Association of STAT6 Gene Polymorphism with Atopic Asthma among Yemeni Children in Sana'a City, Yemen

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The signal transducer and activator of transcription 6 (STAT6) is a crucial gene in immune response, specifically in atopic reactions. It plays a role in the IL-4 and IL-13 signaling pathways in asthma and allergies. Objective This study aimed to determine the association between the STAT6 rs324011 gene polymorphism and atopic asthma among Yemeni children as well as to investigate the impact of the STAT6 rs324011 polymorphism on IL-13, total IgE, and eosinophils. Methods This study included 75 Yemeni children diagnosed with bronchial asthma and 75 healthy controls matched for age and sex. The STAT6 polymorphism (rs324011) was genotyped using RFLP PCR, the IL-13 serum level was measured via ELISA, and the serum IgE level was measured via electrochemiluminescence. Results Under a recessive model, the TT genotype of the STAT6 polymorphism rs324011 was significantly associated with an increased risk of atopic asthma compared to the CC and CT genotypes (χ 2 = 6.6, OR = 2.5, CI = 1.2–5, p = 0.01). IgE levels among asthmatic children were significantly elevated in individuals with the TT genotype compared with those with the CC or CT genotypes (p=0.04). Conclusion The TT genotype and T allele of the STAT6 rs324011 polymorphism may be associated with increased susceptibility to pediatric asthma among Yemeni children. rs324011 SNP IgE IL-13 eosinophils atopic asthma Figures Figure 1 1 Introduction Allergic asthma is a respiratory illness characterized by airway inflammation and hyper-responsiveness caused by exposure to airborne allergens. These allergens cause immediate bronchoconstriction, followed by a late-phase inflammatory reaction. Allergic asthma is the most common phenotype of asthma. It accounts for up to 80% of pediatric asthma cases and almost half of adult asthma cases (1). Asthma can develop at any age; however, most cases occur before the age of 25 years. Despite its complexity, involving many genes and probably gene-environment interactions, asthma has a prevalence of approximately 60%. These findings suggest genetic and environmental factors contribute to pathogenesis (2). Allergic asthma is related to type I hypersensitivity reactions in which different allergens, such as pollen, dust mites, and pollen, induce type 2 immune responses, which are defined by the generation of interleukin-4 (IL-4), IL-5, and IL-13 and class switching to IgE antibodies (3). STAT6 regulates immunological responses and plays a crucial role in the development of allergic illnesses and efficient immunity against helminth parasites (4). It is a key regulator of Th2-mediated allergic inflammation via the IL-4 JAK/STAT signaling pathway (5). STAT6 stimulates immune cell responses through IL-4 and IL-13 signaling. This stimulates the proliferation of B and T cells, the development of alternatively activated macrophages, and the modulation of IgE class switching in B cells via the activation of NF-κB (6). The human STAT6 gene is located on chromosome 12q13.3-q14.1, spanning a total length of 19 kb and comprising 23 exons crossed with 22 introns. The STAT6 protein consists of 847 amino acids and has a monomeric size of 94 kDa (7–9). The 5'UTR (untranslated region) includes the first two exons and part of the third exon, as well as a major part of the last exon. STAT6 generates many mRNA isoforms (8). STAT proteins have six domains: the N-terminal domain (ND), coiled-coil domain (CCD), DNA-binding domain (DBD), linker domain (LD), Src homology 2 (SH2) domain, and transcription activation domain (TAD) (10). We hypothesized that the STAT6 rs324011 polymorphism is associated with an increased susceptibility to atopic asthma among Yemeni children, with the TT genotype conferring a higher risk. This hypothesis aligns with prior evidence from Middle Eastern and South Asian populations. For instance, the TT genotype of rs324011 has been associated with a 2.1-fold increased asthma risk in Saudi Arabian children (13) and a 2.8-fold risk in the Egyptian study (14). Similarly, studies in Pakistani populations linked this SNP to elevated IgE levels and non-atopic asthma (15). The consistency of these findings across genetically and environmentally distinct populations underscores the potential universality of STAT6’s role in asthma pathogenesis, particularly in IgE-mediated pathways. We also examined how this genetic variation might influence IL-13, IgE, and eosinophil levels. 2 Methodology This is a case-control study that included 75 Yemeni children diagnosed with atopic asthma who were compared with 75 healthy controls matched for age and sex. Asthmatic children were selected from hospitalized patients in the pediatric department of Al-Sabeen Hospital for Women and Children, Al-Thawra General Hospital and a pediatric chest clinic in Sana’a City, with confirmation of asthma diagnosis by a pulmonologist based on the criteria of the Global Initiative for Asthma (GINA) guidelines. All participants in this study were Yemeni. To minimize the possibility of population stratification, participants from other ethnic backgrounds were not included. All participants underwent comprehensive medical assessments, including complete medical history, physical examinations, pulmonary function tests, and laboratory investigations. Children with non-atopic asthma or other respiratory or chronic illnesses were excluded from the study. 2.1 Sample collection Ten ml peripheral blood samples were obtained from all study participants. Blood (2.5 ml) was collected in two EDTA-containing tubes, and 5 ml was collected in a plain gel tube. EDTA blood samples were used for hematological assays and DNA extraction. The extracted DNA samples were frozen at -20°C for subsequent genetic analysis. The serum was separated from the gel plain tube after blood clotting and stored for immunological analysis. Measurement of serum IgE levels Total IgE levels were quantified via electrochemiluminescence immunoassay (ECLIA) via a Cobas e 411 analyzer (Roche Diagnostics, Swiss). This assay involves a sandwich immunoassay (Roche Diagnostics, Swiss). The assay was performed by mixing 10 µl of antigen with biotinylated and ruthenium-labeled monoclonal IgE-specific antibodies to form a sandwich complex. Streptavidin-coated microparticles were added to bind the complex to the solid phase. The reaction mixture was transferred