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STUDY OF THE DISTRIBUTION OF FREQUENCIES OF ALLELES AND GENOTYPES OF POLYMORPHIC VARIANTS rs1800795 OF THE IL6 GENE, rs1800629 OF THE TNFA GENE AND rs10490770 OF THE LZTFL1 GENE ASSOCIATED WITH COVID-19 IN POPULATIONS OF THE VOLGA-URAL REGION
Z.R. Sufyanova1*, N.V. Ekomasova1,2 M.A. Dzhaubermezov1,2 S.G. Petrova1, A.V. Kazantseva2,3
D.S. Prokofyeva1, L.R Gabidullina1, I.M. Khidiyatova1,2, A.Kh. Nurgalieva1, Y.Y. Fedorova1,
E.K. Khusnutdinova1,2
1 Federal State Budgetary Educational Institution of Higher Education «Ufa University of Science and Technology», 32 Zaki Validi St., Ufa, 450076, Russia;
2 Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences, 71 Prospekt Oktyabrya St., Ufa, 450054, Russia;
3 Ufa State Petroleum Technological University, 1 Kosmonavtov St., Ufa, 450064, Russia.
* Corresponding author: zemfira.sufyanova@mail.ru
Abstract. The study of the severity and consequences of infectious diseases is a relevant subject of research throughout the world, which was directly demonstrated by the situation with the 2020-2023 coronavirus pandemic. In our study, we analyzed a distribution of genotypes and alleles frequency of polymorphic variants of the IL6 rs1800795, TNFA rs1800629 and LZTFL1 rs10490770 gene polymorphisms, which were previously linked to the pathogenesis of COVID-19, in populations of Burzyan Bashkirs, Sterlibashevsky Bashkirs, Permsky Bashkirs, Kazan Tatars, Chuvash, Udmurts, Mari, Komi and Mordvins. Statistically significant differences were identified in the IL6 rs1800795 between the populations of the Burzyan Bashkirs and the Mari and Komi (p < 0.05). The Sterlibashevsky Bashkirs, Permsky Bashkirs and Udmurts also statistically significantly differed from the Komi population (p < 0.05). When studying the TNFA rs1800629, statistically significant differences were identified between the populations of Sterlibashevsky and Permsky Bashkirs and the Udmurts population (p < 0.05). Analysis of the LZTFL1 rs10490770 revealed statistically significant differences only between the Udmurt and Mari populations (p < 0.05). The data indicate that despite the geographic proximity of the examined populations of the Volga-Ural region, they were able to preserve the uniqueness of their gene pool.
Keywords: COVID-19, IL-6, TNFA, LZTFL1, populations of the Volga-Ural region.
List of Abbreviations
ARDS - Acute respiratory distress syndrome
ARVI - Acute respiratory viral infections CI - Confidence interval COVID-19 - Coronavirus disease 2019 DNA - Deoxyribonucleic acid EDTA - Ethylenediaminetetraacetic acid HWE - Hardy-Weinberg equilibrium MAS - Macrophage activation syndrome mtDNA - Mitochondrial deoxyribonucleic acid
PCR - Polymerase chain reaction RFLP - Restriction Fragment Length Polymorphism
Rospotrebnadzor - The Federal Service for the Oversight of Consumer Protection and Welfare of the Russian Federation
SARS-CoV-2 - Severe acute respiratory syndrome coronavirus 2
VUR - Volga-Ural region
Introduction
More than three years have passed since the discovery of the COVID-19 infection, and to date many studies have been already accumulated on this acute topic, especially on the genes associated with the susceptibility and severity of this disease. According to the World Health Organization (WHO), as of April 2024, there were more than 760 million confirmed cases of COVID-19, including more than 7 million deaths (https://data.who.int/dashboards/
covid19/cases). In our study, we analyzed the distribution of genotype and allele frequencies for three genes, which were previously associ-
ated with severe COVID-19, in nine populations from the Russian Federation (Volga-Ural region). According to Rospotrebnadzor (The Federal Service for the Oversight of Consumer Protection and Welfare of the Russian Federation), more than 102 thousand cases of COVID-19 infection were registered in the Republic of Bashkortostan in 2021, of which 86% were with ARVI (acute respiratory viral infections), 12.5% with pneumonia, and 1.5% were asymptomatic. There were 3,387 fatal cases (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Republic of Bashkortostan & FBIH "Hygienic and Epidemiological Center in the Republic Of Bashkortostan", 2022). In 2022, more than 223 thousand cases of infection were detected in the Republic of Bashkortostan, of which 95.7% were with ARVI, 2.2% with pneumonia, and 2.1% were asymptomatic. With a fatal outcome of 2469 cases (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Republic of Bashkortostan et al, 2023). Also in 2022, according to the Ministry of Health of the Republic of Bashkortostan from the information summary on COVID-19, 736 cases of the disease were recorded in the Sterlibashevsky district, 177 cases of the disease were recorded in the Burzyansky district, and 697 cases of COVID-19 were recorded in the Mishkinsky district (https://health.bashkor-tostan.ru/documents/active/285570/). According to Rospotrebnadzor, more than 130 thousand cases of the disease were registered in the Permsky Region in 2021, among which 85.2% were classified by clinical forms as ARVI, 14.7% as pneumonia, and 0.1% as asymptomatic forms. 6,107 fatal cases were recorded. (Office of Rospotrebnadzor in the Permsky Region & FBIH "Hygienic And Epidemiological Center in the Permsky Region", 2022). In 2022, more than 305 thousand cases of COVID-19 were registered in the Permsky Region, among which 96.7% were classified as having ARVI, 3.2% as having pneumonia, and 0.1% as asymptomatic. And 1143 deaths (Office of Rospotrebnadzor in the Permsky Region & FBIH "Hygienic And Epidemiological Center in the Permsky Region", 2023). In 2021, 29,418
