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The influence of pH on SARS-CoV-2 infection and COVID-19 severity
Authors:
Leandro Jimenez1,2, Ana Campos Codo3, Vanderson de Souza Sampaio4,5,6,7, Antonio E.R.
Oliveira1, Lucas Kaoru Kobo Ferreira1, Gustavo Gastão Davanzo3, Lauar de Brito Monteiro3,
João Victor Virgilio-da-Silva3, Mayla Gabriela Silva Borba4, Gabriela Fabiano de Souza3,
Nathalia Zini8, Flora de Andrade Gandolfi8, Stéfanie Primon Murano3, José Luiz Proença-
Modena3, Fernando Almeida Val4,5,7, Gisely Cardoso Melo4,5, Wuelton Marcelo Monteiro4,5,
Maurício Lacerda Nogueira8, Marcus Vinícius Guimarães Lacerda4,5,9, Pedro M. Moraes-
Vieira3,10,11, Helder I Nakaya1,2,*
Affiliations:
1 Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences,
University of São Paulo, São Paulo, Brazil.
2 Scientific Platform Pasteur-University of São Paulo, São Paulo, Brazil.
3 Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology,
University of Campinas, SP, Brazil.
4 Fundação de Medicina Tropical Dr Heitor Vieira Dourado, Manaus, Brazil
5 Universidade do Estado do Amazonas, Manaus, Brazil
6 Fundação de Vigilância em Saúde do Amazonas, Manaus, Brazil
7 Faculdade de Medicina da Universidade Federal do Amazonas, Manaus, Brazil, UFAM
Amazonas, Manaus, Brazil
8 Faculdade de Medicina de São José do Rio Preto, São Paulo, Brazil
9 Faculdade de Medicina da Universidade Federal do Amazonas, Manaus, Brazil, UFAM
Amazonas, Manaus, Brazil
10 Obesity and Comorbidities Research Center (OCRC), University of Campinas, SP, Brazil.
11 Experimental Medicine Research Cluster (EMRC), University of Campinas, SP, Brazil.
*Correspondence to: hnakaya@usp.br
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Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect a broad
range of human tissues by using the host receptor angiotensin-converting enzyme 2 (ACE2).
Individuals with comorbidities associated with severe COVID-19 display higher levels of
ACE2 in the lungs compared to those without comorbidities, and conditions such as cell
stress, elevated glucose levels and hypoxia may also increase the expression of ACE2. Here
we showed that patients with Barrett’s esophagus (BE) have a higher expression of ACE2 in
BE tissues compared to normal squamous esophagus, and that the lower pH associated with
BE may drive this increase in expression. Human primary monocytes cultured in reduced pH
displayed increased ACE2 expression and viral load upon SARS-CoV-2 infection. We also
showed in two independent cohorts of COVID-19 patients that previous use of proton pump
inhibitors is associated with 2- to 3-fold higher risk of death compared to those not using the
drugs. Our work suggests that pH has a great influence on SARS-CoV-2 Infection and
COVID-19 severity.
Keywords
COVID-19; pH; SARS-CoV-2; proton pump inhibitors; Barrett’s esophagus.
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Introduction
As of August 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-
2) infected over 20 million people worldwide (World Health Organization). The new
coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is characterized by a broad
range of symptoms, from respiratory to neurological and digestive problems (1, 2). Although
a small fraction of patients develop highly lethal pneumonia, at least 20% of COVID-19
patients may display one or more gastrointestinal (GI) symptoms (1), such as diarrhea,
vomiting, and abdominal pain (2, 3).
SARS-CoV-2 tissue tropism can be directly linked to the diverse clinical manifestations
of COVID-19. The receptor used by the virus to enter the cells is the angiotensin-converting
enzyme 2 (ACE2), which is found in several tissues, including the GI epithelial cells and liver
cells (4, 5). SARS-CoV-2 was detected in biopsies of several tissues, including esophagus,
stomach, duodenum and rectum, and endoscopy of hospitalized patients revealed
esophageal bleeding with erosions and ulcers (2, 6).
