Cardiometabolic Risk Factors for COVID-19 Susceptibility and Severity: A Mendelian Randomization Analysis

Abstract

Importance: Early epidemiological studies report associations of diverse cardiometabolic conditions especially body mass index (BMI), with COVID-19 susceptibility and severity, but causality has not been established. Identifying causal risk factors is critical to inform preventive strategies aimed at modifying disease risk. Objective: We sought to evaluate the causal associations of cardiometabolic conditions with COVID-19 susceptibility and severity. Design: Two-sample Mendelian Randomization (MR) Study. Setting: Population-based cohorts that contributed to the genome-wide association study (GWAS) meta-analysis by the COVID-19 Host Genetics Initiative. Participants: Patients hospitalized with COVID-19 diagnosed by RNA PCR, serologic testing, or clinician diagnosis. Population controls defined as anyone who was not a case in the cohorts. Exposures: Selected genetic variants associated with 17 cardiometabolic diseases, including diabetes, coronary artery disease, stroke, chronic kidney disease, and BMI, at p<5 x 10-8 from published largescale GWAS. Main outcomes: We performed an inverse-variance weighted averages of variant-specific causal estimates for susceptibility, defined as people who tested positive for COVID-19 vs. population controls, and severity, defined as patients hospitalized with COVID-19 vs. population controls, and repeated the analysis for BMI using effect estimates from UKBB. To estimate direct and indirect causal effects of BMI through obesity-related cardiometabolic diseases, we performed pairwise multivariable MR. We used p<0.05/17 exposure/2 outcomes=0.0015 to declare statistical significance. Results: Genetically increased BMI was causally associated with testing positive for COVID-19 [6,696 cases / 1,073,072 controls; p=6.7 x 10-4, odds ratio and 95% confidence interval 1.08 (1.03, 1.13) per kg/m2] and a higher risk of COVID-19 hospitalization [3,199 cases/897,488 controls; p=8.7 x 10-4, 1.12 (1.04, 1.21) per kg/m2]. In the multivariable MR, the direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes but persisted when conditioning on the effects on coronary artery disease, stroke, chronic kidney disease, and c-reactive protein. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Conclusions and Relevance: Genetic evidence supports BMI as a causal risk factor for COVID-19 susceptibility and severity. This relationship may be mediated via type 2 diabetes. Obesity may have amplified the disease burden of the COVID-19 pandemic either single-handedly or through its metabolic consequences.

Body mass index and risk of COVID-19 diagnosis, hospitalisation, and death: a population-based multi-state cohort analysis including 2,524,926 people in Catalonia, Spain

“…Our findings are in line with a Mendelian randomization analysis which reported that genetically increased BMI was causally associated with testing positive for COVID-19. [32] In addition, a study among UK Biobank participants reported the association between BMI and risk of testing positive was similarly shaped to the one in our study. [8] These results highlight the importance of avoiding extremely high BMI cut-offs to determine vulnerable groups to the COVID-19 disease (e.g., the NHS only considers BMIs above 40 kg/m 2 as risk groups for COVID-19).…”

Diabetes, obesity, metabolism, and SARS-CoV-2 infection: the end of the beginning

“…Mendelian randomization studies have analyzed potential causal associations linking 17 cardiometabolic risk factors, including BMI, with susceptibility to severe SARS-CoV-2 infection ( Leong et al., 2020 ). Although genetic predisposition to an increased BMI was associated with increased susceptibility to infection and hospitalization, this relationship was mitigated by adjustment of the genetic risk for co-existing T2D.…”

Are psychiatric disorders risk factors for COVID-19 susceptibility and severity? a two-sample, bidirectional, univariable and multivariable Mendelian Randomization study

“…Mendelian Randomization (MR) has the potential to overcome two major limitations of observational studies: unmeasured confounding and uncertainties about cause and effect. Examples of MR studies elucidating risk factors for COVID-19 include two recent studies showing that BMI and smoking are risk factors for COVID-19 7,8 . We are not aware of preprinted or published MR studies of psychiatric disorders and COVID-19.…”