{"paper_id":"80b970c3-4c6f-4cd3-90d7-1cf9235016bd","body_text":"IDENTIFICATION OF HUMAN GENETIC VARIANTS MODULATING THE COURSE OF COVID-19 INFECTION | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Article IDENTIFICATION OF HUMAN GENETIC VARIANTS MODULATING THE COURSE OF COVID-19 INFECTION Adna Ašić, Lana Salihefendić, Ivana Čeko, Larisa Bešić, Naida Mulahuseinović, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2397519/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract COVID-19, caused by the SARS-CoV-2 virus, has been a major focus of scientific research since late 2019 and early 2020. Due to its enormous societal, economic, and clinical impact worldwide, research efforts aimed, among other questions, to address the effect of host genetics in susceptibility and severity of COVID-19. In this research, we performed next-generation sequencing of coding and regulatory regions of 16 selected human genes, involved in the maintenance of the immune system or encoding the receptors for viral entry into the host cells, in a subset of 60 COVID-19 patients from the General Hospital Tešanj, Bosnia and Herzegovina, classified into three groups of patients with clinical conditions of different severity (“mild”, “moderate”, and “severe” clinical groups). In accordance with previous studies, we found out that the male sex and older age are risk factors for severe clinical picture. We identified 13 variants on seven genes (CD55, IL1B, IL4, IRF7, DDX58, TMPRSS2, and ACE2) with potential functional significance, either as genetic markers of modulated susceptibility to SARS-CoV-2 infection or as modifiers of the course of infection in terms of predicted symptom severity. Our results include variants reported for the first time as potentially associated with COVID-19. Future studies on larger patient cohorts, focused on candidate genes and/or candidate genetic variants, have a potential to answer a range of open questions regarding the effect of host (human) genetic makeup on the expected outcome of COVID-19. Biological sciences/Genetics/Population genetics/Genetic variation/Rare variants Biological sciences/Genetics/Genetic markers ACE2 COVID-19 host genetics IRF7 SARS-CoV-2 TMPRSS2 introduction COVID-19, caused by the SARS-CoV-2 virus outbreak in Wuhan, China, was declared a public health emergency of international concern on January 30 th , 2020, and a pandemic on March 12 th , 2020, by the World Health Organization (WHO) [1]. The genome of SARS-CoV-2, at 29,881 nt and 9,860 amino acids, is a larger linear single-stranded RNA viral genome [2]. It encodes four structural proteins (spike S, envelope E, nucleocapsid N, and membrane M) and sixteen non-structural proteins (labeled Nsp1-16) [3-4]. COVID-19 represents an unprecedented challenge to governments all around the world due to virus transmissibility, symptom variability and severity, uncertainty regarding the immunity development following the course of infection, and the overall impact on healthcare systems and global economy [5]. For that reason, multiple parallel scientific approaches were used to address the issue as rapidly and efficiently as possible. In this context, the scientists around the world sequenced the viral genome. For example, the Global Initiative on Sharing Avian Influenza Data (GISAID) has over 14,000,000 sequenced SARS-CoV-2 viruses, as of November 2022, and the number of submissions is growing daily [6]. On the other hand, huge variability in the severity of clinical picture of COVID-19 has also been investigated. It was accepted that environmental, demographic, and clinical factors all have an impact on severity of COVID-19, but that the host genetics may also have a significant role in the severity, as well as susceptibility to SARS-CoV-2 infection at the first place [7]. It is well-stablished that more severe symptoms and higher mortality rate are both observed in older patients (over 60 years of age), males, and people with other comorbidities, such as diabetes mellitus, cardiovascular diseases, and respiratory diseases, among others [8]. Therefore, the aim of our research was to perform the first study of COVID-19 host genetics in Bosnia and Herzegovina, and the Western Balkans region, by sequencing the coding and regulatory regions of 16 human genes in COVID-19 patients classified into three groups of mild, moderate, and severe clinical picture of the disease, in order to establish whether any of detected genetic variants can be associated with severity of COVID-19 and/or susceptibility to the infection. Study genes are mostly involved in maintenance and homeostasis of human immune system or are producing viral (co-)receptors expressed on the surface of human cells. materials and methods Ethical considerations and sample collection Ethical approvals for conducting this study were granted by the Joint Ethics Committee of the General Hospital Tešanj, Bosnia and Herzegovina, for patient DNA sample and clinical record use (January 11 th , 2021, document number 01-4-17/21) and the Ethics Committee of the Faculty of Engineering and Natural Sciences, International Burch University Sarajevo, Bosnia and Herzegovina, for conducting the molecular analyses (March 23 rd , 2021, document number 04-51/21). Prior to sample collection, all patients signed an informed consent form, while physicians in charge filled in the patient questionnaire regarding general demographic characteristics, clinical presentation of COVID-19, and comorbidities. This research was carried out in accordance with the Declaration of Helsinki. Whole blood samples were collected from RT-PCR-confirmed COVID-19 patients (n=60) in the General Hospital Tešanj from March to October 2021, stored at -20°C, and delivered on ice to the ALEA Genetic Center (Sarajevo) laboratory. Based on the patients’ symptoms, overall condition, oxygen saturation levels, and laboratory and radiological testing results, samples were classified into three groups: mild (n=20), moderate (n=20), and severe symptoms group (n=20), based on [9]. Following sample delivery to the DNA laboratory, they were de-frosted, and DNA was extracted immediately using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). The original manufacturer’s protocol was modified only by using 100 µl of ATE buffer, instead of 200 µl, since DNA was not extracted right after sampling. Following extraction, DNA was quantified using Qubit™ 3.0 Fluorometer with dsDNA high-sensitivity (HS) kit (Thermo Fisher Scientific, Waltham, MA, USA). Next-generation sequencing Ion AmpliSeq Designer (Thermo Fisher Scientific) was used to create primers for 16 selected genes and their regulatory sequences, namely HLA-A, HLA-B, HLA-C, ACE2, IL-6, IL-4, TMPRSS2, IFITM3, IL-12, DDX58, IRF-7, IRF-9, IL-1B, IL-1A, CD55 and TNF-α . Thus custom-made primer panel was received frozen in two primer pools, whereby pool 1 contained 93 amplicons and pool 2 contained 92 amplicons. Library preparation was done using Ion AmpliSeq™ Library Kit 2.0 (Thermo Fisher Scientific) according to manufacturer’s instructions. Starting amount of DNA material was ranging from 30 to 100 ng, and the number of cycles was set to 24. Amplicon digestion, adapter ligation, and purification steps were performed according to manufacturer’s instructions. Product clean-up was done using Agencourt™ AMPure™ XP Reagent (Beckman Coulter, Brea, CA, USA). Following purification, libraries were quantified using real-time PCR and Ion Library TaqMan® Quantitation Kit (Thermo Fisher Scientific) according to manufacturer’s instructions. Libraries with concentration over 100 pM were diluted to 100 pM and pooled together before emulsion PCR and enrichment, which was done using Ion Chef System (Thermo Fisher Scientific). The chip was loaded automatically with Ion Chef System using Ion 510™ & Ion 520™ & Ion 530™ Kit (Thermo Fisher Scientific). Next-generation sequencing (NGS) was performed using Ion GeneStudio™ S5 System and data was analyzed using Torrent Browser Software (Thermo Fisher Scientific) through VCF (Variant Caller Files) format and Coverage Analysis. Further modifications were made on the library preparation protocol, as it was concluded that primer pool 2 had lower coverage (more information was published in [10]). Data analysis was ultimately done on 48 samples containing sequences from both primer pools and 12 samples containing only pool 1 amplicons. Finally, clinical exome analysis was performed on three samples from the severe clinical symptoms group, using TruSight One Sequencing Panel (Illumina, San Diego, CA, USA), according to manufacturer’s instructions. Sequencing of these samples was performed on Illumina MiSeq platform. All sequences can be accessed within the Sequence Read Archive (SRA) repository on the National Center for Biotechnology information (NCBI) website, as detailed in the Data Availability Statement below. Confirmatory Sanger sequencing Genetic variants obtained through NGS were confirmed and the custom-made panel was validated via Sanger sequencing of five selected SNPs. Table 1 gives the position of these SNPs, their rs numbers, annealing temperatures, and designed primers. Table 1. Designed primers for confirmatory Sanger sequencing and information about corresponding SNPs. For every SNP, 10 samples were selected, taking care that both wild-type and variant allele-containing genotypes were selected. For genotypes with variant alleles, both heterozygous and homozygous individuals were selected, whenever possible. For PCR amplification, the final concentrations