Higher levels of ACE2 in the tissues may explain in part some of the comorbidities
associated with severe COVID-19. Recently, we showed that ACE2 was highly expressed in
the lungs of people with pulmonary arterial hypertension and chronic obstructive diseases
(7). Since the expression of ACE2 changes under conditions of cell stress, elevated glucose
levels and hypoxia (8, 9), other comorbidities related to the GI tract can be associated with
different forms of COVID-19.
Here we suggest that gastroesophageal reflux disease (GERD) and Barrett’s
esophagus (BE) may represent novel comorbidities associated with COVID-19. In the United
States, it has been estimated that 5.6% of adults have BE, a disease where GERD damages
the esophageal squamous mucosa (10). Here we demonstrated that ACE2 is highly
expressed in the esophagus of patients with BE and that the acid pH associated with this
condition is a key inducer of ACE2 expression. Human primary monocytes cultured in
reduced pH display increased expression of ACE2 and increased viral load upon SARS-CoV-
2 infection. We also show that patients using proton pump inhibitors, which are recommended
for GERD treatment, have a higher risk of developing severe COVID-19, observed by an
increased risk of ICU admittance and death.
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Methods
Acidosis and Barrett’s esophagus meta-analysis
We manually curated the Gene Expression Omnibus (GEO) repository
(https://www.ncbi.nlm.nih.gov/geo/) to find esophagus transcriptome datasets related to
“Barrett’s esophagus” and cell line transcriptome datasets related to “acidosis” and “pH
reduction”. Author-normalized expression values and metadata from these datasets were
downloaded using the GEOquery package (11). We performed differential expression
analyses using the limma package (12). The GEO study ID and the groups of samples
compared are listed in Supplementary Table 1. The MetaVolcanoR package (13) was used
to combine the P values using the Fisher’s method. To adjust for multiple comparisons, we
calculated the false discovery rate (FDR) using the Benjamini-Hochberg procedure. For
enrichment analyses, we utilized the EnrichR tool (14) and fgsea R package (15) with gene
sets from the Gene Ontology Biological Process database. We then selected pathways with
a P value adjusted for multiple comparisons lower than 0.10.
Single cell transcriptomic analysis of Barrett’s esophagus
The single cell RNA-seq (scRNA-seq) data from esophagus, Barrett’s esophagus, gastric and
duodenum cells from patients with BE were acquired from Owen et al. 2018 (16). Cells with
less than 1,000 genes were excluded from analysis using Seurat v3 (17). Raw UMI counts
were log transformed and variable genes called on each dataset independently based on the
VST method. The AddModuleScore function was used to remove batch effects between
samples and based on C1orf43, CHMP2A, EMC7, GPI, PSMB2, PSMB4, RAB7A, REEP5,
SNRPD3, VCP, VPS29 genes. We assigned scores for S and G2/M cell cycle phases based
on previously defined gene sets using the CellCycleScoring function. Scaled z-scores for
each gene were calculated using the ScaleData function and regressed against the number
of UMIs per cell, mitochondrial RNA content, S phase score, G2/M phase score, and
housekeeping score. Scaled data was used as an input into PCA based on variable genes.
These PCA components were used to generate the UMAP reduction visualization. To identify
the number of clusters, UMI log counts were used as input to SC3 (18). Technical variation
was tested using BEARscc (19), which models technical noise from ERCC spike-in
measurements. The clusters were then annotated based on genes previously characterized
(16).
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Peripheral blood mononuclear cells (PBMC) isolation
Buffy coats provided by the Hematology and Hemotherapy Center of the University of
Campinas (SP-Campinas, Brazil) were used for PBMC isolation as described (9). The study
was approved by the Brazilian Committee for Ethics in Human Studies (CAAE:
31622420.0.0000.5404). Briefly, buffy coats were mixed and then diluted in Phosphate Buffer
Saline (PBS) (1:1) and carefully to 50 mL tube containing Ficoll (Sigma-Aldrich) and
centrifuged. PBMCs were cultured in RPMI 1640 for 2-3h to allow cell adhesion. Next, cells
were washed twice with PBS and adherent cells, enriched in monocytes, were further
incubated until infection in RPMI 1640 containing 10% fetal bovine serum (FBS) and 1%
Penicillin-Streptomycin (Pen-Strep) at 37ºC with 5% CO2. Monocytes were maintained in
different pH levels (6, 6.5, and 7.4) during 24h and subsequently infected with SARS-CoV-2,
as described below.
