Association of polymorphism of coding genes IL-10 and IL-12 with the risk of Helicobacter pylori infection

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Genetic variations within crucial immunomodulatory genes, including those for IL-10 and IL-12, are thought to influence an individual's vulnerability to the infection and its clinical consequences by modifying cytokine production. Nonetheless, research data derived from diverse human populations continue to show inconsistent results. Aim This case-control analysis sought to examine a potential link between H. pylori infection susceptibility in an Iranian population and specific genetic variants in the IL-10 (-1082G > A, -819C > T) and IL-12 (+ 1188A > C) genes. Methods In this investigation, 68 individuals with confirmed H. pylori infection diagnosed by a positive rapid urease test and elevated anti- H. pylori IgG levels exceeding 90 ng/ml via ELISA were enrolled alongside 68 healthy controls. The control group was carefully matched to the patient group based on age, sex, and ethnic background. Genotyping for the IL-10 (-1082G > A, -819C > T) and IL-12 (+ 1188A > C) polymorphisms was conducted using the Amplification Refractory Mutation System-PCR (ARMS-PCR) method. To evaluate associations, the distribution of genotypes and alleles between the groups was contrasted using logistic regression, applying additive, dominant, and recessive inheritance models. The strength of any association was expressed as odds ratios (ORs) accompanied by 95% confidence intervals (CIs). Results The analysis revealed no statistically significant correlations linking the investigated IL-10 and IL-12 gene variants to an increased predisposition for H. pylori infection. Regarding the IL-10 -1082G > A locus, the AA genotype was associated with a marginally elevated risk estimate; however, this finding was not statistically significant (OR = 3.45, 95% CI: 0.29–41.36; p = 0.327). Likewise, for the IL-12 + 1188A > C polymorphism, the CC genotype, while more prevalent in the patient cohort, also demonstrated no significant association with infection risk (OR = 1.43, 95% CI: 0.42–4.87; p = 0.567). Furthermore, it was noted that the genotype distributions for all evaluated polymorphisms within the control group departed from Hardy-Weinberg equilibrium. Conclusion This investigation did not establish a significant link between the specific IL-10 and IL-12 gene variants analyzed and susceptibility to H. pylori infection in the studied population. Although minor genetic associations were noted, they lacked statistical significance. Future research with larger sample sizes is required to validate these results and to investigate additional genetic determinants that may affect infection risk. H. pylori Genetic Susceptibility IL-10 IL-12 Polymorphism Case-Control Studies Introduction Helicobacter pylori (H. pylori) is a spiral-shaped, microaerophilic pathogen with a distinct affinity for colonizing the human gastric mucosal lining ( 1 ). This bacterium is an established causative agent for a range of upper gastrointestinal disorders, from chronic gastritis and peptic ulcers to more severe outcomes such as gastric cancer and mucosa-associated lymphoid tissue (MALT) lymphoma ( 2 ). The colonization and long-term survival of H. pylori within the stomach triggers a persistent inflammatory state, which is characterized histopathologically by the infiltration of neutrophils, lymphocytes, and plasma cells into the gastric mucosa.( 3 ). A significant diagnostic challenge arises from the fact that a majority of infected individuals remain asymptomatic carriers ( 3 ). Global seroprevalence studies indicate that infection rates vary substantially, ranging from 0.2% to 1.7% in some populations, to approximately 50% in many developed nations ( 4 ). Notably, regional disparities in prevalence are also observed within individual countries, suggesting the influence of geographic and socioeconomic factors. The pathogenesis of H. pylori is multifactorial, mediated through an array of virulence mechanisms. These include the modulation of gastric acid secretion, induction of epithelial cell hyperproliferation and elongation, disruption of intercellular junctions, and the elicitation of both systemic and mucosal antibody responses (IgG and IgA) ( 5 , 6 ). The ensuing immune activation involves a complex cytokine network orchestrated by cells of both the innate and adaptive immune systems. Evidence underscores that dysregulated cytokine responses can drive the progression from chronic inflammation to precancerous lesions and ultimately to gastric malignancy ( 7 – 10 ). Following infection with H. pylori , dendritic cells (DCs) in the gastric mucosa become activated. This activation triggers them to release interleukin-12 (IL-12), which subsequently directs naïve CD4⁺ T cells to differentiate into a T helper 1 (Th1) subtype. These newly polarized Th1 cells are defined by their secretion of specific pro-inflammatory cytokines, including interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), interleukin-1 (IL-1), and interleukin-6 (IL-6). ( 10 ) ( 11 ). This Th1-dominant response, governed by the transcription factors T-bet and STAT4, is primarily aimed at bacterial clearance. However, in a subset of individuals, this robust inflammatory response becomes chronic and contributes to tissue damage and carcinogenesis ( 12 ). The involvement of the Th2 immune response in H. pylori infection remains poorly understood. Although this pathway is typically essential for eliminating extracellular pathogens, its contribution in this particular context appears to be limited. Th 2 activity is associated with the generation of IgG1 antibodies, whereas the Th1 response augments overall IgG2 levels via IL-12 and IFN-γ ( 13 ). Functioning as a critical regulator of immunity, Interleukin-10 (IL-10) exerts powerful anti-inflammatory effects. It is synthesized by numerous immune cell types such as macrophages, lymphocytes, dendritic cells, and mast cells. The cytokine operates by inhibiting macrophage activation, restraining the release of pro-inflammatory signals from Th1 cells, and fine-tuning the functions of NK cells, antigen-presenting cells (APCs), and mast cells ( 14 ). The gene encoding IL-10 is located on chromosome 1, and functional polymorphisms within its promoter region (notably at positions − 1082 G > A, -819 C > T ( 15 , 16 )) have been linked to altered cytokine expression levels and an increased risk of gastric cancer. Interindividual variation in IL-10 production capacity following immunogenic stimuli (e.g., LPS) is well-documented ( 17 ). Similarly, IL-12 is a key pro-inflammatory cytokine central to protective immunity against intracellular pathogens, yet it also influences infection persistence and disease severity ( 18 ). Single nucleotide polymorphisms (SNPs) in cytokine genes are among the most common sources of genetic variation in humans and can lead to significant differences in cytokine production capacity across different ethnic and racial groups ( 19 ). These genetic variations may predispose individuals to inflammatory conditions, including those related to H. pylori ( 20 ). This research seeks to determine if a correlation exists between specific IL-10 and IL-12 gene variants and an individual's susceptibility to H. pylori infection, by analyzing and contrasting genotype and allele frequencies in infected individuals versus a healthy control group. Materials and Methods Study Design and Participants This case-control investigation enrolled 68 individuals (51 male, 17 female) with a confirmed H. pylori infection. Participants, who had a mean age of 43.65 ± 16.06 years (range: 19-75), were recruited from the gastroenterology departments of Shahid Beheshti Hospital and Imam Reza Hospital in Kabadrahang, Iran, between December 2023 and August 2024. A specialist physician established the diagnosis based on clinical presentation and positive laboratory tests. Individuals with pre-existing inflammatory, autoimmune, metabolic, or chronic infectious diseases were excluded from the study. The control cohort for this study comprised 68 healthy individuals (48 males, 20 females; aged 20–78 years), who were meticulously matched to the patient group based on key demographic factors including age, sex, ethnicity, and geographical residence. All control subjects were screened to ensure an absence of any personal or familial history of H. pylori infection or associated gastric disorders. All control participants were confirmed to be free of infection via negative pathological biopsy and serological testing. Ethical Considerations Ethical approval for this research was granted by the Research Ethics Committee of Hamadan University of Medical Sciences (Ethics Code: IR.UMSHA.REC.1402.774). Prior to enrollment, every participant provided written informed consent following a comprehensive briefing on the study's objectives and methodology. The anonymity and confidentiality of all personal and clinical data were rigorously upheld for the duration of the research. Determination of H. pylori