohort’s patients at an increased risk of hospitalization. Inspection of COVID-19 disease severity outcomes, including admission to intensive care, reveal nominally significant risk associations with A*11:01 (FET p = 0.0078) and C*04:01 (FET p = 0.0087). The association with severe disease outcome is especially evident for patients with C*04:01, where disease prognosis measured by mechanical ventilation-free days was statistically significant after multiple hypothesis correction (Bonferroni p = 0.0323). While prevalence of some of these alleles falls below statistical significance after Bonferroni correction, COVID-19 patients with HLA-I C*04:01 tend to fare worse overall. This HLA allele may hold potential clinical value. |
format | Online Article Text |
id | pubmed-8522641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85226412021-10-28 HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort Warren, René L. Birol, Inanc PeerJ Bioinformatics BACKGROUND: The Human Leukocyte Antigen (HLA) gene locus plays a fundamental role in human immunity, and it is established that certain HLA alleles are disease determinants. Previously, we have identified prevalent HLA class I and class II alleles, including DPA1*02:02, in two small patient cohorts at the COVID-19 pandemic onset. METHODS: We have since analyzed a larger public patient cohort data (n = 126 patients) with controls, associated demographic and clinical data. By combining the predictive power of multiple in silico HLA predictors, we report on HLA-I and HLA-II alleles, along with their associated risk significance. RESULTS: We observe HLA-II DPA1*02:02 at a higher frequency in the COVID-19 positive cohort (29%) when compared to the COVID-negative control group (Fisher’s exact test [FET] p = 0.0174). Having this allele, however, does not appear to put this cohort’s patients at an increased risk of hospitalization. Inspection of COVID-19 disease severity outcomes, including admission to intensive care, reveal nominally significant risk associations with A*11:01 (FET p = 0.0078) and C*04:01 (FET p = 0.0087). The association with severe disease outcome is especially evident for patients with C*04:01, where disease prognosis measured by mechanical ventilation-free days was statistically significant after multiple hypothesis correction (Bonferroni p = 0.0323). While prevalence of some of these alleles falls below statistical significance after Bonferroni correction, COVID-19 patients with HLA-I C*04:01 tend to fare worse overall. This HLA allele may hold potential clinical value. PeerJ Inc. 2021-10-15 /pmc/articles/PMC8522641/ /pubmed/34722002 http://dx.doi.org/10.7717/peerj.12368 Text en ©2021 Warren and Birol https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Warren, René L. Birol, Inanc HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort |
title | HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort |
title_full | HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort |
title_fullStr | HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort |
title_full_unstemmed | HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort |
title_short | HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort |
title_sort | hla alleles measured from covid-19 patient transcriptomes reveal associations with disease prognosis in a new york cohort |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522641/ https://www.ncbi.nlm.nih.gov/pubmed/34722002 http://dx.doi.org/10.7717/peerj.12368 |
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