Viruses and infection
HIAE-02 SARS-CoV-2/SP02/human/2020/BRA (GenBank MT126808.1) virus was isolated
as described (9). Stocks of Sars-CoV-2 were prepared in the Vero cell line. The supernatant
was harvested at 2–3 dpi. Viral titers were obtained by plaque assays on Vero cells.
Monocytes were infected with SARS-CoV-2 at MOI 0.1 under continuous agitation at 15 rpm
for 1 h. Next, monocytes were washed twice and incubated in RPMI with 10% FBS and 1%
Pen-Strep for 24h at 37°C with 5% CO2 for 24 hours.
Viral load and gene expression analyses
Total RNA extraction was performed using TRIzol Reagent (Sigma-Aldrich). RNA
concentration was measured with NanoDrop 2000 spectrophotometer (Thermo Scientific).
RNA was reverse-transcribed using GoScript™ Reverse Transcriptase cDNA synthesis kit
following manufacturer’s instructions. SARS-CoV-2 viral load was determined with primers
targeting the N1 region and a standard curve was generated as described (20). Viral load
and gene expression were made using SYBR Green Supermix in BIO-RAD CFX394 Touch
Real-Time PCR Detection System. Fold change was calculated as 2^-ΔΔCt. Primer
sequences used: 18S (Forward: 5’-CCCAACTTCTTAGAGGGACAAG-3’; Reverse: 5’-
CATCTAAGGGCATCACAGACC-3’); ACE2 (Forward: 5’-GGACCCAGGAAATGTTCAGA-3’;
Reverse: 5’-GGCTGCAGAAAGTGACATGA-3’); SARS-CoV-2_IBS_N1 (Forward: 5’-
CAATGCTGCAATCGTGCTAC-3’; Reverse: 5’-GTTGCGACTACGTGATGAGG-3’).
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Clinical data analysis
We retrieved clinical data from two independent cohorts of 551 and 806 RT-qPCR
confirmed COVID-19 patients aged 18 years or older that went to reference hospitals for
COVID-19 in Manaus, Amazonas, Brazil (North region cohort) and in São José do Rio Preto
city, São Paulo, Brazil (Southeast region cohort), respectively. They were followed for at least
28 days (North region cohort) or 120 days (Southeast region cohort) after recruitment.
Information about the previous history of proton pump inhibitors use (e.g. omeprazole and
pantoprazole), a surrogate evidence of low gastric pH-related diseases, time of
hospitalization, ICU admittance, and time to death, as well as demographics, previous use of
other drugs, clinical, laboratory, and outcome variables were collected. The protocol was
approved by the Brazilian Committee of Ethics in Human Research (CAAE:
30152620.1.0000.0005 and 30615920.2.0000.0005 for North region cohort, and
31588920.0.0000.5415 for Southeast region cohort). Data were collected and managed
using REDCap (v. 10.2.1) electronic data capture tools hosted at Fundação de Medicina
Tropical Dr. Heitor Vieira Dourado.
Adjusted hazard ratios and risk ratios with respective 95% confidence intervals (CI)
were estimated for time to death and ICU admittance, respectively by Cox regression and
log-binomial generalized linear model models. To adjust for confounders, ages higher than
60 years old and obesity, defined by both BMI and fat percentage, were used as covariables
in the multivariable analyses. Wilcoxon Rank-Sum analysis was used to test differences in
the days of hospitalization. A 2-tailed P < 0.05 was considered significant. The statistical
analyses were carried out using Stata v. 13.0 (StataCorp LP, College Station, TX).
Results
To evaluate whether people with BE may have higher chances of being infected with
SARS-CoV-2 when compared to people without the disease, we performed a meta-analysis
of 8 transcriptomic studies of BE (Figure 1A, Table S1). A total of 304 and 256 genes
displayed, respectively higher and lower expression BE compared to normal esophagus
tissue in at least 7 of these studies (Figure 1B). ACE2 was among the genes consistently up-
regulated in the BE compared to normal esophagus (Figure 1C). While pathways related to
keratinocyte differentiation and epidermis development were enriched with down-regulated
genes, we found that bicarbonate transport and regulation of intracellular pH pathways were
enriched with up-regulated genes (Figure 1D), suggesting that pH may influence ACE2
expression. In fact, when human coronary artery endothelial cells were treated with proton
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pump inhibitors – omeprazole or lansoprazole – the expression of ACE2 decreased in
comparison to untreated cells (Figure 1E). Gene set enrichment analysis (GSEA) confirmed
that Barrett’s esophagus tissues have higher expression of genes related to pH alterations
(Figure 1F).
