Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
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Advances in Clinical and Experimental Medicine

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doi: 10.17219/acem/163409

Publication type: original article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

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Tug E, Fidan I, Bozdayi G, et al. The relationship between the clinical course of SARS-CoV-2 infections and ACE2 and TMPRSS2 expression and polymorphisms [published online as ahead of print on June 16, 2023]. Adv Clin Exp Med. 2024. doi:10.17219/acem/163409

The relationship between the clinical course of SARS-CoV-2 infections and ACE2 and TMPRSS2 expression and polymorphisms

Esra Tug1,A,C,D,E, Isil Fidan2,A,B,C,D,E,F, Gulendam Bozdayi2,A,B,E, Fatma Yildirim3,B,E, Ozlem Guzel Tunccan4,A,B,E, Zubeyde Lale5,B,D,E, Dogan Akdogan6,A,B

1 Department of Medical Genetics, Medical University of Gazi, Turkey

2 Department of Medical Microbiology, Medical University of Gazi, Turkey

3 Department of Chest Diseases, Pulmonary Intensive Care Unit, University of Health Sciences, Diskapi Yildirim Beyazit Research and Education Hospital, Turkey

4 Department of Infectious Diseases, Medical University of Gazi, Turkey

5 Department of Medical Microbiology, Dışkapı Yıldırım Beyazit Research and Education Hospital, Turkey

6 Department of Medical Microbiology, Pursaklar State Hospital, Turkey

Graphical abstract


Graphical abstracts

Abstract

Background. The viral spike (S) protein and host ACE2 and TMPRSS2 genetic variations may act as a barrier to viral infections or determine susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections.

Objectives. We investigated the relationship between the expression patterns and polymorphisms of the ACE2 and TMPRSS2 receptor genes associated with coronavirus disease 2019 (COVID-19) and the clinical course of SARS-CoV-2 infections.

Materials and methods. We examined 147 COVID-19 patients (41 asymptomatic, 53 symptomatic and 53 cases treated in the intensive care unit (ICU)) and 33 healthy controls. The ACE2 and TMPRSS2 expression was determined using the One-Run RT-qPCR kit. Genotypic distributions of single nucleotide polymorphisms (SNPs) of ACE2 and TMPRSS2 were obtained using reverse transcription quantitative polymerase chain reaction (RT-qPCR).

Results. The expressions of ACE2 and TMPRSS2 were different between SARS-CoV-2-positive and -negative groups. The ACE2 rs714205GG genotype and G-allele showed significant differences in the asymptomatic SARS-CoV-2-positive group. A significant correlation was found between the expression of TMPRSS2 rs8134378GA, rs2070788GA, rs7364083GA, and rs9974589AC genotypes and SARS-CoV-2 positivity. The rs1978124 C-allele and rs8134378 A-allele expressions were significant in the symptomatic SARS-CoV-2-positive group. The TMPRSS2 rs2070788GA expression was different in all patient groups compared to the control group. There was a difference between SARS-CoV-2-positive and -negative groups regarding the CTTA haplotype formed by ACE2 variants. The AGCAG and AGAAG haplotypes formed by the TMPRSS2 variants were more common in the asymptomatic patient group than in other patient groups.

Conclusions. Identifying the relationship between host genetic variants and COVID-19 susceptibility will contribute to further studies, enabling new vaccines and potential therapeutic approaches to be discovered.

Key words: single nucleotide polymorphisms, expressions, COVID-19, ACE2 gene, TMPRSS2 gene

Background

The new type of severe acute respiratory syndrome (SARS) caused by coronavirus (CoV)-2 (2019-nCoV/SARS-CoV-2) led to a life-threatening coronavirus disease 2019 (COVID-19) pandemic all over the world, resulting in multiple organ failure, immune reactions and septic shock.1, 2 The effect of variations on susceptibility to SARS-CoV-2 infections and the severity of symptoms in certain populations have recently been one of the most emphasized areas, and it is thought that these variations may be an important factor in determining susceptibility to infections and severity of the disease.3 The entry of SARS-CoV-2 into target cells takes place through the binding of the S1 unit of the viral spike (S) protein to the angiotensin-converting enzyme 2 (ACE2) surface receptors of the target cell, then cleaving the S1-S2 unit of the S protein through the transmembrane protease serine 2 (TMPRSS2) receptor, and facilitating the entry of the virus into the cell through membrane fusion of the unit containing S2.3, 4, 5 Virus receptor binding is an important first step in viral infection.5 Therefore, it is thought that variations may affect the expression patterns in host ACE2 and TMPRSS2 receptor genes, and the viral S protein may act as a barrier for viral infection and may determine the susceptibility to COVID-19 infections, affecting the course of the disease.4, 6, 7, 8, 9

The ACE2 gene localized on chromosome Xp22 is expressed in tissues such as the colon and lung, but is more dominant in the heart, kidney and testicles. In addition to the predominance of respiratory system symptoms during infection, the development of complications, mostly in the heart and lungs, is explained by the abundant expression of the gene on type 2 pneumocytes, especially in the lungs.7, 9, 10, 11 Clinical studies have shown that ACE1/ACE2 polymorphisms are associated with a risk for cardiovascular and pulmonary diseases.8, 12 Therefore, the coexistence of hereditary predispositions or common gene polymorphisms affecting the expression of ACE1/ACE2 genes may cause increased capillary permeability in alveolar cells, coagulation, fibrosis, apoptosis, acceleration of lung damage, and pulmonary failure. Thus, although it is not always a rule, SARS-CoV-2 infections can be experienced much more severely in patients with existing chronic diseases.13

