Large-scale study could help inform novel COVID-19 treatment strategies.
A new analysis of data from the Veterans Affairs Million Veteran Program has uncovered genetic links between COVID-19 severity and various medical conditions that are known risk factors for severe COVID-19. Anurag Verma of the Corporal Michael Crescenz VA Medical Center in Philadelphia, Pennsylvania, US, and colleagues published these findings on April 28th, 2022, in the open-access journal PLOS Genetics.
Some patients with COVID-19 have a more severe case of the disease than others. Previous research has found certain variants in specific human genes that are linked with a person experiencing more severe COVID-19. Some of these variations may also be associated with other medical conditions that may already be well understood; discovering these shared variants could increase understanding of COVID-19 and reveal potential new paths for treatment.
To identify shared variants, Verma and colleagues used an unprecedented dataset of genotypic information linked to electronic health record data (EHR) for more than 650,000 U.S. veterans. They conducted a type of analysis known as a phenome-wide association study (PheWAS) to examine links between variants often found in Veterans who experienced severe COVID-19 and variants associated with a broad selection of medical conditions.
The analysis revealed that certain variants associated with COVID-19 are also associated with known risk factors for COVID-19. Particularly strong links were found for variants associated with venous embolism and thrombosis, as well as type 2 diabetes and ischemic heart disease—two known COVID-19 risk factors.
The analysis also found genetic links between severe COVID-19 and neutropenia for Veterans of African and Hispanic ancestry; these links did not appear for those of European ancestry.
Among respiratory conditions, idiopathic pulmonary fibrosis and chronic alveolar lung disease shared genetic links with severe COVID-19, but other respiratory infections and chronic obstructive pulmonary disease (COPD) did not. Some variants associated with severe COVID-19 were also associated with reduced risk of autoimmune conditions, such as psoriasis and lupus. These findings highlight the need to carefully weigh various aspects of the immune system when developing new treatments.
Despite some limitations of the PheWAS method, these findings could help deepen understanding of COVID-19 and guide development of new treatments.
Verma concludes, “The study demonstrates the value and impact of large biobanks linking genetic variations with EHR data in public health response to the current and future pandemics. MVP is one of the most diverse cohorts in the US. We had a unique opportunity to scan thousands of conditions documented before the COVID-19 pandemic. We gained insights into the genetic architecture of COVID-19 risk factors and disease complication.”
“One thing that stood out to us was the high number of immune-mediated conditions that shared genetic architecture with severe manifestations of COVID-19,” coauthor Katherine Liao adds. “The nature of the associations brought to light how the SARS-CoV2 virus pushes on a pressure point in the human immune system and its constant balancing act of fighting infection while maintaining enough control so that it does not also become an autoimmune process, attacking self.”
Reference: “A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program” by Anurag Verma, Noah L. Tsao, Lauren O. Thomann, Yuk-Lam Ho, Sudha K. Iyengar, Shiuh-Wen Luoh, Rotonya Carr, Dana C. Crawford, Jimmy T. Efird, Jennifer E. Huffman, Adriana Hung, Kerry L. Ivey, Michael G. Levin, Julie Lynch, Pradeep Natarajan, Saiju Pyarajan, Alexander G. Bick, Lauren Costa, Giulio Genovese, Richard Hauger, Ravi Madduri, Gita A. Pathak, Renato Polimanti, Benjamin Voight, Marijana Vujkovic, Seyedeh Maryam Zekavat, Hongyu Zhao, Marylyn D. Ritchie, VA Million Veteran Program COVID-19 Science Initiative, Kyong-Mi Chang, Kelly Cho, Juan P. Casas, Philip S. Tsao, J. Michael Gaziano, Christopher O’Donnell, Scott M. Damrauer and Katherine P. Liao, 28 April 2022, PLOS Genetics.
Funding: This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by award MVP035. S.M.D. is supported by US Department of Veterans Affairs (IK2-CX001780). R.C. is supported by NIH grants R01 AA026302 and P30 DK0503060. K.P.L. is supported by NIH P30 AR072577, and the Harold and Duval Bowen Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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