Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program.
<h4>Background</h4>The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.<h4>Methods and resul...
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doaj-5546908fd7844c93a3ce0df05a8a0d662021-05-29T04:31:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01165e025165110.1371/journal.pone.0251651Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program.Rebecca J SongYuk-Lam HoPetra SchubertYojin ParkDaniel PosnerEmily M LordLauren CostaHanna GerlovinKatherine E KurganskyTori Anglin-FooteScott DuVallJennifer E HuffmanSaiju PyarajanJean C BeckhamKyong-Mi ChangKatherine P LiaoLuc DjousseDavid R GagnonStacey B WhitbourneRachel RamoniSumitra MuralidharPhilip S TsaoChristopher J O'DonnellJohn Michael GazianoJuan P CasasKelly ChoVA Million Veteran Program COVID-19 Science Initiative<h4>Background</h4>The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.<h4>Methods and results</h4>We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality.<h4>Conclusions</h4>Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.https://doi.org/10.1371/journal.pone.0251651 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rebecca J Song Yuk-Lam Ho Petra Schubert Yojin Park Daniel Posner Emily M Lord Lauren Costa Hanna Gerlovin Katherine E Kurgansky Tori Anglin-Foote Scott DuVall Jennifer E Huffman Saiju Pyarajan Jean C Beckham Kyong-Mi Chang Katherine P Liao Luc Djousse David R Gagnon Stacey B Whitbourne Rachel Ramoni Sumitra Muralidhar Philip S Tsao Christopher J O'Donnell John Michael Gaziano Juan P Casas Kelly Cho VA Million Veteran Program COVID-19 Science Initiative |
spellingShingle |
Rebecca J Song Yuk-Lam Ho Petra Schubert Yojin Park Daniel Posner Emily M Lord Lauren Costa Hanna Gerlovin Katherine E Kurgansky Tori Anglin-Foote Scott DuVall Jennifer E Huffman Saiju Pyarajan Jean C Beckham Kyong-Mi Chang Katherine P Liao Luc Djousse David R Gagnon Stacey B Whitbourne Rachel Ramoni Sumitra Muralidhar Philip S Tsao Christopher J O'Donnell John Michael Gaziano Juan P Casas Kelly Cho VA Million Veteran Program COVID-19 Science Initiative Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program. PLoS ONE |
author_facet |
Rebecca J Song Yuk-Lam Ho Petra Schubert Yojin Park Daniel Posner Emily M Lord Lauren Costa Hanna Gerlovin Katherine E Kurgansky Tori Anglin-Foote Scott DuVall Jennifer E Huffman Saiju Pyarajan Jean C Beckham Kyong-Mi Chang Katherine P Liao Luc Djousse David R Gagnon Stacey B Whitbourne Rachel Ramoni Sumitra Muralidhar Philip S Tsao Christopher J O'Donnell John Michael Gaziano Juan P Casas Kelly Cho VA Million Veteran Program COVID-19 Science Initiative |
author_sort |
Rebecca J Song |
title |
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program. |
title_short |
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program. |
title_full |
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program. |
title_fullStr |
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program. |
title_full_unstemmed |
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program. |
title_sort |
phenome-wide association of 1809 phenotypes and covid-19 disease progression in the veterans health administration million veteran program. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2021-01-01 |
description |
<h4>Background</h4>The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.<h4>Methods and results</h4>We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality.<h4>Conclusions</h4>Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted. |
url |
https://doi.org/10.1371/journal.pone.0251651 |
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