Association of lipid-lowering drugs with COVID-19 outcomes from a Mendelian randomization study

  1. Wuqing Huang
  2. Jun Xiao
  3. Jianguang Ji
  4. Liangwan Chen

  • Curated by eLife

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    Evaluation Summary:

    There are mixed results from studies of COVID-19 outcomes in patients treated with statins and there are multiple confounders. The authors use two Mendelian randomization methods to explore the association between HMGCoA reductase inhibitors (statins) and other lipid lowering drugs and outcomes and find that increased expression of HMGCoA reductase and HMGCoA reductase mediated LDL cholesterol increase hospitalization risk. This makes it possible but does not prove that statins could improve outcomes which will be of broad interest.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

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Abstract

Lipid metabolism plays an important role in viral infections. We aimed to assess the causal effect of lipid-lowering drugs (HMGCR inhibitiors, PCSK9 inhibitiors, and NPC1L1 inhibitior) on COVID-19 outcomes using two-sample Mendelian randomization (MR) study.

Methods:

We used two kinds of genetic instruments to proxy the exposure of lipid-lowering drugs, including expression quantitative trait loci of drugs target genes, and genetic variants within or nearby drugs target genes associated with low-density lipoprotein (LDL cholesterol from genome-wide association study). Summary-data-based MR (SMR) and inverse-variance-weighted MR (IVW-MR) were used to calculate the effect estimates.

Results:

SMR analysis found that a higher expression of HMGCR was associated with a higher risk of COVID-19 hospitalization (odds ratio [OR] = 1.38, 95% confidence interval [CI] = 1.06–1.81). Similarly, IVW-MR analysis observed a positive association between HMGCR-mediated LDL cholesterol and COVID-19 hospitalization (OR = 1.32, 95% CI = 1.00–1.74). No consistent evidence from both analyses was found for other associations.

Conclusions:

This two-sample MR study suggested a potential causal relationship between HMGCR inhibition and the reduced risk of COVID-19 hospitalization.

Funding:

Start-up Fund for high-level talents of Fujian Medical University.

Article activity feed

  1. Version published to 10.7554/elife.73873 on eLife
  2. eLife

    Evaluation Summary:

    There are mixed results from studies of COVID-19 outcomes in patients treated with statins and there are multiple confounders. The authors use two Mendelian randomization methods to explore the association between HMGCoA reductase inhibitors (statins) and other lipid lowering drugs and outcomes and find that increased expression of HMGCoA reductase and HMGCoA reductase mediated LDL cholesterol increase hospitalization risk. This makes it possible but does not prove that statins could improve outcomes which will be of broad interest.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    Given that lipid metabolism plays an important role in viral infections, that lipid lowering drugs especially statins (HMGCoA reductase inhibitors) are widely used and that observational studies investigating the association between statin use and COVID-19 outcomes have given mixed results it's attractive to resort to mendelian randomization to minimize confounding and avoid reverse causation to address the potential benefits of lipid lowering drugs in this context.

    The authors use selected target genes for three lipid lowering drug classes - HMGCoA reductase inhibitors (statins), PCSK9 inhibitors and the NPC1L1 inhibitor ( ezetimibe) ; large well characterized COVID GWAS case and control data sets; summary -data-based MR (SMR) and inverse variance weighted MR ( IVW-MR) and sensitivity analysis.

    They demonstrate with SMR that a higher expression of HMGCR was associated with a higher risk of COVID-19 hospitalization. With IVW-MR they observed a positive association between HMGCR -mediated LDL cholesterol and COVID-19 hospitalization. For the other two drug classes no clear associations were shown.

    This suggests but does not prove that HMGCR drugs ie statins might improve outcomes. For the other two classes its unclear if there would be sufficient users of these drugs in the data sets to provide enough power to adequately address the issue.

    Overall this is a well conducted study providing important further insights but the final sentence of the abstract as well as the related discussion section including the limitations should be more expressed more conservatively.

  4. eLife

    Reviewer #2 (Public Review):

    Lipid metabolism plays an important role in viral infection. The study aimed to assess a putative causal effect of lipid-lowering drugs including HMGCR inhibitors, PCSK9 inhibitors and NPC1L1 inhibitors on COVID-19 outcomes.

    Two kinds of genetic instruments to proxy the exposure of lipid-lowering drugs, including eQTLs of drugs target genes, and genetic variants within or nearby drugs target genes associated with LDL cholesterol from GWAS were used. Mendelian randomisation analysis was performed. A higher expression of HMGCR was associated with a higher risk of COVID-19 hospitalisation (OR=1.38, 95%CI=1.06-1.81) at suggestive significance. Similarly, a positive association between HMGCR-mediated LDL cholesterol and COVID-19 hospitalisation (OR=1.32, 95%CI=1.00-1.74) was also observed.

    The authors conclude a potential causal evidence that HMGCR inhibitors could reduce the risk of COVID-19 hospitalisation, providing insights into the prevention and management of COVID19 infection.

  5. ScreenIT

    SciScore for 10.1101/2021.07.20.21260813: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: All these studies had been approved by the relevant institutional review boards and participants had provided informed consents.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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:
    As a genetic epidemiological method, MR study could overcome the limitations of traditional observational studies. In this MR study, we used genetic variants related to HMGCR expression or HMGCR-mediated LDL cholesterol as instruments to proxy the exposure of statins. Both analyses found a suggestive evidence that statins could reduce the risk of COVID-19 hospitalization, rather than COVID-19 susceptibility and very severe outcome. Although strong evidence is lacking, these results provided a causal evidence supporting the finding from the largest cohort study (2), which calls for additional observational studies in different populations, mechanistic studies, and randomized controlled studies to examine its potential effect against COVID-19. Besides, although no association was found between NPC1L1 expression in adipose subcutaneous and COVID-19 outcomes, there was a strong evidence of the association between NPC1L1-mediated LDL cholesterol and COVID-19 susceptibility. The effect of NPC1L1 inhibitor on COVID-19 susceptibility may be worth further studies as well. Study strengths: The main strength of our study is the use of genetic instruments to proxy drug exposure, which could minimize confounding bias and avoid reverse causation. Besides, we used two different kinds of genetic instruments to proxy the studied drug, which contributes to validate the effect estimates from each other. And a number of sensitivity analyses have been performed to test the efficacy of genetic ins...

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  6. Version published to 10.1101/2021.07.20.21260813v1 on medRxiv