of 1x PCR Master Mix (Thermo Fisher Scientific) and 1 µM of both forward and reverse primers were used in a reaction of a total volume of 25 µl, including 10 ng of DNA. Initial denaturation was performed at 95°C for 3 minutes, followed by 40 cycles of denaturation at 95°C for 30 seconds, annealing for 30 seconds, and elongation at 72°C for 1 minute. Final elongation was done at 72°C for 10 minutes. Cycle sequencing was done using BigDye™ Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific) according to manufacturer’s instructions. Products were purified using Macherey-Nagel™ NucleoSpin™ Gel and PCR Clean-up columns (Macherey-Nagel, Düren, Germany) and Sanger sequencing was performed on SeqStudio™ Genetic Analyzer (Thermo Fisher Scientific). Statistical analysis Statistical analysis was performed using the chi-square test of goodness-of-fit to compare clinical severity categories between male and female participants, as well as among the patients with different comorbidities (cardiovascular, metabolic, respiratory, and other comorbidities). The same test was used to investigate the influence of detected genetic variants on the severity of COVID-19 presentation and infection susceptibility. One-way ANOVA was used to compare the mean age among the different clinical severity groups. Kruskal-Wallis test was deployed as a non-parametric alternative to one-way ANOVA, whereby it assumes that mean ranks are the same among the three age groups. In all analyses, p-value of 0.05 was considered critical for detection of significant differences between the study groups. Results In this study, we analyzed the effect of demographic characteristics, comorbidities and genetic background of patients on severity of and susceptibility to COVID-19. Population age was ranging from 15 to 80, with median of 62.5, mean of 59.067, and standard deviation of 15.029, at a 95% confidence interval of 3.88 (upper 62.95, lower 55.18). Our results demonstrated that the male sex and older age are risk factors for severe symptoms of COVID-19 (Table 2). By collecting patients’ clinical records, we were able to analyze the frequency of observed comorbidities in three clinical groups. Cardiovascular comorbidities were significantly more common in severe when compared to mild and moderate symptom groups, and include hypertension, chronic cardiomyopathy, brain stroke, angina pectoris, atrial fibrillation, aortic aneurysm, and myocardial infarction. Respiratory comorbidities, including bronchitis, asthma, and history of tuberculosis, were more common in moderate and severe groups, when compared to mild, but also in the moderate symptom group when compared to severe. We have also detected significantly less patients with metabolic comorbidities in mild symptom group when compared to both moderate and severe groups. These comorbidities include diabetes, hypothyroidism, glucose intolerance and chronic sideropenic anemia (iron insufficiency). Other comorbidities encompass rheumatoid arthritis, renal insufficiency, acute liver lesion, chronic gastritis, and hepatitis C infection, and were assessed together. We found that these comorbidities were significantly more common in severe symptom group when compared to either mild or moderate groups (Table 2). Table 2. Demographic characteristics and comorbidities compared between three study groups. p-values denoting statistically significant differences between the study groups are bolded. In 11 of the study genes, we have observed genetic variants in our patients. Observed variants include single nucleotide polymorphisms, insertions, deletions, and complex variants (Table 3). We have detected variants that might be predisposing the patients towards milder or more severe symptoms of COVID-19, based on significant differences in the frequency of appearance of the study variants between the defined clinical groups. In our analyses, we grouped heterozygous and homozygous carriers of the variants together (Table 4). Table 3. The number of patients and percentage of the total patient population in which variants on 13 study genes were observed, regardless of the genotype, and the total number of variants observed in the custom-made panel. Table 4. Detected genetic polymorphisms with significant differences in frequency of appearance between the study groups. Frequencies are given as percentage of all tested patients per study group in which variant was detected, regardless of genotype. p-values denoting statistically significant differences between the study groups are bolded. When it comes to confirmatory Sanger sequencing, done with the goal of validating the results of the custom-made NGS panel, we have re-sequenced five SNPs, namely rs2243290 C>A ( IL4 gene), rs370862493 G>A ( IFITM3 gene), rs2285666 C>T ( ACE2 gene), rs17854725 A>G, and rs12329760 C>T (both from TMPRSS2 gene). We obtained 100% agreement for the variants rs370862493, rs2285666, and rs12329760. As for 90% agreement between the methods for rs2243290 polymorphism on IL4 gene, one sample from the severe symptom group was sequenced as homozygous variant using the Sanger method, while NGS reported it as a carrier of heterozygous genotype. When it comes to the TMPRSS2 variant rs178854725, the designed primers for this variant could not be optimized for Sanger sequencing, since the bands on gel electrophoresis were acquired during PCR protocol optimization, but the sequencing results did not give clear, readable electropherograms. Discussion In the present study, we identified 13 variants of interest dispersed among seven human genes, playing different roles in the immune system maintenance and viral binding and entry into the host cells. TMPRSS2 is one of the main discoveries in understanding the mechanism of SARS-CoV-2 infection, as it codes for a cell-surface protein expressed by epithelial cells of different tissues, including the aerodigestive tract. SARS-CoV-2 entry into the host cells is dependent upon TMPRSS2 since viral S glycoprotein is cleaved by TMPRSS2, which helps with viral activation [11]. It is now widely researched as a biomarker for COVID-19 disease susceptibility and symptom severity in different populations [12-13]. ACE2 is also crucial in SARS-CoV-2 infection, since the viral entry into the cell depends on ACE2 receptor, which can be found in respiratory tract, oral mucosa and heart cells [14]. Kuba et al. (2005) found that expression of ACE2 gene is downregulated in cells infected by SARS-CoV [15]. It was speculated that the genetic variants and loss-of-function mutations in ACE2 might confer resistance to COVID-19, while hypomorphic variants of this gene could be protective against severe cases of COVID-19 disease [16]. There is evidence of sex-specific differences in the COVID-19 severity [12]. For example, higher testosterone level increases the expression of TMPRSS2 , which may cause higher susceptibility to COVID-19 in male patients [17]. DDX58 is involved in viral double-stranded RNA recognition and antiviral immune response. It has been reported that DDX58 gene expression under SARS-CoV-2 infection is upregulated [18]. IL1B is an inflammatory cytokine involved in initiating the immunological response against the viral infection. Feng et al. (2022) concluded that variants in IL1B could be the cause of a cytokine storm and critical COVID-19 symptoms [19]. IL4 has also been studied regarding susceptibility to SARS-CoV infection, and it was found that IL4 downregulates cell surface expression of ACE2, therefore inhibiting SARS-CoV replication [20]. IRF7 codes for protein necessary to produce IFN-I. Autosomal recessive IRF7 deficiency was reported in three patients with COVID-19 pneumonia symptoms, while IRF7 -deficient patients are generally more prone to viral infection of the respiratory tract [21]. Moving onto specific variants found in varying frequencies between our study groups, CD55 variant rs11120753 (G>A) is reported in seven patients in our study, including one heterozygous carrier in severe symptom group, two homozygotes in moderate, and four patients from the mild symptom group, including three homozygous and one heterozygous carrier. This is an intronic variant and there have been no previously published data on this variant regarding COVID-19 disease involvement. According to the ALFA Project results [22], obtained from 17,796 individuals of European ancestry, alternate allele A is present with the frequency of 0.2697, which is higher when compared to our study population with allele frequency of 0.125, but the difference is not significant (p=0.258). Intronic variant rs1681980552 (delAAA) in IL1B gene was detected in nine patients. Five patients belong to the severe clinical group (two homozygotes and three heterozygotes), two to the moderate (one homozygote and one heterozygote), and two to the mild clinical group (both heterozygous carriers). There are no reports on this variant for any disease association and there are no population studies on its frequency, but we are reporting it as a promising target for predicting possible severe symptoms of COVID-19. Polymorphism rs1143634 (G>A) is detected in nine patients, including six patients from the severe, one patient from the moderate, and two patients from the mild clinical group, whereby all variant alleles were detected in heterozygous genotypes. This is a synonymous variant (p.Phe105=) reported in ClinVar [23] as associated with antisynthetase syndrome and endometriosis. Jafrin, Aziz, & Islam (2021) performed a meta-analysis which revealed that the