Abstract
The pandemic coronavirus disease 2019 (COVID-19) has caused a high mortality rate and poses a significant threat to the population. The disease may progress with mild symptoms or may cause the need for intensive care, depending on many factors. In this study, it was aimed to determine if there is a tendency due to genetic factors in COVID-19 patients. Ninety-four of 188 patients with mild clinical and 94 with severe clinical symptoms were included in the study. The targeted panel including coagulopathy (F2, F5), viral invasion (ACE2), and inflammation (CXCL8, IFNAR2, IFNL4, IL10, IL2, IL6, IRF7, TLR3, TLR7, TNF) related genes was performed sequenced by the next generation sequencing (NGS). The variants found were classified and univariate analyses were performed to select candidate variables for logistic model. Risk factors and variants were compared. It was revealed that the presence of 2 or more risk factors caused the disease to progress severely (p < 0.001). Heterozygous IRF7:c.1357−23dup variant had a 2.5 times higher risk for mild disease compared to severe disease. Other variants were found to be more significant in mild disease. Since polymorphic variants were not evaluated in the literature, the findings of our study could not be compared with the literature. However, as variants that may be effective in the severity of infections may differ according to ethnicity. This study has the feature of being a guide for subsequent studies to be carried out especially in Turkish population. Clinical course of the COVID-19 is likely to depend on a variety of risk factors, including age, sex, clinical status, immunology and genetic factors.
Introduction
Coronaviruses (CoVs) are transmitted to humans through mammalian hosts and cause respiratory system, gastrointestinal system and central nervous system diseases. The new coronavirus started an epidemic in the Wuhan province of China, causing a pandemic that also affected our country at the end of 2019. This coronavirus that caused the pandemic was named as SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the disease as coronavirus disease 2019 (COVID-19) (Chakravarty 2021). Since it is able to spread quickly and cause deaths, studies on pathogenesis, treatment and vaccination of the virus have been started rapidly in many centers worldwide, as well as in our country. The severity of the disease ranges from asymptomatic to fatal for the individuals affected by SARS-CoV-2 infection (Guo et al. 2020). It has been known that genetic factors play an substantial role in the emergence of many infectious diseases observed in humans as well as microorganisms (Pairo-Castineira et al. 2021). In some cases, severe mutations in a gene may cause susceptibility to infections, whereas coexistence of mutations in more than one gene may lead to the development of infection or susceptibility to infection (Anastassopoulou et al. 2020; Wang et al. 2020). Advances in genetics have provided understanding of the onset, progression and prognosis of the disease. Thus, it is possible to see which genetic variants create a response against the infectious agent. It has been observed that there is a clinical variability among patients with COVID-19 disease, which has affected more than 500 million people and caused the death of more than 6 million people so far.
In the course of the disease, patients are divided into two groups: those who are generally asymptomatic or recover with mild clinical findings, and those who are required intensive care due to respiratory or multisystem failure (Anastassopoulou et al. 2020). The reason for this clinical variability among patients shows the possibility that differences in human genetic structure may be effective, as well as mutations in the virus (Chakravarty 2021). It has been suggested that ACE2 receptor gene polymorphisms may be effective in the intracellular entry of the virus by changing the virus affinity to this receptor (Hou et al. 2020; Pairo-Castineira et al. 2021; Flemming 2021). Genes involved in the immune system and coagulopathy pathway may also be effective. In this study, it was aimed to determine if there is a tendency to infectious diseases due to genetic factors in COVID-19 patients.
Methods
Patients
Patients over 18 years old who were evaluated in the Ankara City Hospital Infectious Diseases and Clinical Microbiology Clinic, General Hospital Anaesthesia Intensive Care Service, and Internal Medicine Intensive Care Service were included in the study. Real-time PCR results of all the patients were positive for COVID-19 disease. The patients were grouped as nonsevere and severe/critical according to the World Health Organization interim guidance (Guner et al. 2021). Ninety-four out of 188 patients had mild clinic (nonsevere), 94 had severe clinic. Risk factors of the patients such as hypertension, diabetes mellitus, chronic renal failure, coronary artery disease and chronic lung disease were not taken into account at the patient selection criteria. Ages and sex of the patients were among the inclusion criteria. Demographic findings are shown in Table 1.