Figure 1. Meta-analysis of gastroesophageal junction transcriptomes of patients with
Barrett’s esophagus. A. Meta-analysis of 8 studies of Barrett's esophagus transcriptomes.
B. Number of differentially expressed genes in Barrett's esophagus compared with non-
Barrett’s esophagus. The lines show the number of genes (y-axis) considered up-regulated
(red lines) or down-regulated (blue lines) in Barrett's esophagus (P value < 0.05; log2 fold-
change > 1; combined FDR < 0.01) in one or more datasets (x-axis). The numbers of up-
regulated and down-regulated genes in at least 7 studies are indicated. C. ACE2 is
upregulated in patients with Barrett’s esophagus. Each bar represents the log2 expression
fold-change between patients and control individuals. The error bars indicate the 95%
confidence interval. Bars in red represent a P value < 0.05 and in grey a non-significant P
value. D. Pathway enrichment analysis using the up-regulated and down-regulated genes in
at least 7 studies. The bars represent the combined score (x axis) calculated by Enrichr tool
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for selected Gene Ontology gene sets (y axis). E. ACE2 expression in cells treated with
proton pump inhibitors. Each boxplot represents the log2 expression of untreated (CTRL)
cells and cells treated with either omeprazole (OPZ) or lansoprazole (LPZ). F. Gene Set
Enrichment Analysis (GSEA) of the 8 studies of Barrett's esophagus transcriptomes using
pH-related gene sets. The size and color of the circles are proportional to the normalized
enrichment score (NES) of the gene sets (columns) on each study (rows). The Gene Ontology
IDs are indicated at the top.
We also investigated ACE2 expression in Barrett’s esophagus at single-cell level. Our
analysis showed that single cells from Barrett’s esophagus patients are distinct than normal
esophagus cells, as well as cells from duodenum and gastric tissues (Figure 2A). While a
large fraction of duodenum cells expresses ACE2 (21), only 11% of the single cells from
Barrett’s samples have ACE2 expression above 0 (Figure 2B). However, among the cells
expressing ACE2, higher levels of the gene were found in gastric, Barrett’s, and duodenum
cells when compared to esophagus cells (Figure 2C). Using GSEA, we found that genes
associated with regulation of cellular pH were enriched among the up-regulated genes in
gastric, Barrett’s and duodenum cells when compared to esophagus cells (Figure 2D).
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Figure 2. Single cell transcriptomics of Barrett’s esophagus. A. Dimension reduction of
single cells using Uniform Manifold Approximation and Projection (UMAP). Cells from 4
patients with Barrett’s esophagus (n = 1,168) are shown. The colors represent the tissue
types. B. ACE2 expression by tissue type. The pie charts show the number of single cells
with (black) or without (grey) ACE2 expression (expression values > 0). The fractions of
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ACE2-expressing cells are indicated. C. Distribution of ACE2 expression by cells from
different tissue types. The colors of histograms represent the tissue types. The dashed
vertical line shows the median values of each tissue type. Student’s t-test P-value between
tissue types versus esophagus is indicated. D. Gene Set Enrichment Analysis (GSEA) of the
3 tissue types compared to esophagus using the regulation of cellular pH gene set. The
normalized enrichment score (NES) are shown in the x-axis for each one of the tissue types.
The adjusted P-value of the enrichment is displayed right next to the corresponding bar.
To further evaluate whether pH may influence the expression of ACE2, we analyzed
publicly available transcriptomic studies of cells under experimentally-induced acidosis. Cells
cultured at lower pH displayed higher expression levels of ACE2 when compared to those
cultured under higher pH (Figure 3A and B). We validated this finding with human primary
monocytes cultured at pH 7.4, 6.5 and 6.0 under normoxia. ACE2 expression was
significantly increased at pH 6.5 and 6.0 compared to pH 7.4 (Figure 3C). The reduction of
pH alone also significantly increased SARS-CoV-2 infection of human monocytes (Figure
3D), indicating that pH plays a role in ACE2-mediated SARS-CoV-2 infection.