presence of this polymorphism increases the risk of cancer development, more precisely gastric and breast cancers and multiple myeloma, especially in Asian populations [24]. Several studies connect rs1143634 with chronic periodontitis, including a meta-analysis by da Silva et al. (2017), in which it was significantly associated with chronic periodontitis disease in Caucasian, Asian and mixed populations [25]. There is no reported data on this variant regarding its association with SARS-CoV-2 infection or the clinical course of the disease, prior to our study in which this variant seems to be overrepresented in the severe symptom group when compared to the other two. rs2243290 (C>T) is an intronic variant of IL4 gene and it has been detected in 15 patients in our study (six from severe, six from moderate and three form mild clinical group). Just like other variants on genes encoding for interleukins, this variant is enriched in the study groups with more pronounced COVID-19 symptoms and, therefore, might be associated with disease severity. rs34948036 (insT) is an intronic variant from IRF7 gene is detected in 16 patients, four of them belonging to mild, four to moderate, and eight to severe clinical symptom group. Its alternative allele (insT) frequency in European population is 0.259, based on the ALFA Project [22] on 24,292 individuals. Our results show, for the first time, that this single-nucleotide insertion could be clinically relevant and associated with severe clinical symptoms of COVID-19. rs1051390 (G>C), rs12422022 (A>G), and rs1131665 (T>C) variants, also on IRF7 gene, were detected in nine patients with identical distribution, as a haplotype. Six of these patients belong to severe clinical symptoms group, one belongs to moderate, and two belong to mild symptoms group, whereby all nine participants presented with heterozygous genotype. While rs1051390 and rs12422022 are intronic, rs1131665 is a missense variant (g.613208T>C, p.Gln412Arg). rs10813831 (G>A) is a missense variant (g.5177C>T, p.Arg7Cys) in DDX58 gene, that was detected in eight patients in our study, including five from the severe clinical group (one heterozygous and four homozygous genotypes), one heterozygote from the moderate clinical group, and two heterozygotes from the mild clinical group. While this variant, although protein-coding and missense, was not reported in ClinVar as clinically relevant [23], our results point towards its involvement in progression of more severe COVID-19, especially in homozygous carriers of the variant. Previous research connected this variant with other conditions. For example, Wu et al. (2019) concluded that Chinese individuals carrying the rs10813831-G-allele-containing genotype were more liable to achieve spontaneous hepatitis C virus (HCV) clearance than the patients who were carriers of the alternate allele [26]. Another interesting variant from DDX58 gene is rs1213032873 (insA), which is detected in only two heterozygous patients in the severe symptom group. It is an intronic variant with no clinical significance described in ClinVar [23], including no reports on the variant association with COVID-19 susceptibility and/or severity. This insertion is extremely rare, with alternative allele frequency of 0.0002 in 8,676 individuals of European ancestry, according to the latest release of the ALFA Project [22], as compared to our allele frequency of 0.021 in the COVID-19 patient population, which is significantly different (p=5.31 x 10 -16 ). Since we are reporting this variant for the first time, to the best of our knowledge, as the variant potentially associated with severe COVID-19 manifestation and increased susceptibility to COVID-19, it should be researched on a large patient population and compared to the general population frequencies of the insertion allele. rs73230068 (G>C) is a single nucleotide change in the intronic region of TMPRSS2 , which was present in five of our patients, whereby three of them belong to severe and two to moderate clinical symptoms group; all five individuals are heterozygous carriers. Our study, therefore, shows an increase in variant frequency in patients with more severe forms of COVID-19. While it was not a subject of previous research aiming to associate this variant with any diseases or clinical conditions, it has been a subject of a population study. Alternative allele frequency of 0.037 was recorded in 14,286 individuals of European ancestry [22], which is in good agreement with our allele frequency of 0.042 (p=0.904) in a set of COVID-19 patients. rs17854725 A>G is a silent variant (c.879T>C, p.Ile293=) in the same gene, which is present in a significantly higher proportion of patients from the severe, when compared to mild and moderate symptom groups. The same variant is also present as a missense variant (c.879T>G, p.Ile293Met), which was not recorded in our study. This variant was previously investigated in terms of its association with COVID-19. Namely, rs17854725/rs75603675/rs12329760/rs4303795 polymorphisms have been associated with increased susceptibility to COVID-19 and more severe clinical symptoms [27]. In that study, mortality was more frequent in individuals who carried the rs17854725/AG genotype. They also showed that G allele of this SNP is related to increased susceptibility to COVID-19 infection. Combined haplotype rs17854725/AG, rs75603675/AC, rs12329760/TT, and rs4303795/AG was ruled as a risk factor for COVID-19 susceptibility, especially in the case of GATG and GCTG haplotypes. Most COVID-19 patients whose rs17854725 genotype was AG were affected by the severe form of the disease, while about 64% of the AA genotype carriers had mild clinical symptoms [27]. Additionally, in a bioinformatic prediction study [13], rs75603675 was predicted to affect TMPRSS2 protein function according to PolyPen-2, but not according to SIFT [13]. Our study showed the presence of three polymorphisms together, that is, rs17854725/rs75603675/rs12329760 in two patients, whereby one patient belongs to mild and the other belongs to severe clinical symptoms group. rs2285666 (C>T) intronic variant on X-chromosomal gene ACE2 was detected in nine samples in our study, including one male from the severe clinical symptoms group, five patients from the moderate group (three heterozygous females and two males), and three patients from the mild group (two heterozygous females and one male). rs2285666 polymorphism is located at the beginning of the intron 3, and it could theoretically affect gene expression with alternative splicing mechanisms [28]. Srivastava et al. (2020) made a correlation between lower SARS-CoV-2 infection rate and the minor allele (T) in Indian population, therefore establishing a possibility of this polymorphism being associated with a protective role against infection [29]. Möhlendick et al. (2021) have found a two-fold increased risk of SARS-CoV-2 infection and a three-fold increased risk for COVID-19-related fatality or severe form of COVID-19 in CC genotype (or C allele) carriers in German population [30]. Nonetheless, it is important to note that different studies report conflicting results regarding this polymorphism. Our study shows that there is an increased number of alternative allele carriers in mild and moderate groups, when compared to the group of patients with severe form of COVID-19, meaning that our results corroborate the hypothesis of this SNP being more prevalent in mild and moderate clinical groups. However, this is not necessarily the case when considering the sex of the study participants. Males, carrying one alternative allele and having one copy of the gene, are distributed across three groups. Females are all heterozygous, which is important considering the fact that ACE2 escapes X chromosome inactivation [31] and both copies of the gene remain transcriptionally active in all cells of female patients. This gives higher gene dosage to females, as well as evolutionary advantage in case of heterozygous carriers of harmful variants. This SNP, however, seems to be protective in females since it is found in moderate and mild groups only. COVID-19 is probably the best representation of how significant discoveries can be made in short time periods, assuming that research teams are given adequate support. By studying COVID-19 from different perspectives, we accumulated a significant wealth of knowledge in less than three years since the beginning of the pandemic. Research into the host genetics of SARS-CoV-2 infection is still active and ongoing, with large consortia being formed with the goal of completing whole-genome or whole-exome studies on large patient and control groups, such as the COVID-19 Host Genetics Initiative [32], the COVID Human Genetic Effort [16], and the Severe COVID-19 GWAS Group [33]. Apart from studying the influence of host genetics on COVID-19 susceptibility and severity, these research groups aim towards better understanding of critical COVID-19 and post-COVID. Overall, given current importance of this topic and availability of technical support, COVID-19 research promises to be one of the most fruitful areas of research in foreseeable future. Declarations DATA AVAILABILITY STATEMENT Raw data produced during the study can be accessed at https://www.ncbi.nlm.nih.gov/bioproject/912097 . ACKNOWLEDGEMENTS The authors are grateful to all volunteers for accepting to participate in the study. AUTHOR CONTRIBUTIONS LS participated in sample collection, performed experimental analyses, and participated in manuscript