Genetic analysis
Blood samples were collected into ethylenediaminetetraacetic acid (EDTA) tubes. Genomic DNA of patients were extracted by QIAsymphony® automated DNA isolation system (Qiagen Inc., Mississauga, ON, Canada).
A targeted next-generation gene panel was designed based on the literature data. The genes in the panel were related with coagulopathy (F2, F5), viral invasion (ACE2), and inflammation (CXCL8, IFNAR2, IFNL4, IL10, IL2, IL6, IRF7, TLR3, TLR7 and TNF).
The fragmented DNA was barcoded with unique molecular indices to track the original DNA molecule and provide a highly sensitive detection. Then, targeted genes were amplified with single primer extension technology and bead clean-up step was performed to discard unwanted fragments. The concentration optimization of libraries was performed with Qiaseq Quant Assay Kit (QIAGEN, Hilden, Germany) and all libraries were diluted to 4 nM. Libraries with different sample indexes were combined in equimolar amounts in the final pool. Then, the final pool was sequenced in Miseq System, Illumina (Illumina Inc., San Diego, CA, USA) according to the manufacturer’s guide. The secondary analysis of FASTQ files were performed on Qiagen Clinical Insight-Analyse Universal with panel-specific pipeline. The VCF files were clinically interpreted using Qiagen Clinical Insight-Interpret (QIAGEN). Firstly, the pathogenic/likely pathogenic variants were classified according to the ACMG 2015 criteria (Richards et al. 2015). Statistical analysis was performed according to the mildly and severely affected patient groups.
Statistical analysis
First, univariate analyses were performed to select candidate variables for logistic model. α = 0.25 was taken while selecting candidate variables. To purify age effect on univariate model results, age variable was taken as covariate for all univariate analyses. Odds ratio (OR) and 95% confidence interval (CI) of the estimates were reported. A p-value < 0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics 21.0 (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY, USA).
Results
A total of 188 patients followed up with the diagnosis of COVID-19, 94 with mild clinics and 94 with severe clinics, were included in our study. The mean age of mild and severe patient groups was 47.35 ± 10.84 (mean ± SD) and 54.59 ± 8.87, respectively. Of these individuals, 122 were male, 66 were female (Table 1). The effect of sex on the severity of the disease was not significant (p = 0.760). In addition, risk factors were evaluated. Hypertension was not found to be significantly different between the groups (p = 0.092). However, diabetes mellitus, chronic kidney disease, coronary artery disease and chronic lung disease were statistically significantly higher in the severe group (p = 0.021, p = 0.001, p = 0.014, p = 0.025, respectively). Although the presence of less than 2 risk factors did not have a significant effect on the severity of the disease, it was revealed that the presence of 2 or more risk factors caused the disease to progress severely (p < 0.001).
We sequenced 13 genes with the NGS method. As a result of the evaluation, 103 variants were detected. A statistically significant difference was detected for 29 variants at the genes in the panel list. The incidence of 29 variants associated with mild and severe COVID-19 infection groups were shown in the Table 2. Statistical analyses in which each variable was evaluated independently are also included in Table 2.
In our study, heterozygous IRF7:c.1357−23dup variant had a 2.5 times higher risk for mild disease compared to severe disease (p = 0.019). Heterozygous IRF7:c.847+28T>C variant had a 2 times higher risk for mild disease than severe disease (p = 0.031). Homozygous IRF7:c.847+28T>C variant had a 4.4 times higher risk for mild disease than severe disease (p < 0.001).