Infection Status A multi-method diagnostic approach, incorporating both invasive and serological techniques, was employed to accurately identify H. pylori infection. As part of this protocol, two biopsy samples were obtained from the gastric antrum of each subject during upper gastrointestinal endoscopy. One of these specimens was promptly analyzed using a rapid urease test (CLOtest®, Delta West, Australia) for the preliminary detection of bacterial urease activity. A positive result was defined by the development of a pink or red coloration within a 24-hour observation period. Simultaneously, venous blood samples (approximately 2 ml) were drawn from all participants both the patient and the meticulously matched control groups into EDTA-containing vacuum tubes for subsequent serological and molecular analyses. Serological confirmation of the infection was achieved by quantifying anti- H. pylori IgG antibody levels. For this purpose, we employed a validated, commercially sourced ELISA kit (Sigma-Aldrich, Cat. no. RAB0242), meticulously adhering to the manufacturer's instructions. To guarantee analytical reproducibility, every sample was tested in duplicate. An antibody titer exceeding 90 ng/ml was defined as seropositive, confirming active H. pylori infection for inclusion in the patient group. Conversely, individuals in the control group were required to yield negative results from both the rapid urease test and the ELISA (titer < 90 ng/ml), ensuring they were unequivocally infection-free. DNA Extraction and Genotyping Total genomic DNA was isolated from the anti-coagulated whole blood of all study subjects employing a commercial extraction kit (Sina-Clon, Iran) per the supplier's guidelines. The resulting DNA was then assessed for concentration and purity using a NanoDrop™ 2000 spectrophotometer (Thermo Fisher Scientific, USA). Following quantification, all samples were standardized to a uniform working concentration of 50 ng/μL to facilitate downstream genetic analyses. The IL-10 (-1082G>A, -819C>T) and IL-12 (+1188A/C) polymorphisms were genotyped employing the Amplification Refractory Mutation System (ARMS)-PCR technique. Genotyping for the IL-10 promoter polymorphisms (-1082G>A and -819C>T) was performed using established primer sequences and cycling conditions, as previously described by reference (21) . The polymerase chain reaction (PCR) was carried out using a commercial pre-mixed master mix (PCR 2X Taq Premix Mastermix, Pars Tous Co., Iran). Each 20 µL reaction mixture contained approximately 100 ng of genomic DNA template, along with 1 µL of each forward and reverse primer (10 pmol/µL). Amplification was executed on a C 1000 Touch Thermal Cycler (Bio-Rad, USA) with the following profile: an initial denaturation step at 95°C for 4 minutes; 25 cycles of denaturation at 95°C for 20 seconds, annealing at 56°C for the -1082G>A and 58°C for the -819C>T variant for 20 seconds, and extension at 72°C for 30 seconds; culminating in a final extension at 72°C for 5 minutes. Concurrently, the Beta-2 Microglobulin (B2M) gene was co-amplified as an internal control under identical conditions, utilizing a specific annealing temperature of 66°C. To ensure the thorough elongation of all PCR products, a final synthesis phase was implemented at 72°C for a duration of 10 minutes. The amplification of the IL-12 (+1188A/C) locus was performed using a thermal cycling protocol initiated by a 3-minute denaturation at 94°C. This was followed by 35 cycles, each comprising denaturation at 94°C for 30 seconds, primer annealing at 65°C for 45 seconds, and strand extension at 72°C for 45 seconds. The process concluded with a final elongation step at 72°C for 5 minutes to ensure the complete amplification of all target fragments, as per the established methodology(22). Subsequently, the PCR amplicons were resolved by electrophoresis on a 2% agarose gel, which was pre-stained with SYBR Safe DNA gel stain at a concentration of 0.5 µg/mL. The resulting DNA bands were then visualized and documented under ultraviolet light using a UV transillumination system. Statistical Analysis Descriptive statistics for categorical data are presented as counts and percentages, while continuous data are expressed as mean ± standard deviation. Intergroup comparisons for age, which followed a normal distribution, were conducted using an independent samples t-test. For continuous variables deviating from normality, the non-parametric Mann-Whitney U test was applied. Differences in genotype and allele distributions between the case and control cohorts were evaluated by applying multivariate logistic regression analysis. This analysis generated odds ratios (ORs) and corresponding 95% confidence intervals (CIs) across additive, dominant, and recessive inheritance models. The genotype distribution within the control group was tested for conformity to Hardy-Weinberg equilibrium (HWE) using a Chi-square (χ²) goodness-of-fit test. The entire statistical analysis was executed with SPSS software (Version 16), and statistical significance was defined a priori as a two-tailed p -value of less than 0.05. Results Baseline Characteristics of the Study Participants This case-control analysis comprised 68 patients and an equal number of matched controls. The demographic composition of both cohorts is detailed in Table 1. The mean age (± standard deviation) was 51.96 ± 12.28 years in the patient cohort and 49.63 ± 13.87 years in the control group. The gender distribution was comparable between the two groups, with males constituting 75.0% (n=51) of the patient group and 73.5% (n=50) of the controls. Statistical evaluation of lifestyle factors identified significant risk associations. The prevalence of smoking was markedly higher in patients (57.4%) compared to controls (25.0%), a difference that was highly statistically significant ( p < 0.001). Similarly, a positive family history was exclusively reported within the patient group, affecting 32.4% of individuals ( p < 0.001). In contrast, no significant differences were observed between the groups for the variables of education level ( p = 0.421) or alcohol consumption (p = 0.211). (Table.1) Genetic Association Analysis : This case-control investigation was designed to evaluate the potential relationship between susceptibility to the disease and specific genetic variations in the IL-10 (-1082 G/A, -819 C/T) and IL-12 (+1188 A/C) genes. The analysis, which included 68 matched patient-control pairs, yielded the following detailed statistical outcomes. IL-10 (-1082 G/A) Polymorphism The heterozygous A/G genotype was the most common variant in both the patient and control cohorts, with frequencies of 66.2% and 76.5%, respectively. A higher prevalence of the homozygous A/A genotype was observed in patients (32.4%) relative to controls (20.6%). In contrast, the homozygous G/G genotype was infrequent, occurring in only 1.5% of patients and 2.9% of controls. Correspondingly, the A allele was more common in the patient group (65.4%) than in the control group (58.8%). Analysis of the genetic data revealed no statistically discernible differences in the distribution of genotypes ( p = 0.200) or alleles ( p = 0.232) between the patient and control cohorts. Evaluation using a codominant inheritance model showed a non-significant trend toward increased risk for individuals with the A/A genotype (OR = 3.45, 95% CI: 0.29–41.36, p = 0.327) when referenced against the G/G genotype. This pattern of elevated, yet non-significant, risk was similarly observed under a recessive model (A/A vs. A/G+G/G; OR = 1.81, 95% CI: 0.85–3.87, p = 0.122). The allelic comparison (A vs. G) also failed to attain statistical significance (OR = 1.33, 95% CI: 0.83–2.14, p = 0.232). (Table.2) IL-10 (-819 C/T) Polymorphism The C/T genotype was highly prevalent in both patients (86.8%) and controls (89.7%), indicating it is the most common genotype in the studied population. The T/T genotype frequency was identical in both groups (10.3%), while the C/C genotype was absent in controls (0%) and observed in only 2.9% of patients. The T allele demonstrated a marginally higher frequency in controls (55.1%) than in patients (53.7%), with only a minimal disparity between the groups. The analysis of genetic distributions showed no statistically discernible differences between the patient and control groups, either for overall genotype ( p = 0.243) or allele frequencies ( p = 0.791). Under a codominant inheritance pattern, the comparison of the T/T genotype against the C/C reference group showed no association with disease status (OR = 1.00, p = 1.000). This null finding was consistent across other genetic models. A recessive model (T/T vs. C/T + C/C) also demonstrated no effect (OR = 1.00, 95% CI: 0.33-3.02, p = 1.000), as did an allelic model comparing the T allele to the C allele (OR = 1.06, 95% CI: 0.69-1.63, p = 0.791). None of the investigated genetic variants exhibited statistically discernible protective or risk effects on predisposition to the disease. The T/T genotype was found to have a neutral effect on susceptibility risk within