cases of COVID-19 were registered in the Republic of Tatarstan. Of these, 5.2% were asymptomatic. 34.2% of cases were hospitalized (Office of Rospotrebnadzor in the Republic of Tatarstan & FBIH "Hygienic And Epidemiological Center in the Republic of Tatarstan", 2022). In 2022, more than 150 thousand cases of COVID-19 were recorded. Of these, 1.4% were asymptomatic. 13.3% of cases were hospitalized (Office of Rospotrebnadzor in the Republic of Tatarstan & FBIH "Hygienic And Epidemiological Center in the Republic of Tatarstan", 2023). In the Chuvash Republic, more than 69 thousand cases of COVID-19 were registered in 2022 (Office of Rospotrebnadzor in the Chuvash Republic (Chuvashia) & FBIH "Hygienic And Epidemiological Center in the Chuvash Republic (Chuvashia)", 2023). In 2021, more than 59 thousand cases of the disease were registered in the Udmurt Republic, among which, according to clinical forms, 64.8% are with ARVI, 18.5% are asymptomatic forms of COVID-19, and 16.7% are pneumonia (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Udmurt Republic & FBIH "Hygienic and Epidemiological Center in the Udmurt Republic",
2022). In 2022, more than 153 thousand cases of infection were registered, among which community-acquired pneumonia makes up 1.2%, ARVI - 83.2%, asymptomatic forms - 15.6% (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Udmurt Republic & FBIH "Hygienic and Epidemiological Center in the Udmurt Republic",
2023). In the Komi Republic, more than 97 thousand cases of COVID-19 were registered in 2021. The predominant symptom when registering the disease was ARVI - 71.3%. Symptoms of community-acquired pneumonia were detected in 22.2% of cases and 6.5% of patients had no symptoms. The number of deaths is 489 (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Komi Republic & FBIH "Hygienic and Epidemiological Center in the Komi Republic", 2022). In 2022, more than 103 thousand cases of COVID-19 were registered. According to the clinical forms of the disease, symptoms of
ARVI were registered, which amounted to 77.9%. Symptoms of community-acquired pneumonia were detected in 13.7% of cases. And 8.9% of those infected had no symptoms of the disease. With a fatal outcome of 107 cases (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Komi Republic & FBIH "Hygienic and Epidemiological Center in the Komi Republic", 2023). In the Republic of Mordovia, 26,895 cases were registered in 2021 and 44,514 cases of COVID-19 in 2022 (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Republic of Mordovia & FBIH "Hygienic and Epidemiological Center in the Republic of Mordovia", 2023). In 2021, more than 22,292 cases of COVID-19 were registered in the Republic of Mari El. The most common clinical forms of the disease were ARVI - 55.7%, community-acquired pneumonia - 39.9%, and asymptomatic forms - 4.4% (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Republic of Mari El, 2022). In 2022, 22,926 cases were registered. The most common clinical forms of the disease were ARVI - 90.1%, asymptomatic forms - 6.3%, and community-acquired pneumonia - 3.5% (Office of the Federal Service for the Oversight of Consumer Protection and Welfare in the Republic of Mari El, 2023).
Genes involved in infectious processes include interleukins, a group of cytokines produced primarily by lymphocytes and mono-cytes that are part of the immune system. One of the well-known genes is the interleukin 6 (IL-6) gene (7p15.3), encoding a pleiotropic cy-tokine, which affects the functions of various cell types (Fara et al., 2020). This cytokine is involved in antiviral immunity and multiple inflammatory and immunological diseases (Kang et al., 2020). Thus, a search for causal relationship has been previously conducted using Men-delian randomization approach, which resulted in a causal link between the IL-6 signaling pathway and multiple diseases, including depression (Kelly et al., 2021), rheumatoid arthritis (Li et al., 2016), systemic lupus erythematosus (Xiang et al., 2023), and breast cancer (Zhang
et al, 2023; Jing et al, 2024). Interleukin 6 has also been associated with the progression of severe COVID-19 infection. For example, a study of interleukin 6 in diabetic patients infected with SARS-CoV-2 reported increased IL-6 levels, suggesting that the pro-inflammatory state of diabetes may contribute to the cytokine storm and systemic inflammatory response that accompanies acute respiratory distress syndrome in patients with COVID-19 (Guo et al., 2020; Lima-Martínez et al, 2021). One of the IL-6 gene polymorphisms is rs1800795 (-174G >C), which is located in the promoter region of the IL-6 gene, and, as a consequence, is associated with the level of IL-6 gene expression (Khafaei et al., 2024). In the study based on the sample of 280 Iran patients with COVID-19, the association of IL-6 rs1800795 G/G genotype and the G allele and COVID-19 severity was detected (Khafaei et al., 2024). In addition, rs1800795 G/G genotype was significantly associated with disease mortality. In another study based on the sample of 70 COVID-19 patients from Turkey, the analysis of the rs1800795 polymorphism in patients with macrophage activation syndrome (MAS) showed that the G allele might be one of the risk factors for increased serum IL-6 levels and MAS progression (Kerget & Kerget, 2021). However, several studies, including the study by Gianni-trapani et al. (2022), reported an enhanced frequency of the IL-6 rs1800795 C/C genotype in critically ill patients compared to non-critically ill patients (p = 0.044) from Sicilia (Italy) (Giannitrapani et al., (2022). In Verma et al. (2023), the results demonstrate that the IL6 rs1800795 C allele may be a risk factor for severe disease caused by SARS-CoV-2 infection in a North Indian population (Verma et al., 2023).