Nine variants in the IFNAR2 gene were statistically significant. Heterozygous IFNAR2:c.841−33C>T variant had a 3.3 times higher risk for severe disease than mild disease (p = 0.040). c.394+250A>G (p = 0.030), c.541−50A>G (p = 0.001), c.841−220G>A (p = 0.021), c.841−290C>T (p < 0.001), c.841−4del (p < 0.001), c.841−5del (p < 0.001), c.97+138T>C (p = 0.001), c.98−43T>C (p < 0.001) variants were found statistically more frequent in the mildly affected patient group compared to the severely affected group.
Heterozygous IL10:c.225+56A>G variant had a 3.3 times higher risk for mild disease than severe disease (p = 0.032). Heterozygous IL10:c.378+140A>T variant had a 13.2 times higher risk for mild disease than severe disease (p = 0.001). Heterozygous IL10:c.378+19T>C variant had a 6.2 times higher risk for mild disease than severe disease (p = 0.015). If there was homozygosity for this variant, the odd ratio would be 4.7 (p = 0.035).
Heterozygous CXCL8:c.200+125dup variant had a 20.8 times higher risk for mild disease than severe disease (p < 0.001). If there was homozygosity for this variant, the odd ratio would be 3.3 (p = 0.001). Heterozygous CXCL8:c.284+161C>T variant had a 6.4 times higher risk for mild disease than severe disease (p < 0.001). If there was homozygosity for this variant, the odd ratio would be 7.9 (p = 0.001). Heterozygous CXCL8:c.284+129del variant had a 3.4 times higher risk for mild disease than severe disease (p = 0.001).
Heterozygous IL2:c.351+45del variant had a 15.2 times higher risk for mild disease than severe disease (p < 0.001).
Heterozygous TLR3:c.634−135G>A variant had a 15.6 times higher risk for mild disease than severe disease (p < 0.001). If there was homozygosity for this variant, the odd ratio would be 6.8 (p = 0.006). Heterozygous TLR3:c.633+136G>T variant had a 11.1 times higher risk for mild disease than severe disease (p = 0.027).
Heterozygous TNF:c.186+123G>A variant had a 8.8 times higher risk of mild disease than severe disease (p = 0.001).
Heterozygous IL6:c.210+180A>G variant had a 142.857 times higher risk of mild disease than severe disease (p < 0.001). If there was homozygosity for this variant, the odd ratio would be 90.9 (p < 0.001). Heterozygous IL6:c.211−188C>A variant had a 62.5 times higher risk of mild disease than severe disease (p < 0.001). If there was homozygosity for this variant, the odd ratio would be 142.9 (p < 0.001). Heterozygous IL6:c.211−93C>T variant had a 5.5 times higher risk of mild disease than severe disease (p = 0.004).
Heterozygous F5:c.4095C>T variant had a 4.8 times higher risk of mild disease than severe disease (p = 0.001). There were no significant variants in F2.
Homozygous ACE2:c.2115−268A>G variant had a 17.5 times higher risk of mild disease than severe disease (p < 0.001). Homozygous ACE2:c.1297+68insCTTAT variant had a 4.2 times higher risk of mild disease than severe disease (p < 0.001). Homozygous ACE2:c.584−71A>G variant had 6.6 times higher risk of mild disease than severe disease (p < 0.001). If there was heterozygous for this variant, the odd ratio would be 7.7.
Discussion
Many different reasons including viral agent-related factors and host-related factors are held responsible for the clinical heterogeneity of COVID-19 (Pairo-Castineira et al. 2021). Determination of the factors causing different clinical courses among the asymptomatic and severely affected patients could improve understanding of the pathogenesis of the disease. SARS-CoV-2 can infect people of any age, but those over 60 years of age and those with underlying comorbidities (such as smoking habits, diabetes, hypertension, obesity, cardiovascular disease, chronic lung and kidney diseases, immune suppression, cancer, and organ transplantation) are more likely to develop serious or fatal conditions. In addition, sex, lifestyle choices, and viral exposure levels can determine the susceptibility of an individual to infections and critical diseases (Ou et al. 2020; Yin et al. 2021). In our study, no significant difference was found between the severely and mildly affected patient groups in terms of age. In addition, in accordance with the literature, as well as two or more accompanying comorbidities, each of the comorbidity was observed more frequently in the severely affected patient group compared to the mildly one.