The ACE2 is a polymorphic gene in the human genome with approx. 140 single nucleotide polymorphism (SNP) loci, some of which are associated with COVID-19.5 In previous studies, special attention was drawn to rs2285666 (G8790A), which is in the 3rd intron of the ACE2 and affects the expression of the gene with alternative splicing. It has been suggested that rs1978124 at intron 1 and rs714205 SNPs at intron 16 of the gene show a strong linkage disequilibrium with rs2285666. It has been stated that the rs73635825 variant causes significant differences in intermolecular interactions between the receptor and S protein.5, 9, 11 Additionally, polymorphisms in the TMPRSS2 gene localized at 21q22.3 may have greater importance in society in terms of the spread of influenza A and coronavirus infections. In this context, it has been stated that some SNPs in the TMPRSS2 gene have functional significance by affecting the expression of the gene in genome-wide association studies.14, 15 Single nucleotide polymorphisms affecting proinflammatory and anti-inflammatory cytokine levels in cytokine genes have been indicated in the development of the “cytokine storm” in severe COVID-19 infection.16, 17

Objectives

The genetic differences observed in ACE2 and TMRPSS2 receptors, which play a role in the attachment of the virus to host cells, are important for the susceptibility of individuals to infection, and some SNPs in the ACE2 may affect the susceptibility to SARS-CoV-2 infections by creating a predisposition for hypertension and other cardiovascular diseases.18 Therefore, in our study, we aimed to determine the expression levels of ACE2 and TMPRSS2 in Turkish patients with SARS-CoV-2 infection, as well as the relationship between some common SNPs in these genes and the clinical course of the COVID-19 infection.

Materials and methods

Subjects

Individuals presenting to our hospital between December 2020 and May 2021 due to infection or contact with individuals infected with SARS-CoV-2, and who were tested for COVID-19 using the real-time polymerase chain reaction (PCR) method from a nasal-throat swab at the Gazi University (Ankara, Turkey) were included in this study.

Our case-control study followed the principles of the Declaration of Helsinki and was approved by the Gazi University Faculty of Medicine Clinical Research Ethics Committee (approval No. 2020-611).

The power analysis was conducted using G*Power v. 3.1.9.7 software (https://g-power.apponic.com/) to determine the minimum sample size required to test the study hypothesis. Results indicated that the required total sample size (power = 0.80, α = 0.05, effect size = 0.25) was 180. The eta squared (η2) was used to determine the effect size.

The participant flow diagram for the study is shown in Figure 1. The individuals included in the study were grouped as follows:

Group 1: Asymptomatic patients who were found to be positive for SARS-CoV-2 (n = 41);

Group 2: Symptomatic patients who were found to be positive for SARS-CoV-2 and did not require treatment in the intensive care unit (ICU) (n = 53);

Group 3: Symptomatic patients who were found to be positive for SARS-CoV-2 and treated in the ICU (n = 53);

Group 4: Control group – individuals who had a history of contact with individuals determined to be SARS-CoV-2-positive, who were found to be SARS-CoV-2 negative (n = 33).

Peripheral venous blood samples of each patient who agreed to participate in the study had been stored in 4-milliliter ethylenediaminetetraacetic acid (EDTA) tubes at −80°C until the beginning of the study.

RNA extraction and reverse transcription quantitative PCR (RT-qPCR)

Total RNA was extracted from the peripheral venous blood samples using the NucleoSpin® RNA Blood kit (Macherey-Nagel GmbH & Co. KG, Düren, Germany), following the manufacturer’s protocols. The concentration and quality of total RNA were assessed spectrophotometrically at 260 nm absorbance (NanoDrop 1000 Spectrophotometer; Thermo Fisher Scientific, Waltham, USA). We used the NCBI Primer-BLAST designing tool for primer design (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). In primer design, care was taken to ensure that almost all primers had a similar melting temperature, and primers with prominent hairpins, homodimers or heterodimers were excluded.19 The ACE2 and TMPRSS2 expressions were determined using the One-Run RT-qPCR kit (catalog No. 18R-01-100; SNP Biotechnology, Ankara, Turkey), together with the specific primers for ACE2 and TMPRSS2 from the total RNA using the CFX96 Thermocycler (Bio-Rad, Hercules, USA). The sequences of oligonucleotides used for the RNA isolations of ACE2 and TMPRSS2 genes are given in Table 1. The expressions of ACE2 and TMPRSS2 were determined after RT-qPCR consisting of 50 cycles of 8 min at 42°C, 1 s at 96°C and 25 s at 60°C were normalized to the β-actin gene as a control. Each real-time PCR reaction was performed in duplicate. The gene expressions were analyzed using the Gene Study software (CFX96; Bio-Rad).

Genomic DNA extraction and determination of SNPs

After obtaining genomic DNA from the 100 µL of peripheral venous blood of the SARS-CoV-2-positive patient groups and control group using the DNA isolation kit (SNP Biotechnology), the genotype and allele distributions of rs714205, rs73635825, rs2285666, and rs1978124 in ACE2, and rs8134378, rs2070788, rs7364083, rs13052975, and rs9974589 in TMPRSS2 were investigated using real-time PCR (CFX96; Bio-Rad), and haplotype analyzes were performed. The RT-qPCR mixture used per sample was prepared with 1.25 µL of primer/probe, 12.5 µL of TaqMan 2x PCR Mix, 9.375 µL of RNAse-free water, and 1.875 µL of template DNA with a total reaction volume of 25 µL, following the manufacturer’s recommendations. While PCR amplification was performed, the genotypes were determined according to the high-resolution melting curve analysis by the glow of the fluorescent dye used (EvaGreen; Metabion, Martinsried, Germany). The genotyping was made according to the melting temperature (Tm) of double-stranded DNA, which was denatured during PCR by increasing the temperature and the presence of DNA binding dye. Homozygous and heterozygous mutations cause the Tm to shift compared to a wild-type sample.19