drafting. IČ, Na. Mu., SD, DP, and EK participated in experimental analyses and manuscript revision. LB performed statistical analysis and participated in manuscript drafting. LP participated in patient recruitment, sample collection, data analysis, and manuscript revision. Ne. Me. participated in data analysis and manuscript revision. TB, BP, and DM overlooked the study from the beginning and contributed significantly to the manuscript revision. RK participated in all parts of the study, most prominently in experimental analysis, data processing, and manuscript revision. AA conceived the study, overlooked the study, participated in data processing and in manuscript drafting. All authors approved the final version of the manuscript. All authors agree to be accountable for all the aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. FUNDING This research is a part of the project titled “Personalized approach to COVID-19 infection through analysis of molecular genetic predisposition of the patients for a differential immune response”, that is co-financed by the Ministry of Science, Education, and Youth of the Sarajevo Canton (decision no. 11/05-34-12880-8/20). ETHICAL APPROVAL Ethical approvals for conducting this study were granted by the Joint Ethics Committee of the General Hospital Tešanj, Bosnia and Herzegovina, for patient DNA sample and clinical record use (January 11 th , 2021, document number 01-4-17/21) and the Ethics Committee of the Faculty of Engineering and Natural Sciences, International Burch University Sarajevo, Bosnia and Herzegovina, for conducting the molecular analyses (March 23 rd , 2021, document number 04-51/21). COMPETING INTERESTS Parts of this research have been presented at the 12 th ISABS Conference on Forensic and Anthropological Genetics and Mayo Clinic Lectures in Individualized Medicine held in June 2022 in Dubrovnik, Croatia. The authors have no other financial or non-financial competing interests to disclose. References Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. 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Aguiar JA, Tremblay BJ, Mansfield MJ, Woody O, Lobb B, Banerjee A, et al. Gene expression and in situ protein profiling of candidate SARS-CoV-2 receptors in human airway epithelial cells and lung tissue. Eur Respir J. 2020; 56(3):2001123. doi: 10.1183/13993003.01123-2020. Kuba K, Imai Y, Rao S, Gao H, Guo F, Guan B, et al. A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus-induced lung injury. Nat Med. 2005; 11(8):875-9. doi: 10.1038/nm1267. Casanova JL, Su HC, COVID Human Genetic Effort. A Global Effort to Define the Human Genetics of Protective Immunity to SARS-CoV-2 Infection. Cell. 2020; 181(6):1194-1199. doi: 10.1016/j.cell.2020.05.016. Bennani NN, Bennani-Baiti IM. Androgen deprivation therapy may constitute a more effective COVID-19 prophylactic than therapeutic strategy. Ann Oncol. 2020; 31(11):1585-1586. doi: 10.1016/j.annonc.2020.08.2095. Fricke-Galindo I, Falfán-Valencia R. Genetics Insight for COVID-19 Susceptibility and Severity: A Review. Front Immunol. 2021; 12:622176. doi: 10.3389/fimmu.2021.622176. Feng S, Song F, Guo W, Tan J, Zhang X, Qiao F, et al. Potential Genes Associated with COVID-19 and Comorbidity. Int J Med Sci. 2022; 19(2):402-415. doi: 10.7150/ijms.67815. de Lang A, Osterhaus AD, Haagmans BL. Interferon-gamma and interleukin-4 downregulate expression of the SARS coronavirus receptor ACE2 in Vero E6 cells. Virology. 2006; 353(2):474-81. doi: 10.1016/j.virol.2006.06.011. Campbell TM, Liu Z, Zhang Q, Moncada-Velez M, Covill LE, Zhang P, et al. Respiratory viral infections in otherwise healthy humans with inherited IRF7 deficiency. J Exp Med. 2022; 219(7):e20220202. doi: 10.1084/jem.20220202. Phan L, Jin Y, Zhang H, Qiang W, Shekhtman E, Shao D et al. ALFA: Allele Frequency Aggregator. 2020. www.ncbi.nlm.nih.gov/snp/docs/gsr/alfa/ . Landrum MJ, Lee JM, Benson M, Brown GR, Chao C, Chitipiralla S, et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018; 46(D1):D1062-D1067. doi: 10.1093/nar/gkx1153. Jafrin S, Aziz MA, Islam MS. Role of IL-1β rs1143634 (+3954C>T) polymorphism in cancer risk: an updated meta-analysis and trial sequential analysis. J Int Med Res. 2021; 49(12):3000605211060144. doi: 10.1177/03000605211060144. da Silva MK, de Carvalho ACG, Alves EHP, da Silva FRP, Pessoa LDS, Vasconcelos DFP. Genetic Factors and the Risk of Periodontitis Development: Findings from a Systematic Review Composed of 13 Studies of Meta-Analysis with 71,531 Participants. Int J Dent. 2017; 2017:1914073. doi: 10.1155/2017/1914073. Wu X, Zang F, Liu M, Zhuo L, Wu J, Xia X, et al. Genetic variants in RIG-I-like receptor influences HCV clearance in Chinese Han population. Epidemiol Infect. 2019; 147:e195. doi: 10.1017/S0950268819000827. Rokni M, Heidari Nia M, Sarhadi M, Mirinejad S, Sargazi S, Moudi M, et al. Association of TMPRSS2 Gene Polymorphisms with COVID-19 Severity and Mortality: a Case-Control Study with Computational Analyses. Appl Biochem Biotechnol. 2022; 194(8):3507-3526. doi: 10.1007/s12010-022-03885-w. Yang M, Zhao J, Xing L, Shi L. The association between angiotensin-converting enzyme 2 polymorphisms and essential hypertension risk: A meta-analysis involving 14,122 patients. J Renin Angiotensin Aldosterone Syst. 2015; 16(4):1240-4. doi: 10.1177/1470320314549221. Srivastava A, Bandopadhyay A, Das D, Pandey RK, Singh V, Khanam N, et al. Genetic Association of ACE2 rs2285666 Polymorphism With COVID-19 Spatial Distribution in India. Front Genet. 2020; 11:564741. doi: 10.3389/fgene.2020.564741. Möhlendick B, Schönfelder K, Breuckmann K, Elsner C, Babel N, Balfanz P, et al. ACE2 polymorphism and susceptibility for SARS-CoV-2 infection and severity of COVID-19. Pharmacogenet Genomics. 2021; 31(8):165-171. doi: 10.1097/FPC.0000000000000436. Gagliardi MC, Tieri P, Ortona E, Ruggieri A. ACE2 expression and sex disparity in COVID-19. Cell Death Discov. 2020; 6:37. doi: 10.1038/s41420-020-0276-1. COVID-19 Host Genetics Initiative. The COVID-19 Host Genetics Initiative, a global initiative to elucidate the role of host genetic factors in susceptibility and severity of the SARS-CoV-2 virus pandemic. Eur J Hum Genet. 2020; 28(6):715-718. doi: 10.1038/s41431-020-0636-6. Severe Covid-19 GWAS Group, Ellinghaus D, Degenhardt F, Bujanda L, Buti M, Albillos A et al. Genomewide Association Study of Severe Covid-19 with Respiratory Failure. N Engl J Med. 2020; 383(16):1522-1534. doi: 10.1056/NEJMoa2020283. Tables Tables 1-4 are available in the Supplementary Files section Additional Declarations (Not answered) Supplementary Files Table1.xlsx Table 1. Designed primers for confirmatory Sanger sequencing and information about corresponding SNPs. Table2.xlsx Table 2.Demographic characteristics and comorbidities compared between three study groups. p-values denoting statistically significant differences between the study groups are bolded. Table3.xlsx Table 3.The number of patients and percentage of the total patient population in which variants on 13 study genes were observed, regardless of the genotype, and the total number of variants observed in the custom-made panel. Table4.xlsx Table 4.Detected genetic polymorphisms with significant differences in frequency of appearance between the study groups. Frequencies are given as percentage of all tested patients per study group in which variant was detected, regardless of genotype. p-values denoting statistically significant differences between the study groups are bolded. 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13:01:17\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-2397519/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-2397519/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":31506997,\"identity\":\"b9f27631-acba-4ff2-b560-39a89e868899\",\"added_by\":\"auto\",\"created_at\":\"2023-01-12 23:49:07\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":244676,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2397519/v1/0bebd6c3-42d4-4e21-8782-9ef7df4a639a.pdf\"},{\"id\":31506920,\"identity\":\"e5df62e3-8d3d-4050-b8c8-bd8ad253c1b1\",\"added_by\":\"auto\",\"created_at\":\"2023-01-12 23:41:02\",\"extension\":\"xlsx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":10557,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 1.\\u003c/strong\\u003e Designed primers for confirmatory Sanger sequencing and information about corresponding SNPs.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table1.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2397519/v1/80503ae064d7cd4fa1bcf6fd.xlsx\"},{\"id\":31506918,\"identity\":\"afec80f8-23d6-4c73-aa4c-556382d3eb49\",\"added_by\":\"auto\",\"created_at\":\"2023-01-12 23:41:02\",\"extension\":\"xlsx\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":10941,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 2.\\u003c/strong\\u003eDemographic characteristics and comorbidities compared between three study groups. p-values denoting statistically significant differences between the study groups are bolded.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table2.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2397519/v1/234ae1524234752e786cfa0e.xlsx\"},{\"id\":31506996,\"identity\":\"640423bf-e239-45cb-ba5d-6b0047f1c680\",\"added_by\":\"auto\",\"created_at\":\"2023-01-12 23:49:02\",\"extension\":\"xlsx\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":10104,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 3.