to a measuring cell where microparticles were magnetically captured on the electrode surface. Unbound substances were removed via ProCell/ProCell M. Applying a voltage to the electrode triggered chemiluminescence, which was measured via a photomultiplier. The results were obtained through a 2-point calibration method using a calibration curve and master curve from the reagent barcode. Measurement of Interleukin 13 (IL-13) IL-13 levels were measured using enzyme-linked immunosorbent assay (ELISA) (Meril, India). This assay employed a sandwich ELISA technique (Elabscience, USA). The samples were bound to a micro-ELISA plate precoated with an antibody specific for IL-13. Biotinylated detection antibody and avidin-HRP conjugate were sequentially added and incubated. Unbound components were washed away, and a substrate mixture was added, resulting in a blue color in the presence of IL-13. The reaction was stopped, causing the color change to yellow. The optical density was measured at 450 nm, with higher values indicating higher levels of human IL-13. The IL-13 concentrations in the samples were determined using a standard curve. 2.2 Genetic analysis DNA was extracted from whole blood using an extraction kit (Promega, USA) according to the manufacturer’s protocol. The genotype of the STAT6 rs324011 SNP was determined using the PCR-RFLP method. The PCRs (50 µl) included 2 µl of DNA (5–15 µg), 25 µl of DreamTaq Green Master Mix (Thermo Scientific, USA), 1 µl of forward primer (10 pmoles/µl), 1 µl of reverse primer (10 pmoles/µl) (Apical Scientific, Malaysia), and 21 µl of nuclease-free water. The reaction mixture was analyzed using a thermal cycler (Biometra, Germany) (Table 1 ). Table 1 Primer sequences and PCR protocol SNP primer Sequence PCR Program STAT6 rs324011 STAT6-Fwd 5'-CTC TTC CCA CCC CTG TGT CTA TC-3' 1 cycle 95°C 3 min; 35 cycles 95°C 30 sec, 67°C 30 sec, 72°C 1 min; 1 cycle 72°C 5 min STAT6-Rev 5’-TCC CAT AGA TAG CCC TCC TAG GTA C-3’ Following the PCR procedure, the amplicon was digested using the BshNI restriction enzyme (Thermo Scientific, USA). BshNI splits between G-G nucleotides. The resulting fragments were visualized on a 2% agarose gel stained with ethidium bromide and run alongside a 100 bp DNA ladder marker (Kapa Biosystems, Spain). 2.3 Statistical analysis Data were analyzed using mean and standard deviation, median, range, frequency, and percentage as appropriate. The chi-square test, or Fisher's exact test, was used. To compare means between groups, one-way ANOVA was applied for normally distributed data, whereas the Kruskal-Wallis H test was used for nonparametric data. The strength and direction of relationships between continuous variables were assessed using Pearson correlations, depending on the data distribution. Odds ratios with 95% confidence intervals (CIs) were calculated to assess genotype differences between cases and controls. Statistical significance was defined as a p-value less than 0.05. All analyses were conducted using IBM SPSS Statistics version 22. 3 Results Demographic characteristics of the study population are summarized in Table 2 . Most participants were aged 6–10 years (41% cases, 44% controls), with fewer participants aged 11–14 years (28% cases, 24% controls). Most children with asthma lived in urban areas (82.7%) compared to rural areas (17.3%), suggesting a possible environmental influence. 61% of children with asthma had a family history of asthma, and 36% had other allergies, while these factors were absent in the control group, this difference highlights the significant role of family history and allergies in asthma susceptibility. The TT genotype under the recessive model was significantly more common in asthmatic children (44%) than in controls (24%), with a 2.5-fold increased risk of asthma (OR = 2.5, 95% CI = 1.2–5.0, p = 0.01) (Table 3 ). This indicates that Yemeni children with the TT genotype might be 2.5 times more likely to develop asthma compared to those with CC/CT genotypes, with the true population risk ranging from moderate (lower CI = 1.2) to high (upper CI = 5.0). Additionally, the frequency of the T allele was significantly higher in cases (58%) compared to controls (44%), with an odds ratio of 1.8 (OR = 1.8, 95% CI = 1.1–2.8, p = 0.01) (Table 4 ). The T allele is significantly associated with asthma, suggesting that individuals carrying this allele may have an increased risk of developing atopic asthma. Table 2 Demographic characteristics of patients and controls Variable Case (n = 75) Control (= 75) No. % No. % Age 1–5 years 23 31% 24 32% 6–10 years 31 41% 33 44% 11–14 years 21 28% 18 24% Gender Male 40 53% 37 49.3% Female 35 47% 38 50.7% Residence Urban 62 82.7% 71 94.7% Rural 13 17.3% 4 5.3% Family history No 29 39% 75 100% Yes 46 61% 0 0% Other allergic disease No 48 64% 75 100% Yes 27 36% 0 0% Table 3 Comparison of STAT6 rs324011 in the dominant/recessive model between atopic asthma children and controls SNP Genotype Model Case (n = 75) Control (n = 75) OR CI 95% χ 2 P value rs324011 CC Dominant 21 (28%) 27 (36%) 0.7 0.3–1.4 1 0.3 CT, TT 54 (72%) 48 (64%) 1.4 0.7–2.9 CT, CC Recessive 42 (56%) 57 (76%) 0.4 0.2–0.8 6.6 0.01 TT 33 (44%) 18 (24%) 2.5 1.2-5 χ2 = chi-square test, p value = probability value, OR = odds ratio, CI = confidence interval Table 4 Alleles frequency in atopic asthma children and controls SNP Genotype/Allele Case (n = 75) Control (n = 75) OR CI 95% χ 2 p value rs324011 C allele 63 (42%) 84 (56%) 1.8 1.1–2.8 5.9 0.01 T allele 87 (58%) 66 (44%) χ 2 = chi-square test, p value = probability value, OR = odds ratio, CI = confidence interval Children carrying the TT genotype had significantly higher IgE levels (499 ± 211 IU/ml) than those with the CC (387.3 IU/ml) or CT (376 IU/ml) genotypes (p = 0.04). However, no significant differences were observed in IL-13 levels among the genotypes CC (75 pg/ml, range: 49–182), CT (71 pg/ml, range: 44–211), and TT (70 pg/ml, range: 35–180) genotypes (p = 0.7). Similarly, eosinophil proportions showed no significant variation among genotypes, with CC (7.1 ± 3.08%), CT (7.8 ± 3.06%), and TT (7.55 ± 3.06%) (p = 0.7) (Table 5 ). Table 5 Association of STAT6 rs324011 genotype with IgE, IL-13, and eosinophil levels in atopic asthmatic children Test STAT6 rs324011 genotype p value CC (n = 21) CT (n = 21) TT (n = 33) IgE level (IU/ml) 387.3 ± 147.3 376 ± 163 499 ± 211 0.04* IL-13 level (pg/ml) 75 (49–182) 71 (44–211) 70 (35–180) 0.7** Eosinophil % 7.1 ± 3.08 7.8 ± 3.06 7.55 ± 