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Research Article
Cardiometabolic Risks of SARS-CoV-2 Hospitalization Using Mendelian Randomization
Xiaofeng Zhu
Case Western Reserve University
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Intro
Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences.
Methods & materials
We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n=2,956) and multi-ethnic populations (COVID-19 GWAS n=10,808) to better understand extant causal associations between Type II Diabetes (GWAS n=659,316), BMI (n=681,275), diastolic and systolic blood pressure, and pulse pressure (n=757,601 for each) and COVID-19 hospitalization risk across populations.
Results
Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI: 1.67, 0.96-2.92) and pulse pressure (OR, 95% CI: 1.27, 0.97-1.66) in the multi-ethnic sample.
Conclusions
Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.
Keywords
SARS-CoV-2, Mendelian Randomization, Cardiometabolic risks, hospitalization
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CURRENT STATUS: Under Review
Version 1
Posted 18 Dec, 2020
No community comments so far
Review #2 received
Received 14 Jan, 2021
Review #1 received
Received 14 Jan, 2021
Reviewer #4 agreed
On 04 Jan, 2021
Reviewer #3 agreed
On 04 Jan, 2021
Reviewer #1 agreed
On 04 Jan, 2021
Reviewer #2 agreed
On 04 Jan, 2021
Reviewers invited
Invitations sent on 04 Jan, 2021
Editor assigned
On 29 Dec, 2020
Editor invited
On 17 Dec, 2020
Submission checks complete
On 17 Dec, 2020
First submitted
On 11 Dec, 2020
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This preprint is under consideration at Scientific Reports. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Cardiometabolic Risks of SARS-CoV-2 Hospitalization Using Mendelian Randomization
Xiaofeng Zhu
Case Western Reserve University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 18 Dec, 2020
No community comments so far
Review #2 received
Received 14 Jan, 2021
Review #1 received
Received 14 Jan, 2021
Reviewer #4 agreed
On 04 Jan, 2021
Reviewer #3 agreed
On 04 Jan, 2021
Reviewer #1 agreed
On 04 Jan, 2021
Reviewer #2 agreed
On 04 Jan, 2021
Reviewers invited
Invitations sent on 04 Jan, 2021
Editor assigned
On 29 Dec, 2020
Editor invited
On 17 Dec, 2020
Submission checks complete
On 17 Dec, 2020
First submitted
On 11 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Intro
Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences.
Methods & materials
We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n=2,956) and multi-ethnic populations (COVID-19 GWAS n=10,808) to better understand extant causal associations between Type II Diabetes (GWAS n=659,316), BMI (n=681,275), diastolic and systolic blood pressure, and pulse pressure (n=757,601 for each) and COVID-19 hospitalization risk across populations.
Results
Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI: 1.67, 0.96-2.92) and pulse pressure (OR, 95% CI: 1.27, 0.97-1.66) in the multi-ethnic sample.
Conclusions
Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.
Figure 1
Figure 2
Figure 3
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.