\\u003c/strong\\u003eThe number of patients and percentage of the total patient population in which variants on 13 study genes were observed, regardless of the genotype, and the total number of variants observed in the custom-made panel.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table3.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2397519/v1/c3e5066c9fff6f46736e7d5d.xlsx\"},{\"id\":31506921,\"identity\":\"10a23b51-20b3-4d49-b0e5-69711ba29a42\",\"added_by\":\"auto\",\"created_at\":\"2023-01-12 23:41:02\",\"extension\":\"xlsx\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":11818,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 4.\\u003c/strong\\u003eDetected genetic polymorphisms with significant differences in frequency of appearance between the study groups. Frequencies are given as percentage of all tested patients per study group in which variant was detected, regardless of genotype. p-values denoting statistically significant differences between the study groups are bolded.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Table4.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2397519/v1/6e3fdb83e38cf3254e3cebcf.xlsx\"}],\"financialInterests\":\"(Not answered)\",\"formattedTitle\":\"IDENTIFICATION OF HUMAN GENETIC VARIANTS MODULATING THE COURSE OF COVID-19 INFECTION\",\"fulltext\":[{\"header\":\"introduction\",\"content\":\"\\u003cp\\u003eCOVID-19, caused by the SARS-CoV-2 virus outbreak in Wuhan, China, was declared a public health emergency of international concern on January 30\\u003csup\\u003eth\\u003c/sup\\u003e, 2020, and a pandemic on March 12\\u003csup\\u003eth\\u003c/sup\\u003e, 2020, by the World Health Organization (WHO) [1]. The genome of SARS-CoV-2, at 29,881 nt and 9,860 amino acids, is a larger linear single-stranded RNA viral genome [2]. It encodes four structural proteins (spike S, envelope E, nucleocapsid N, and membrane M) and sixteen non-structural proteins (labeled Nsp1-16) [3-4].\\u003c/p\\u003e\\n\\u003cp\\u003eCOVID-19 represents an unprecedented challenge to governments all around the world due to virus transmissibility, symptom variability and severity, uncertainty regarding the immunity development following the course of infection, and the overall impact on healthcare systems and global economy [5]. For that reason, multiple parallel scientific approaches were used to address the issue as rapidly and efficiently as possible. In this context, the scientists around the world sequenced the viral genome. For example, the Global Initiative on Sharing Avian Influenza Data (GISAID) has over 14,000,000 sequenced SARS-CoV-2 viruses, as of November 2022, and the number of submissions is growing daily [6]. On the other hand, huge variability in the severity of clinical picture of COVID-19 has also been investigated. It was accepted that environmental, demographic, and clinical factors all have an impact on severity of COVID-19, but that the host genetics may also have a significant role in the severity, as well as susceptibility to SARS-CoV-2 infection at the first place [7]. It is well-stablished that more severe symptoms and higher mortality rate are both observed in older patients (over 60 years of age), males, and people with other comorbidities, such as diabetes mellitus, cardiovascular diseases, and respiratory diseases, among others [8].\\u003c/p\\u003e\\n\\u003cp\\u003eTherefore, the aim of our research was to perform the first study of COVID-19 host genetics in Bosnia and Herzegovina, and the Western Balkans region, by sequencing the coding and regulatory regions of 16 human genes in COVID-19 patients classified into three groups of mild, moderate, and severe clinical picture of the disease, in order to establish whether any of detected genetic variants can be associated with severity of COVID-19 and/or susceptibility to the infection. Study genes are mostly involved in maintenance and homeostasis of human immune system or are producing viral (co-)receptors expressed on the surface of human cells.\\u003c/p\\u003e\"},{\"header\":\"materials and methods\",\"content\":\"\\u003cp\\u003e\\u003cem\\u003eEthical considerations and sample collection\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEthical approvals for conducting this study were granted by the Joint Ethics Committee of the General Hospital Te\\u0026scaron;anj, Bosnia and Herzegovina, for patient DNA sample and clinical record use (January 11\\u003csup\\u003eth\\u003c/sup\\u003e, 2021, document number 01-4-17/21) and the Ethics Committee of the Faculty of Engineering and Natural Sciences, International Burch University Sarajevo, Bosnia and Herzegovina, for conducting the molecular analyses (March 23\\u003csup\\u003erd\\u003c/sup\\u003e, 2021, document number 04-51/21). Prior to sample collection, all patients signed an informed consent form, while physicians in charge filled in the patient questionnaire regarding general demographic characteristics, clinical presentation of COVID-19, and comorbidities. This research was carried out in accordance with the Declaration of Helsinki.\\u003c/p\\u003e\\n\\u003cp\\u003eWhole blood samples were collected from RT-PCR-confirmed COVID-19 patients (n=60) in the General Hospital Te\\u0026scaron;anj from March to October 2021, stored at -20\\u0026deg;C, and delivered on ice to the ALEA Genetic Center (Sarajevo) laboratory. Based on the patients\\u0026rsquo; symptoms, overall condition, oxygen saturation levels, and laboratory and radiological testing results, samples were classified into three groups: mild (n=20), moderate (n=20), and severe symptoms group (n=20), based on [9].\\u003c/p\\u003e\\n\\u003cp\\u003eFollowing sample delivery to the DNA laboratory, they were de-frosted, and DNA was extracted immediately using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). The original manufacturer\\u0026rsquo;s protocol was modified only by using 100 \\u0026micro;l of ATE buffer, instead of 200 \\u0026micro;l, since DNA was not extracted right after sampling. Following extraction, DNA was quantified using Qubit\\u0026trade; 3.0 Fluorometer with dsDNA high-sensitivity (HS) kit (Thermo Fisher Scientific, Waltham, MA, USA).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNext-generation sequencing\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eIon AmpliSeq Designer (Thermo Fisher Scientific) was used to create primers for 16 selected genes and their regulatory sequences, namely \\u003cem\\u003eHLA-A, HLA-B, HLA-C, ACE2, IL-6, IL-4, TMPRSS2, IFITM3, IL-12, DDX58, IRF-7, IRF-9, IL-1B, IL-1A, CD55\\u003c/em\\u003e and \\u003cem\\u003eTNF-\\u0026alpha;\\u003c/em\\u003e. Thus custom-made primer panel was received frozen in two primer pools, whereby pool 1 contained 93 amplicons and pool 2 contained 92 amplicons.\\u003c/p\\u003e\\n\\u003cp\\u003eLibrary preparation was done using Ion AmpliSeq\\u0026trade; Library Kit 2.0 (Thermo Fisher Scientific) according to manufacturer\\u0026rsquo;s instructions. Starting amount of DNA material was ranging from 30 to 100 ng, and the number of cycles was set to 24. Amplicon digestion, adapter ligation, and purification steps were performed according to manufacturer\\u0026rsquo;s instructions. Product clean-up was done using Agencourt\\u0026trade; AMPure\\u0026trade; XP Reagent (Beckman Coulter, Brea, CA, USA). Following purification, libraries were quantified using real-time PCR and Ion Library TaqMan\\u0026reg; Quantitation Kit (Thermo Fisher Scientific) according to manufacturer\\u0026rsquo;s instructions. Libraries with concentration over 100 pM were diluted to 100 pM and pooled together before emulsion PCR and enrichment, which was done using Ion Chef System (Thermo Fisher Scientific). The chip was loaded automatically with Ion Chef System using Ion 510\\u0026trade; \\u0026amp; Ion 520\\u0026trade; \\u0026amp; Ion 530\\u0026trade; Kit (Thermo Fisher Scientific). Next-generation sequencing (NGS) was performed using Ion GeneStudio\\u0026trade; S5 System and data was analyzed using Torrent Browser Software (Thermo Fisher Scientific) through VCF (Variant Caller Files) format and Coverage Analysis.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFurther modifications were made on the library preparation protocol, as it was concluded that primer pool 2 had lower coverage (more information was published in [10]). Data analysis was ultimately done on 48 samples containing sequences from both primer pools and 12 samples containing only pool 1 amplicons.\\u003c/p\\u003e\\n\\u003cp\\u003eFinally, clinical exome analysis was performed on three samples from the severe clinical symptoms group, using TruSight One Sequencing Panel (Illumina, San Diego, CA, USA), according to manufacturer\\u0026rsquo;s instructions. Sequencing of these samples was performed on Illumina MiSeq platform.\\u003c/p\\u003e\\n\\u003cp\\u003eAll sequences can be accessed within the Sequence Read Archive (SRA) repository on the National Center for Biotechnology information (NCBI) website, as detailed in the Data Availability Statement below.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eConfirmatory Sanger sequencing\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eGenetic variants obtained through NGS were confirmed and the custom-made panel was validated via Sanger sequencing of five selected SNPs. Table 1 gives the position of these SNPs, their rs numbers, annealing temperatures, and designed primers.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 1.\\u003c/strong\\u003e Designed primers for confirmatory Sanger sequencing and information about corresponding SNPs.