3.06 0.7* *ANOVA test ** Kruskal‒Walli’s test 4 Discussion Asthma is the most chronic disease in children and is characterized by airway hyperresponsiveness, excessive mucus production, and pronounced inflammation (11). Allergic asthma is most prevalent in early childhood and decreases with age, whereas non-allergic asthma remains rare until it peaks in late adulthood. After approximately 40 years of age, most asthma cases are nonallergic (12). Our findings reveal a significant association between the STAT6 rs324011 polymorphism and the risk of developing atopic asthma. Specifically, under the recessive inheritance model, the TT genotype was significantly more common among asthmatic children (44%) than among controls (24%) (OR = 2.5, 95% CI = 1.2–5.0, p = 0.01). This suggests that Yemeni children with the TT genotype are 2.5 times more likely to develop asthma compared to those with CC/CT genotypes, with the true population risk ranging from moderate (CI = 1.2) to high (CI = 5.0). These results indicate that the TT genotype, which carries two copies of the T allele, is associated with a greater risk of asthma. The risk is increased only when an individual inherits two copies of the T allele rather than just one. This finding suggests that the STAT6 rs324011 polymorphism may be a potential candidate marker for identifying individuals at increased risk of asthma, particularly in high-risk families. Furthermore, understanding the role of STAT6 in asthma pathogenesis could lead to the development of targeted therapies. However, additional research is needed to confirm these findings and to explore the functional consequences of the TT genotype. Our results are consistent with those of a study conducted in Saudi Arabia (13), which reported that the TT genotype was significantly associated with asthma compared with the CC and CT genotypes. However, their study differed from ours in that they reported no statistically significant difference in the frequency of C and T alleles between patients and controls. The difference in sample sizes between the studies may have led to variations in statistical power, potentially explaining the observed discrepancy. Further research exploring gene-environment interactions is needed to investigate this possibility. Further research exploring gene-environment interactions is needed to investigate this possibility. Furthermore, a study from Egypt (14) revealed that both the rs324011 TT genotype and T alleles were significantly associated with increased susceptibility to developing bronchial asthma. Similarly, a Pakistani study indicated that the rs324011 polymorphism was significantly associated with non-atopic asthma (15). These studies, in conjunction with our findings, provide further evidence supporting the role of the STAT6 rs324011 polymorphism in asthma susceptibility across diverse populations and asthma. This consistency strengthens the potential clinical utility of this polymorphism as a risk marker for asthma. STAT6 is critical in the signaling pathways associated with cytokines IL-4 and IL-13, which play essential roles in the pathogenesis of many allergic disorders (16). The STAT6 rs324011 variant may increase asthma risk because STAT6 mediates the biological effects of a cytokine necessary for type 2 differentiation of T cells and B-cell survival, proliferation, and class switching to IgE (17). Compared with that in healthy controls, the transcriptional activity of mutant STAT6 was increased even without IL-4 stimulation, and the phosphorylation of STAT6 was more strongly induced by IL-4 stimulation. The patient's lymphoblastoid cell lines showed nuclear presence of STAT6 protein even without IL-4 stimulation (18). Our study investigated the relationships between three genotypes (CC, CT, and TT) and IgE, IL-13, and eosinophil levels in children with atopic asthma. While individuals with the TT genotype presented significantly higher IgE levels than those with the CC or CT genotypes, no significant differences were found in IL-13 or eosinophil levels. These results partially aligned with those of (14), who reported significant associations between STAT6 SNP genotypes and IgE and eosinophil levels. The lack of significant differences in IL-13 or eosinophil levels may be attributed to the fact that STAT6 primarily regulates IgE production through the B cell pathway, whereas IL-13 and eosinophil levels are likely influenced by other pathways, such as those involving IL-5 or GM-CSF. Additionally, IL-13 and eosinophil levels may be modulated by independent genetic, epigenetic, or environmental factors, which were not directly related to STAT6. The present study revealed highly statistically significant increases in the levels of IL-13, IgE, and eosinophils among patients compared to those in the control group. STAT6 SNPs can alter gene expression, suggesting that these variants are expression SNPs associated with transcription. Consequently, changes in the mRNA expression levels of the five major IL-4/IL-13 pathway genes, which are DNA variants, lead to gene expression changes, which lead to asthma susceptibility and subsequently elevated serum IgE (19). The observed increase in IL-13, IgE, and eosinophils in asthma patients compared to controls reinforces the established role of these inflammatory mediators in asthma pathogenesis. This highlights the importance of targeting these pathways in the development of effective asthma treatments. The present study revealed highly statistically significant increases in the levels of IL-13, IgE, and eosinophils among patients compared with those in the control group. Our findings are consistent with those of a Pakistani study, which revealed that bronchial asthma patients had significantly increased levels of total serum IgE and IL-13 (20). Similar results have been reported in many studies, which revealed significantly higher levels of IgE and IL-13, as well as eosinophil percentages, in allergic asthma patients than in healthy individuals (2, 21-24). Early asthmatic responses are triggered by T cells, derived cytokines, IgE, mast cells, and recruitment and activation of eosinophils, which appear to contribute to the persistent asthma phenotype with chronic airflow obstruction (2). IgE is responsible for the release of several asthma-associated inflammatory mediators from mast cells, such as histamine and prostaglandins (25). The functions of specific cytokines in asthma are clear; specifically, IL-13 plays an important