this cohort. The C/C genotype was absent in the control group and occurred at a vanishingly low frequency in patients (2.9%), precluding any definitive assessment of its potential impact. The negligible disparity in T allele frequency between controls (55.1%) and patients (53.7%) provides additional evidence against a substantive role for this polymorphism in disease etiology in the studied population. (Table.2) IL-12 (1188 A/C) Polymorphism The A/C genotype demonstrated the highest frequency in both cohorts, present in 82.4% of patients and 88.2% of controls. Conversely, the C/C genotype was more common in the patient group (10.3%) than among controls (7.4%). The A/A genotype was rare in both groups, though slightly more common in patients (7.4%) than controls (4.4%). The C and A alleles were equally distributed between groups, with identical frequencies of 51.5% and 48.5%, respectively. Analysis of the data showed no statistically discernible differences in the distribution of either genotypes ( p = 0.722) or alleles ( p = 1.000) when comparing the patient and control groups. Furthermore, under a codominant inheritance model, the comparison of the C/C genotype against the A/A reference genotype revealed no discernible correlation with disease status (OR = 0.83, p = 0.830). Under a recessive genetic model (C/C versus A/C + A/A), the analysis suggested a non-significant increase in risk (OR = 1.43, 95% CI: 0.42–4.87, p = 0.567). Conversely, the allelic comparison (C versus A) showed no association with susceptibility (OR = 1.00, 95% CI: 0.64–1.56, p = 1.000). Although the C/C genotype appeared more frequently in patients and showed a slight non-significant trend toward risk elevation in the recessive model, the wide confidence intervals crossing unity and the lack of statistical significance in all genetic models indicate that this observation cannot be considered conclusive. Similarly, the A/A genotype, despite its slightly higher frequency in patients, does not demonstrate a statistically meaningful association with disease risk. The equal distribution of C and A alleles further supports the absence of a significant allelic effect. Thus, while the C/C genotype may suggest a non-significant risk trend, there is no robust evidence to classify it as a risk or protective factor. (Table.2) Discussion This investigation assessed the relationship between specific functional gene variants IL-10 (-1082G>A, -819C>T) and IL-12B (+1188A>C) and the predisposition to H. pylori infection within a case-control population from Iran. The core outcome of our analysis was the absence of a statistically significant link between the tested genetic variants and susceptibility to H. pylori . A non-significant trend was noted for the IL-10 (-1082) A/A genotype, which was more common in patients (32.4%) than controls (20.6%), yielding an odds ratio of 3.45 (95% CI: 0.29–41.36). Our findings add a nuanced layer to the intricate tapestry of immunogenetic research concerning H. pylori . The data reveal a pattern of both concordance and discordance with the existing literature. Specifically, the lack of a significant correlation between IL-12 genetic variants and susceptibility to infection corroborates the null findings of Petkevicius et al.,(23) regarding the IL-12 p40 polymorphism and peptic ulcer disease. This collective evidence posits that variations in the IL-12B gene are unlikely to be a major determinant in the initial pathogenic cascade following H. pylori exposure. Nevertheless, our findings diverge from a segment of the international literature. For example, research conducted by Örenay et al. within an Indian population established a significant association of the IL-12B rs3212227 polymorphism with gastric carcinoma, the premalignant condition of intestinal metaplasia, and H. pylori infection.(24). Correspondingly, research by Miley Cárdenas et al. identified statistically significant links between specific IL-10 gene variants and the development of gastric carcinoma in a Brazilian population. (25). In an Iraqi cohort, the research of Al-Shuwaikh et al. established a significant correlation between specific polymorphisms in the IL-10 promoter region and the development of gastric pathology subsequent to H. pylori infection (26). These discrepancies highlight the substantial ethnic-specific variations in genetic susceptibility to H. pylori -related diseases and suggest that these polymorphisms may exert more pronounced effects in the carcinogenic evolution of infection rather than in initial susceptibility. The biological plausibility of our observations is supported by functional studies. Martínez-Campos et al.(27) revealed that certain inherited variations in the IL-10 gene are associated with a concomitant rise in constitutive interleukin-10 expression and a greater propensity for H. pylori colonization. Although we did not measure cytokine levels, the absence of significant genetic association in our cohort may suggest that the functional impact of these specific SNPs is modulated by other genetic or environmental factors within our population. A key methodological finding was that the control group demonstrated significant deviations from HWE across all genotyped polymorphisms. While HWE deviation is often considered a quality control concern, in our study it may reflect the rigorous selection criteria applied to our control group, which consisted of individuals strictly confirmed to be free of H. pylori infection through both histopathological and serological methods. This stringent selection process may have identified a genetically distinct subpopulation that does not fully represent the general population's genetic structure. Several constraints warrant consideration in the evaluation of our findings. The study's statistical power, particularly for stratified analyses, was potentially constrained by the limited cohort size, which may have obscured genetic associations of smaller magnitude. Second, the observed deviation from HWE in our control group, while potentially explained by our rigorous selection criteria, suggests caution in generalizing these findings to the broader population. Third, we did not measure actual cytokine expression levels, which would have provided valuable functional validation of the genetic associations. Fourth, we did not analyze H. pylori virulence factors (such as CagA and VacA status), which might interact with host genetic factors in determining infection outcomes. The geographically and ethnically defined cohort from Hamadan, Iran, central to this investigation, means that the extrapolation of our results to other populations should be approached with caution. Notwithstanding its limitations, this research offers crucial insights into the multifaceted interplay between host immunogenetics and susceptibility to H. pylori within a Middle Eastern cohort. The divergent findings between our study and international research underscore the critical importance of considering population-specific genetic backgrounds and disease endpoints when evaluating the contribution of immunogenetic factors to H. pylori -related outcomes. Conclusion This investigation concludes that the analyzed polymorphisms in the IL-10 and IL-12 genes are not significantly associated with an increased or decreased risk of acquiring H. pylori infection in our specific participant sample from Iran. The divergent findings between studies highlight the ethnic-specific nature of genetic associations and suggest that these polymorphisms may be more relevant for disease progression than initial infection susceptibility. Future research should include larger, multi-center studies with adequate power to detect modest genetic effects, incorporate functional measures of cytokine expression, analyze bacterial virulence factors, and employ haplotype-based approaches rather than single SNP analyses. Research of this breadth is crucial for unraveling the intricate molecular and immunological dynamics that govern the diverse clinical manifestations of H. pylori pathogenesis in heterogeneous human groups. Abbreviations H. pylori : Helicobacter pylori IL-10: Interleukin-10 IL-12: Interleukin-12 Th1: T helper 1 cells Th2: T helper 2 cells IFN-γ: Interferon-gamma TNF-α: Tumor Necrosis Factor-alpha IL-1: Interleukin-1 IL-6: Interleukin-6 NK cells: Natural Killer cells APCs: Antigen-Presenting Cells SNPs: Single Nucleotide Polymorphisms ARMS-PCR: Amplification Refractory Mutation System - Polymerase Chain Reaction Declarations Ethics approval and consent to participate The ethics committee of the Hamadan University of Medical Sciences approved the study protocol (Ethical approval code: IR.UMSHA.REC.1402.774). Ethical Review Board approved written consent taken from all the participants. Clinical Trial Not applicable. Consent for publication Not applicable. Availability of data and material The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The Vice-chancellor of Research and Technology, Hamadan University of Medical Sciences, Hamadan, Iran supported financially the study (Grant Number: 1402121511033). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Author contributions: SK designed and supervised the study. MYA, MM, performed data interpretation. SK, SM, MM, ARH, EA, FD, PK were responsible for data collection and doing experiments SK performed clinical examination and interpreted the results. SK analyzing the statistical results of the study. SK, PK, MAY, AS, interpretation of data. All authors read and approved the final manuscript. Acknowledgements The authors would like to acknowledge Vice-chancellor of Research and Technology, Hamadan University of Medical Sciences, Hamadan, Iran, and microbiology laboratory staffs. References Fagoonee S, Pellicano R. 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Petkevicius V, Salteniene V, Juzenas S, Wex T, Link A, Leja M, et al. Polymorphisms of microRNA target genes IL12B, INSR, CCND1 and IL10 in gastric cancer. World Journal of Gastroenterology. 2017;23(19):3480. Orenay-Boyacioglu S, Kasap E, Yuceyar H, Korkmaz M. Association of interleukin 12B rs3212227 polymorphism with gastric cancer, intestinal metaplasia, and helicobacter pylori infection. Genetika. 2020;52(1):115-26. Cárdenas DM, Sánchez AC, Rosas DA, Rivero E, Paparoni MD, Cruz MA, et al. Preliminary analysis of single-nucleotide polymorphisms in IL-10, IL-4, and IL-4Rα genes and profile of circulating cytokines in patients with gastric Cancer. BMC gastroenterology. 2018;18(1):184. Salih AM, Shaheed OM. Association between IL-10 Gene Polymorphisms in Helicobacter pylori infection and Gastric Illness in Among Iraq Population. Martínez-Campos C, Torres-Poveda K, Camorlinga-Ponce M, Flores-Luna L, Maldonado-Bernal C, Madrid-Marina V, et al. Polymorphisms in IL-10 and TGF-β gene promoter are associated with lower risk to gastric cancer in a Mexican population. BMC cancer. 2019;19(1):453. Tables Table 1: Distribution of demographic and clinical characteristics in case and control groups. Variable Category Patients (%) Controls (%) p -value Gender Male 51 (75.0) 50 (73.5) 1.000 Female 17 (25) 18 (26.5) Smoking Status Smoker 39 (57.4) 17 (25.0) < 0.001 Non-Smoker 29 (42.6) 51 (75.0) Family History Positive 22 (32.4) 0 (0.0) < 0.001 Negative 46 (67.6) 68 (100.0) Education Level Diploma 26 (38.2) 30 (44.1) 0.421 Undergraduate 27 (39.7) 21 (30.9) Bachelor 12 (17.6) 11 (16.2) Master 3 (4.4) 6 (8.8) Drinking Status Drinker 5 (7.4) 1 (1.5) 0.211 Non-Drinker 63 (92.6) 67 (98.5) Table 2: Comprehensive Genetic Association Analysis of IL-10 and IL-12 Polymorphisms SNP Model Genotype Patients no (%) Controls no (%) OR (95% CI) p -value IL-10 (-1082G/A) Codominant G/G 1 (1.5%) 2 (2.9%) Ref. – A/G 45 (66.2%) 52 (76.5%) 1.73 (0.15–20.08) 0.662 A/A 22 (32.4%) 14 (20.6%) 3.45 (0.29–41.36) 0.327 Dominant A/G + A/A 67 (98.5%) 66 (97.1%) 1.81 (0.16–20.73) 0.634 Recessive A/A 22 (32.4%) 14 (20.6%) 1.81 (0.85–3.87) 0.122 Allelic A 89 (65.4%) 80 (58.8%) 1.33 (0.83–2.14) 0.232 G 47 (34.6%) 56 (41.2%) IL-10 (-819 C/T) Codominant C/C 2 (2.9%) 0 (0.0%) Ref. – C/T 59 (86.8%) 61 (89.7%) 0.97 (0.13–7.10) 0.974 T/T 7 (10.3%) 7 (10.3%) 1.00 (0.14–7.28) 1.000 Dominant C/T + T/T 66 (97.1%) 68 (100%) 0.98 (0.14–6.94) 0.984 Recessive T/T 7 (10.3%) 7 (10.3%) 1.00 (0.33–3.02) 1.000 Allelic T 73 (53.7%) 75 (55.1%) 1.06 (0.69–1.63) 0.791 C 63 (46.3%) 61 (44.9%) IL-12 (+1188 A/C) Codominant A/A 5 (7.4%) 3 (4.4%) Ref. – A/C 56 (82.4%) 60 (88.2%) 0.56 (0.13–2.41) 0.438 C/C 7 (10.3%) 5 (7.4%) 0.83 (0.16–4.36) 0.830 Dominant A/C + C/C 63 (92.6%) 65 (95.6%) 0.60 (0.15–2.45) 0.477 Recessive C/C 7 (10.3%) 5 (7.4%) 1.43 (0.42–4.87) 0.567 Allelic C 70 (51.5%) 70 (51.5%) 1.00 (0.64–1.56) 1.000 A 66 (48.5%) 66 (48.5%) Additional Declarations No competing interests reported. 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10:11:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":898909,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7832834/v1/bb080f8e-dabb-4635-8fb2-6939d2cc8d53.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of polymorphism of coding genes IL-10 and IL-12 with the risk of Helicobacter pylori infection","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eHelicobacter pylori (H. pylori) is a spiral-shaped, microaerophilic pathogen with a distinct affinity for colonizing the human gastric mucosal lining\u003c/em\u003e (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This bacterium is an established causative agent for a range of upper gastrointestinal disorders, from chronic gastritis and peptic ulcers to more severe outcomes such as gastric cancer and mucosa-associated lymphoid tissue (MALT) lymphoma (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The colonization and long-term survival of \u003cem\u003eH. pylori\u003c/em\u003e within the stomach triggers a persistent inflammatory state, which is characterized histopathologically by the infiltration of neutrophils, lymphocytes, and plasma cells into the gastric mucosa.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA significant diagnostic challenge arises from the fact that a majority of infected individuals remain asymptomatic carriers (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Global seroprevalence studies indicate that infection rates vary substantially, ranging from 0.2% to 1.7% in some populations, to approximately 50% in many developed nations (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Notably, regional disparities in prevalence are also observed within individual countries, suggesting the influence of geographic and socioeconomic factors.\u003c/p\u003e\u003cp\u003eThe pathogenesis of \u003cem\u003eH. pylori\u003c/em\u003e is multifactorial, mediated through an array of virulence mechanisms. These include the modulation of gastric acid secretion, induction of epithelial cell hyperproliferation and elongation, disruption of intercellular junctions, and the elicitation of both systemic and mucosal antibody responses (IgG and IgA) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The ensuing immune activation involves a complex cytokine network orchestrated by cells of both the innate and adaptive immune systems. Evidence underscores that dysregulated cytokine responses can drive the progression from chronic inflammation to precancerous lesions and ultimately to gastric malignancy (\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFollowing infection with \u003cem\u003eH. pylori\u003c/em\u003e, dendritic cells (DCs) in the gastric mucosa become activated. This activation triggers them to release interleukin-12 (IL-12), which subsequently directs na\u0026iuml;ve CD4⁺ T cells to differentiate into a T helper 1 (Th1) subtype. These newly polarized Th1 cells are defined by their secretion of specific pro-inflammatory cytokines, including interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), interleukin-1 (IL-1), and interleukin-6 (IL-6). (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This Th1-dominant response, governed by the transcription factors T-bet and STAT4, is primarily aimed at bacterial clearance. However, in a subset of individuals, this robust inflammatory response becomes chronic and contributes to tissue damage and carcinogenesis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe involvement of the Th2 immune response in \u003cem\u003eH. pylori\u003c/em\u003e infection remains poorly understood. Although this pathway is typically essential for eliminating extracellular pathogens, its contribution in this particular context appears to be limited. Th\u003csub\u003e2\u003c/sub\u003e activity is associated with the generation of IgG1 antibodies, whereas the Th1 response augments overall IgG2 levels via IL-12 and IFN-γ (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFunctioning as a critical regulator of immunity, Interleukin-10 (IL-10) exerts powerful anti-inflammatory effects. It is synthesized by numerous immune cell types such as macrophages, lymphocytes, dendritic cells, and mast cells. The cytokine operates by inhibiting macrophage activation, restraining the release of pro-inflammatory signals from Th1 cells, and fine-tuning the functions of NK cells, antigen-presenting cells (APCs), and mast cells (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The gene encoding IL-10 is located on chromosome 1, and functional polymorphisms within its promoter region (notably at positions \u0026minus;\u0026thinsp;1082 G\u0026thinsp;\u0026gt;\u0026thinsp;A, -819 C\u0026thinsp;\u0026gt;\u0026thinsp;T (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)) have been linked to altered cytokine expression levels and an increased risk of gastric cancer. Interindividual variation in IL-10 production capacity following immunogenic stimuli (e.g., LPS) is well-documented (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSimilarly, IL-12 is a key pro-inflammatory cytokine central to protective immunity against intracellular pathogens, yet it also influences infection persistence and disease severity (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Single nucleotide polymorphisms (SNPs) in cytokine genes are among the most common sources of genetic variation in humans and can lead to significant differences in cytokine production capacity across different ethnic and racial groups (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). These genetic variations may predispose individuals to inflammatory conditions, including those related to \u003cem\u003eH. pylori\u003c/em\u003e (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis research seeks to determine if a correlation exists between specific IL-10 and IL-12 gene variants and an individual's susceptibility to \u003cem\u003eH. pylori\u003c/em\u003e infection, by analyzing and contrasting genotype and allele frequencies in infected individuals versus a healthy control group.