The TNFA gene (6p21.33) encodes a multifunctional proinflammatory cytokine, tumor necrosis factor a (TNF-a), which is involved in the regulation of many processes in the human body, such as cell proliferation, apoptosis and coagulation. The TNF-a is secreted by cells such as adipocytes, activated monocytes, macrophages, B cells, T cells, and fibroblasts. This cytokine is involved in multiple autoimmune,
chronic and infectious diseases, since it is an important mediator of the immune response (Luo et al, 2023; Fricke-Galindo et al, 2022). This cytokine is also thought to play an important role in establishing a complex relationship between inflammation and cancer (Wei et al., 2023). When charged by viral infections, TNF-a is one of the first effectors that alerts the host immune system to danger (Mohd Zawawi et al, 2023). The TNF-a binds to its receptors, one of which is TNFR1, which is found in almost all cell types. Therefore, it may have different modulating effects on a large set of different cells (Chen et al, 2022). The COVID-19 severity is highly linked to cytokine storm caused by proinflammatory cytokines such as TNF-a (Mohd Zawawi et al, 2023). Among the most studied TNFA gene polymorphisms is rs1800629 (-308G>A), which is located in the promoter region of the gene. This polymorphism is associated with susceptibility to hepatitis C viral infection (Tharwat et al, 2019) and has been suggested as a possible candidate for developing asthma (Yang et al, 2014). In a study conducted in Chinese population, the TNFA rs1800629 A allele was shown to be associated with the risk for developing ARDS (acute respiratory distress syndrome) and, in contrast, the G/G genotype was associated with lower mortality (Ding et al, 2019). The study by Iranian scientists demonstrated that TNFA rs1800629 (-311A/G) A allele resulted in a moderate reduction in the risk of COVID-19. Also, the A/A genotype, compared with the G/G plus G/A genotype, had a protective effect on susceptibility to SARS-CoV-2 infection (Heidari Nia et al, 2022). In the study conducted by scientists from Egypt based on the sample of 900 COVID-19 patients and 184 controls, it was shown that disease severity was related to the TNFA G-308A A/A genotype compared with carriers of G/A genotype and G/G genotype with P = 0.001 (Saleh et al, 2022).
Another prominent gene is the LZTFL1 (3p21.31), which encodes a cytoplasmic and ciliary protein, expressed in many places and interacting with other cytosolic proteins (Seo et al, 2011). It is localized in the cytoplasm. The LZTFL1 is a known inhibitor of epithelial-mes-
enchymal transition. This protein interacts with Bardet-Biedl syndrome protein, which regulates protein transport to the ciliary membrane. The expression of the LZTFL1 gene occurs particularly in pulmonary epithelial cells, where ciliated epithelial cells are known to be located and are considered the main cellular targets of SARS-CoV-2 infection (Niemi et al., 2022; Gonzalez-Rubio et al, 2023). Nowadays, the LZTFL1 is known to be a part of the chromosome 3 gene cluster, which was inherited by modern humans from the Neanderthals about 50,000 years ago (Zeberg & Paabo, 2020). In the present study we genotyped the rs10490770 variant of the LZTFL1 gene. The study by Nakanishi et al. showed that the likelihood of death or severe illness from SARS-CoV-2 infection was increased by 2.7 times in LZTFL1 rs10490770 C allele carriers aged 60 years and younger (Nakanishi et al., 2021).
The sample of our study includes three subpopulations of Bashkirs such as Burzyan, Ster-libashevsky and Permsky, as well as populations of Kazan Tatars, Chuvash, Udmurts, Mari, Komi and Mordvins. Moreover, each ethnic group has its own unique history and culture, which has been studied by various researchers (Serebrennikov, 1967; Kuzeev, 1974; Khaidu, 1985; Kuzeev, 1992; Belykh & Napol-skikh, 1994; Ivanov, 2000; Mokshin, 2000; Fedyuneva, 2000; Iskhakov & Izmailov, 2001; Belykh, 2006; Yanguzin & Khisamitdinova, 2007). All these populations live primarily in the Volga-Ural region (VUR) of the Russian Federation. The Turkic peoples of the VUR include subpopulations of Bashkirs, populations of Chuvash and Tatars. The Finno-Ugric peoples of the VUR include the Mordvins, Udmurts, Mari and Komi. Our colleagues have previously carried out the study of a genetic structure of abovementioned populations based on the data on mtDNA and Y-chromosome variability. Their results indicated that despite the geographical proximity of these peoples, they managed to maintain their uniqueness, which was reflected in the gene pool of these peoples (Trofimova, 2015). Therefore, we are extremely interested in studying the distribution of genotypes and alleles frequency of the genes
associated with the COVID-19 severity in these populations from the Volga-Ural region.