role in eosinophil accumulation and is considered a critical factor in IgE synthesis by B cells, differentiation of naïve T cells into Th2 effector cells, AHR, and airway inflammation (2). Furthermore, IL-13 contributes to regulation and driving type 2 inflammation. It plays a key role in asthma by promoting airway hyper-responsiveness, mucus secretion, and airway remodeling (26). Eosinophil levels are elevated in both the bloodstream and airways of many asthma patients (27). The influx of eosinophils and their activation of the bronchial mucosa is a characteristic feature of asthma (28). Eosinophilic airway inflammation is observed in approximately 40–60% of individuals with severe asthma (29). Our findings revealed that 82.7% of children with asthma resided in urban areas compared to 17.3% in rural regions, which may reflect higher exposure to environmental pollutants. Environmental factors, particularly air pollution, play a significant role in the higher prevalence of asthma in urban areas. Urban environments typically have higher levels of outdoor air pollutants such as ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and particulate matter (PM), which are linked to asthma development and exacerbation. Chronic exposure to traffic-related pollution can impair lung function in children, increasing the risk of asthma. Additionally, indoor air quality in urban settings, influenced by pollutants from building materials, cleaning products, and other sources, further contributes to asthma risk and symptoms in children (9,30). This study has some limitations. First , while our sample size was determined through rigorous power analysis and sufficient to detect the observed associations, a larger sample size incorporating diverse geographic regions within Yemen would enhance generalizability and reduce selection bias. Such efforts would also better capture population-wide genetic variability. However, limited funding caused by the ongoing conflict in Yemen restricted the ability to include a larger sample size. Second , while this study provides valuable insights into the association between the STAT6 rs324011 polymorphism and atopic asthma in Yemeni children, it's important to recognize the limitations of focusing on a single SNP. Analyzing additional SNPs in STAT6 (e.g., rs324015, rs3024944, rs71802646) and other genes (e.g., IL1RL1, GATA3, ADAM33, TSLP, FOXO3a) would expand the scope of genetic analysis and provide a comprehensive understanding of asthma susceptibility in the population. Future studies in Yemen should prioritize multi-SNP analyses and gene-environment interplay to refine predictive models and therapeutic targets for this complex disease Third, our study did not include environmental factors such as air pollution, allergens, dietary factors, or socioeconomic conditions. Future research in Yemen should incorporate gene-environment interaction analyses to evaluate how these external factors influence the genetic risks associated with STAT6 variants. Finally , while our current study focused on validating the genetic association between rs324011 and asthma susceptibility, detailed clinical data regarding treatment failure, acute exacerbations, or advanced therapies were not comprehensively captured. Future studies should integrate clinical parameters with genetic markers would significantly enhance the translational relevance of these findings. Conclusion Children with the TT genotype or the T allele of the STAT6 rs324011 polymorphism might be at a greater risk of developing asthma than children without this genetic variation. This finding indicates a possible association between this genetic variation and the development of asthma in Yemeni children. Further research is necessary to investigate additional genetic markers and their interactions with environmental factors. Abbreviations STAT6 Signal transducer and activator of transcription 6 ND N-terminal domain CCD Coiled-coil domain DBD DNA-binding domain LD Linker domain SH2 Src homology 2 TAD Transcription activation domain GINA Global Initiative for Asthma CIs Confidence intervals OR Odds ratio p -value Probability value Declarations Ethics approval and consent to participate The study protocol was approved by Ethical Research Committee at Faculty of Medicine and Health Sciences, Sana’a University. In accordance with ethical guidelines, written informed consent was obtained from the parents/legal guardians of all participants under 16 years of age prior to their inclusion in the study . The study's procedures, risks, and benefits were explained to the guardians, and their written consent was secured before involving the minors in the research. Consent for publication Not applicable Availability of data and materials The data that support the findings of this study are available for interested researchers upon reasonable request from the corresponding author. Competing interests The authors report no competinginterest Conflict of interest The authors report no conflicts of interest Funding Declaration This study did not receive any specific funding. Clinical Trial Number Clinical trial number: not applicable. Author Contributions Statement HAM conceived and designed the study, collected samples, performed laboratory investigations, analyzed data, and drafted the manuscript. AMO and NNS provided supervision for the practical and theoretical aspects of the study. FAG provided technical support, NMH, and MS provided guidance, and contributed to participant recruitment. All authors reviewed and approved the final manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5588927","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":435958893,"identity":"ee3f5464-ab76-485e-8f34-06b8ec3de2c9","order_by":0,"name":"Haitham Abdulwahab Masood","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBACAwbGBmY4j8dAQg5EH3iAX0tjM0JLgYUxWEsCXi0MjEhaPlQkNoAY+LSYsx9uf1xQsy2av//wwQdvDCTS54cdfgi0xU5OtwG7FsuexMbmGcdu5864kZZsOMdAInfj7TQDoJZkY7MDOBx2AKiFh+12bsMNHjNpHpCW2QkgLQcSt+HScv4hUMu/27nzz58Ba0k3nJ3+Ab+WG0BbeNtu5244kAPWkiAvnUPAlhsPG2fz9t3O3Qj1i+EG6ZyCAwkGePxyPv3BZ55vt3PnnQeF2J86efnZ6Zs/fKiwk8OlBVuAgElilYOAfAMpqkfBKBgFo2AkAACRDWpp1s5rYgAAAABJRU5ErkJggg==","orcid":"","institution":"Sana University","correspondingAuthor":true,"prefix":"","firstName":"Haitham","middleName":"Abdulwahab","lastName":"Masood","suffix":""},{"id":435958894,"identity":"41d7e8cc-cbb8-4ead-984a-ddb185ed17b4","order_by":1,"name":"Arwa Mohammed Othman","email":"","orcid":"","institution":"Sana