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design and Participants\u003c/strong\u003e\u003cbr\u003eThis case-control investigation enrolled 68 individuals (51 male, 17 female) with a confirmed \u003cem\u003eH. pylori\u003c/em\u003e infection. Participants, who had a mean age of 43.65 \u0026plusmn; 16.06 years (range: 19-75), were recruited from the gastroenterology departments of Shahid Beheshti Hospital and Imam Reza Hospital in Kabadrahang, Iran, between December 2023 and August 2024. A specialist physician established the diagnosis based on clinical presentation and positive laboratory tests. Individuals with pre-existing inflammatory, autoimmune, metabolic, or chronic infectious diseases were excluded from the study.\u003c/p\u003e\n\u003cp\u003eThe control cohort for this study comprised 68 healthy individuals (48 males, 20 females; aged 20\u0026ndash;78 years), who were meticulously matched to the patient group based on key demographic factors including age, sex, ethnicity, and geographical residence. All control subjects were screened to ensure an absence of any personal or familial history of \u003cem\u003eH. pylori\u003c/em\u003e infection or associated gastric disorders. All control participants were confirmed to be free of infection via negative pathological biopsy and serological testing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Considerations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this research was granted by the Research Ethics Committee of Hamadan University of Medical Sciences (Ethics Code: IR.UMSHA.REC.1402.774). Prior to enrollment, every participant provided written informed consent following a comprehensive briefing on the study\u0026apos;s objectives and methodology. The anonymity and confidentiality of all personal and clinical data were rigorously upheld for the duration of the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of \u003cem\u003eH. pylori\u003c/em\u003e Infection Status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA multi-method diagnostic approach, incorporating both invasive and serological techniques, was employed to accurately identify \u003cem\u003eH. pylori\u003c/em\u003e infection. As part of this protocol, two biopsy samples were obtained from the gastric antrum of each subject during upper gastrointestinal endoscopy. One of these specimens was promptly analyzed using a rapid urease test (CLOtest\u0026reg;, Delta West, Australia) for the preliminary detection of bacterial urease activity. A positive result was defined by the development of a pink or red coloration within a 24-hour observation period.\u003c/p\u003e\n\u003cp\u003eSimultaneously, venous blood samples (approximately 2 ml) were drawn from all participants both the patient and the meticulously matched control groups into EDTA-containing vacuum tubes for subsequent serological and molecular analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSerological confirmation of the infection was achieved by quantifying anti-\u003cem\u003eH. pylori\u003c/em\u003e IgG antibody levels. For this purpose, we employed a validated, commercially sourced ELISA kit (Sigma-Aldrich, Cat. no. RAB0242), meticulously adhering to the manufacturer\u0026apos;s instructions. To guarantee analytical reproducibility, every sample was tested in duplicate. An antibody titer exceeding 90 ng/ml was defined as seropositive, confirming active \u003cem\u003eH. pylori\u003c/em\u003e infection for inclusion in the patient group. Conversely, individuals in the control group were required to yield negative results from both the rapid urease test and the ELISA (titer \u0026lt; 90 ng/ml), ensuring they were unequivocally infection-free.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA Extraction and Genotyping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal genomic DNA was isolated from the anti-coagulated whole blood of all study subjects employing a commercial extraction kit (Sina-Clon, Iran) per the supplier\u0026apos;s guidelines. The resulting DNA was then assessed for concentration and purity using a NanoDrop\u0026trade; 2000 spectrophotometer (Thermo Fisher Scientific, USA). Following quantification, all samples were standardized to a uniform working concentration of 50 ng/\u0026mu;L to facilitate downstream genetic analyses.\u003c/p\u003e\n\u003cp\u003eThe IL-10 (-1082G\u0026gt;A, -819C\u0026gt;T) and IL-12 (+1188A/C) polymorphisms were genotyped employing the Amplification Refractory Mutation System (ARMS)-PCR technique.\u003c/p\u003e\n\u003cp\u003eGenotyping for the IL-10 promoter polymorphisms (-1082G\u0026gt;A and -819C\u0026gt;T) was performed using established primer sequences and cycling conditions, as previously described by reference (21) . The polymerase chain reaction (PCR) was carried out using a commercial pre-mixed master mix (PCR 2X Taq Premix Mastermix, Pars Tous Co., Iran). Each 20 \u0026micro;L reaction mixture contained approximately 100 ng of genomic DNA template, along with 1 \u0026micro;L of each forward and reverse primer (10 pmol/\u0026micro;L). Amplification was executed on a C 1000 Touch Thermal Cycler (Bio-Rad, USA) with the following profile: an initial denaturation step at 95\u0026deg;C for 4 minutes; 25 cycles of denaturation at 95\u0026deg;C for 20 seconds, annealing at 56\u0026deg;C for the -1082G\u0026gt;A and 58\u0026deg;C for the -819C\u0026gt;T variant for 20 seconds, and extension at 72\u0026deg;C for 30 seconds; culminating in a final extension at 72\u0026deg;C for 5 minutes. Concurrently, the Beta-2 Microglobulin (B2M) gene was co-amplified as an internal control under identical conditions, utilizing a specific annealing temperature of 66\u0026deg;C. To ensure the thorough elongation of all PCR products, a final synthesis phase was implemented at 72\u0026deg;C for a duration of 10 minutes.\u003c/p\u003e\n\u003cp\u003eThe amplification of the IL-12 (+1188A/C) locus was performed using a thermal cycling protocol initiated by a 3-minute denaturation at 94\u0026deg;C. This was followed by 35 cycles, each comprising denaturation at 94\u0026deg;C for 30 seconds, primer annealing at 65\u0026deg;C for 45 seconds, and strand extension at 72\u0026deg;C for 45 seconds. The process concluded with a final elongation step at 72\u0026deg;C for 5 minutes to ensure the complete amplification of all target fragments, as per the established methodology(22).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubsequently, the PCR amplicons were resolved by electrophoresis on a 2% agarose gel, which was pre-stained with SYBR Safe DNA gel stain at a concentration of 0.5 \u0026micro;g/mL. The resulting DNA bands were then visualized and documented under ultraviolet light using a UV transillumination system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics for categorical data are presented as counts and percentages, while continuous data are expressed as mean \u0026plusmn; standard deviation. Intergroup comparisons for age, which followed a normal distribution, were conducted using an independent samples t-test. For continuous variables deviating from normality, the non-parametric Mann-Whitney U test was applied. Differences in genotype and allele distributions between the case and control cohorts were evaluated by applying multivariate logistic regression analysis. This analysis generated odds ratios (ORs) and corresponding 95% confidence intervals (CIs) across additive, dominant, and recessive inheritance models. The genotype distribution within the control group was tested for conformity to Hardy-Weinberg equilibrium (HWE) using a Chi-square (\u0026chi;\u0026sup2;) goodness-of-fit test. The entire statistical analysis was executed with SPSS software (Version 16), and statistical significance was defined a priori as a two-tailed \u003cem\u003ep\u003c/em\u003e-value of less than 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline Characteristics of the Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis case-control analysis comprised 68 patients and an equal number of matched controls. The demographic composition of both cohorts is detailed in Table 1. The mean age (± standard deviation) was 51.96 ± 12.28 years in the patient cohort and 49.63 ± 13.87 years in the control group. The gender distribution was comparable between the two groups, with males constituting 75.0% (n=51) of the patient group and 73.5% (n=50) of the controls.