Materials and Methods
The study sample included 594 samples of populations and subpopulations from the Volga-Ural region, including 49 presumably healthy representatives of the Bashkirs subpopulation of the Burzyansky district of the Republic of Bashkortostan and 88 representatives of the Sterlibashevsky district of the Republic of Bashkortostan and 75 representatives of the Bashkirs subpopulation from the Permsky region of the Russian Federation, as well as 48 representatives of the Tatars population from the city of Kazan, Russian Federation, 44 representatives of the Chuvash population from the city of Cheboksary, Russian Federation, 94 representatives of the Udmurts population from the city of Izhevsk and settlements of the Yakshur-Bodyinsky district, Udmurtia of the Russian Federation, 47 representatives of the Mari population from the Mishkinsky district of the Republic of Bashkortostan, 60 representatives Komi population from the city of Syktyvkar and Koygorodsky district of the Komi Republic of the Russian Federation and 89 representatives of the Mordvins population from the Republic of Mordovia of the Russian Federation. The ethnicity of each participant was determined up to the third generation based on a questionnaire. A participation in the study was voluntary, which was carried out after the informed consent was obtained from all the examined individuals. All procedures were carried out in accordance with the ethical standards of the Bioethics Committee, developed by the WMA Declaration of Helsinki - «Ethical Principles for the Conduct of Medical Research Involving Human Subjects». The study was approved by the Local Ethics Committee of the Institute of Biochemistry and Genetics of the UFRC RAS (protocol No. 19 of November 25, 2021).
DNA was isolated by phenol-chloroform extraction (Mathew, 1984). Blood was collected into Vacutainer® tubes with EDTA anticoagulant. Subsequently, the tubes with blood were stored at -20 °C until isolation. Genotyping of IL6 rs1800795 and TNFA rs1800629 gene pol-
ymorphisms was carried out using the KASP (Kompetitive Allele Specific PCR) method, which is based on a competitive allele-specific PCR and makes it possible to determine single-nucleotide polymorphism in both alleles, as well as insertion or deletion of a specific region. A mixture of SNP-specific primers and twofold reaction mixture (mastermix) universal for genotyping were added to the DNA sample, then PCR was carried out, followed by fluorescence reading at the end point. The BioRad CFX96 C1000 Touch™ (USA) was used for real-time PCR. The analysis of the LZTFL1 rs10490770 gene polymorphism was performed using PCR on BioRad T100TM (USA) (Mullis et al, 1986) followed by RFLP analysis. RFLP was performed using the appropriate restriction enzymes produced by SibEnzyme (Russia). Separation of DNA fragments after PCR and RFLP was carried out using electrophoresis in 7% polyacrylamide gel. After elec-trophoresis, the gel was stained with a solution of an intercalating dye (ethidium bromide) and visualized in ultraviolet light using the Quantum video system (France). Allele frequencies in the examined populations were calculated based on the observed genotype frequencies. The correspondence of the genotype frequencies to the Hardy-Weinberg equilibrium was assessed using Pearson's x2 test (at p > 0.05). The significance of differences in allele frequencies in the sample was calculated by the x2 test using the Yates correction for continuity.
Results
In the present study we examined the distribution of genotype and alleles frequencies of three polymorphic variants rs1800795 of the IL6 gene, rs1800629 of the TNFA gene, rs10490770 of the LZTFL1 gene, which were previously associated with severe COVID-19. The distribution of genotype frequencies for almost all studied loci corresponded to the Hardy-Weinberg distribution, with the exception of the IL6 rs1800795 variant in the population of Sterlibashevsky Bashkirs (Tables 1, 2, 3).
We have also conducted pairwise comparisons of allele frequencies of all studied loci in the examined ethnic groups. Our analysis was
also based on the data obtained for some other world populations within the 1000 Genomes Project (Supplementary tables 1, 2, 3) (The 1000 Genomes Project Consortium, 2012).
In our study we revealed that the highest frequency of the IL6 rs1800795 G/G genotype was observed in the Burzyan Bashkirs (51.02%), while the lowest valueswere detected in the Komi population (23.33%). The frequency of the C/C genotype was the highest in the Mari population (21.28%), while the lowest values were detected in the populations of Burzyan and Sterlibashevsky Bashkirs (2.04% and 2.27%, respectively). The frequency of the minor allele varies from 25.51% (95% CI 17.2435.31) in the Burzyan Bashkir population to 47.50% (95% CI 38.31-56.82) in the Komi population. A pairwise comparison of the studied populations with several world populations revealed that statistically significant differences were identified among the populations of Burzyan Bashkirs, Sterlibashevsky Bashkirs, Permsky Bashkirs, Udmurts, Mari and Komi. Among the world's populations, statistically significant differences were found between African, Peruvian, Colombian, Mexican Ancestors, Finns, British, Iberian, Tuscan, and East and South Asian populations (Table 1, Supplementary table 1).