University","correspondingAuthor":false,"prefix":"","firstName":"Arwa","middleName":"Mohammed","lastName":"Othman","suffix":""},{"id":435958895,"identity":"4ed365d6-99d6-42a8-b11e-52984478e3ee","order_by":2,"name":"Najla Nasr Addin Al-Sonboly","email":"","orcid":"","institution":"Sana University","correspondingAuthor":false,"prefix":"","firstName":"Najla","middleName":"Nasr Addin","lastName":"Al-Sonboly","suffix":""},{"id":435958896,"identity":"a779553a-058a-4c07-96c8-3fff4883062c","order_by":3,"name":"Faiza Abdulnoor Ghlab","email":"","orcid":"","institution":"Sana University","correspondingAuthor":false,"prefix":"","firstName":"Faiza","middleName":"Abdulnoor","lastName":"Ghlab","suffix":""},{"id":435958897,"identity":"cea1324a-bfce-4179-8458-73be94157223","order_by":4,"name":"Naif Mohammed Al-Haidary","email":"","orcid":"","institution":"Sana University","correspondingAuthor":false,"prefix":"","firstName":"Naif","middleName":"Mohammed","lastName":"Al-Haidary","suffix":""},{"id":435958898,"identity":"47b78c8c-491d-46d8-80dd-62aea7741182","order_by":5,"name":"Muhanna Al-Shaibani","email":"","orcid":"","institution":"Taiz University","correspondingAuthor":false,"prefix":"","firstName":"Muhanna","middleName":"","lastName":"Al-Shaibani","suffix":""}],"badges":[],"createdAt":"2024-12-05 18:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5588927/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5588927/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12887-025-05710-9","type":"published","date":"2025-05-15T15:56:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79581670,"identity":"3b12a6b6-4b20-4ff6-94b4-838426a1a448","added_by":"auto","created_at":"2025-03-31 11:58:31","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73545,"visible":true,"origin":"","legend":"\u003cp\u003eGenotype results\u003c/p\u003e\n\u003cp\u003eillustrates the genotyping results for the STAT6 rs324011 polymorphism using PCR-RFLP\u003cstrong\u003e. Photo 1 \u003c/strong\u003eshows the gel electrophoresis results for the STAT6 rs324011 polymorphism. lanes 2, 3, and 4 are heterozygous (CT) with three bands at 132, 107, \u0026amp; 25 bp. Lanes 1 and 5 were homozygous polymorphic (TT) with two bands at 107 \u0026amp; 25 bp. \u003cstrong\u003ePhoto 2\u003c/strong\u003e further validates these patterns, with lanes 2, 3, 4, and 5 were heterozygous (CT) with three bands at 132, 107, and 25 bp. Lane 1 was homozygous wild (CC) with a single band at 132 bp. The 25 bp band appears obscure.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5588927/v1/2b22f0312843e62831fa2372.jpg"},{"id":83067901,"identity":"6eb25719-88bd-4ab7-a155-c963e1f767e2","added_by":"auto","created_at":"2025-05-19 16:07:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":811640,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5588927/v1/e6787082-ef19-4565-8e6e-ac8cf2c8c062.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of STAT6 Gene Polymorphism with Atopic Asthma among Yemeni Children in Sana'a City, Yemen","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAllergic asthma is a respiratory illness characterized by airway inflammation and hyper-responsiveness caused by exposure to airborne allergens. These allergens cause immediate bronchoconstriction, followed by a late-phase inflammatory reaction. Allergic asthma is the most common phenotype of asthma. It accounts for up to 80% of pediatric asthma cases and almost half of adult asthma cases (1).\u003c/p\u003e \u003cp\u003eAsthma can develop at any age; however, most cases occur before the age of 25 years. Despite its complexity, involving many genes and probably gene-environment interactions, asthma has a prevalence of approximately 60%. These findings suggest genetic and environmental factors contribute to pathogenesis (2). Allergic asthma is related to type I hypersensitivity reactions in which different allergens, such as pollen, dust mites, and pollen, induce type 2 immune responses, which are defined by the generation of interleukin-4 (IL-4), IL-5, and IL-13 and class switching to IgE antibodies (3).\u003c/p\u003e \u003cp\u003eSTAT6 regulates immunological responses and plays a crucial role in the development of allergic illnesses and efficient immunity against helminth parasites (4). It is a key regulator of Th2-mediated allergic inflammation via the IL-4 JAK/STAT signaling pathway (5). STAT6 stimulates immune cell responses through IL-4 and IL-13 signaling. This stimulates the proliferation of B and T cells, the development of alternatively activated macrophages, and the modulation of IgE class switching in B cells via the activation of NF-κB (6). The human STAT6 gene is located on chromosome 12q13.3-q14.1, spanning a total length of 19 kb and comprising 23 exons crossed with 22 introns. The STAT6 protein consists of 847 amino acids and has a monomeric size of 94 kDa (7\u0026ndash;9). The 5'UTR (untranslated region) includes the first two exons and part of the third exon, as well as a major part of the last exon. STAT6 generates many mRNA isoforms (8). STAT proteins have six domains: the N-terminal domain (ND), coiled-coil domain (CCD), DNA-binding domain (DBD), linker domain (LD), Src homology 2 (SH2) domain, and transcription activation domain (TAD) (10).\u003c/p\u003e \u003cp\u003eWe hypothesized that the STAT6 rs324011 polymorphism is associated with an increased susceptibility to atopic asthma among Yemeni children, with the TT genotype conferring a higher risk. This hypothesis aligns with prior evidence from Middle Eastern and South Asian populations. For instance, the TT genotype of rs324011 has been associated with a 2.1-fold increased asthma risk in Saudi Arabian children (13) and a 2.8-fold risk in the Egyptian study (14). Similarly, studies in Pakistani populations linked this SNP to elevated IgE levels and non-atopic asthma (15). The consistency of these findings across genetically and environmentally distinct populations underscores the potential universality of STAT6\u0026rsquo;s role in asthma pathogenesis, particularly in IgE-mediated pathways. We also examined how this genetic variation might influence IL-13, IgE, and eosinophil levels.\u003c/p\u003e"},{"header":"2 Methodology","content":"\u003cp\u003eThis is a case-control study that included 75 Yemeni children diagnosed with atopic asthma who were compared with 75 healthy controls matched for age and sex. Asthmatic children were selected from hospitalized patients in the pediatric department of Al-Sabeen Hospital for Women and Children, Al-Thawra General Hospital and a pediatric chest clinic in Sana\u0026rsquo;a City, with confirmation of asthma diagnosis by a pulmonologist based on the criteria of the Global Initiative for Asthma (GINA) guidelines.