Iron status and the risk of sepsis and severe COVID-19: A two-sample Mendelian randomization study

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Abstract

Introduction

Observational studies have indicated an association between iron status and risk of sepsis and severe COVID-19. However, these findings may be affected by residual confounding, reverse causation.

Methods

In a two-sample Mendelian randomization study using inverse variance weighted method, we estimated the effect of genetically-predicted iron biomarkers (serum iron, transferrin saturation (TSAT), total iron binding capacity (TIBC) and ferritin) on risk of sepsis and risk of being hospitalized with COVID-19. For the COVID-19 outcomes we additionally conducted sex-stratified analyses. Weighted median, Weighted mode and MR Egger were used as sensitivity analyses.

Results

For risk of sepsis, one standard deviation increase in genetically-predicted serum iron was associated with odds ratio (OR) of 1.14 (95% confidence interval [CI] 1.01 to 1.29, P =0.031). The findings were supported in the analyses for transferrin saturation and total iron binding capacity, while the estimate for ferritin was inconclusive. We found a tendency of higher risk of hospitalization with COVID-19 for serum iron; OR 1.29 (CI 0.97–1.72, P =0.08), where sex stratified analyses showed OR 1.63 (CI 0.94–2.86, P =0.09) for women and OR 1.21 (CI 0.92–1.62, P =0.17) for men. Sensitivity analyses supported the main findings and did not suggest bias due to pleiotropy.

Conclusions

Our findings suggest a causal effect of genetically-predicted higher iron status and risk of hospitalization due to sepsis and indications of an increased risk of being hospitalized with COVID-19. These findings warrant further studies to assess iron status in relation to severe infections, including the potential of improved management.

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  1. SciScore for 10.1101/2022.06.02.22275901: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableThe included numbers of SNPs with F-statistics and explained variance of the iron biomarkers is presented for all and separately for men and women, in Supplemental Table S1.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisMR Egger allows directional pleiotropic effects where some SNPs could be acting on the outcome through another pathway than the exposure of interest, but at the cost of statistical power (34).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Independence between SNPs were ensured by using the LD-reference panel of European populations in 10,000 kb windows and R2 < 0.01 that is included in the TwoSampleMR (version 0.5.6) package in R (25), and we adjusted for correlation between SNPs using MendelianRandomization (version 0.6.0) in R (version 4.2.1) (26)
    MendelianRandomization
    suggested: None
    We estimated R2 in the TwoSampleMR package and calculated F-statistics using the formula F= ([n-k-1]/k)([ R2/1-R2]) (24).
    TwoSampleMR
    suggested: (TwoSampleMR, RRID:SCR_019010)

    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:
    This is discordant to our MR results where higher genetically-predicted iron status is related to increased risk of sepsis and being hospitalized due to COVID-19, and could be attributed to differences in the epidemiological methods applied, such as residual confounding, but also limitations with the two-sample MR method used that is restricted to assess linear models (37). Few MR studies have explored iron status and risk of severe infections. An MR-study using iron related SNPs identified in the Genetics of Iron Status-consortia (38) found evidence that higher serum-iron, TSAT and ferritin were related to increased risk of sepsis (21). Using a more updated set of genetic instruments for iron status biomarkers, we replicated these findings for serum iron and TSAT, a tendency for TIBC, but not for ferritin. Another MR study found evidence of increased risk of skin and soft-tissue infections with higher serum iron levels (39). To the best of our knowledge, no previous study has conducted MR analysis to investigate the effect of iron status on incidence or outcome of COVID-19. Observational studies that have investigated iron status at the time of infection and found evidence of low iron status being a risk factor for a severe course of COVID-19 (12). Another study with COVID-19 patients compared to non-COVID-19 patients showed lower serum iron and TSAT levels in patients with COVID-19 independently of severity. Whereas COVID-19 patients defined as severe and critical had subst...

    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.


    About SciScore

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