The analysis of the distribution of genotype and allele frequencies of the TNFA rs1800629 demonstrated that the frequency of the G/G genotype predominated in the sample and varied from 68% in the population of Permsky Bashkirs to 85.11% in the Udmurts population.
The A/A genotype was detected only in the populations of Sterlibashevsky Bashkirs and Kazan Tatars with a frequency of 3.41% and 2.08%, respectively. The lowest frequency of the minor allele was found in the Udmurts population 7.45% (95% CI 4.13-12.18), and the highest value was observed in the Permsky Bashkirs with a frequency of 16% (95% CI 10.53-22.86). Statistically significant differences were identified between the populations of the Udmurts, Sterlibashevsky and Permsky Bashkirs, as well as between the populations of South America (Peruvians, Colombians), Mexican Ancestors, Iberians, East and South Asia (Table 2, Supplementary table 2).
The analysis of the distribution of genotype and allele frequencies of the LZTFL1 rs10490770 demonstrated that the frequency of the T/T genotype ranged from 75.53% in the Udmurts population to 89.36% in the Mari population. The frequency of the C/C genotype was detected only in the populations of Sterlibashevsky Bashkirs (2.27%), Udmurts (4.26%) and Komi (1.67%). The frequency of the minor allele varied from 5.32% (95% CI 1.75-11.98) in the Mari population and to 14.36% (95% CI 9.68-20.20) in the Udmurts population. Statistically significant differences among the studied populations were found only between the Mari and Udmurts populations. Among the world populations of statistically significant differences were detected between Africans, Peruvians, Colombians, British, Iberians and populations of East and South Asia (Table 3, Supplementary table 3).
Population N G/G G/C C/C Minor allele frequency (95% CI) X2 Deviations from HWE, P
Observed (N) Expected (N) % Observed (N) Expected (N) % Observed (N) Expected (N) %
Burzyan Bashkirs 49 25 27.2 51.02 23 18.6 46.94 1 3.2 2.04 25.51 (17.24-35.31) 2.708 0.10
Sterlibashevsky Bashkirs 88 38 43.7 43.18 48 36.6 54.55 2 7.7 2.27 29.55 (22.92-36.88) 8.466 0.004
Permsky Bashkirs 75 28 31.4 37.33 41 34.3 54.67 6 9.4 8.00 35.33 (27.71-43.55) 2.889 0.09
Kazan Tatars 48 21 19.4 43.75 19 22.2 39.58 8 6.4 16.67 36.46 (26.87-46.91) 1.019 0.31
Chuvash 44 18 16.6 40.91 18 20.9 40.91 8 6.6 18.18 38.64 (28.44-49.62) 0.829 0.36
Udmurts 94 38 39.6 40.43 46 42.8 48.94 10 11.6 10.64 35.11 (28.30-42.39) 0.515 0.47
Mari 47 19 16.7 40.43 18 22.6 38.30 10 7.7 21.28 40.43 (30.42-51.05) 1.973 0.16
Komi 60 14 16.5 23.33 35 29.9 58.33 11 13.5 18.33 47.50 (38.31-56.82) 1.726 0.19
Mordvins 89 40 35.9 44.94 33 41.3 37.08 16 11.9 17.98 36.52 (29.44-44.05) 3.570 0.06
Population N G/G G/A A/A Minor allele frequency (95% CI) X2 Deviations from HWE, P
Observed (N) Expected (N) % Observed (N) Expected (N) % Observed (N) Expected (N) %
Burzyan Bashkirs 49 39 39.5 79.59 10 9.0 20.41 0 0.5 0 10.20 (5.00-17.97) 0.633 0.43
Sterlibashevsky Bashkirs 88 64 63.1 72.73 21 22.9 23.86 3 2.1 3.41 15.34 (10.36-21.53) 0.581 0.45
Permsky Bashkirs 75 51 52.9 68.00 24 20.2 32.00 0 1.9 0 16.00 (10.53-22.86) 2.721 0.10
Kazan Tatars 48 37 36.8 77.08 10 10.5 20.83 1 0.8 2.08 12.50 (6.63-20.82) 0.109 0.74
Chuvash 44 36 36.4 81.82 8 7.3 18.18 0 0.4 0 9.09 (4.01-17.13) 0.44 0.51
Udmurts 94 80 80.5 85.11 14 13.0 14.89 0 0.5 0 7.45 (4.13-12.18) 0.609 0.44
Mari 47 38 38.4 80.85 9 8.1 19.15 0 0.4 0 9.57 (4.47-17.40) 0.527 0.47
Komi 60 48 48.6 80.00 12 10.8 20.00 0 0.6 0 10.00 (5.27-16.82) 0.741 0.39
Mordvins 89 70 71 78.65 19 17 21.35 0 1 0 10.67 (6.55-16.17) 1.271 0.26
Population N T/T T/C C/C Minor allele frequency (95% CI) X2 Deviations from HWE, P
Observed (N) Expected (N) % Observed (N) Expected (N) % Observed (N) Expected (N) %
Burzyan Bashkirs 49 42 42.3 85.71 7 6.5 14.29 0 0.3 0 7.14 (2.92-14.16) 0.290 0.59
Sterlibashevsky Bashkirs 88 72 70.9 81.82 14 16.2 15.91 2 0.9 2.27 10.23 (6.17-15.68) 1.571 0.21
Permsky Bashkirs 75 60 60.8 80.00 15 13.5 20.00 0 0.8 0 10.00 (5.71-15.96) 0.926 0.34
Kazan Tatars 48 41 41.3 85.42 7 6.5 14.58 0 0.3 0 7.29 (2.98-14.45) 0.297 0.59
Chuvash 44 36 36.4 81.82 8 7.3 18.18 0 0.4 0 9.09 (4.01-17.13) 0.44 0.51
Udmurts 94 71 68.9 75.53 19 23.1 20.21 4 1.9 4.26 14.36 (9.68-20.20) 2.988 0.08
Mari 47 42 42.1 89.36 5 4.7 10.64 0 0.1 0 5.32 (1.75-11.98) 0.148 0.70
Komi 60 48 47.7 80.00 11 11.6 18.33 1 0.7 1.67 10.83 (5.90-17.81) 0.156 0.69
