| Title: | Association Between Genetic Predictors for C-Reactive Protein and Venous Thromboembolism With Severe Adverse Coronavirus Disease 2019 Outcomes |
| Journal: | Critical Care Explorations |
| Published: | 1 Dec 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34957408/ |
| DOI: | https://doi.org/10.1097/cce.0000000000000602 |
Publication 13818
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Abstract
To assess if genetic predictors for C-reactive protein and risk of venous thromboembolism are associated with severe outcomes among individuals who tested positive for severe acute respiratory syndrome coronavirus 2.</p>
DESIGN: Retrospective cohort study.</p>
SETTING: U.K. Biobank.</p>
PATIENTS OR SUBJECTS: U.K. Biobank participants with European ancestry who were recorded to have a positive polymerase chain reaction test result for severe acute respiratory syndrome coronavirus 2 between March 16, 2020, and August 14, 2020.</p>
INTERVENTIONS: Not applicable.</p>
MEASUREMENTS AND MAIN RESULTS: We constructed separate genetic risk scores for C-reactive protein and venous thromboembolism consisting of 56 and 37 genetic variants that have been significantly associated with venous thromboembolism and C-reactive protein, respectively. Among 1,126 individuals who were diagnosed with coronavirus disease 2019, 48% had a coronavirus disease 2019-related hospitalization, 16% received critical care support, 10% had critical respiratory support, and 21% died from coronavirus disease 2019. Genetic predisposition to high C-reactive protein concentrations was marginally associated with a lower risk of death from coronavirus disease 2019 (odds ratio, 0.85; 95% CI, 0.73-1.00; p = 0.05). No other associations were significant.</p>
CONCLUSIONS: Our results do not support associations between polygenic risk for elevated blood C-reactive protein concentrations or venous thromboembolism and severe coronavirus disease 2019 health outcomes. Thus, considering genetic predisposition associated with C-reactive protein concentrations or venous thromboembolism risk is not meaningful for predicting severe coronavirus disease 2019 health outcomes.</p>
6 Authors
- Boya Guo
- Jessica Williams-Nguyen
- Lu Wang
- Cameron B Haas
- Christopher Kabrhel
- Sara Lindström
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