Figure 3. Acidosis increases ACE2 expression and SARS-CoV-2 infection. A. Human
cells exposed to acidosis. Each boxplot represents the log2 expression of samples untreated
(grey) or treated with lactic acidosis (brown) for two microarray studies (GSE9649 and
GSE70051). Student’s t-test P-values are indicated. B. MCF7 cells exposed to pH reduction
increases ACE2 expression. Grey and brown lines represent, respectively cells treated with
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control media or with 25mM lactic acid for 1, 4, and 12 hours (x-axis). Each point represents
the mean log2 expression and the error bars the standard deviation of biological replicates.
C. Acid pH increases ACE2 expression in monocytes. Human peripheral blood monocytes
were incubated in medium at 3 different pH (6, 6.5, 7.4) for 24h. Each boxplot represents the
fold change ACE2 expression. D. Acid pH increases SARS-CoV-2 viral load. Human
peripheral blood monocytes were incubated in medium at 3 different pH (6, 6.5, 7.4) for 24h.
The cells were infected with CoV-2 (MOI 0.1) for 1h under continuous agitation. The RNA
viral load was measured by qPCR.
Proton pump inhibitors (PPI) decrease the amount of acid produced in the stomach
and are often utilized to treat subjects with GERD symptoms or with certain stomach and
esophagus problems (22). The use of PPIs prior to COVID-19 may serve as a proxy for
identifying subjects with tissue irritation and inflammation caused by stomach acid. In two
independent cohorts of 551 and 806 RT-qPCR confirmed COVID-19 patients from North and
Southeast regions of Brazil, respectively, we investigated the effects of gastrointestinal
discomfort and COVID-19 severity. Survival curve analysis showed that people using PPIs
had a 2- to 3-fold higher risk of death compared to those not using the drug (Figure 4A).
When controlling for potential confounders (i.e. age above 60 years old, diabetes, and
hypertension), the adjusted hazard ratio was 2.183 (95CI: 1.635 - 2.914; P<0.0001) for the
North region cohort and 2.332 (95CI: 1.661 - 3.274; P<0.0001) for the Southeast cohort
(Figure 4B). These clinical findings indicate that the reduction of physiological pH (caused by
stomach acid) may play a significant role in SARS-CoV-2 infection and COVID-19 severity.
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Figure 4. Increase risk of death in individuals with COVID-19 using proton pump
inhibitors prior infection. A. Time to death. Kaplan-Meier survival curves showing a higher
risk of death for the group of patients that used PPIs (brown) prior to admittance when
compared to those not using them (grey). The North region cohort result is shown at the top
and Southeast region cohort result is shown at the bottom. B. Risk of death. The forest plot
presents the hazard ratios and respective 95CI for the main explanatory variable (brown), as
well as the potential confounders (black) used in the multivariate model. The North region
cohort result is shown at the top and Southeast region cohort result is shown at the bottom.
Discussion
Our findings suggest that acid pH increases SARS-CoV-2 infection by up-regulating
the ACE2 receptor, and this may have clinical implications for patients with GERD or Barrett’s
esophagus. No clear mechanism exists linking alterations in pH and ACE2 expression.
Although evidence indicates that hypoxic conditions can increase the expression of ACE2 (8,
9), the expression of neither SIRT1 nor HIF1A seem to be associated with Barrett’s
esophagus (Table S2). We found that known regulators of ACE2 – HNF1B (23) and FOXA2
(24) – were up-regulated in 6 out of 8 Barrett’s esophagus transcriptomic studies (Table S2),
suggesting that they may be involved with the pH-induced ACE2 expression in Barrett’s
esophagus.
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Pulmonary damage, one of the main features of severe COVID-19, may lead to acute
hypoxia and further respiratory acidosis. It is possible that the acidosis in the blood of some
patients with severe COVID-19 (25) worsen the disease by increasing the levels of ACE2
and facilitating the entry of SARS-CoV-2 into human cells. Hypoxia itself may contribute to
the regulation of ACE2 (9, 26). In addition, elevated levels of the enzyme lactate
dehydrogenase (which converts lactate from pyruvate) has been associated with worse
outcomes in patients with COVID-19 (27). The excess of lactate may directly alter the
extracellular and intracellular pH which in turn can impact ACE2 expression. The extent to
which acute systemic acidosis contributes to COVID-19 severity is poorly known and
deserves further research.