Mordvins 89 74 74.6 83.15 15 13.7 16.85 0 0.6 0 8.43 (4.79-13.52) 0.754 0.39
Discussion
The IL6 gene, as previously noted, encodes a cytokine that is involved in antiviral immunity and multiple inflammatory and immunological diseases (Kang et al, 2020). The association with severe COVID-19 was found with both the G/G genotype and the G allele (Turkey, Iran) (Kerget & Kerget, 2021; Khafaei et al, 2024) and the C/C genotype and the C allele (Italy, North India) (Giannitrapani et al., 2022; Verma et al, 2023). According to the results of our study, statistically significant differences were found in the IL6 rs1800795 between the Turkic populations of the VUR, including Burzyan Bashkirs, and the Finno-Ugric populations such as Mari and Komi. The populations of Sterlibashevsky Bashkirs, Permsky Bashkirs and Ud-murts also differed statistically significantly from the Komi population. When compared with world populations, there were statistically significant differences between all examined VUR populations and populations of Africa, Peruvians, Mexican Ancestors, East and South Asia. In addition, there were statistically significant differences between the populations of the Burzyan and Sterlibashevsky Bashkirs and the Northern European populations of the British and Finns. Statistically significant differences were observed between the populations of Udmurts and Finns, which represent Finno-Ugric ethnic groups. In addition, statistically significant differences were revealed between the Komi population and the populations of Colombians from South America and the European populations of Iberians and Tuscans (Supplementary table 1).
The TNFA gene encodes a proinflammatory cytokine involved in various autoimmune, chronic and infectious diseases (Luo et al, 2023; Fricke-Galindo et al., 2022). There are studies reporting the association of the TNFA rs1800629 A/A genotype and A allele with the risk of developing acute respiratory distress syndrome and COVID-19, while G/G genotype was linked to lower mortality (China, Egypt) (Ding et al, 2019; Saleh et al, 2022). However, another study found that the A allele led to a moderate reduction in the risk of COVID-19 (Iran) (Heidari Nia et al, 2022). Our data obtained for the TNFA rs1800629 evidenced in
statistically significant differences between the Turkic populations of Sterlibashevsky and Permsky Bashkirs and the Finno-Ugric population of Udmurts. Moreover, statistically significant differences were revealed between the populations of Sterlibashevsky and Permsky Bashkirs and the populations of South and North America (Peruvians, Colombians, Mexican Ancestors). In the Udmurts population statistically significant differences from the Iberian population of Spain were also determined. Statistically significant differences were also identified between the populations of East and South Asia and the populations of the Sterlibashevsky and Permsky Bashkirs, Kazan Tatars and Mordvins; on the contrary, no differences were identified between the populations of the Burzyan Bashkirs, Chuvash, Udmurts, Mari and Komi. In addition, no statistically significant differences were found between the African population and the studied populations (Supplementary table 2).
The LZTFL1 gene encoding a cytoplasmic, ciliary protein (Seo et al, 2011), which is also expressed in pulmonary epithelial cells, where ciliated epithelial cells are known to be located and represent cellular targets during SARS-CoV-2 infection (Niemi et al., 2022; Gonzalez-Rubio et al, 2023). Previously, carriers of the LZTFL1 rs10490770 risky C allele aged 60 years and younger had an increased likelihood of death or severe illness from COVID-19 (Nakanishi et al., 2021). When we studied the rs10490770 variant of the LZTFL1 gene, statistically significant differences were identified only between the Udmurts and Mari populations, and were not found between the other VUR populations. Statistically significant differences were also determined between all VUR populations and populations from Africa, East and South Asia. Statistically significant values were identified between the populations of Sterlibashevsky and Permsky Bashkirs, Ud-murts, Komi, Mordvins, and the population of Peruvians. In addition, statistically significant differences were identified between the Ud-murts population and the populations of Colombians and European populations (British and Iberian) (Supplementary table 3).