Although there is a positive correlation between disease severity and the accompanying risk factors, young or healthy individuals are reported to have severe or life-threatening disease, too. Many researchers have shown that clinical diversity observed in the SARS-CoV-2 infection are result from genetic factors affecting disease severity, susceptibility and resistance (Gupta et al. 2022).
In our study, we have screened genes implicated in different pathways for sequence variants that may have modifying effect in the pathogenesis of COVID-19 in a panel including ACE2, CXCL8, F2, F5, IFNAR2, IFNL4, IL10, IL2, IL6, IRF7, TLR3, TLR7 andTNF genes.
Cytokine storm, autoimmune features, and dysfunctions of myeloid cells are known to be significant contributing factors in severe COVID-19. It has been suggested that different genes in the inflammatory pathway may cause a serious disease. In our study, the effect of cytokine pathway proteins was also investigated. We sequenced the CXCL8, IFNAR2, IFNL4, IL10, IL2, IL6, IRF7, TLR3, TLR7 andTNF genes in inflammatory pathway. Many variants in these genes were found in both of the groups and most of these variants were found significantly higher in the mildly affected patient group. Although, it was previously reported that patients with immunodeficiency had a more severe disease, different underlying conditions and comorbidities could be suggested for the severe course of the disease in some patients who had no immunodeficiency (Manik and Singh 2022). It is noteworthy that most of these variants are located in the intronic regions of the genes. The significant excess of variants in these genes in the mild group raises the idea of whether intronic variants of these immune pathway genes may have a protective effect from severe disease by increasing the activity of the immune system (Manik and Singh 2022). This issue needs to be investigated in more patients.
Interleukin-8 (IL8) synthesized by CXCL8 is a member of the CXC chemokine family. IL8 is highly expressed at the tracheal aspirates of infants with respiratory syncytial virus (RSV) bronchiolitis, and the level of IL8 was correlated with disease severity (Melero et al. 2022; Sagulkoo et al. 2022). In relation with this, CXCL8 may be considered to be involved in the pathogenesis of COVID-19, but in our study, no variant of CXCL8 had a significant association in severely affected patient group.
SARS‐CoV‐2 infection activates both the innate and adaptive immune system in the alveolar tissue, inducing cytokine release syndrome. Cytokine release syndrome causes high levels of proinflammatory cytokines (IL‐1, IL‐6, IL‐8, TNF‐α and IFN), which have important roles for mortality. The type I IFN pathway plays a crucial role in mediating innate immune responses to viral infections. This cytokine family is comprised of 13 IFN-α subtypes, IFN-β, IFN-ω, IFN-κ, and IFN-ϵ, all of them signal through the heterodimeric IFN I receptor, composed of IFN-α/β receptor 1 (IFNAR1) and IFNAR2 (Beck and Aksentijevich 2020). By analysing patients with severe COVID-19, these two studies provide evidence that type I IFNs are actually protective against COVID-19; however, through either gene mutations or autoantibodies, they lead to severe disease. We observed IFNAR2:c.841−33C>T variant had a 3.309 times higher risk for severe disease than wild type. IFNAR2:c.841−33C>T is located at intron 8 of the IFNAR2 gene. Although it has no effect on protein structure, it may have an effect on protein function.
In another study of 987 patients with COVID-19 pneumonia, it was reported that 101 patients had autoantibodies against a variety of type I interferons (IFNs), including IFN-ω and/or IFN-α. These autoantibodies were absent in patients with mild or asymptomatic disease, and noted in only a few healthy controls (Beer et al. 2022).