Statistical analyses

The statistical analysis of the data obtained at the end of the study was performed using the IBM SPSS v. 20 software (IBM Corp., Armonk, USA). Parametric variables were expressed as mean and standard deviation (M ±SD). The η2 was used to determine the effect size. To determine the differences between ACE2 and TMPRSS2 expression levels in the SARS-CoV-2-positive and -negative groups, we performed t-tests with Bonferroni correction (Supplementary Table 1). We also compared ACE2 and TMPRSS2 expression levels between the subgroups (asymptomatic patients, symptomatic patients, ICU-treated patients, and controls). As a result of the groups not being normally distributed, the Kruskal–Wallis test was used to compare the expression levels between the subgroups (Supplementary Tables 2 and 3). There were statistically significant differences between the subgroups. The homogeneity of variance was examined using Levene’s test. Variances were not assumed equal; thus, a post hoc Dunn’s test was used to perform pairwise comparisons (Supplementary Table 4). The Hardy–Weinberg balance for the distributions of genotypes was calculated using the χ2 test. A p-value <0.05 was considered statistically significant. The odds ratio (OR) and corresponding 95% confidence interval (95% CI) values were analyzed using multiple logistic regression tests in order to estimate the association of genotypes, allele frequencies and other variables with the occurrence and severity of COVID-19. Moreover, the correlation between COVID-19 and risk factors such as comorbidities, age, gender, ACE2, and TMPRSS2 expressions was analyzed with a multinomial logistic regression model (Supplementary Table 5).

Results

The demographic data of study groups are shown in Table 2. The multinomial logistic regression results of independent variables affecting COVID-19 severity are presented in Supplementary Table 6.

ACE2 and TMPRSS2 expression

The ACE2 expression was determined as 1.34 ±0.14 (M ±SD) in the control group and 21.58 ±4.12 in the SARS-CoV-2-positive group, with a statistical difference between the groups (p = 0.001). The TMPRSS2 expression was determined as 1.20 ±0.15 and 132 ±41.61 in the SARS-CoV-2-positive and -negative groups, respectively, and a significant difference was found between the 2 groups (p = 0.002; Figure 2).

The ACE2 and TMPRSS2 expressions were higher in the ICU-treated patient group compared to the control group (p = 0.001). Although ACE2 and TMPRSS2 expressions were higher in the asymptomatic and symptomatic patient groups compared to the control group, a significant difference was only observed between the symptomatic patient group and the control group (p = 0.013 and p = 0.041, respectively). The ACE2 and TMPRSS2 expressions were also higher in the ICU-treated patient group compared to the other patient groups (p = 0.001 and p = 0.001 for the ACE2 gene, respectively; p = 0.020 and p = 0.002 for the TMPRSS2 gene, respectively). There was no difference between the asymptomatic and symptomatic patient groups in terms of ACE2 and TMPRSS2 expression (p = 0.456 and p = 0.953, respectively; Figure 3).

In the study groups, ACE2 and TMPRSS2 expressions did not differ according to gender (p > 0.05). There was no significant difference in terms of clinical severity of the disease according to gender among the patient groups (p = 0.956 and p = 0.458 respectively).

The mean age was higher in the SARS-CoV-2-positive patient group who were treated in the ICU compared to the other patient and control groups (p = 0.001). Also, there was a significant difference between the clinical course of infection and age in the SARS-CoV-2-positive patient groups (p = 0.001). To determine the relationship between patient age and ACE2 and TMPRSS2 expressions, the patients were divided into 3 different age groups: 20–40 years, 40–60 years and over 60 years of age. The ACE2 expression in the over 60 years of age patient group was higher than in the 2 other age groups (p = 0.004 and p = 0.039, respectively). The TMPRSS2 expression was higher in patients over 60 years of age compared to patients aged 20–40 years (p = 0.049), but not different from patients aged 40–60 years (p = 0.415).

The presence of comorbid diseases was more common in those treated in the ICU than in the other patient groups (p = 0.001). It was determined that ACE2 and TMPRSS2 expression levels increased in the presence of comorbid diseases in the SARS-CoV-2-positive patient group (p = 0.001 and p = 0.02, respectively). There was no difference between ACE2 and TMPRSS2 expressions and the presence of comorbid diseases in the asymptomatic and symptomatic patient groups (p = 0.795 and p = 0.311 for the ACE2 gene, respectively; p = 0.469 and p = 0.302 for the TMPRSS2 gene, respectively). Higher ACE2 and TMPRSS2 expression levels were detected in the presence of comorbid diseases in the ICU-treated patient group (p = 0.019 and p = 0.018, respectively).

ACE2 and TMPRSS2 SNPs

The sum of the genotypes obtained for each of the ACE2 and TMPRSS2 SNPs in our study groups was equal to 1, and the genotype and allele distributions were in the Hardy–Weinberg equilibrium. The genotype and allele distributions of ACE2 SNPs were similar in the SARS-CoV-2-positive and -negative groups (p > 0.05; p-values are given in Table 3). When the genotype and allele distributions of TMPRSS2 polymorphisms were examined, the expressions of rs2070788GA, rs7364083GA and rs9974589AC genotypes were higher in the SARS-CoV-2-positive group (p-values = 0.001, 0.036 and 0.024, respectively) compared to the control group (Table 3).

Although the rs714205GG genotype was more common in asymptomatic, symptomatic and ICU-treated patients than in the control group, a statistical difference was observed only in the asymptomatic patient group (p = 0.049). Similarly, the expression of rs714205 G-allele was found to be higher in the asymptomatic patient group (p = 0.032). In the symptomatic patient group, the expressions of rs1978124 C-allele, rs8134378GA genotype and A-allele were statistically different compared to the other patient and control groups (p = 0.032, 0.014 and 0.006, respectively). The expression of rs2070788GA genotype was different in all groups compared to the control group (p = 0.039, 0.001 and 0.001, respectively). The expressions of rs7364083GA and rs9974589AC genotypes were statistically different in the symptomatic patient group compared to the other patient and control groups (p = 0.003 and 0.005, respectively; Table 4).