\u003c/p\u003e\n\u003cp\u003eStatistical evaluation of lifestyle factors identified significant risk associations. The prevalence of smoking was markedly higher in patients (57.4%) compared to controls (25.0%), a difference that was highly statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Similarly, a positive family history was exclusively reported within the patient group, affecting 32.4% of individuals (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). In contrast, no significant differences were observed between the groups for the variables of education level (\u003cem\u003ep\u003c/em\u003e = 0.421) or alcohol consumption (p = 0.211). (Table.1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic Association Analysis\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThis case-control investigation was designed to evaluate the potential relationship between susceptibility to the disease and specific genetic variations in the IL-10 (-1082 G/A, -819 C/T) and IL-12 (+1188 A/C) genes. The analysis, which included 68 matched patient-control pairs, yielded the following detailed statistical outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-10 (-1082 G/A) Polymorphism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe heterozygous A/G genotype was the most common variant in both the patient and control cohorts, with frequencies of 66.2% and 76.5%, respectively. A higher prevalence of the homozygous A/A genotype was observed in patients (32.4%) relative to controls (20.6%). In contrast, the homozygous G/G genotype was infrequent, occurring in only 1.5% of patients and 2.9% of controls. Correspondingly, the A allele was more common in the patient group (65.4%) than in the control group (58.8%).\u003c/p\u003e\n\u003cp\u003eAnalysis of the genetic data revealed no statistically discernible differences in the distribution of genotypes (\u003cem\u003ep\u003c/em\u003e = 0.200) or alleles (\u003cem\u003ep\u003c/em\u003e = 0.232) between the patient and control cohorts. Evaluation using a codominant inheritance model showed a non-significant trend toward increased risk for individuals with the A/A genotype (OR = 3.45, 95% CI: 0.29–41.36, \u003cem\u003ep\u003c/em\u003e = 0.327) when referenced against the G/G genotype. This pattern of elevated, yet non-significant, risk was similarly observed under a recessive model (A/A vs. A/G+G/G; OR = 1.81, 95% CI: 0.85–3.87, \u003cem\u003ep\u003c/em\u003e = 0.122). The allelic comparison (A vs. G) also failed to attain statistical significance (OR = 1.33, 95% CI: 0.83–2.14, \u003cem\u003ep\u003c/em\u003e = 0.232). (Table.2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-10 (-819 C/T) Polymorphism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u0026nbsp;The C/T genotype was highly prevalent in both patients (86.8%) and controls (89.7%), indicating it is the most common genotype in the studied population. The T/T genotype frequency was identical in both groups (10.3%), while the C/C genotype was absent in controls (0%) and observed in only 2.9% of patients. The T allele demonstrated a marginally higher frequency in controls (55.1%) than in patients (53.7%), with only a minimal disparity between the groups.\u003c/p\u003e\n\u003cp\u003eThe analysis of genetic distributions showed no statistically discernible differences between the patient and control groups, either for overall genotype (\u003cem\u003ep\u003c/em\u003e = 0.243) or allele frequencies (\u003cem\u003ep\u003c/em\u003e = 0.791). Under a codominant inheritance pattern, the comparison of the T/T genotype against the C/C reference group showed no association with disease status (OR = 1.00, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 1.000). This null finding was consistent across other genetic models. A recessive model (T/T vs. C/T + C/C) also demonstrated no effect (OR = 1.00, 95% CI: 0.33-3.02, \u003cem\u003ep\u003c/em\u003e = 1.000), as did an allelic model comparing the T allele to the C allele (OR = 1.06, 95% CI: 0.69-1.63, \u003cem\u003ep\u003c/em\u003e = 0.791).\u003c/p\u003e\n\u003cp\u003eNone of the investigated genetic variants exhibited statistically discernible protective or risk effects on predisposition to the disease. The T/T genotype was found to have a neutral effect on susceptibility risk within this cohort. The C/C genotype was absent in the control group and occurred at a vanishingly low frequency in patients (2.9%), precluding any definitive assessment of its potential impact. The negligible disparity in T allele frequency between controls (55.1%) and patients (53.7%) provides additional evidence against a substantive role for this polymorphism in disease etiology in the studied population. (Table.2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-12 (1188 A/C) Polymorphism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u0026nbsp;The A/C genotype demonstrated the highest frequency in both cohorts, present in 82.4% of patients and 88.2% of controls. Conversely, the C/C genotype was more common in the patient group (10.3%) than among controls (7.4%).\u0026nbsp;The A/A genotype was rare in both groups, though slightly more common in patients (7.4%) than controls (4.4%). The C and A alleles were equally distributed between groups, with identical frequencies of 51.5% and 48.5%, respectively. Analysis of the data showed no statistically discernible differences in the distribution of either genotypes (\u003cem\u003ep\u003c/em\u003e = 0.722) or alleles (\u003cem\u003ep\u003c/em\u003e = 1.000) when comparing the patient and control groups. Furthermore, under a codominant inheritance model, the comparison of the C/C genotype against the A/A reference genotype revealed no discernible correlation with disease status (OR = 0.83, \u003cem\u003ep\u003c/em\u003e = 0.830).\u0026nbsp;Under a recessive genetic model (C/C versus A/C + A/A), the analysis suggested a non-significant increase in risk (OR = 1.43, 95% CI: 0.42–4.87, \u003cem\u003ep\u003c/em\u003e = 0.567). Conversely, the allelic comparison (C versus A) showed no association with susceptibility (OR = 1.00, 95% CI: 0.64–1.56, \u003cem\u003ep\u003c/em\u003e = 1.000).\u0026nbsp;Although the C/C genotype appeared more frequently in patients and showed a slight non-significant trend toward risk elevation in the recessive model, the wide confidence intervals crossing unity and the lack of statistical significance in all genetic models indicate that this observation cannot be considered conclusive. Similarly, the A/A genotype, despite its slightly higher frequency in patients, does not demonstrate a statistically meaningful association with disease risk. The equal distribution of C and A alleles further supports the absence of a significant allelic effect. Thus, while the C/C genotype may suggest a non-significant risk trend, there is no robust evidence to classify it as a risk or protective factor. (Table.2)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis investigation assessed the relationship between specific functional gene variants\u0026nbsp;IL-10 (-1082G\u0026gt;A, -819C\u0026gt;T) and IL-12B (+1188A\u0026gt;C)\u0026nbsp;and the predisposition to \u003cem\u003eH. pylori\u003c/em\u003e infection within a case-control population from Iran.\u0026nbsp; The core outcome of our analysis was the absence of a statistically significant link between the tested genetic variants and susceptibility to \u003cem\u003eH. pylori\u003c/em\u003e. A non-significant trend was noted for the IL-10 (-1082) A/A genotype, which was more common in patients (32.4%) than controls (20.6%), yielding an odds ratio of 3.45 (95% CI: 0.29–41.36).\u003c/p\u003e\n\u003cp\u003eOur findings add a nuanced layer to the intricate tapestry of immunogenetic research concerning \u003cem\u003eH. pylori\u003c/em\u003e. The data reveal a pattern of both concordance and discordance with the existing literature. Specifically, the lack of a significant correlation between IL-12 genetic variants and susceptibility to infection corroborates the null findings of Petkevicius et al.,(23)\u0026nbsp; regarding the IL-12 p40 polymorphism and peptic ulcer disease. This collective evidence posits that variations in the IL-12B gene are unlikely to be a major determinant in the initial pathogenic cascade following \u003cem\u003eH. pylori\u003c/em\u003e exposure.\u003c/p\u003e\n\u003cp\u003eNevertheless, our findings diverge from a segment of the international literature. For example, research conducted by Örenay et al. within an Indian population established a significant association of the IL-12B rs3212227 polymorphism with gastric carcinoma, the premalignant condition of intestinal metaplasia, and \u003cem\u003eH. pylori\u003c/em\u003e infection.(24). Correspondingly, research by Miley Cárdenas et al. identified statistically significant links between specific IL-10 gene variants and the development of gastric carcinoma in a Brazilian population. (25). In an Iraqi cohort, the research of Al-Shuwaikh et al. established a significant correlation between specific polymorphisms in the IL-10 promoter region and the development of gastric pathology subsequent to \u003cem\u003eH. pylori\u003c/em\u003e infection (26). These discrepancies highlight the substantial ethnic-specific variations in genetic susceptibility to \u003cem\u003eH.