\u003c/p\u003e \u003cp\u003eAll participants in this study were Yemeni. To minimize the possibility of population stratification, participants from other ethnic backgrounds were not included. All participants underwent comprehensive medical assessments, including complete medical history, physical examinations, pulmonary function tests, and laboratory investigations. Children with non-atopic asthma or other respiratory or chronic illnesses were excluded from the study.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Sample collection\u003c/h2\u003e \u003cp\u003eTen ml peripheral blood samples were obtained from all study participants. Blood (2.5 ml) was collected in two EDTA-containing tubes, and 5 ml was collected in a plain gel tube. EDTA blood samples were used for hematological assays and DNA extraction. The extracted DNA samples were frozen at -20\u0026deg;C for subsequent genetic analysis. The serum was separated from the gel plain tube after blood clotting and stored for immunological analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasurement of serum IgE levels\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTotal IgE levels were quantified via electrochemiluminescence immunoassay (ECLIA) via a Cobas e 411 analyzer (Roche Diagnostics, Swiss). This assay involves a sandwich immunoassay (Roche Diagnostics, Swiss). The assay was performed by mixing 10 \u0026micro;l of antigen with biotinylated and ruthenium-labeled monoclonal IgE-specific antibodies to form a sandwich complex. Streptavidin-coated microparticles were added to bind the complex to the solid phase. The reaction mixture was transferred to a measuring cell where microparticles were magnetically captured on the electrode surface. Unbound substances were removed via ProCell/ProCell M. Applying a voltage to the electrode triggered chemiluminescence, which was measured via a photomultiplier. The results were obtained through a 2-point calibration method using a calibration curve and master curve from the reagent barcode.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasurement of Interleukin 13 (IL-13)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIL-13 levels were measured using enzyme-linked immunosorbent assay (ELISA) (Meril, India). This assay employed a sandwich ELISA technique (Elabscience, USA). The samples were bound to a micro-ELISA plate precoated with an antibody specific for IL-13. Biotinylated detection antibody and avidin-HRP conjugate were sequentially added and incubated. Unbound components were washed away, and a substrate mixture was added, resulting in a blue color in the presence of IL-13. The reaction was stopped, causing the color change to yellow. The optical density was measured at 450 nm, with higher values indicating higher levels of human IL-13. The IL-13 concentrations in the samples were determined using a standard curve.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Genetic analysis\u003c/h2\u003e \u003cp\u003eDNA was extracted from whole blood using an extraction kit (Promega, USA) according to the manufacturer\u0026rsquo;s protocol. The genotype of the STAT6 rs324011 SNP was determined using the PCR-RFLP method. The PCRs (50 \u0026micro;l) included 2 \u0026micro;l of DNA (5\u0026ndash;15 \u0026micro;g), 25 \u0026micro;l of DreamTaq Green Master Mix (Thermo Scientific, USA), 1 \u0026micro;l of forward primer (10 pmoles/\u0026micro;l), 1 \u0026micro;l of reverse primer (10 pmoles/\u0026micro;l) (Apical Scientific, Malaysia), and 21 \u0026micro;l of nuclease-free water. The reaction mixture was analyzed using a thermal cycler (Biometra, Germany) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer sequences and PCR protocol\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eprimer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePCR Program\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSTAT6 rs324011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTAT6-Fwd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5'-CTC TTC CCA CCC CTG TGT CTA TC-3'\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1 cycle 95\u0026deg;C 3 min; 35 cycles 95\u0026deg;C 30 sec, 67\u0026deg;C 30 sec, 72\u0026deg;C 1 min; 1 cycle 72\u0026deg;C 5 min\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTAT6-Rev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026rsquo;-TCC CAT AGA TAG CCC TCC TAG GTA C-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFollowing the PCR procedure, the amplicon was digested using the BshNI restriction enzyme (Thermo Scientific, USA). BshNI splits between G-G nucleotides. The resulting fragments were visualized on a 2% agarose gel stained with ethidium bromide and run alongside a 100 bp DNA ladder marker (Kapa Biosystems, Spain).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using mean and standard deviation, median, range, frequency, and percentage as appropriate. The chi-square test, or Fisher's exact test, was used. To compare means between groups, one-way ANOVA was applied for normally distributed data, whereas the Kruskal-Wallis H test was used for nonparametric data. The strength and direction of relationships between continuous variables were assessed using Pearson correlations, depending on the data distribution. Odds ratios with 95% confidence intervals (CIs) were calculated to assess genotype differences between cases and controls. Statistical significance was defined as a p-value less than 0.05. All analyses were conducted using IBM SPSS Statistics version 22.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003eDemographic characteristics of the study population are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Most participants were aged 6\u0026ndash;10 years (41% cases, 44% controls), with fewer participants aged 11\u0026ndash;14 years (28% cases, 24% controls). Most children with asthma lived in urban areas (82.7%) compared to rural areas (17.3%), suggesting a possible environmental influence. 