The drug famotidine suppresses gastric acid production by blocking the histamine 2
receptor in the stomach. Recently, Freedberg et al (28) have shown that early treatment of
patients tested positive for SARS-CoV-2 significantly improved clinical outcomes among the
hospitalized patients. Although the authors hypothesized that famotidine may have antiviral
effects, it is possible that pH itself can play an important role in regulating ACE2 expression
and limiting SARS-CoV-2 infection in patients.
We showed here that the previous use of PPIs is associated with unfavorable
outcomes, such as the time of hospitalization, ICU admittance, and death. To the best of our
knowledge, none of these associations were previously reported. Almario et al. (29) recently
described that individuals using PPIs had higher chances for testing positive for COVID-19
when compared to those not using PPIs. Their hypothesis is that PPIs might increase the risk
for COVID-19 by undermining the gastric barrier to SARS-CoV-2 and reducing the microbial
diversity in the gut (29). Rather, we believe that PPIs are important markers of hidden
comorbidities that involve the damage caused by the excess stomach acid in GI tissues.
By going from disease (Barrett’s esophagus) to molecule (ACE2) to cells (in vitro
experiments) and back to clinical findings (COVID-19 patients), we showed that pH may have
a great influence on SARS-CoV-2 infection and COVID-19 severity. Additional studies should
be performed to not only confirm the clinical findings on a larger scale but also to assess the
molecular mechanism related to pH-induced ACE2 expression.
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References
1. R. Tariq et al., Prevalence and Mortality of COVID-19 Patients With Gastrointestinal Symptoms: A
Systematic Review and Meta-analysis. Mayo Clin Proc 95, 1632-1648 (2020).
2. L. Zhang et al., Diarrhea and altered inflammatory cytokine pattern in severe coronavirus disease 2019:
Impact on disease course and in-hospital mortality. J Gastroenterol Hepatol, (2020).
3. K. S. Cheung et al., Gastrointestinal Manifestations of SARS-CoV-2 Infection and Virus Load in Fecal
Samples From a Hong Kong Cohort: Systematic Review and Meta-analysis. Gastroenterology 159, 81-95
(2020).
4. A. R. Bourgonje et al., Angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 and the
pathophysiology of coronavirus disease 2019 (COVID-19). J Pathol, (2020).
5. X. Zou et al., Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential
risk of different human organs vulnerable to 2019-nCoV infection. Front Med 14, 185-192 (2020).
6. L. Lin et al., Gastrointestinal symptoms of 95 cases with SARS-CoV-2 infection. Gut 69, 997-1001
(2020).
7. B. G. G. Pinto et al., ACE2 Expression Is Increased in the Lungs of Patients With Comorbidities
Associated With Severe COVID-19. J Infect Dis 222, 556-563 (2020).
8. N. E. Clarke, N. D. Belyaev, D. W. Lambert, A. J. Turner, Epigenetic regulation of angiotensin-
converting enzyme 2 (ACE2) by SIRT1 under conditions of cell energy stress. Clin Sci (Lond) 126, 507-516
(2014).
9. A. C. Codo et al., Elevated Glucose Levels Favor SARS-CoV-2 Infection and Monocyte Response
through a HIF-1α/Glycolysis-Dependent Axis. Cell Metab, (2020).
10. S. J. Spechler, R. F. Souza, Barrett's esophagus. N Engl J Med 371, 836-845 (2014).
11. S. Davis, P. S. Meltzer, GEOquery: a bridge between the Gene Expression Omnibus (GEO) and
BioConductor. Bioinformatics 23, 1846-1847 (2007).
12. M. E. Ritchie et al., limma powers differential expression analyses for RNA-sequencing and microarray
studies. Nucleic Acids Res 43, e47 (2015).
13. C. Prada, D. Lima, H. I. Nakaya. (Bioconductor, 2019).
14. E. Y. Chen et al., Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC
Bioinformatics 14, 128 (2013).