\u003c/em\u003e \u003cem\u003epylori\u003c/em\u003e-related diseases and suggest that these polymorphisms may exert more pronounced effects in the carcinogenic evolution of infection rather than in initial susceptibility.\u003c/p\u003e\n\u003cp\u003eThe biological plausibility of our observations is supported by functional studies. Martínez-Campos et al.(27) revealed that certain inherited variations in the IL-10 gene are associated with a concomitant rise in constitutive interleukin-10 expression and a greater propensity for \u003cem\u003eH. pylori\u003c/em\u003e colonization. Although we did not measure cytokine levels, the absence of significant genetic association in our cohort may suggest that the functional impact of these specific SNPs is modulated by other genetic or environmental factors within our population.\u003c/p\u003e\n\u003cp\u003eA key methodological finding was that the control group demonstrated significant deviations from HWE across all genotyped polymorphisms. While HWE deviation is often considered a quality control concern, in our study it may reflect the rigorous selection criteria applied to our control group, which consisted of individuals strictly confirmed to be free of \u003cem\u003eH. pylori\u003c/em\u003e infection through both histopathological and serological methods. This stringent selection process may have identified a genetically distinct subpopulation that does not fully represent the general population's genetic structure.\u003c/p\u003e\n\u003cp\u003eSeveral constraints warrant consideration in the evaluation of our findings. The study's statistical power, particularly for stratified analyses, was potentially constrained by the limited cohort size, which may have obscured genetic associations of smaller magnitude. Second, the observed deviation from HWE in our control group, while potentially explained by our rigorous selection criteria, suggests caution in generalizing these findings to the broader population. Third, we did not measure actual cytokine expression levels, which would have provided valuable functional validation of the genetic associations. Fourth, we did not analyze \u003cem\u003eH. pylori\u003c/em\u003e virulence factors (such as CagA and VacA status), which might interact with host genetic factors in determining infection outcomes. The geographically and ethnically defined cohort from Hamadan, Iran, central to this investigation, means that the extrapolation of our results to other populations should be approached with caution.\u003c/p\u003e\n\u003cp\u003eNotwithstanding its limitations, this research offers crucial insights into the multifaceted interplay between host immunogenetics and susceptibility to \u003cem\u003eH. pylori\u003c/em\u003e within a Middle Eastern cohort. The divergent findings between our study and international research underscore the critical importance of considering population-specific genetic backgrounds and disease endpoints when evaluating the contribution of immunogenetic factors to \u003cem\u003eH. pylori\u003c/em\u003e-related outcomes.\u003c/p\u003e"},{"header":"Conclusion ","content":"\u003cp\u003eThis investigation concludes that the analyzed polymorphisms in the IL-10 and IL-12 genes are not significantly associated with an increased or decreased risk of acquiring \u003cem\u003eH. pylori\u003c/em\u003e infection in our specific participant sample from Iran. The divergent findings between studies highlight the ethnic-specific nature of genetic associations and suggest that these polymorphisms may be more relevant for disease progression than initial infection susceptibility. Future research should include larger, multi-center studies with adequate power to detect modest genetic effects, incorporate functional measures of cytokine expression, analyze bacterial virulence factors, and employ haplotype-based approaches rather than single SNP analyses. Research of this breadth is crucial for unraveling the intricate molecular and immunological dynamics that govern the diverse clinical manifestations of \u003cem\u003eH. pylori\u003c/em\u003e pathogenesis in heterogeneous human groups.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e: \u003cem\u003eHelicobacter pylori\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIL-10: Interleukin-10\u003c/p\u003e\n\u003cp\u003eIL-12: Interleukin-12\u003c/p\u003e\n\u003cp\u003eTh1: T helper 1 cells\u003c/p\u003e\n\u003cp\u003eTh2: T helper 2 cells\u003c/p\u003e\n\u003cp\u003eIFN-γ: Interferon-gamma\u003c/p\u003e\n\u003cp\u003eTNF-α: Tumor Necrosis Factor-alpha\u003c/p\u003e\n\u003cp\u003eIL-1: Interleukin-1\u003c/p\u003e\n\u003cp\u003eIL-6: Interleukin-6\u003c/p\u003e\n\u003cp\u003eNK cells: Natural Killer cells\u003c/p\u003e\n\u003cp\u003eAPCs: Antigen-Presenting Cells\u003c/p\u003e\n\u003cp\u003eSNPs: Single Nucleotide Polymorphisms\u003c/p\u003e\n\u003cp\u003eARMS-PCR: Amplification Refractory Mutation System - Polymerase Chain Reaction\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethics committee of the Hamadan University of Medical Sciences approved the study protocol (Ethical approval code: IR.UMSHA.REC.1402.774). Ethical Review Board approved written consent taken from all the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Vice-chancellor of Research and Technology, Hamadan University of Medical Sciences, Hamadan, Iran supported financially the study (Grant Number: 1402121511033). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSK designed and supervised the study.\u003c/p\u003e\n\u003cp\u003eMYA, MM, performed data interpretation.\u003c/p\u003e\n\u003cp\u003eSK, SM, MM, ARH, EA, FD, PK were responsible for data collection and doing experiments\u003c/p\u003e\n\u003cp\u003eSK performed clinical examination and interpreted the results.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;SK analyzing the statistical results of the study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;SK, PK, MAY, AS, interpretation of data.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge Vice-chancellor of Research and Technology, Hamadan University of Medical Sciences, Hamadan, Iran, and microbiology laboratory staffs.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFagoonee S, Pellicano R. 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Polymorphisms of microRNA target genes IL12B, INSR, CCND1 and IL10 in gastric cancer. World Journal of Gastroenterology. 2017;23(19):3480.\u003c/li\u003e\n \u003cli\u003eOrenay-Boyacioglu S, Kasap E, Yuceyar H, Korkmaz M. Association of interleukin 12B rs3212227 polymorphism with gastric cancer, intestinal metaplasia, and helicobacter pylori infection. Genetika. 2020;52(1):115-26.\u003c/li\u003e\n \u003cli\u003eC\u0026aacute;rdenas DM, S\u0026aacute;nchez AC, Rosas DA, Rivero E, Paparoni MD, Cruz MA, et al. Preliminary analysis of single-nucleotide polymorphisms in IL-10, IL-4, and IL-4R\u0026alpha; genes and profile of circulating cytokines in patients with gastric Cancer. BMC gastroenterology. 2018;18(1):184.\u003c/li\u003e\n \u003cli\u003eSalih AM, Shaheed OM. Association between IL-10 Gene Polymorphisms in Helicobacter pylori infection and Gastric Illness in Among Iraq Population.\u003c/li\u003e\n \u003cli\u003eMart\u0026iacute;nez-Campos C, Torres-Poveda K, Camorlinga-Ponce M, Flores-Luna L, Maldonado-Bernal C, Madrid-Marina V, et al. Polymorphisms in IL-10 and TGF-\u0026beta; gene promoter are associated with lower risk to gastric cancer in a Mexican population. BMC cancer. 2019;19(1):453.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDistribution of demographic and clinical characteristics in case and control groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eControls (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50 (73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSmoker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNon-Smoker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily History\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46 (67.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUndergraduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 (30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBachelor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDrinker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNon-Drinker\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63 (92.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67 (98.5)\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Comprehensive Genetic Association Analysis of IL-10 and IL-12 Polymorphisms\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients no (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eControls no (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIL-10 (-1082G/A)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCodominant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eG/G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 (66.