61% of children with asthma had a family history of asthma, and 36% had other allergies, while these factors were absent in the control group, this difference highlights the significant role of family history and allergies in asthma susceptibility. The TT genotype under the recessive model was significantly more common in asthmatic children (44%) than in controls (24%), with a 2.5-fold increased risk of asthma (OR\u0026thinsp;=\u0026thinsp;2.5, 95% CI\u0026thinsp;=\u0026thinsp;1.2\u0026ndash;5.0, p\u0026thinsp;=\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This indicates that Yemeni children with the TT genotype might be 2.5 times more likely to develop asthma compared to those with CC/CT genotypes, with the true population risk ranging from moderate (lower CI\u0026thinsp;=\u0026thinsp;1.2) to high (upper CI\u0026thinsp;=\u0026thinsp;5.0). Additionally, the frequency of the T allele was significantly higher in cases (58%) compared to controls (44%), with an odds ratio of 1.8 (OR\u0026thinsp;=\u0026thinsp;1.8, 95% CI\u0026thinsp;=\u0026thinsp;1.1\u0026ndash;2.8, p\u0026thinsp;=\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The T allele is significantly associated with asthma, suggesting that individuals carrying this allele may have an increased risk of developing atopic asthma.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of patients and controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCase (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eControl (=\u0026thinsp;75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u0026ndash;14 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFamily history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOther allergic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of STAT6 rs324011 in the dominant/recessive model between atopic asthma children and controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCase\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCI 95%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ers324011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3\u0026ndash;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCT, TT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7\u0026ndash;2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCT, CC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRecessive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2\u0026ndash;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.2-5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eχ2\u0026thinsp;=\u0026thinsp;chi-square test, p value\u0026thinsp;=\u0026thinsp;probability value, OR\u0026thinsp;=\u0026thinsp;odds ratio, CI\u0026thinsp;=\u0026thinsp;confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAlleles frequency in atopic asthma children and controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotype/Allele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCI 95%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eχ \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ers324011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC allele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.1\u0026ndash;2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT allele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (44%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;chi-square test, p value\u0026thinsp;=\u0026thinsp;probability value, OR\u0026thinsp;=\u0026thinsp;odds ratio, CI\u0026thinsp;=\u0026thinsp;confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eChildren carrying the TT genotype had significantly higher IgE levels (499\u0026thinsp;\u0026plusmn;\u0026thinsp;211 IU/ml) than those with the CC (387.3 IU/ml) or CT (376 IU/ml) genotypes (p\u0026thinsp;=\u0026thinsp;0.04). However, no significant differences were observed in IL-13 levels among the genotypes CC (75 pg/ml, range: 49\u0026ndash;182), CT (71 pg/ml, range: 44\u0026ndash;211), and TT (70 pg/ml, range: 35\u0026ndash;180) genotypes (p\u0026thinsp;=\u0026thinsp;0.7). Similarly, eosinophil proportions showed no significant variation among genotypes, with CC (7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08%), CT (7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06%), and TT (7.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06%) (p\u0026thinsp;=\u0026thinsp;0.7) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of STAT6 rs324011 genotype with IgE, IL-13, and eosinophil levels in atopic asthmatic children\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSTAT6 rs324011 genotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCC (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTT (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgE level (IU/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387.3\u0026thinsp;\u0026plusmn;\u0026thinsp;147.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e376\u0026thinsp;\u0026plusmn;\u0026thinsp;163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e499\u0026thinsp;\u0026plusmn;\u0026thinsp;211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-13 level (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (49\u0026ndash;182)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (44\u0026ndash;211)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 (35\u0026ndash;180)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEosinophil %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*ANOVA test ** Kruskal‒Walli\u0026rsquo;s test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eAsthma is the most chronic disease in children and is characterized by airway hyperresponsiveness, excessive mucus production, and pronounced inflammation (11). Allergic asthma is most prevalent in early childhood and decreases with age, whereas non-allergic asthma remains rare until it peaks in late adulthood. After approximately 40 years of age, most asthma cases are nonallergic (12).