In conclusion, we demonstrated the distributions of genotype and allele frequencies of the IL6 rs1800795, TNFA rs1800629, LZTFL1 rs10490770 gene variants previously associated with severe COVID-19 in nine populations from the Volga-Ural region (Russian Federation). Thus, for the rs1800795 variant of the IL6 gene, the highest frequency of the G/G genotype was observed in the Burzyan Bashkirs population (51.02%), and the lowest in the Komi population (23.33%). The frequency of the C/C genotype was higher in the Mari population (21.28%), and the lowest values were detected in the populations of the Burzyan and Sterlibashevsky Bashkirs at 2.04% and 2.27%, respectively. We observed that the frequency of the TNFA rs1800629 G/G genotype was the highest in the sample and varied from 68% in the population of Permsky Bashkirs to 85.11% in the Udmurts population. The A/A genotype was identified only in two of nine populations, including the Sterlibashevsky Bashkirs and Kazan Tatars with a frequency of 3.41% and 2.08%, respectively. For the rs10490770 variant of the LZTFL1 gene, it was found that the frequency of the T/T genotype ranged from 75.53% in the Udmurts population to 89.36% in the Mari population. The frequency of the C/C genotype was found in only three of nine populations, including Sterlibashevsky Bashkirs (2.27%), Udmurts (4.26%) and Komi (1.67%).
Our study is congruent with the general understanding of the distribution of frequencies of gen-
otypes and alleles of the IL6 rs1800795, TNFA rs1800629, LZTFL1 rs10490770 gene variants, which are potentially involved in the pathogen-esis of COVID-19, in populations of the Russian Federation (Volga-Ural region). Such fundamental studies of the genetic structure of populations are important, since they enable to identify a specific distribution of risk alleles and genotypes of various genes associated with infectious diseases. In turn, it provides the alacrity to novel outbreaks of such diseases and to propose effective methods for treating existing ones.
Conflict of interest: the authors declare no conflict of interest.
Acknowledgments
The study was supported by a grant from the Ministry of Education and Science of the Republic of Bashkortostan Agreement № 1 dated August 14, 2023 on the topic "Prospects for the use of population genetic features of mtDNA as diagnostic markers of stomach cancer" in terms of statistical data processing and state assignment dated February 15, 2024 № 075-03-2024123/1 regarding genotyping. DNA samples for the study were taken from the "Collection of Human Biological Materials" of the Institute of Biochemistry and Genetics of the UFRC RAS, supported by the Program of Bioresource Collections of the FASO Russia (agreement № 007-030164/2).
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Population N Minor allele frequency% Burzyan Bashkirs Sterlibashevsky Bashkirs Permsky Bashkirs Kazan Tatars Chuvash Udmurts Mari Komi Mordvins
Burzyan Bashkirs 49 25.5 0.567 0.137 0.135 0.078 0.129 0.041 0,001 0.083
Sterlibashevsky Bashkirs 88 29.6 0.567 0.265 0.302 0.178 0.257 0.095 0,003 0.163
Permsky Bashkirs 75 35.3 0.137 0.265 0.966 0.71 0.965 0.506 0.043 0.824
Kazan Tatars 48 36.5 0.135 0.302 0.966 0.879 0.925 0.68 0,136 0.903
Chuvash 44 38.6 0.078 0.178 0.71 0.879 0.664 0.924 0.258 0.84
Udmurts 94 35.1 0.129 0.257 0.965 0.925 0.664 0.458 0.03 0.778
Mari 47 40.4 0.041 0.095 0.506 0.68 0.924 0.458 0.371 0.617
Komi 60 47.5 0.001 0.003 0.043 0.136 0.258 0.03 0.371 0.059
Mordvins 89 36.5 0.083 0.163 0.824 0.903 0.84 0.778 0.617 0.059
Africa1 661 1.8 0 0 0 0 0 0 0 0 0
Peruvian in Lima, Peru1 85 5.3 0.000004 0 0 0 0 0 0 0 0
Colombian in Medellin, Colombia1 94 28.7 0.662 0.863 0.194 0.232 0.131 0.184 0.066 0.0008 0.112
Mexican Ancestry in Los Angeles, California1 64 13.3 0.03 0.001 0.00004 0.00009 0.00003 0.00003 0.000008 0 0.00001
Finnish in Finland1 99 45.5 0.001 0.002 0.057 0.181 0.345 0.038 0.495 0.723 0.079
British in England and Scotland1 91 41.2 0.013 0.021 0.274 0.521 0.786 0.227 0.997 0.281 0.361
Iberian population in Spain1 107 35.1 0.122 0.249 0.955 0.911 0.647 0.99 0.439 0.026 0.762
Toscani in Italy1 107 35.5 0.105 0.212 0.972 0.974 0.703 0.932 0.488 0.032 0.837
East Asia1 504 0.1 0 0 0 0 0 0 0 0 0
South Asia1 489 13.9 0.003 0 0 0 0 0 0 0 0
Note: Bold indicates statistically significant differences (P<0.05). 1 - (The 1000 Genomes Project Consortium, 2012).