15. A. Alexeyenko et al., Network enrichment analysis: extension of gene-set enrichment analysis to gene
networks. BMC Bioinformatics 13, 226 (2012).
16. R. P. Owen et al., Single cell RNA-seq reveals profound transcriptional similarity between Barrett's
oesophagus and oesophageal submucosal glands. Nat Commun 9, 4261 (2018).
17. T. Stuart et al., Comprehensive Integration of Single-Cell Data. Cell 177, 1888-1902.e1821 (2019).
18. V. Y. Kiselev et al., SC3: consensus clustering of single-cell RNA-seq data. Nat Methods 14, 483-486
(2017).
19. D. T. Severson, R. P. Owen, M. J. White, X. Lu, B. Schuster-Böckler, BEARscc determines robustness
of single-cell clusters using simulated technical replicates. Nat Commun 9, 1187 (2018).
20. J. Won et al., Development of a Laboratory-safe and Low-cost Detection Protocol for SARS-CoV-2 of
the Coronavirus Disease 2019 (COVID-19). Exp Neurobiol 29, 107-119 (2020).
21. M. Y. Li, L. Li, Y. Zhang, X. S. Wang, Expression of the SARS-CoV-2 cell receptor gene ACE2 in a wide
variety of human tissues. Infect Dis Poverty 9, 45 (2020).
22. D. E. Freedberg, B. Lebwohl, J. A. Abrams, The impact of proton pump inhibitors on the human
gastrointestinal microbiome. Clin Lab Med 34, 771-785 (2014).
23. S. Senkel, B. Lucas, L. Klein-Hitpass, G. U. Ryffel, Identification of target genes of the transcription
factor HNF1beta and HNF1alpha in a human embryonic kidney cell line. Biochim Biophys Acta 1731, 179-190
(2005).
24. K. B. Pedersen, H. Chodavarapu, E. Lazartigues, Forkhead Box Transcription Factors of the FOXA
Class Are Required for Basal Transcription of Angiotensin-Converting Enzyme 2. J Endocr Soc 1, 370-384
(2017).
25. T. Chen et al., Clinical characteristics of 113 deceased patients with coronavirus disease 2019:
retrospective study. BMJ 368, m1091 (2020).
26. R. Zhang et al., Role of HIF-1alpha in the regulation ACE and ACE2 expression in hypoxic human
pulmonary artery smooth muscle cells. Am J Physiol Lung Cell Mol Physiol 297, L631-640 (2009).
27. B. M. Henry et al., Lactate dehydrogenase levels predict coronavirus disease 2019 (COVID-19) severity
and mortality: A pooled analysis. Am J Emerg Med 38, 1722-1726 (2020).
28. D. E. Freedberg et al., Famotidine Use is Associated with Improved Clinical Outcomes in Hospitalized
COVID-19 Patients: A Propensity Score Matched Retrospective Cohort Study. Gastroenterology, (2020).
. CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted September 11, 2020. .https://doi.org/10.1101/2020.09.10.20179135doi: medRxiv preprint
15
29. C. V. Almario, W. D. Chey, B. M. R. Spiegel, Increased Risk of COVID-19 Among Users of Proton Pump
Inhibitors. American Journal of Gastroenterology NA, NA (2020).
Funding:
This work was supported by Brazilian National Council for Scientific and Technological
Development (grant number 313662/2017-7); the São Paulo Research Foundation (grant
numbers 2018/14933-2; 2018/21934–5; 2017/27131-9; 2013/08216-2; 2020/04836-0); and
CAPES.
Author declaration
Authors declare no competing interests.
Author contributions
L.J., A.E.R.O., L.K.K.F., H.I.N. performed the transcriptome analyses. A.C.C., G.G.D.,
L.B.M., J.V.V, G.F.S., S.P.M., J.L.P., P.M.M. performed the experimental work. V.S.S.,
M.G.S.B., N.Z., F.A.G., M.L.N., F.A.V., G.C.M., W.M.M., M.V.G.L. performed the clinical
analysis. H.I.N. coordinated the study. L.J. and H.I.N. wrote the manuscript with inputs from
all of the co-authors.
Supplementary Materials:
Tables S1 and S2
. CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted September 11, 2020. .https://doi.org/10.1101/2020.09.10.20179135doi: medRxiv preprint