No significant relationship was found between SNPs investigated in our study and ACE2 and TMPRSS2 expression levels (p > 0.05).

The multinomial logistic regression results of independent variables affecting genotypic distribution are shown in Supplementary Table 7.

ACE2 and TMPRSS2 haplotype frequencies

Based on the CCTA haplotype formed by the wild-type alleles of ACE2 variants, 9 and 8 haplotypes with frequencies above 5% were detected in the patient and control groups, respectively. The CCTA haplotype was the highest in the SARS-CoV-2-positive patient group, and the CCTA and CCCA haplotypes were similar in the control group. While the CTTA haplotype showed a statistical difference between the SARS-CoV-2-positive patient group and the control group (p = 0.02), there was no difference between the SARS-CoV-2-positive patient groups in terms of ACE2 haplotype frequencies (p > 0.05; p-values are given in Table 5). Thirty haplotypes were identified in the SARS-CoV-2-positive patient groups with TMPRSS2 variants, 16 haplotypes were identified in the control group, and GGAGG consisting of wild-type alleles was taken as the reference haplotype. There was no statistical difference between the SARS-CoV-2-positive patient and control groups in terms of haplotype distributions (p > 0.05; p-values are given in Table 6).

In the SARS-CoV-2-positive asymptomatic patient group, AGCAG and AGAAG haplotypes had a higher frequency than those in the other patient groups (symptomatic and ICU-treated, p = 0.03 and p = 0.01, respectively).

Discussion

Variations in the nucleotide sequences of the 2 host genes, ACE2 and TMPRSS2, indispensable in the introduction of coronavirus into host cells, may alter the expression and functionality of these proteins.20 Although recent studies have attempted to associate these variants with susceptibility to SARS-CoV-2 infections,5, 21, 22 there is not yet sufficient evidence that rare variants in ACE2 can modulate susceptibility to SARS-CoV-2 infections. However, TMPRSS2, which plays a role in the proteolytic cleavage of the SARS-CoV-2 S proteins and thus facilitates the entry of the virus into the host cell, contains many variants of different frequencies among human populations.20 Therefore, the relationship between the risk and susceptibility of SARS-CoV-2 infections and different polymorphisms of ACE2 and TMPRSS2 and expression levels was investigated in COVID-19 patients and a control group. According to our results, ACE2 and TMPRSS2 expressions were significantly increased in the SARS-CoV-2-positive patient group compared to the control group, and the expressions of the genes were higher in the ICU-treated group compared to the asymptomatic and symptomatic COVID-19 patient groups (Figure 3). The data obtained from patients with a more severe clinical course of COVID-19 support the claim that ACE2 and TMPRSS2 genes may be directly related to the severity of COVID-19. Especially since the ACE2 receptor is the target molecule for the entry of SARS-CoV-2 into cells, and the TMPRSS2 is the main protease facilitating the entry of SARS-CoV-2 into host cells, the increased expression of both genes indicates that these patients have more severe SARS-CoV-2 viremia. In other words, it can be said that there is a cause-effect relationship. This important finding suggests that in the future, inhibition strategies targeting ACE2 or TMPRSS2 at the gene or receptor level may be developed and used as an antivirus and/or therapeutic approach to reduce the entry of SARS-CoV-2 into host cells and minimize the mortality rate.

The localization of the ACE2 gene on the X chromosome leads to the fact that females are potentially heterozygous for the expression of this gene and males are hemizygous.23 Therefore, it is natural that there are differences in ACE2 expression between males and females in theory, yet in practice and in our study, no difference was observed between the genders in terms of ACE2 expression. Although, it is argued that the reactions of females to SARS-CoV-2 viremia may be different due to the localization of inflammation-related genes, including innate and adaptive immune response-related genes on the X chromosome.24 The gender difference between females and males and the fact that males were hemizygous in terms of ACE2 did not have any effect on the more severe course of COVID-19 in our study groups. Similarly, Alimoradi et al. showed that gender was not significantly associated with the severity and incidence of COVID-19.5 The mean age and the presence of comorbid diseases in COVID-19 patients in the ICU-treated group differed compared to the other groups in our study. The ACE2 and TMPRSS2 expression levels were higher in the SARS-CoV-2-positive patients over 60 years old. The ACE2 and TMPRSS2 expression levels were different in ICU-treated patients with comorbid diseases compared to those without comorbid diseases.

Of the ACE2 polymorphisms, only the expression of rs714205GG genotype and G-allele showed a significant difference in the SARS-CoV-2-positive asymptomatic group, suggesting that this variant may be associated with a lighter clinical course. In the SARS-CoV-2-positive symptomatic patient group, the expression of rs1978124 C-allele was statistically different from other groups. According to this result, it can be concluded that the rs1978124 C-allele is effective in the symptomatic course of infection. However, taking into account the patient’s immunity and comorbid diseases, such interpretation is appropriate. In addition, other possibilities should be considered, such as gene–RNA interactions and epigenetic factors, where there may be other ACE2 polymorphisms or interactions of different genes that may affect ACE2 receptor function. Möhlendick et al. reported that carriers of the ACE2 rs2285666GG genotype or G-allele have a twofold increased risk for SARS-CoV-2 infections compared to the AA genotype.9 This conclusion was also supported by Alimoradi et al.5 In our study, the rs2285666 G- and A-alleles were not found in the patient and control groups, and there was no difference between the groups in terms of the determined C- and T-alleles. However, this result does not reflect the whole population, and allele frequencies may vary between populations. Therefore, the susceptibility of different ethnic groups to SARS-CoV-2 may vary in relation to different genotypes.