\\u003c/p\\u003e\\n\\u003cp\\u003eFor every SNP, 10 samples were selected, taking care that both wild-type and variant allele-containing genotypes were selected. For genotypes with variant alleles, both heterozygous and homozygous individuals were selected, whenever possible. For PCR amplification, the final concentrations of 1x PCR Master Mix (Thermo Fisher Scientific) and 1 \\u0026micro;M of both forward and reverse primers were used in a reaction of a total volume of 25 \\u0026micro;l, including 10 ng of DNA. Initial denaturation was performed at 95\\u0026deg;C for 3 minutes, followed by 40 cycles of denaturation at 95\\u0026deg;C for 30 seconds, annealing for 30 seconds, and elongation at 72\\u0026deg;C for 1 minute. Final elongation was done at 72\\u0026deg;C for 10 minutes.\\u003c/p\\u003e\\n\\u003cp\\u003eCycle sequencing was done using BigDye\\u0026trade; Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific) according to manufacturer\\u0026rsquo;s instructions. Products were purified using Macherey-Nagel\\u0026trade; NucleoSpin\\u0026trade; Gel and PCR Clean-up columns (Macherey-Nagel, D\\u0026uuml;ren, Germany) and Sanger sequencing was performed on SeqStudio\\u0026trade; Genetic Analyzer (Thermo Fisher Scientific).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eStatistical analysis\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eStatistical analysis was performed using the chi-square test of goodness-of-fit to compare clinical severity categories between male and female participants, as well as among the patients with different comorbidities (cardiovascular, metabolic, respiratory, and other comorbidities). The same test was used to investigate the influence of detected genetic variants on the severity of COVID-19 presentation and infection susceptibility. One-way ANOVA was used to compare the mean age among the different clinical severity groups. Kruskal-Wallis test was deployed as a non-parametric alternative to one-way ANOVA, whereby it assumes that mean ranks are the same among the three age groups. In all analyses, p-value of 0.05 was considered critical for detection of significant differences between the study groups.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eIn this study, we analyzed the effect of demographic characteristics, comorbidities and genetic background of patients on severity of and susceptibility to COVID-19. Population age was ranging from 15 to 80, with median of 62.5, mean of 59.067, and standard deviation of 15.029, at a 95% confidence interval of 3.88 (upper 62.95, lower 55.18). Our results demonstrated that the male sex and older age are risk factors for severe symptoms of COVID-19 (Table 2).\\u003c/p\\u003e\\n\\u003cp\\u003eBy collecting patients\\u0026rsquo; clinical records, we were able to analyze the frequency of observed comorbidities in three clinical groups. Cardiovascular comorbidities were significantly more common in severe when compared to mild and moderate symptom groups, and include hypertension, chronic cardiomyopathy, brain stroke, angina pectoris, atrial fibrillation, aortic aneurysm, and myocardial infarction. Respiratory comorbidities, including bronchitis, asthma, and history of tuberculosis, were more common in moderate and severe groups, when compared to mild, but also in the moderate symptom group when compared to severe. We have also detected significantly less patients with metabolic comorbidities in mild symptom group when compared to both moderate and severe groups. These comorbidities include diabetes, hypothyroidism, glucose intolerance and chronic sideropenic anemia (iron insufficiency). Other comorbidities encompass rheumatoid arthritis, renal insufficiency, acute liver lesion, chronic gastritis, and hepatitis C infection, and were assessed together. We found that these comorbidities were significantly more common in severe symptom group when compared to either mild or moderate groups (Table 2).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2.\\u003c/strong\\u003e Demographic characteristics and comorbidities compared between three study groups. p-values denoting statistically significant differences between the study groups are bolded.\\u003c/p\\u003e\\n\\u003cp\\u003eIn 11 of the study genes, we have observed genetic variants in our patients. Observed variants include single nucleotide polymorphisms, insertions, deletions, and complex variants (Table 3). We have detected variants that might be predisposing the patients towards milder or more severe symptoms of COVID-19, based on significant differences in the frequency of appearance of the study variants between the defined clinical groups. In our analyses, we grouped heterozygous and homozygous carriers of the variants together (Table 4).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 3.\\u003c/strong\\u003e The number of patients and percentage of the total patient population in which variants on 13 study genes were observed, regardless of the genotype, and the total number of variants observed in the custom-made panel.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 4.\\u003c/strong\\u003e Detected genetic polymorphisms with significant differences in frequency of appearance between the study groups. Frequencies are given as percentage of all tested patients per study group in which variant was detected, regardless of genotype. p-values denoting statistically significant differences between the study groups are bolded.\\u003c/p\\u003e\\n\\u003cp\\u003eWhen it comes to confirmatory Sanger sequencing, done with the goal of validating the results of the custom-made NGS panel, we have re-sequenced five SNPs, namely rs2243290 C\\u0026gt;A (\\u003cem\\u003eIL4\\u003c/em\\u003e gene), rs370862493 G\\u0026gt;A (\\u003cem\\u003eIFITM3\\u003c/em\\u003e gene), rs2285666 C\\u0026gt;T (\\u003cem\\u003eACE2\\u003c/em\\u003e gene), rs17854725 A\\u0026gt;G, and rs12329760 C\\u0026gt;T (both from \\u003cem\\u003eTMPRSS2\\u003c/em\\u003e gene). We obtained 100% agreement for the variants rs370862493, rs2285666, and rs12329760. As for 90% agreement between the methods for rs2243290 polymorphism on \\u003cem\\u003eIL4\\u003c/em\\u003e gene, one sample from the severe symptom group was sequenced as homozygous variant using the Sanger method, while NGS reported it as a carrier of heterozygous genotype. When it comes to the \\u003cem\\u003eTMPRSS2\\u003c/em\\u003e variant rs178854725, the designed primers for this variant could not be optimized for Sanger sequencing, since the bands on gel electrophoresis were acquired during PCR protocol optimization, but the sequencing results did not give clear, readable electropherograms.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn the present study, we identified 13 variants of interest dispersed among seven human genes, playing different roles in the immune system maintenance and viral binding and entry into the host cells.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eTMPRSS2\\u003c/em\\u003e is one of the main discoveries in understanding the mechanism of SARS-CoV-2 infection, as it codes for a cell-surface protein expressed by epithelial cells of different tissues, including the aerodigestive tract. SARS-CoV-2 entry into the host cells is dependent upon \\u003cem\\u003eTMPRSS2\\u003c/em\\u003e since viral S glycoprotein is cleaved by TMPRSS2, which helps with viral activation [11]. It is now widely researched as a biomarker for COVID-19 disease susceptibility and symptom severity in different populations [12-13]. \\u003cem\\u003eACE2\\u003c/em\\u003e is also crucial in SARS-CoV-2 infection, since the viral entry into the cell depends on ACE2\\u0026nbsp;receptor, which can be found in respiratory tract, oral mucosa and heart cells [14]. Kuba et al. (2005) found that expression of \\u003cem\\u003eACE2\\u003c/em\\u003e gene is downregulated in cells infected by SARS-CoV [15]. It was speculated that the genetic variants and loss-of-function mutations in \\u003cem\\u003eACE2\\u003c/em\\u003e might confer resistance to COVID-19, while hypomorphic variants of this gene could be protective against severe cases of COVID-19 disease [16]. There is evidence of sex-specific differences in the COVID-19 severity [12]. For example, higher testosterone level increases the expression of \\u003cem\\u003eTMPRSS2\\u003c/em\\u003e, which may cause higher susceptibility to COVID-19 in male patients [17]. \\u003cem\\u003eDDX58\\u003c/em\\u003e is involved in viral double-stranded RNA recognition and antiviral immune response. It has been reported that \\u003cem\\u003eDDX58\\u003c/em\\u003e gene expression under SARS-CoV-2 infection is upregulated [18].\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eIL1B\\u003c/em\\u003e is an inflammatory cytokine involved in initiating the immunological response against the viral infection. Feng et al. (2022) concluded that variants in \\u003cem\\u003eIL1B\\u003c/em\\u003e could be the cause of a cytokine storm and critical COVID-19 symptoms [19]. \\u003cem\\u003eIL4\\u003c/em\\u003e has also been studied regarding susceptibility to SARS-CoV infection, and it was found that IL4 downregulates cell surface expression of ACE2, therefore inhibiting SARS-CoV replication [20]. \\u003cem\\u003eIRF7\\u003c/em\\u003e codes for protein necessary to produce IFN-I. Autosomal recessive \\u003cem\\u003eIRF7\\u003c/em\\u003e deficiency was reported in three patients with COVID-19 pneumonia symptoms, while \\u003cem\\u003eIRF7\\u003c/em\\u003e-deficient patients are generally more prone to viral infection of the respiratory tract [21].