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (76.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.73 (0.15\u0026ndash;20.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.45 (0.29\u0026ndash;41.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDominant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/G + A/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67 (98.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66 (97.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.81 (0.16\u0026ndash;20.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRecessive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.81 (0.85\u0026ndash;3.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAllelic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89 (65.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80 (58.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.33 (0.83\u0026ndash;2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47 (34.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 (41.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIL-10 (-819 C/T)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCodominant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n 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valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eT/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.14\u0026ndash;7.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDominant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC/T + T/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66 (97.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.98 (0.14\u0026ndash;6.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRecessive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eT/T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.33\u0026ndash;3.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAllelic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73 (53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75 (55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.06 (0.69\u0026ndash;1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61 (44.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIL-12 (+1188 A/C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCodominant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 (82.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60 (88.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.56 (0.13\u0026ndash;2.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.83 (0.16\u0026ndash;4.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDominant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA/C + C/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63 (92.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65 (95.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.60 (0.15\u0026ndash;2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRecessive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.43 (0.42\u0026ndash;4.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAllelic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70 (51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70 (51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.64\u0026ndash;1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66 (48.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66 (48.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"H. pylori, Genetic Susceptibility, IL-10, IL-12, Polymorphism, Case-Control Studies","lastPublishedDoi":"10.21203/rs.3.rs-7832834/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7832834/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe host's immune response to \u003cem\u003eHelicobacter pylori\u003c/em\u003e (\u003cem\u003eH. pylori\u003c/em\u003e) infection is largely determined by its cytokine profile. Genetic variations within crucial immunomodulatory genes, including those for IL-10 and IL-12, are thought to influence an individual's vulnerability to the infection and its clinical consequences by modifying cytokine production. Nonetheless, research data derived from diverse human populations continue to show inconsistent results.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAim\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis case-control analysis sought to examine a potential link between \u003cem\u003eH. pylori\u003c/em\u003e infection susceptibility in an Iranian population and specific genetic variants in the IL-10 (-1082G\u0026thinsp;\u0026gt;\u0026thinsp;A, -819C\u0026thinsp;\u0026gt;\u0026thinsp;T) and IL-12 (+\u0026thinsp;1188A\u0026thinsp;\u0026gt;\u0026thinsp;C) genes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn this investigation, 68 individuals with confirmed \u003cem\u003eH. pylori\u003c/em\u003e infection diagnosed by a positive rapid urease test and elevated anti-\u003cem\u003eH. pylori\u003c/em\u003e IgG levels exceeding 90 ng/ml via ELISA were enrolled alongside 68 healthy controls. The control group was carefully matched to the patient group based on age, sex, and ethnic background. Genotyping for the IL-10 (-1082G\u0026thinsp;\u0026gt;\u0026thinsp;A, -819C\u0026thinsp;\u0026gt;\u0026thinsp;T) and IL-12 (+\u0026thinsp;1188A\u0026thinsp;\u0026gt;\u0026thinsp;C) polymorphisms was conducted using the Amplification Refractory Mutation System-PCR (ARMS-PCR) method. To evaluate associations, the distribution of genotypes and alleles between the groups was contrasted using logistic regression, applying additive, dominant, and recessive inheritance models. The strength of any association was expressed as odds ratios (ORs) accompanied by 95% confidence intervals (CIs).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe analysis revealed no statistically significant correlations linking the investigated IL-10 and IL-12 gene variants to an increased predisposition for \u003cem\u003eH. pylori\u003c/em\u003e infection. Regarding the IL-10 -1082G\u0026thinsp;\u0026gt;\u0026thinsp;A locus, the AA genotype was associated with a marginally elevated risk estimate; however, this finding was not statistically significant (OR\u0026thinsp;=\u0026thinsp;3.45, 95% CI: 0.29\u0026ndash;41.36; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.327). Likewise, for the IL-12\u0026thinsp;+\u0026thinsp;1188A\u0026thinsp;\u0026gt;\u0026thinsp;C polymorphism, the CC genotype, while more prevalent in the patient cohort, also demonstrated no significant association with infection risk (OR\u0026thinsp;=\u0026thinsp;1.43, 95% CI: 0.42\u0026ndash;4.87; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.567). Furthermore, it was noted that the genotype distributions for all evaluated polymorphisms within the control group departed from Hardy-Weinberg equilibrium.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis investigation did not establish a significant link between the specific IL-10 and IL-12 gene variants analyzed and susceptibility to \u003cem\u003eH. pylori\u003c/em\u003e infection in the studied population. Although minor genetic associations were noted, they lacked statistical significance. Future research with larger sample sizes is required to validate these results and to investigate additional genetic determinants that may affect infection risk.\u003c/p\u003e","manuscriptTitle":"Association of polymorphism of coding genes IL-10 and IL-12 with the risk of Helicobacter pylori infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 02:59:53","doi":"10.21203/rs.3.rs-7832834/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-20T08:28:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-17T19:01:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68741763717029882101045825007780286791","date":"2025-11-15T20:58:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-12T10:25:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-11T17:09:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170016939481396831565506649930585147025","date":"2025-11-11T17:04:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-11T17:01:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332656360189822910603658987580031809581","date":"2025-11-11T16:21:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321835257448227139871092712977682851534","date":"2025-11-11T05:59:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297833679370257493411744890061075514288","date":"2025-11-10T20:20:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-10T20:10:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-17T20:11:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-17T01:48:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-17T01:45:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-10-11T07:16:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d8e95ed-b487-4ee9-a3c8-cb04a92458ac","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-27T18:39:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 02:59:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7832834","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7832834","identity":"rs-7832834","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}