According to our results, the expression of TMPRSS2 rs2070788GA, rs7364083GA and rs9974589AC genotypes showed significant differences in SARS-CoV-2-positive patients. Especially regarding the rs2070788GA genotype, there was a significant difference in all SARS-CoV-2-positive patient groups. Therefore, we believe that the presence of rs2070788GA is associated with SARS-CoV-2 sensitivity rather than the clinical course of COVID-19. The minor allele frequencies (MAFs) of rs7364083 and rs9974589 differed in populations according to the genome aggregation database (gnomAD) (https://gnomad.broadinstitute.org/). In our study groups, the frequency of variant alleles rs7364083 and rs9974589 was found to be higher, which is similar to the literature.25 Moreover, the rs7364083GA and rs9974589AC genotypes were higher in the SARS-CoV-2-positive groups, and a statistical difference was observed only in the symptomatic patient group. Thus, the rs7364083GA and rs9974589AC genotypes may be associated with SARS-CoV-2 susceptibility and may correlate with the clinical course of COVID-19 infections. The rs8134378 A-allele, which differs significantly in SARS-CoV-2-positive symptomatic patients, may also be associated with infection sensitivity.

Previous studies have suggested that the ACE2 rs2285666 A-allele is associated with increased ACE2 expression in healthy individuals as well as in patients with diabetes and cerebral stroke.9, 26 Gómez et al. declared that there was no difference in terms of ACE2 rs2285666 variants in COVID-19 patients with mild and severe course of the disease, but this variant was associated with hypertension in the elderly population.12 In patients with multiple sclerosis who have a SARS-CoV-2 infection, TMPRSS2 rs61735792 and rs61735794 variants are reported to be associated with the severity of the infection.27 In our study, 13.2% of the SARS-CoV-2-positive symptomatic patients and 84.9% of the ICU-treated patients had at least 1 comorbid disease such as hypertension, cardiovascular disease, diabetes mellitus, chronic lung diseases, kidney diseases, liver diseases, and malignancies. In the SARS-CoV-2-positive patient groups with comorbid diseases, ACE2 and TMPRSS2 expressions were higher. In the ICU-treated patient group, ACE2 and TMPRSS2 expression levels were higher in the presence of comorbid diseases. There was no relationship between the SNPs examined and ACE2 and TMPRSS2 expression levels, but it should not be ignored that there may be other genetic factors, such as other intragenic variations, regulatory genes and epigenetic factors that may affect ACE2 and TMPRSS2 expression levels.

Gemmati et al. suggest a strong linkage disequilibrium between ACE2 rs1978124, rs714205 and rs2285666 variants.11 According to our results, the CTTA haplotype frequency formed with ACE2 variants in the SARS-CoV-2-positive patient group was lower than in the control group. Therefore, the CTTA haplotype may be more resistant to SARS-CoV-2 infections. In terms of the TMPRSS2 haplotypes, although there was no difference between the SARS-CoV-2-positive patient groups and the control group, AGCAG and AGAAG haplotypes were identified more frequently in the asymptomatic SARS-CoV-2-positive patient group compared to the other patient groups. Therefore, these haplotypes may have a role in a milder course of COVID-19.

Martínez-Sanz et al. reported that ACE2 rs2106806 and rs6629110 variants may be responsible for SARS-CoV-2 infection susceptibility in hospital staff not infected with SARS-CoV-2 and in hospitalized COVID-19 patients.18 Similarly, Hou et al. stated that polymorphisms in ACE2 and TMPRSS2 genes may be associated with genetic susceptibility to COVID-19.4 Irham et al. suggested that there is an increase in TMPRRS2 expression associated with rs464397, rs469390, rs2070788, and rs383510 variations in lung tissue, which is the major infection site for SARS-CoV-2, and this increase may affect infection severity as well as SARS-CoV-2 sensitivity.28 According to our study, the high frequency of the rs2070788GA genotype in the SARS-CoV-2-positive group and the increased TMPRSS2 expression detected in the ICU-treated group support the view that TMPRSS2 variants affect the expression of the gene and increase the susceptibility to SARS-CoV-2 infections. Irham et al. showed that there is a higher TMPRSS2 expression in lung tissues in the rs2070788GG genotype.28 In our study, although there was no relationship between ACE2 and TMPRSS2 expressions and genotypes in the peripheral venous blood of the patient and control groups, it was not possible to evaluate ACE2 and TMPRSS2 expressions in target tissues, especially the lungs.

Abdelsattar et al. reported that ACE2 rs2285666 and TMPRSS2 rs12329760 variants may be associated with COVID-19 disease severity.29 However, in our study, no finding reported the relationship between ACE2 rs2285666 genotype and allele frequency with disease severity. Pandey et al. stated that SARS-CoV-2 host sensitivity in South Asian population is similar to the Western Eurasian population, and this sensitivity is associated with the TMPRSS2 gene.30 Thus, there is a significant relationship between rs2070788 G-allele and the COVID-19 mortality rate. In our study, the frequency of the rs2070788GA genotype was also found to be high in the SARS-CoV-2-positive patient groups, especially in the symptomatic and ICU-treated patients, but it was detected at a significantly different frequency from the control group. Therefore, we believe that this variant is associated with COVID-19 disease severity, but it is quite difficult to associate the TMPRSS2 expression level with this variant alone, and it is more appropriate to conduct multicenter studies from different populations to confirm this finding.

Hussain et al. reported that ACE2 variants such as rs73635825 and rs143936283 may create a positive prognosis for COVID-19 course in some individuals.6 The ACE2 rs73635825 variant, which is quite rare, was found in only 1 patient in our study group, and no difference was observed between the groups.

It is suggested that there is no relationship between ACE2 expression and variants and severity of COVID-19 and gender in the Italian population. However, TMPRSS2 expression and variants differed according to gender and may be effective in the prognosis of the disease.24 According to our results, ACE2 and TMPRSS2 expressions, variants and the severity of infection did not differ between the genders in the SARS-CoV-2-positive patient and control groups. However, it would be more appropriate to support these results with similar studies in a larger study population.