\\u003c/p\\u003e\\n\\u003cp\\u003eMoving onto specific variants found in varying frequencies between our study groups, \\u003cem\\u003eCD55\\u003c/em\\u003e variant rs11120753 (G\\u0026gt;A) is reported in seven patients in our study, including one heterozygous carrier in severe symptom group, two homozygotes in moderate, and four patients from the mild symptom group, including three homozygous and one heterozygous carrier. This is an intronic variant and there have been no previously published data on this variant regarding COVID-19 disease involvement. According to the ALFA Project results [22], obtained from 17,796 individuals of European ancestry, alternate allele A is present with the frequency of 0.2697, which is higher when compared to our study population with allele frequency of 0.125, but the difference is not significant (p=0.258).\\u003c/p\\u003e\\n\\u003cp\\u003eIntronic variant rs1681980552 (delAAA) in \\u003cem\\u003eIL1B\\u003c/em\\u003e gene was detected in nine patients. Five patients belong to the severe clinical group (two homozygotes and three heterozygotes), two to the moderate (one homozygote and one heterozygote), and two to the mild clinical group (both heterozygous carriers). There are no reports on this variant for any disease association and there are no population studies on its frequency, but we are reporting it as a promising target for predicting possible severe symptoms of COVID-19.\\u003c/p\\u003e\\n\\u003cp\\u003ePolymorphism rs1143634 (G\\u0026gt;A) is detected in nine patients, including six patients from the severe, one patient from the moderate, and two patients from the mild clinical group, whereby all variant alleles were detected in heterozygous genotypes. This is a synonymous variant (p.Phe105=) reported in ClinVar [23] as associated with antisynthetase syndrome and endometriosis. Jafrin, Aziz, \\u0026amp; Islam (2021) performed a meta-analysis which revealed that the presence of this\\u0026nbsp;polymorphism increases the risk of cancer development, more precisely gastric and breast cancers and multiple myeloma, especially in Asian populations [24]. Several studies connect rs1143634 with chronic periodontitis, including a meta-analysis by da Silva et al. (2017), in which it was significantly associated with chronic periodontitis disease in Caucasian, Asian and mixed populations [25]. There is no reported data on this variant regarding its association with SARS-CoV-2 infection or the clinical course of the disease, prior to our study in which this variant seems to be overrepresented in the severe symptom group when compared to the other two.\\u003c/p\\u003e\\n\\u003cp\\u003ers2243290 (C\\u0026gt;T) is an intronic variant of \\u003cem\\u003eIL4\\u003c/em\\u003e gene and it has been detected in 15 patients in our study (six from severe, six from moderate and three form mild clinical group). Just like other variants on genes encoding for interleukins, this variant is enriched in the study groups with more pronounced COVID-19 symptoms and, therefore, might be associated with disease severity.\\u003c/p\\u003e\\n\\u003cp\\u003ers34948036 (insT) is an intronic variant from \\u003cem\\u003eIRF7\\u003c/em\\u003e gene is detected in 16 patients, four of them belonging to mild, four to moderate, and eight to severe clinical symptom group. Its alternative allele (insT) frequency in European population is 0.259, based on the ALFA Project [22] on 24,292 individuals. Our results show, for the first time, that this single-nucleotide insertion could be clinically relevant and associated with severe clinical symptoms of COVID-19.\\u003c/p\\u003e\\n\\u003cp\\u003ers1051390 (G\\u0026gt;C), rs12422022 (A\\u0026gt;G), and rs1131665 (T\\u0026gt;C) variants, also on \\u003cem\\u003eIRF7\\u003c/em\\u003e gene, were detected in nine patients with identical distribution, as a haplotype. Six of these patients belong to severe clinical symptoms group, one belongs to moderate, and two belong to mild symptoms group, whereby all nine participants presented with heterozygous genotype. While rs1051390 and rs12422022 are intronic, rs1131665 is a missense variant (g.613208T\\u0026gt;C, p.Gln412Arg).\\u003c/p\\u003e\\n\\u003cp\\u003ers10813831 (G\\u0026gt;A) is a missense variant (g.5177C\\u0026gt;T, p.Arg7Cys) in \\u003cem\\u003eDDX58\\u003c/em\\u003e gene, that was detected in eight patients in our study, including five from the severe clinical group (one heterozygous and four homozygous genotypes), one heterozygote from the moderate clinical group, and two heterozygotes from the mild clinical group. While this variant, although protein-coding and missense, was not reported in ClinVar as clinically relevant [23], our results point towards its involvement in progression of more severe COVID-19, especially in homozygous carriers of the variant. Previous research connected this variant with other conditions. For example, Wu et al. (2019) concluded that Chinese individuals carrying the rs10813831-G-allele-containing genotype were more liable to achieve spontaneous hepatitis C virus (HCV) clearance than the patients who were carriers of the alternate allele [26].\\u003c/p\\u003e\\n\\u003cp\\u003eAnother interesting variant from \\u003cem\\u003eDDX58\\u003c/em\\u003e gene is rs1213032873 (insA), which is detected in only two heterozygous patients in the severe symptom group. It is an intronic variant with no clinical significance described in ClinVar [23], including no reports on the variant association with COVID-19 susceptibility and/or severity. This insertion is extremely rare, with alternative allele frequency of 0.0002 in 8,676 individuals of European ancestry, according to the latest release of the ALFA Project [22], as compared to our allele frequency of 0.021 in the COVID-19 patient population, which is significantly different (p=5.31 x 10\\u003csup\\u003e-16\\u003c/sup\\u003e). Since we are reporting this variant for the first time, to the best of our knowledge, as the variant potentially associated with severe COVID-19 manifestation and increased susceptibility to COVID-19, it should be researched on a large patient population and compared to the general population frequencies of the insertion allele.\\u003c/p\\u003e\\n\\u003cp\\u003ers73230068 (G\\u0026gt;C) is a single nucleotide change in the intronic region of \\u003cem\\u003eTMPRSS2\\u003c/em\\u003e, which was present in five of our patients, whereby three of them belong to severe and two to moderate clinical symptoms group; all five individuals are heterozygous carriers. Our study, therefore, shows an increase in variant frequency in patients with more severe forms of COVID-19. While it was not a subject of previous research aiming to associate this variant with any diseases or clinical conditions, it has been a subject of a population study. Alternative allele frequency of 0.037 was recorded in 14,286 individuals of European ancestry [22], which is in good agreement with our allele frequency of 0.042 (p=0.904) in a set of COVID-19 patients.\\u003c/p\\u003e\\n\\u003cp\\u003ers17854725 A\\u0026gt;G is a silent variant (c.879T\\u0026gt;C, p.Ile293=) in the same gene, which is present in a significantly higher proportion of patients from the severe, when compared to mild and moderate symptom groups. The same variant is also present as a missense variant (c.879T\\u0026gt;G, p.Ile293Met), which was not recorded in our study. This variant was previously investigated in terms of its association with COVID-19. Namely, rs17854725/rs75603675/rs12329760/rs4303795 polymorphisms have been associated with increased susceptibility to COVID-19 and more severe clinical symptoms [27]. In that study, mortality was more frequent in individuals who carried the rs17854725/AG genotype. They also showed that G allele of this SNP is related to increased susceptibility to COVID-19 infection. Combined haplotype rs17854725/AG, rs75603675/AC, rs12329760/TT, and rs4303795/AG was ruled as a risk factor for COVID-19 susceptibility, especially in the case of GATG and GCTG haplotypes. Most COVID-19 patients whose rs17854725 genotype was AG were affected by the severe form of the disease, while about 64% of the AA genotype carriers had mild clinical symptoms [27]. Additionally, in a bioinformatic prediction study [13], rs75603675 was predicted to affect TMPRSS2 protein function according to PolyPen-2, but not according to SIFT [13]. Our study showed the presence of three polymorphisms together, that is, rs17854725/rs75603675/rs12329760 in two patients, whereby one patient belongs to mild and the other belongs to severe clinical symptoms group.