A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine

Salvatore, Maxwell; Gu, Tian; Mack, Jasmine A.; Prabhu Sankar, Swaraaj; Patil, Snehal; Valley, Thomas S.; Singh, Karandeep; Nallamothu, Brahmajee K.; Kheterpal, Sachin; Lisabeth, Lynda; Fritsche, Lars G.; Mukherjee, Bhramar

doi:10.3390/jcm10071351

Submit to this Journal Review for this Journal Edit a Special Issue

Article Menu

...

Open AccessArticle

A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine

Maxwell Salvatore

^1,2,3

Tian Gu

^1,2

Jasmine A. Mack

Swaraaj Prabhu Sankar

^2,4,5,

Snehal Patil

^1,2,

Thomas S. Valley

^6,7,8,

Karandeep Singh

^8,9,

Brahmajee K. Nallamothu

^7,10,

Sachin Kheterpal

^8,11,

Lynda Lisabeth

³,

Lars G. Fritsche

^1,2,4,12

and

Bhramar Mukherjee

^1,2,3,*

Department of Biostatistics, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, USA

Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI 48109, USA

Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA

⁴

Rogel Cancer Center, Michigan Medicine, Ann Arbor, MI 48109, USA

⁵

Data Office for Clinical and Translational Research, University of Michigan, Ann Arbor, MI 41809, USA

⁶

Division of Pulmonary and Critical Care Medicine, University of Michigan Medicine, Ann Arbor, MI 48109, USA

⁷

Department of Internal Medicine, Michigan Medicine, Ann Arbor, MI 48109, USA

⁸

Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI 48109, USA

⁹

Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI 48109, USA

¹⁰

Division of Cardiovascular Medicine, Michigan Medicine, Ann Arbor, MI 48109, USA

¹¹

Department of Anesthesiology, Michigan Medicine, Ann Arbor, MI 48109, USA

¹²

Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA

Show full affiliation list

Hide full affiliation list

Author to whom correspondence should be addressed.

Academic Editor: Alessandra Falchi

J. Clin. Med. 2021, 10(7), 1351; https://doi.org/10.3390/jcm10071351

Received: 10 February 2021 / Revised: 10 March 2021 / Accepted: 17 March 2021 / Published: 25 March 2021

(This article belongs to the Section Epidemiology & Public Health)

View Full-Text Download PDF

Browse Figures

Review Reports Citation Export

Abstract

Background: We performed a phenome-wide association study to identify pre-existing conditions related to Coronavirus disease 2019 (COVID-19) prognosis across the medical phenome and how they vary by race. Methods: The study is comprised of 53,853 patients who were tested/diagnosed for COVID-19 between 10 March and 2 September 2020 at a large academic medical center. Results: Pre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with intensive care unit (ICU) admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. Conclusions: Understanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery. View Full-Text

Keywords: biobank; health disparities; EHR; phenome; odds ratio; risk profile

▼ Show Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Supplementary Material

Supplementary File 1:
PDF-Document (PDF, 808 KiB)

Share and Cite

MDPI and ACS Style

Salvatore, M.; Gu, T.; Mack, J.A.; Prabhu Sankar, S.; Patil, S.; Valley, T.S.; Singh, K.; Nallamothu, B.K.; Kheterpal, S.; Lisabeth, L.; Fritsche, L.G.; Mukherjee, B. A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine. J. Clin. Med. 2021, 10, 1351. https://doi.org/10.3390/jcm10071351

AMA Style

Salvatore M, Gu T, Mack JA, Prabhu Sankar S, Patil S, Valley TS, Singh K, Nallamothu BK, Kheterpal S, Lisabeth L, Fritsche LG, Mukherjee B. A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine. Journal of Clinical Medicine. 2021; 10(7):1351. https://doi.org/10.3390/jcm10071351

Chicago/Turabian Style

Salvatore, Maxwell, Tian Gu, Jasmine A. Mack, Swaraaj Prabhu Sankar, Snehal Patil, Thomas S. Valley, Karandeep Singh, Brahmajee K. Nallamothu, Sachin Kheterpal, Lynda Lisabeth, Lars G. Fritsche, and Bhramar Mukherjee. 2021. "A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine" Journal of Clinical Medicine 10, no. 7: 1351. https://doi.org/10.3390/jcm10071351

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine

Abstract

Supplementary Material

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI