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Assessing Causal Associations of T2D and Obesity with Severe COVID-19 Using Mendelian Randomization

Abstract Number:

2001 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Wonil Chung (1), Taesung Park (2), Liming Liang (3)

Institutions:

(1) Soongsil University, Seoul, Korea, (2) Seoul National University, Seoul, Korea, (3) Harvard School of Public Health, Boston, MA

Co-Author(s):

Taesung Park  
Seoul National University
Liming Liang  
Harvard School of Public Health

First Author:

Wonil Chung  
Soongsil University

Presenting Author:

Wonil Chung  
N/A

Abstract Text:

Observational studies have reported high comorbidity between type 2 diabetes (T2D), obesity, and severe COVID-19. However, the causality among T2D, obesity, and severe COVID-19 has not yet been fully validated. We performed genetic correlation and Mendelian randomization (MR) analyses to assess genetic relationships and potential causal associations of T2D and obesity with two COVID-19 outcomes: SARS-CoV-2 infection and COVID-19 severity. Our study incorporated two-sample MR, one-sample MR, and nonlinear MR analyses, utilizing summary-level and individual-level data from the GIANT and DIAGRAM consortia, and the UK Biobank. We identified a high genetic overlap between T2D and each of the COVID-19 outcomes. The two-sample MR analyses indicate that genetic liability to T2D confers a causal effect on COVID-19 severity (beta=0.1500, p=0.0012), and genetic liability to body mass index (BMI) exerts a causal effect on COVID-19 severity (beta=0.3958, p=4.36e-18). The results from the one-sample and nonlinear MR analyses suggest similar causal relationships of T2D and BMI with COVID-19 outcomes. Our analyses conclude that T2D and obesity are causal risk factors for COVID-19 severity.

Keywords:

Mendelian Randomization|Causal Inference|Type 2 diabetes|Obesity|COVID-19|

Sponsors:

Section on Statistics in Genomics and Genetics

Tracks:

Miscellaneous

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