\\u003c/p\\u003e\\n\\u003cp\\u003ers2285666 (C\\u0026gt;T) intronic variant on X-chromosomal gene \\u003cem\\u003eACE2\\u003c/em\\u003e was detected in nine samples in our study, including one male from the severe clinical symptoms group, five patients from the moderate group (three heterozygous females and two males), and three patients from the mild group (two heterozygous females and one male). rs2285666 polymorphism is located at the beginning of the intron 3, and it could theoretically affect gene expression with alternative splicing mechanisms [28]. Srivastava et al. (2020) made a correlation between lower SARS-CoV-2 infection rate and the minor allele (T) in Indian population, therefore establishing a possibility of this polymorphism being associated with a protective role against infection [29]. M\\u0026ouml;hlendick et al. (2021) have found a two-fold increased risk of SARS-CoV-2 infection and a three-fold increased risk for COVID-19-related fatality or severe form of COVID-19 in CC genotype (or C allele) carriers in German population [30]. Nonetheless, it is important to note that different studies report conflicting results regarding this polymorphism. Our study shows that there is an increased number of alternative allele carriers in mild and moderate groups, when compared to the group of patients with severe form of COVID-19, meaning that our results corroborate the hypothesis of this SNP being more prevalent in mild and moderate clinical groups. However, this is not necessarily the case when considering the sex of the study participants. Males, carrying one alternative allele and having one copy of the gene, are distributed across three groups. Females are all heterozygous, which is important considering the fact that \\u003cem\\u003eACE2\\u003c/em\\u003e escapes X chromosome inactivation [31] and both copies of the gene remain transcriptionally active in all cells of female patients. This gives higher gene dosage to females, as well as evolutionary advantage in case of heterozygous carriers of harmful variants. This SNP, however, seems to be protective in females since it is found in moderate and mild groups only.\\u003c/p\\u003e\\n\\u003cp\\u003eCOVID-19 is probably the best representation of how significant discoveries can be made in short time periods, assuming that research teams are given adequate support. By studying COVID-19 from different perspectives, we accumulated a significant wealth of knowledge in less than three years since the beginning of the pandemic. Research into the host genetics of SARS-CoV-2 infection is still active and ongoing, with large consortia being formed with the goal of completing whole-genome or whole-exome studies on large patient and control groups, such as the COVID-19 Host Genetics Initiative [32], the COVID Human Genetic Effort [16], and the Severe COVID-19 GWAS Group [33]. Apart from studying the influence of host genetics on COVID-19 susceptibility and severity, these research groups aim towards better understanding of critical COVID-19 and post-COVID. Overall, given current importance of this topic and availability of technical support, COVID-19 research promises to be one of the most fruitful areas of research in foreseeable future.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eDATA AVAILABILITY STATEMENT\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eRaw data produced during the study can be accessed at \\u003ca data-fr-linked=\\\"true\\\" href=\\\"https://www.ncbi.nlm.nih.gov/bioproject/912097\\\"\\u003ehttps://www.ncbi.nlm.nih.gov/bioproject/912097\\u003c/a\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eACKNOWLEDGEMENTS\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors are grateful to all volunteers for accepting to participate in the study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAUTHOR CONTRIBUTIONS\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLS participated in sample collection, performed experimental analyses, and participated in manuscript drafting. IČ, Na. Mu., SD, DP, and EK participated in experimental analyses and manuscript revision. LB performed statistical analysis and participated in manuscript drafting. LP participated in patient recruitment, sample collection, data analysis, and manuscript revision. Ne. Me. participated in data analysis and manuscript revision. TB, BP, and DM overlooked the study from the beginning and contributed significantly to the manuscript revision. RK participated in all parts of the study, most prominently in experimental analysis, data processing, and manuscript revision. AA conceived the study, overlooked the study, participated in data processing and in manuscript drafting. All authors approved the final version of the manuscript. All authors agree to be accountable for all the aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFUNDING\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research is a part of the project titled \\u0026ldquo;Personalized approach to COVID-19 infection through analysis of molecular genetic predisposition of the patients for a differential immune response\\u0026rdquo;, that is co-financed by the Ministry of Science, Education, and Youth of the Sarajevo Canton (decision no. 11/05-34-12880-8/20).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eETHICAL APPROVAL\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEthical approvals for conducting this study were granted by the Joint Ethics Committee of the General Hospital Te\\u0026scaron;anj, Bosnia and Herzegovina, for patient DNA sample and clinical record use (January 11\\u003csup\\u003eth\\u003c/sup\\u003e, 2021, document number 01-4-17/21) and the Ethics Committee of the Faculty of Engineering and Natural Sciences, International Burch University Sarajevo, Bosnia and Herzegovina, for conducting the molecular analyses (March 23\\u003csup\\u003erd\\u003c/sup\\u003e, 2021, document number 04-51/21).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCOMPETING INTERESTS\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eParts of this research have been presented at the 12\\u003csup\\u003eth\\u003c/sup\\u003e ISABS Conference on Forensic and Anthropological Genetics and Mayo Clinic Lectures in Individualized Medicine held in June 2022 in Dubrovnik, Croatia.\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors have no other financial or non-financial competing interests to disclose.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eHuang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, \\u003cem\\u003eet al.\\u003c/em\\u003e Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5.\\u003c/li\\u003e\\n \\u003cli\\u003eCheng CY, Lee YL, Chen CP, Lin YC, Liu CE, Liao CH, \\u003cem\\u003eet al.\\u003c/em\\u003e Lopinavir/ritonavir did not shorten the duration of SARS CoV-2 shedding in patients with mild pneumonia in Taiwan. J Microbiol Immunol Infect. 2020; 53(3):488-492. doi: 10.1016/j.jmii.2020.03.032.\\u0026nbsp;\\u003c/li\\u003e\\n \\u003cli\\u003eNaqvi AAT, Fatima K, Mohammad T, Fatima U, Singh IK, Singh A, \\u003cem\\u003eet al.\\u003c/em\\u003e Insights into SARS-CoV-2 genome, structure, evolution, pathogenesis and therapies: Structural genomics approach. Biochim Biophys Acta Mol Basis Dis. 2020; 1866(10):165878. doi: 10.1016/j.bbadis.2020.165878.\\u0026nbsp;\\u003c/li\\u003e\\n \\u003cli\\u003eWang MY, Zhao R, Gao LJ, Gao XF, Wang DP, Cao JM. SARS-CoV-2: Structure, Biology, and Structure-Based Therapeutics Development. 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N Engl J Med. 2020; 383(16):1522-1534. doi: 10.1056/NEJMoa2020283.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003eTables 1-4 are available in the Supplementary Files section\\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"ACE2, COVID-19, host genetics, IRF7, SARS-CoV-2, TMPRSS2\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-2397519/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-2397519/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"COVID-19, caused by the SARS-CoV-2 virus, has been a major focus of scientific research since late 2019 and early 2020. Due to its enormous societal, economic, and clinical impact worldwide, research efforts aimed, among other questions, to address the effect of host genetics in susceptibility and severity of COVID-19. In this research, we performed next-generation sequencing of coding and regulatory regions of 16 selected human genes, involved in the maintenance of the immune system or encoding the receptors for viral entry into the host cells, in a subset of 60 COVID-19 patients from the General Hospital Tešanj, Bosnia and Herzegovina, classified into three groups of patients with clinical conditions of different severity (“mild”, “moderate”, and “severe” clinical groups). In accordance with previous studies, we found out that the male sex and older age are risk factors for severe clinical picture. We identified 13 variants on seven genes (CD55, IL1B, IL4, IRF7, DDX58, TMPRSS2, and ACE2) with potential functional significance, either as genetic markers of modulated susceptibility to SARS-CoV-2 infection or as modifiers of the course of infection in terms of predicted symptom severity. Our results include variants reported for the first time as potentially associated with COVID-19. Future studies on larger patient cohorts, focused on candidate genes and/or candidate genetic variants, have a potential to answer a range of open questions regarding the effect of host (human) genetic makeup on the expected outcome of COVID-19.\",\"manuscriptTitle\":\"IDENTIFICATION OF HUMAN GENETIC VARIANTS MODULATING THE COURSE OF COVID-19 INFECTION\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2023-01-12 23:40:57\",\"doi\":\"10.21203/rs.3.rs-2397519/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"fdab753a-7ed8-4e63-a99d-98360ea1f155\",\"owner\":[],\"postedDate\":\"January 12th, 2023\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":18262870,\"name\":\"Biological sciences/Genetics/Population genetics/Genetic variation/Rare variants\"},{\"id\":18262871,\"name\":\"Biological sciences/Genetics/Genetic markers\"}],\"tags\":[],\"updatedAt\":\"2023-01-12T23:40:57+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2023-01-12 23:40:57\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-2397519\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-2397519\",\"identity\":\"rs-2397519\",\"version\":[\"v1\"]},\"buildId\":\"MNcDy3x_fV0tqtF8t3uB_\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}