Background There is considerable variability in COVID-19 outcomes among younger adults, and some of this variation may be due to genetic predisposition.Methods We combined individual level data from 13,888 COVID-19 patients (n = 7185 hospitalized) from 17 cohorts in 9 countries to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. We next performed metaanalyses using FinnGen and the Columbia University COVID-19 Biobank.Results We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (HR, 1.4; 95% CI, 1.2–1.7). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (OR, 2.1; 95% CI, 1.6–2.6), venous thromboembolism (OR, 1.7; 95% CI, 1.2–2.4), and hepatic injury (OR, 1.5; 95% CI, 1.2–2.0). Risk allele carriers age 60 years and younger had higher odds of death or severe respiratory failure (OR, 2.7; 95% CI, 1.8–3.9) compared with those of more than 60 years (OR, 1.5; 95% CI, 1.2–1.8; interaction, P = 0.038). Among individuals 60 years and younger who died or experienced severe respiratory failure, 32.3% were risk-variant carriers compared with 13.9% of those not experiencing these outcomes. This risk variant improved the prediction of death or severe respiratory failure similarly to, or better than, most established clinical risk factors.Conclusions The major common COVID-19 genetic risk factor is associated with increased risks of morbidity and mortality, which are more pronounced among individuals 60 years or younger. The effect was similar in magnitude and more common than most established clinical risk factors, suggesting potential implications for future clinical risk management.
Tomoko Nakanishi, Sara Pigazzini, Frauke Degenhardt, Mattia Cordioli, Guillaume Butler-Laporte, Douglas Maya-Miles, Luis Bujanda, Youssef Bouysran, Mari E.K. Niemi, Adriana Palom, David Ellinghaus, Atlas Khan, Manuel Martínez-Bueno, Selina Rolker, Sara Amitrano, Luisa Roade Tato, Francesca Fava, FinnGen, The COVID-19 Host Genetics Initiative (HGI), Christoph D. Spinner, Daniele Prati, David Bernardo, Federico Garcia, Gilles Darcis, Israel Fernández-Cadenas, Jan Cato Holter, Jesus M. Banales, Robert Frithiof, Krzysztof Kiryluk, Stefano Duga, Rosanna Asselta, Alexandre C. Pereira, Manuel Romero-Gómez, Beatriz Nafría-Jiménez, Johannes R. Hov, Isabelle Migeotte, Alessandra Renieri, Anna M. Planas, Kerstin U. Ludwig, Maria Buti, Souad Rahmouni, Marta E. Alarcón-Riquelme, Eva C. Schulte, Andre Franke, Tom H. Karlsen, Luca Valenti, Hugo Zeberg, J. Brent Richards, Andrea Ganna
Usage data is cumulative from April 2024 through April 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 2,683 | 267 |
180 | 182 | |
Figure | 246 | 5 |
Table | 184 | 0 |
Supplemental data | 188 | 6 |
Citation downloads | 117 | 0 |
Totals | 3,598 | 460 |
Total Views | 4,058 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.