Kim and Jeong reported that ACE2 rs2074192 and TMPRSS2 rs2298659 showed a higher correlation compared to other ACE2 and TMPRSS2 variants, while IFITM3 rs6598045 was associated with COVID-19-related mortality rates.31 We found that ACE2 rs714205 may be effective in the milder clinical manifestation of COVID-19, and even ACE2 rs1978124 and TMPRSS2 rs8134378, rs2070788, rs7364083, and rs9974589 may be effective in varying degrees of symptomatic courses of COVID-19. We also demonstrated a correlation between changes in ACE2 and TMPRSS2 expression levels and the clinical findings of COVID-19.

Conclusions

In conclusion, our study demonstrated that genetic factors of the host may affect the sensitivity and clinical course of COVID-19. Since SARS-CoV-2 is a new virus on which studies have been conducted for the last 2 years, it is a long process to define the genetic factors affecting infection sensitivity. Conducting studies aimed at determining genetically-based prognostic factors that will enable the early detection of individuals at high risk who require urgent medical treatment for COVID-19 is even more important, especially during epidemic periods. Studies in different populations in which the number of patients, examined genes and polymorphisms are increased will provide more information about the genetic variations at the receptor level and host genetic characteristics that may be effective in the sensitivity and clinical course of COVID-19.

Limitations

The main limitation of our study is that ACE2 and TMPRSS2 expression levels can only be studied in peripheral venous blood. We also observed a total of 9 SNPs in these 2 genes. Moreover, the possible role of host genetics on SARS-CoV-2 vaccine efficacy was not evaluated. Future research should address the correlation between host genetic factors and the response to the SARS-CoV-2 vaccine.

Conclusions

The data of our study shed light on the establishment of genetic biomarkers in the predetermination of susceptible populations for COVID-19, the identification of new and effective drug targets for COVID-19 patients, and the development of new vaccines.

Supplementary data

The supplementary materials are available at https://doi.org/10.5281/zenodo.7826506. The package contains the following files:

Supplementary Table 1. T-test (ACE2 and TMPRSS2 expression levels in the SARS-CoV-2-positive and negative groups).

Supplementary Table 2. Normal distribution test (ACE2 and TMPRSS2 expression levels between the subgroups (asymptomatic patient, symptomatic patient, ICU-treated, and control groups)).

Supplementary Table 3. Kruskal–Wallis test results.

Supplementary Table 4. Post hoc tests results.

Supplementary Table 5. Assumption checking results.

Supplementary Table 6. Multinomial logistic regression results of independent variables affecting COVID-19 disease severity.

Supplementary Table 7. Multinomial logistic regression results of independent variables affecting genotypic distribution.

Tables


Table 1. Sequences of oligonucleotides used in the multiplex polymerase chain reaction (PCR) assay for RNA isolation of the ACE2 and TMPRSS2 genes

Oligonucleotide name

Sequence

ACTB forward

5’-CCCAGCACAATGAAGATCAAGATC-3’

ACTB reverse

5’-GGGTGTAACGCAACTAAGTCATAGTC-3’

ACTB molecular beacon

5’-FAM-AGATCATTGCTCCTCCTGAGCGCAAG-3’

ACE2 forward

5’-GATCAGAGATCGGAAGAAGAAAAATAAAGC-3’

ACE2 reverse

5’-CTAAAAGGAGGTCTGAACATCATCAGTG-3’

ACE2 molecular beacon

5’-FAM-AGAAAATCCTTATGCCTCCATCGATATTAGC-3’

TMPRSS2 forward

5’-GAATGTGATGGTATTCACGGACTG-3’

TMPRSS2 reverse

5’-CTTGTAAAACGACGTCAAGGACGAAG-3’

TMPRSS2 molecular beacon

5’-TCGACAAATGAGGGCAGACGGCTAATC-3’

ACTB – human B-actin gene; ACE2 – angiotensin-converting enzyme 2 gene; FAM – fluorescein; TMPRSS2 – transmembrane protease serine 2 gene.
Table 2. Demographic data of the study groups

Demographic and comorbidity data

Controls
(n = 33)

Asymptomatic patients (n = 41)

Symptomatic patients (n = 53)

ICU-treated patients (n = 53)

Gender, n (%)

female

16 (48.5)

20 (48.8)

28 (52.8)

26 (49)

male

17 (51.5)

21 (51.2)

25 (47.2)

27 (51)

Age (M ±SD)

41.72 ±8.16

42.65 ±10.91

42.52 ±9.66

67.15 ±15.35

Comorbid disease*, n (%)

3 (7.3)

7 (13.2)

45 (84.9)

* comorbid diseases: hypertension, cardiovascular diseases, diabetes mellitus, chronic lung diseases, kidney diseases, liver diseases, and malignancies; ICU – intensive care unit; M ±SD – mean ± standard deviation.
Table 3. Genotype and allele distribution of ACE2 and TMPRSS2 polymorphisms in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive and -negative groups

dbSNP ID

SARS-CoV-2-negative* (n = 33)

SARS-CoV-2-positive (n = 147)

