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

• Published in: PloS one Vol. 16; no. 5; p. e0251651
• Main Authors: Song, Rebecca J, Ho, Yuk-Lam, Schubert, Petra, Park, Yojin, Posner, Daniel, Lord, Emily M, Costa, Lauren, Gerlovin, Hanna, Kurgansky, Katherine E, Anglin-Foote, Tori, DuVall, Scott, Huffman, Jennifer E, Pyarajan, Saiju, Beckham, Jean C, Chang, Kyong-Mi, Liao, Katherine P, Djousse, Luc, Gagnon, David R, Whitbourne, Stacey B, Ramoni, Rachel, Muralidhar, Sumitra, Tsao, Philip S, O'Donnell, Christopher J, Gaziano, John Michael, Casas, Juan P, Cho, Kelly
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 13.05.2021; Public Library of Science (PLoS)
• Subjects: Aging; Analysis; Asthma; Asymptomatic; Bioinformatics; Biology and life sciences; Cardiovascular diseases; Computer and Information Sciences; Coronaviruses; COVID-19; Data analysis; Diabetes; Diabetes mellitus; Disease; Editing; Electronic health records; Electronic medical records; Epidemiology; Funding; Health care; Health care facilities; Health care policy; Health risks; Hospital administration; Hospitalization; Information centers; Lam Ho; Medical electronics; Medical schools; Medicine; Medicine and Health Sciences; Mental disorders; Methodology; Phenotype; Phenotypes; Psychiatry; Public health; R&D; Research & development; Reviews; Risk analysis; Risk factors; Severe acute respiratory syndrome coronavirus 2; Socio-economic aspects; Socioeconomics; Toruses; Veterans; Viral diseases; Womens health; United States; North Carolina; Palo Alto California; United States > US; Massachusetts; California; Utah; Pennsylvania
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0251651

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.