Causal Associations Between Blood Lipids and COVID-19 Risk: A Two-Sample Mendelian Randomization Study

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Abstract

Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus 2. It has been reported that dyslipidemia is correlated with COVID-19, and blood lipids levels, including total cholesterol, HDL-C (high-density lipoprotein cholesterol), and LDL-C (low-density lipoprotein cholesterol) levels, were significantly associated with disease severity. However, the causalities of blood lipids on COVID-19 are not clear.

Approach and Results:

We performed 2-sample Mendelian randomization (MR) analyses to explore the causal effects of blood lipids on COVID-19 susceptibility and severity. Using the outcome data from the UK Biobank (1221 cases and 4117 controls), we observed potential positive causal effects of dyslipidemia (odds ratio [OR], 1.27 [95% CI, 1.08–1.49], P =3.18×10 −3 ), total cholesterol (OR, 1.19 [95% CI, 1.07–1.32], P =8.54×10 −4 ), and ApoB (apolipoprotein B; OR, 1.18 [95% CI, 1.07–1.29], P =1.01×10 −3 ) on COVID-19 susceptibility after Bonferroni correction. In addition, the effects of total cholesterol (OR, 1.01 [95% CI, 1.00–1.02], P =2.29×10 −2 ) and ApoB (OR, 1.01 [95% CI, 1.00–1.02], P =2.22×10 −2 ) on COVID-19 susceptibility were also identified using outcome data from the host genetics initiative (14 134 cases and 1 284 876 controls).

Conclusions:

In conclusion, we found that higher total cholesterol and ApoB levels might increase the risk of COVID-19 infection.

Graphic Abstract:

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  1. SciScore for 10.1101/2020.07.07.20147926: (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
    Instrumental variables (IVs) selection: We selected independent and genome-wide significant GWAS SNPs of HDL-c, LDL-c, TG, TC and dyslipidemia by use of the clumping algorithm in PLINK (http://pngu.mgh.harvard.edu/purcell/plink/) 13 at a suggestive threshold (r2 threshold = 0.001, window size = 1 Mb, p-value = 5 × 10−8).
    PLINK
    suggested: (PLINK, RRID:SCR_001757)
    The 1000 Genomes Project (http://www.internationalgenome.org/) data were used as the reference for linkage disequilibrium (LD) estimation.
    1000 Genomes Project
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)
    In order to …