OR

95% CI

df

p-value

rs714205

genotype

CC

24

98

1

reference

CG

6

18

0.735

0.2632.050

1

0.556

GG

3

31

2.531

0.7138.978

1

0.151

allele

C

54

214

1

reference

G

12

80

1.714

0.8723.372

1

0.118

rs73635825

genotype

AA

32

146

1

reference

AG

1

1

0.219

0.0133.597

1

0.288

GG

0

0

allele

A

65

293

1

reference

G

1

1

0.221

0.0143.581

1

0.288

rs2285666

genotype

CC

22

98

1

reference

CT

5

17

0.763

0.2542.291

1

0.630

TT

6

32

1.197

0.4463.212

1

0.721

allele

C

49

213

1

reference

T

17

81

1.096

0.5972.014

1

0.767

rs1978124

genotype

TT

13

74

1

reference

CT

8

28

0.615

0.2301.642

1

0.332

CC

12

45

0.659

0.2771.569

1

0.346

allele

T

34

176

1

reference

C

32

118

0.712

0.4171.218

1

0.215

rs8134378

genotype

GG

29

107

1

reference

GA

4

37

2.507

0.8267.609

1

0.105

AA

0

3

allele

G

62

251

1

reference

A

4

43

2.655

0.9197.677

1

0.071

rs2070788

genotype

GG

11

32

1

reference

GA

4

72

7.535

2.3923.734

1

0.001

AA

18

43

1.218

0.5062.932

1

0.660

allele

G

26

136

1

reference

A

40

158

1.324

0.7682.282

1

0.312

rs7364083

genotype

GG

6

22

1

reference

GA

12

83

2.470

0.1065.750

1

0.036

AA

15

42

1.310

0.4463.849

1

0.624

allele

G

24

127

1

reference

A

42

167

1.320

0.7602.294

1

0.324

rs13052975

genotype

GG

23

98

1

reference

GA

8

45

1.320

0.5483.178

1

0.535

AA

2

4

0.469

0.0812.720

1

0.399

allele

G

54

241

1

reference

A

12

53

0.990

0.4951.978

1

0.976

rs9974589

genotype

AA

6

28

1

reference

AC

12

81

2.664

1.1376.242

1

0.024

CC

15

38

1.842

0.6355.345

0.261

allele

A

24

137

1

reference

C

42

157

1.527

0.8802.650

1

0.132

* individuals who had a history of contact with individuals determined to be SARS-CoV-2-positive, who were found to be SARS-CoV-2-negative using polymerase chain reaction (PCR), and who were not infected with SARS-CoV-2 (control group). OR – odds ratio; 95% CI – 95% confidence interval; df – degrees of freedom; dbSNP – Single Nucleotide Polymorphism Database. Values in bold indicate statistical significance.
Table 4. Genotype and allele distributions of ACE2 and TMPRSS2 polymorphisms in the study groups including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patient groups consisting of asymptomatic, symptomatic and ICU-treated individuals, and a SARS-CoV-2-negative group

dbSNP ID

SARS-CoV-2-negative* (n = 33)

