Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 15 01 2021
accepted: 30 04 2021
entrez: 13 5 2021
pubmed: 14 5 2021
medline: 25 5 2021
Statut: epublish

Résumé

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. 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. 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.

Sections du résumé

BACKGROUND
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.
METHODS AND RESULTS
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.
CONCLUSIONS
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.

Identifiants

pubmed: 33984066
doi: 10.1371/journal.pone.0251651
pii: PONE-D-21-01512
pmc: PMC8118298
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0251651

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Rebecca J Song (RJ)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, United States of America.

Yuk-Lam Ho (YL)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Petra Schubert (P)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Yojin Park (Y)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Daniel Posner (D)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Emily M Lord (EM)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Lauren Costa (L)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Hanna Gerlovin (H)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Katherine E Kurgansky (KE)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Tori Anglin-Foote (T)

VA Salt Lake City Health Care System, Salt Lake City, Utah, United States of America.

Scott DuVall (S)

VA Salt Lake City Health Care System, Salt Lake City, Utah, United States of America.
Office of Research and Development, Veterans Health Administration, Washington, DC, United States of America.
Department of Medicine, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.

Jennifer E Huffman (JE)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Saiju Pyarajan (S)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Division of Aging, Brigham & Women's Hospital, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

Jean C Beckham (JC)

Durham VA Medical Center, Durham, North Carolina, United States of America.
Department of Psychiatry and Behavioral Sciences, University Medical Center, Durham, North Carolina, United States of America.
VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, United States of America.

Kyong-Mi Chang (KM)

Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America.
Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.

Katherine P Liao (KP)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.
Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America.

Luc Djousse (L)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Division of Aging, Brigham & Women's Hospital, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

David R Gagnon (DR)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America.

Stacey B Whitbourne (SB)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

Rachel Ramoni (R)

Office of Research and Development, Veterans Health Administration, Washington, DC, United States of America.

Sumitra Muralidhar (S)

Office of Research and Development, Veterans Health Administration, Washington, DC, United States of America.

Philip S Tsao (PS)

Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
VA Palo Alto Health Care System, Palo Alto, California, United States of America.

Christopher J O'Donnell (CJ)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

John Michael Gaziano (JM)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Division of Aging, Brigham & Women's Hospital, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

Juan P Casas (JP)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Division of Aging, Brigham & Women's Hospital, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

Kelly Cho (K)

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.
Department of Medicine, Division of Aging, Brigham & Women's Hospital, Boston, Massachusetts, United States of America.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.

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