To the Editor:
We read with interest the research article published by Ji and colleagues, in the Journal of Hepatology, showing that patients with metabolic-associated fatty liver disease (MAFLD) have a higher risk of COVID-19 disease progression and higher likelihood of abnormal liver blood tests from admission to discharge than patients without MAFLD.1 Given the absence of data on medical history of these patients, this persistence of liver blood test abnormalities could be either a mere reflection of pre-existing abnormalities related to MAFLD or could alternatively be due to a higher susceptibility of the fatty liver to SARS-CoV-2 infection.
We therefore investigated whether MAFLD is associated with altered liver expression of SARS-CoV-2 critical entry proteins. SARS-CoV-2 attaches to cells by binding to angiotensin-converting enzyme 2 (ACE2). The cellular protease transmembrane protease serine 2 (TMPRSS2) cleaves the SARS-CoV-2 spike protein, allowing fusion of cellular and viral membranes.2 , 3 Moreover, in the HEK293 cell line, overexpressing human ACE2, SARS-CoV-2 enters through endocytosis with critical roles played by endocytosis-regulating protein phosphatidylinositol 3-phosphate 5-kinase (PIKFYVE).4 Finally, as described for SARS-CoV and MERS-CoV, cathepsin L is also critical for priming of the SARS-CoV-2 spike protein in lysosomes following entry through endocytosis.4
We analysed the influence of MAFLD on liver gene expression of these 4 proteins implicated in SARS-CoV-2 infection by analysing public data from patients and from mice with MAFLD. In 2013, Ahrens and colleagues published microarray data obtained on human liver biopsies.5 , 6 They made available transcriptomic data from 12 lean patients without MAFLD, 16 obese patients without MAFLD, 9 patients with simple steatosis and 17 patients with biopsy proven non-alcoholic steatohepatitis (NASH). Using these datasets, we observed that none of the genes necessary for SARS-CoV-2 infection was differentially expressed between lean or obese controls and patients with simple steatosis or with NASH (Table 1 ).
Table 1.
Gene name | Lean without MAFLD (n = 12) vs. NASH (n = 17) |
Lean without MAFLD (n = 12) vs. simple steatosis (n = 9) |
Obese without MAFLD (n = 16) vs. simple steatosis (n = 9) |
Obese without MAFLD (n = 16) vs. NASH (n = 17) |
Lean and obese without MAFLD (n = 28) vs. simple steatosis or NASH (n = 26) |
|||||
---|---|---|---|---|---|---|---|---|---|---|
Fold-change | adj. p value | Fold-change | adj. p value | Fold-change | adj. p value | Fold-change | adj. p value | Fold-change | adj. p value | |
ACE2 | 1.41 | 0.39 | 1.00 | 0.99 | 0.99 | 0.97 | 1.39 | 0.14 | 1.24 | 0.24 |
CTSL | 0.98 | 0.96 | 1.10 | 0.69 | 1.04 | 0.73 | 0.92 | 0.67 | 0.99 | 0.95 |
TMPRSS2 | 0.85 | 0.72 | 0.78 | 0.57 | 0.87 | 0.64 | 0.94 | 0.95 | 0.88 | 0.60 |
PIKFYVE | 1.03 | 0.93 | 0.77 | 0.94 | 0.85 | 0.11 | 0.92 | 0.64 | 0.94 | 0.53 |
Human microarray data6 was made available by Ahrens and colleagues5 and reanalysed by us using Geo2R7 default settings. Geo2R is based on the "Linear Models for Microarray Data" R package that computes a moderated t-statistic for each gene and corresponding p value. Adjustment for multiple testing was performed using Benjamini and Hochberg's correction. CSTL gene encodes cathepsin L protein. Human transcriptomics data is available on GEO Dataset under the accession number GSE48452.
MAFLD, metabolic-associated fatty liver disease; NASH, non-alcoholic steatohepatitis.
We performed the same analysis in a mouse dataset published by Xiong and colleagues.8 Similarly, we observed no increase in liver gene expression of the 4 proteins implicated in SARS-CoV-2 infection between MAFLD mice and control mice (data not shown).
In conclusion, MAFLD is not associated with changes in liver expression of genes implicated in SARS-CoV-2 infection. The observed persistence of liver blood test abnormalities reported by Ji and colleagues is thus likely not explained by increased hepatic SARS-CoV-2 uptake.
Financial support
This work was supported by the “Institut National de la Santé et de la Recherche Médicale” (ATIP AVENIR), the “Agence Nationale pour la Recherche” (ANR-18-CE14-0006-01, RHU QUID-NASH) and by “Émergence, Ville de Paris”.
Authors' contributions
L.B. performed the bioinformatic analysis; L.B. and P.E.R. wrote the manuscript; D.V. provided guidance and proof-read the manuscript; all authors revised and approved the final version.
Conflict of interest
The authors declare no conflict of interest.
Please refer to the accompanying ICMJE disclosure forms for further details.
Footnotes
Author names in bold designate shared co-first authorship
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jhep.2020.04.035.
Supplementary data
References
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