SARS-CoV-2-positive asymptomatic patients

SARS-CoV-2-positive symptomatic patients

SARS-CoV-2-positive symptomatic and ICU-treated patients

= 41

OR

95% CI

p-value

= 53

OR

95% CI

p-value

= 53

OR

95% CI

p-value

rs714205

genotype

CC

24

25

1

reference

40

1

reference

33

1

reference

CG

6

4

0.650

1.1602.553

0.527

6

0.600

0.1742.073

0.419

8

0.970

0.2973.162

0.959

GG

3

12

3.840

0.96315.319

0.049

7

1.400

0.3305.933

0.648

12

0.209

0.73911.449

0.127

allele

C

54

54

1

reference

86

1

reference

74

1

reference

G

12

28

2.333

1.0765.061

0.032

20

1.098

0.4962.428

0.818

32

1.946

0.9194.122

0.082

rs73635825

genotype

AA

32

40

1

reference

53

1

reference

53

1

reference

AG

1

1

0.800

0.04813.295

0.876

0

0

GG

0

0

0

0

allele

A

65

81

1

reference

106

1

reference

106

1

reference

G

1

1

0.793

0.04912.917

0.870

0

0

rs2285666

genotype

CC

22

26

1

reference

40

1

reference

32

1

reference

CT

5

3

0.508

0.1092.368

0.388

6

0.660

0.1812.412

0.530

8

1.100

0.3183.810

0.880

TT

6

12

1.692

0.5455.252

0.363

7

0.642

0.1922.148

0.472

13

1.490

0.4914.516

0.481

allele

C

49

55

1

reference

86

1

reference

72

1

reference

T

17

27

1.415

0.6902.903

0.344

20

0.670

0.3211.399

0.287

34

1.361

0.6852.703

0.378

rs1978124

genotype

TT

13

19

1

reference

30

1

reference

25

1

reference

CT

8

7

0.599

0.1742.060

0.416

12

0.650

0.2151.965

0.445

9

0.585

0.1831.875

0.367

CC

12

15

1.169

0.3032.411

0.767

11

0.397

0.1401.130

0.083

19

0.823

0.3072.206

0.699

allele

T

34

45

1

reference

72

1

reference

59

1

reference

C

32

37

1.145

0.5982.192

0.684

34

0.502

0.2670.944

0.032

47

0.946

0.4571.568

0.596

rs8134378

genotype

GG

29

35

1

reference

32

1

reference

41

1

reference

GA

4

6

1.243

0.3204.830

0.754

19

4.444

1.35014.624

0.014

12

2.122

0.6227.241

0.230

AA

0

0

3

0

allele

G

62

76

1

reference

83

1

reference

94

1

reference

A

4

6

1.224

0.3314.530

0.762

25

4.784

1.58314.459

0.006

12

1.979

0.6106.415

0.255

rs2070788

genotype

GG

11

11

1

reference

9

1

reference

12

1

reference

GA

4

14

3.937

1.07414.438

0.039

32

12.000

3.36942.748

0.001

26

7.800

2.22127.389

0.001

AA

18

16

1.125

0.3853.291

0.830

12

1.227

0.3913.854

0.726

15

1.309

0.4503.806

0.621

allele

G

26

36

1

reference

50

1

reference

50

1

reference

A

40

46

1.204

0.6232.327

0.581

56

1.374

0.7362.563

0.319

56

1.374

0.7362.563

0.319

rs7364083

genotype

GG

6

6

1

reference

5

1

reference

11

1

reference

GA

12

22

2.115

0.7615.883

0.151

38

4.750

1.69513.309

0.003

23

1.513

0.5724.001

0.404

AA

15

13

1.154

0.2984.467

0.836

10

1.250

0.2995.230

0.760

19

1.447

0.4354.821

0.547

allele

G

24

34

1

reference

48

1

reference

45

1

reference

A

42

48

1.240

0.6362.415

0.528

58

1.448

0.7602.294

0.250

61

1.262

0.6702.379

0.471

rs13052975

genotype

GG

23

24

1

reference

37

1

reference

37

1

reference

GA

8

14

1.677

0.5934.745

0.330

16

1.243

0.4593.364

0.668

15

1.166

0.4273.180

0.765

AA

2

3

1.437

0.2209.405

0.705

0

1

0.311

0.0273.624

0.351

allele

G

54

62

1

reference

90

1

reference

89

1

reference

A

12

20

1.452

0.6503.241

0.363

16

0.940

0.5171.708

0.84

17

0.860

0.3811.937

0.715

rs9974589

genotype

AA

6

8

1

reference

8

1

reference

12

1

reference

AC

12

20

1.923

0.6865.394

0.214

35

4.375

1.55512.310

0.005

26

2.167

0.8055.831

0.126

CC

15

13

1.538

0.4225.606

0.514

10

2.000

0.5317.539

0.306

15

2.000

0.5946.730

0.263

allele

A

24

36

1

reference

51

1

reference

50

1

reference

C

42

46

1.204

0.6232.327

0.581

55

1.623

0.8643.042

0.132

56

1.224

0.8322.934

0.165

* individuals who had a history of contact with individuals determined to be SARS-CoV-2-positive, who were found to be SARS-CoV-2-negative by polymerase chain reaction (PCR), and who were not infected with SARS-COV-2 (control group); ICU – intensive care unit; OR – odds ratio; 95% CI – 95% confidence interval; dbSNP – Single Nucleotide Polymorphism Database. Values in bold indicate statistical significance.
Table 5. ACE2 rs714205 (C/G), rs2285666 (C/T), rs1978124 (T/C), and rs73635825 (A/G) haplotype frequencies in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patient and control groups

Haplotype

SARS-CoV-2-negative
(n = 60), n (%)

SARS-CoV-2-positive (n = 225), n (%)

OR

95% CI

df

p-value

CCTA

16 (26.6)

81 (36)

1

reference

CCCA

16 (26.6)

46 (20.4)

0.568

0.260–1.241

1

0.15

CTTA

7 (11.6)

10 (4.4)

0.282

0.093–0.852

1

0.02

GTTA

6 (10)

27 (12)

0.889

0.316–2.501

1

0.82

GTCA

5 (8.3)

31 (13.7)

1.225

0.413–3.629

1

0.71

GCTA

4 (6.6)

11 (4.8)

0.543

0.154–1.922

1

0.34

GCCA

3 (5)

9 (4)

0.593

0.144–2.433

1

0.46

CTCA

3 (5)

10 (4.4)

0.658

0.163–2.663

1

0.55

CCTG

0 (0)

1 (0.4)

OR – odds ratio; 95% CI – 95% confidence interval; df – degrees of freedom. Haplotypes are given according to the localization of microsatellite markers on the X chromosome. Values in bold indicate statistical significance.
Table 6. TMPRSS2 rs13052975 (G/A), rs2070788 (G/A), rs9974589 (A/C), rs7364083 (G/A), and rs8134378 (G/A) haplotype frequencies between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patient and control groups

Haplotype

SARS-CoV-2-negative
(n = 101), n (%)

SARS-CoV-2-positive
(n = 818), n (%)

OR

95% CI

df

p-value

GGAGG

14 (13.9)

95 (11.6)

1

reference

GACAG

21 (20.8)

106 (13.0)

0.744

0.358–1.545

1

0.42

GGAAG

7 (6.9)

81 (9.2)

1.705

0.657–4.429

1

0.27

GAAGG

7 (6.9)

68 (8.3)

1.432

0.549–3.736

1

0.46

GAAAG

7 (6.9)

74 (9.0)

1.558

0.598–4.056

1

0.36

GACGG

6 (5.9)

71 (8.7)

1.495

0.573–3.896

1

0.41

GGCGG

8 (7.9)

69 (8.4)

1.271

0.505–3.197

1

0.61

GGCAG

7 (6.9)

71 (8.7)

1.495

0.573–3.896

1

0.41

AACAG

6 (5.9)

46 (5.7)

1.130

0.408–3.130

1

0.81

AGAGG

5 (5.0)

24 (3.0)

0.707

0.232–2.157

1

0.54

AGCAG

2 (2.0)

12 (1.5)

0.884

0.179–4.374

1

0.88

AGCGG

3 (3.0)

16 (1.9)

0.786

0.203–3.046

1

0.72

AGAAG

3 (3.0)

13 (1.6)

0.639

0.161–2.526

1

0.52

GGAGA

3 (3.0)

34 (4.2)

1.670

0.452–6.172

1

0.44

GACAA

1 (1.0)

30 (3.7)

4.421

0.558–35.031

1

0.15

AACAA

1 (1.0)

8 (1.0)

1.179

0.137–10.154

1

0.88

OR – odds ratio; 95% CI – 95% confidence interval; df – degrees of freedom. Haplotypes are given according to the localization of microsatellite markers on the chromosome 21.

Figures


Fig. 1. CONSORT 2010 flow diagram
SARS-CoV-2 – severe acute respiratory syndrome coronavirus 2.
Fig. 2. ACE2 (A) and TMPRSS2 (B) expression levels in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patient group and the control group (**p < 0.05); t-test (t = 4.899 for the ACE2 and 3.165 for the TMPRSS2)
Fig. 3. ACE2 (A) and TMPRSS2 (B) expression levels in study groups (**p < 0.05); Kruskal–Wallis test (degrees of freedom (df) = 3 for the ACE2 and TMPRSS2)
ICU – intensive care unit; COVID-19 – coronavirus disease 2019.

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