Causal associations between body fat accumulation and COVID-19 severity: A Mendelian randomization study

  1. Satoshi Yoshiji
  2. Daisuke Tanaka
  3. Hiroto Minamino
  4. Takaaki Murakami
  5. Yoshihito Fujita
  6. J. Brent Richards
  7. Nobuya Inagaki

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Abstract

Purpose

The causal effects of body fat mass and body fat-free mass on coronavirus disease 2019 (COVID-19) severity remain unclear. Here, we used Mendelian randomization (MR) to evaluate the causal relationships between body fat-related traits and COVID-19 severity.

Material and Methods

We identified single nucleotide polymorphisms associated with body mass index (BMI) and direct measures of body fat (i.e., body fat percentage, body fat mass, and body fat-free mass) in 461,460, 454,633, 454,137, and 454,850 individuals of European ancestry from the UK Biobank, respectively. We then performed two-sample MR to ascertain their effects on severe COVID-19 (cases: 4,792; controls: 1,054,664) from the COVID-19 Host Genetics Initiative.

Results

We found that an increase in BMI, body fat percentage, and body fat mass by one standard deviation were each associated with severe COVID-19 (odds ratio (OR) BMI = 1.49, 95%CI: 1.19–1.87, P = 5.57×10 −4 ; OR body fat percentage = 1.94, 95%CI: 1.41–2.67, P = 5.07×10 −5 ; and OR body fat mass = 1.61, 95%CI: 1.28–2.04, P = 5.51×10 −5 ). Further, we evaluated independent causal effects of body fat mass and body fat-free mass using multivariable MR and revealed that only body fat mass was independently associated with severe COVID-19 (OR body fat mass = 2.91, 95%CI: 1.71–4.96, P = 8.85×10 −5 and OR body fat-free mass = 1.02, 95%CI: 0.61–1.67, P = 0.945).

Conclusions

This study demonstrates the causal effects of body fat accumulation on COVID-19 severity and indicates that the biological pathways influencing the relationship between COVID-19 and obesity are likely mediated through body fat mass.

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    SciScore for 10.1101/2022.01.20.22269593: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    To select instrumental variables, SNPs were clumped using PLINK (v1.90) according to a linkage disequilibrium threshold of r2 < 0.001 with a clumping window of 10,000 kb using the 1000G European reference panel (9, 14) in order to select an independent SNP with the lowest P-value in each linkage disequilibrium block.
    PLINK
    suggested: (PLINK, RRID:SCR_001757)
    We calculated F-statistics for the exposure traits and a genetic correlation between body fat mass and body fat-free mass using LDAK (v5.1) (15).
    LDAK
    suggested: (LDAK, RRID:SCR_015504)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    To overcome these limitations, several MR studies have been performed to evaluate the causal relationship between obesity-related traits and COVID-19 outcomes. Among anthropometric traits including BMI, waist circumference, hip circumference, and waist-to-hip ratio, BMI showed an association with poor COVID-19 outcomes (23). However, BMI is calculated only from height and weight and does not consider body compositions. Moreover, these anthropometric traits are indirect measures of obesity and might not be accurate proxies for body fat. Therefore, it is necessary to evaluate associations between directly measured fat traits (i.e., body fat mass and body fat percentage) and COVID-19 severity. In this MR study, we adopted these directly measured traits as exposure traits and provided novel findings that indicate the causal association of body fat accumulation with severe COVID-19 outcome. We used multivariable MR since most instrumental variables of adiposity effect both fat mass and fat-free mass, although some variants more strongly and proportionally influence fat mass, whereas others influence fat-free mass more strongly. Therefore, multivariable MR can test the differential causal effects of fat mass and fat-free mass. Using this approach, recent MR studies showed differential associations between body fat mass and body fat-free mass with various disorders (10-13). The present findings extend this knowledge to COVID-19. Results from multivariable MR showed that body fat mas...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2022.01.20.22269593v1 on medRxiv