Population N Minor allele frequency% Burzyan Bashkirs Sterlibashevsky Bashkirs Permsky Bashkirs Kazan Tatars Chuvash Udmurts Mari Komi Mordvins
Burzyan Bashkirs 49 10.2 0.313 0.268 0.781 0.994 0.566 0.924 0.860 0.934
Sterlibashevsky Bashkirs 88 15.3 0.313 0.992 0.647 0.223 0.027 0.254 0.247 0.251
Permsky Bashkirs 75 16.0 0.268 0.992 0.567 0.190 0.021 0.216 0.207 0.208
Kazan Tatars 48 12.5 0.781 0.647 0.567 0.614 0.238 0.681 0.717 0.798
Chuvash 44 9.1 0.994 0.223 0.190 0.614 0.817 0.886 0.985 0.852
Udmurts 94 7.5 0.566 0.027 0.021 0.238 0.817 0.701 0.565 0.371
Mari 47 9.6 0.924 0.254 0.216 0.681 0.886 0.701 0.898 0.941
Komi 60 10.0 0.860 0.247 0.207 0.717 0.985 0.565 0.898 0.995
Mordvins 89 10.7 0.934 0.251 0.208 0.798 0.852 0.371 0.941 0.995
Africa1 661 12.0 0.723 0.199 0.153 0.998 0.525 0.069 0.600 0.526 0.620
Peruvian in Lima, Peru1 85 5.9 0.291 0.008 0.006 0.099 0.483 0.704 0.388 0.281 0.155
Colombian in Medellin, Colombia1 94 6.9 0.458 0.016 0.013 0.177 0.695 1.000 0.583 0.452 0.277
Mexican Ancestry in Los Angeles, California1 64 5.5 0.279 0.012 0.010 0.104 0.449 0.643 0.365 0.271 0.161
Finnish in Finland1 99 12.6 0.677 0.543 0.459 0.875 0.507 0.129 0.573 0.598 0.669
British in England and Scotland1 91 12.1 0.783 0.458 0.386 0.926 0.598 0.183 0.670 0.707 0.798
Iberian population in Spain1 107 14.5 0.391 0.926 0.804 0.772 0.279 0.038 0.319 0.315 0.330
Toscani in Italy1 107 9.4 0.975 0.098 0.080 0.521 0.882 0.615 0.882 0.999 0.789
East Asia1 504 5.9 0.139 0.00002 0.00002 0.020 0.325 0.502 0.226 0.117 0.026
South Asia1 486 5.3 0.080 0.000003 0.000003 0.009 0.219 0.325 0.142 0.063 0.010
Note: Bold indicates statistically significant differences (P < 0.05). 1 - (The 1000 Genomes Project Consortium, 2012).
Population N Minor allele frequency% Burzyan Bashkirs Sterlibashevsky Bashkirs Permsky Bashkirs Kazan Tatars Chuvash Udmurts Mari Komi Mordvins
Burzyan Bashkirs 49 7.1 0.528 0.586 0.812 0.828 0.110 0.823 0.482 0.885
Sterlibashevsky Bashkirs 88 10.2 0.528 0.907 0.561 0.942 0.299 0.251 0.979 0.689
Permsky Bashkirs 75 10.0 0.586 0.907 0.619 0.998 0.298 0.290 0.982 0.764
Kazan Tatars 48 7.3 0.812 0.561 0.619 0.860 0.123 0.794 0.512 0.923
Chuvash 44 9.1 0.828 0.942 0.998 0.860 0.302 0.484 0.858 0.960
Udmurts 94 14.4 0.110 0.299 0.298 0.123 0.302 0.040 0.469 0.106
Mari 47 5.3 0.823 0.251 0.290 0.794 0.484 0.040 0.232 0.490
Komi 60 10.8 0.482 0.979 0.982 0.512 0.858 0.469 0.232 0.620
Mordvins 89 8.4 0.885 0.689 0.764 0.923 0.960 0.106 0.490 0.620
Africa1 661 0.4 0 0 0 0 0 0 0.000001 0 0
Peruvian in Lima, Peru1 85 2.9 0.195 0.012 0.018 0.182 0.066 0.0003 0.527 0.013 0.049
Colombian in Medellin, Colombia1 94 6.4 0.996 0.253 0.309 0.969 0.576 0.018 0.930 0.238 0.584
Mexican Ancestry in Los Angeles, California1 64 3.9 0.438 0.066 0.084 0.416 0.199 0.005 0.862 0.063 0.179
Finnish in Finland1 99 10.1 0.537 0.896 0.882 0.571 0.960 0.261 0.254 0.986 0.704
British in England and Scotland1 91 7.1 0.808 0.396 0.463 0.843 0.751 0.039 0.746 0.363 0.796
Iberian population in Spain1 107 4.7 0.533 0.055 0.077 0.505 0.228 0.001 0.964 0.056 0.191
Toscani in Italy1 107 10.3 0.499 0.880 0.929 0.532 0.918 0.273 0.231 0.978 0.652
East Asia1 504 0.5 0 0 0 0 0 0 0.00003 0 0
South Asia1 489 29.6 0.000004 0 0.000001 0.000006 0.00007 0.00002 0.000001 0.00002 0
Note: Bold indicates statistically significant differences (P < 0.05). 1 - (The 1000 Genomes Project Consortium, 2012).