Since the underlying mechanisms of thromboembolic events, which are known to be one of the major mortality and morbidity reasons for COVID-19, include complex processes and interactions, it has been demonstrated in different studies that variants in F2 and F5 predispose to thrombosis (Klok et al. 2020). Inherited thrombophilia has been suggested to be a risk factor for severe COVID-19. Investigations on the genetic profiles of thrombophilia-related genes are important, for both in treating and avoiding COVID-19-related mortality (Badulescu et al. 2022). In our study, not only known variants but also all F2 and F5 genes were sequenced and no significant differences were detected. A pilot study for the association between COVID-19 and thrombophilia recommended that a large number of patients should be studied to find a significant result (de la Morena-Barrio et al. 2021).
ACE2 was also reported to have an important role in the pathogenesis of the COVID-19 (El-Arif et al. 2021). It is expressed mostly in the alveolar epithelial cells. Polymorphisms in the protein encoding regions of ACE2 can affect the binding affinity of the viral spike protein to host cells, as well as membrane fusion efficiency, modulating the host susceptibility to COVID-19. ACE2 gene can have rarely synonymous and nonsynonymous mutations, and some of them could modify the susceptibility to human coronavirus infections (Badawi et al. 2022). It has been suggested that some polymorphisms (S19P, I21V, E23K, K26R, T27A, N64K, T92I, Q102P, and H378R) located in the coding region of the ACE2 and ACE2 peptidase domain (PD), which binds SARS-CoV-2, may increase the risk of virus infection (Suryamohan et al. 2021). In a study from Turkey, ACE1 insertion/deletion polymorphisms and ACE2 PD domain variants were evaluated in patients with COVID-19 pneumonia and they were found to have no impact on severe COVID-19 infection (Bastug et al. 2022). In another study from Turkey, the changes in the ACE2 gene were evaluated retrospectively, and 2 nonsynonymous variants were observed. However, the relationship between these variants and COVID-19 disease could not be established (Duman et al. 2022). These two nonsynonymous variants (p.Lys26Arg and p.Asn720Asp) in the ACE2 gene were not detected in our study. In our study, the entire ACE2 gene, also consisting the PD domain, were sequenced. There was no significant difference between the severe and mild patient groups. The ACE2 gene is important in binding the spike protein, but we revealed that changes on the gene had no effect on the course of the disease.
It is critical to assess variations across all genes in an unbiased way, rather than preselecting genes representing as a priori hypothesis. While this candidate-gene approach was widely employed in the past, it has largely failed. In new cohorts, reported candidate-gene studies are not replicable. In our study, we designed a prospective study by carefully selecting and classifying the cohort. Data from other studies were analyzed, but we studied targeted gene panels in selected cohorts, demonstrating that reported variants and hypotheses may not be valid.
As a result, in order to confirm that the 29 variants detected in our study are effective in the clinical severity of the disease, studies with larger numbers of patients are required.
Since polymorphic variants were not evaluated in the literature, the findings of our study could not be compared with the findings in the literature. However, as variants that may be effective in the severity of infections may differ according to ethnicity, this study has the feature of being a guide for subsequent studies to be carried out especially in Turkish population.
In summary, there is currently no convincing evidence that individuals with monogenic immune disorders are at increased risk for severe COVID-19 outcomes. The hypothesis remains viable, but more compelling evidence will be needed to substantiate it. Therefore, clinical course of the COVID-19 infection is likely to depend on a variety of risk factors, including age, sex, clinical status, immunology and genetic factors.
Acknowledgments
We thank all participants for their participation in the current study. A prospective study was planned after obtaining the approval of the Ankara Yıldırım Beyazıt University, School of Medicine, Ethics Committee, No.28 (approval date 13.05.2020). The study was conducted in concordance with the Helsinki declaration and written in accordance with the STROBE statement. This research was supported by the Ankara Yıldırım Beyazıt University, Scientific Research Project Number TSG-2020-2106.
Conflict of Interest
The authors declare no conflict of interest.
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