\u003c/p\u003e\n\u003cp\u003eOur findings reveal a significant association between the STAT6 rs324011 polymorphism and the risk of developing atopic asthma. Specifically, under the recessive inheritance model, the TT genotype was significantly more common among asthmatic children (44%) than among controls (24%) (OR = 2.5, 95% CI = 1.2–5.0, \u003cem\u003ep\u003c/em\u003e = 0.01). This suggests that Yemeni children with the TT genotype are 2.5 times more likely to develop asthma compared to those with CC/CT genotypes, with the true population risk ranging from moderate (CI = 1.2) to high (CI = 5.0). These results indicate that the TT genotype, which carries two copies of the T allele, is associated with a greater risk of asthma. The risk is increased only when an individual inherits two copies of the T allele rather than just one. This finding suggests that the STAT6 rs324011 polymorphism may be a potential candidate marker for identifying individuals at increased risk of asthma, particularly in high-risk families. Furthermore, understanding the role of STAT6 in asthma pathogenesis could lead to the development of targeted therapies. However, additional research is needed to confirm these findings and to explore the functional consequences of the TT genotype. Our results are consistent with those of a study conducted in Saudi Arabia (13), which reported that the TT genotype was significantly associated with asthma compared with the CC and CT genotypes. However, their study differed from ours in that they reported no statistically significant difference in the frequency of C and T alleles between patients and controls. The difference in sample sizes between the studies may have led to variations in statistical power, potentially explaining the observed discrepancy. Further research exploring gene-environment interactions is needed to investigate this possibility. Further research exploring gene-environment interactions is needed to investigate this possibility. \u0026nbsp;Furthermore, a study from Egypt (14) revealed that both the rs324011 TT genotype and T alleles were significantly associated with increased susceptibility to developing bronchial asthma. Similarly, a Pakistani study indicated that the rs324011 polymorphism was significantly associated with non-atopic asthma (15). These studies, in conjunction with our findings, provide further evidence supporting the role of the STAT6 rs324011 polymorphism in asthma susceptibility across diverse populations and asthma. This consistency strengthens the potential clinical utility of this polymorphism as a risk marker for asthma.\u003c/p\u003e\n\u003cp\u003eSTAT6 is critical in the signaling pathways associated with cytokines IL-4 and IL-13, which play essential roles in the pathogenesis of many allergic disorders (16). The STAT6 rs324011 variant may increase asthma risk because STAT6 mediates the biological effects of a cytokine necessary for type 2 differentiation of T cells and B-cell survival, proliferation, and class switching to IgE (17). Compared with that in healthy controls, the transcriptional activity of mutant STAT6 was increased even without IL-4 stimulation, and the phosphorylation of STAT6 was more strongly induced by IL-4 stimulation. The patient's lymphoblastoid cell lines showed nuclear presence of STAT6 protein even without IL-4 stimulation (18). Our study investigated the relationships between three genotypes (CC, CT, and TT) and IgE, IL-13, and eosinophil levels in children with atopic asthma. While individuals with the TT genotype presented significantly higher IgE levels than those with the CC or CT genotypes, no significant differences were found in IL-13 or eosinophil levels. These results partially aligned with those of (14), who reported significant associations between STAT6 SNP genotypes and IgE and eosinophil levels. The lack of significant differences in IL-13 or eosinophil levels may be attributed to the fact that STAT6 primarily regulates IgE production through the B cell pathway, whereas IL-13 and eosinophil levels are likely influenced by other pathways, such as those involving IL-5 or GM-CSF. Additionally, IL-13 and eosinophil levels may be modulated by independent genetic, epigenetic, or environmental factors, which were not directly related to STAT6.\u003c/p\u003e\n\u003cp\u003eThe present study revealed highly statistically significant increases in the levels of IL-13, IgE, and eosinophils among patients compared to those in the control group. STAT6 SNPs can alter gene expression, suggesting that these variants are expression SNPs associated with transcription. Consequently, changes in the mRNA expression levels of the five major IL-4/IL-13 pathway genes, which are DNA variants, lead to gene expression changes, which lead to asthma susceptibility and subsequently elevated serum IgE (19).\u003c/p\u003e\n\u003cp\u003eThe observed increase in IL-13, IgE, and eosinophils in asthma patients compared to controls reinforces the established role of these inflammatory mediators in asthma pathogenesis. This highlights the importance of targeting these pathways in the development of effective asthma treatments. The present study revealed highly statistically significant increases in the levels of IL-13, IgE, and eosinophils among patients compared with those in the control group. Our findings are consistent with those of a Pakistani study, which revealed that bronchial asthma patients had significantly increased levels of total serum IgE and IL-13 (20). Similar results have been reported in many studies, which revealed significantly higher levels of IgE and IL-13, as well as eosinophil percentages, in allergic asthma patients than in healthy individuals (2, 21-24).\u003c/p\u003e\n\u003cp\u003eEarly asthmatic responses are triggered by T cells, derived cytokines, IgE, mast cells, and recruitment and activation of eosinophils, which appear to contribute to the persistent asthma phenotype with chronic airflow obstruction (2). IgE is responsible for the release of several asthma-associated inflammatory mediators from mast cells, such as histamine and prostaglandins (25). The functions of specific cytokines in asthma are clear; specifically, IL-13 plays an important role in eosinophil accumulation and is considered a critical factor in IgE synthesis by B cells, differentiation of naïve T cells into Th2 effector cells, AHR, and airway inflammation (2). Furthermore, IL-13 contributes to regulation and driving type 2 inflammation. It plays a key role in asthma by promoting airway hyper-responsiveness, mucus secretion, and airway remodeling (26). Eosinophil levels are elevated in both the bloodstream and airways of many asthma patients (27). The influx of eosinophils and their activation of the bronchial mucosa is a characteristic feature of asthma (28). Eosinophilic airway inflammation is observed in approximately 40–60% of individuals with severe asthma (29).\u003c/p\u003e\n\u003cp\u003eOur findings revealed that 82.7% of children with asthma resided in urban areas compared to 17.3% in rural regions, which may reflect higher exposure to environmental pollutants. Environmental factors, particularly air pollution, play a significant role in the higher prevalence of asthma in urban areas. Urban environments typically have higher levels of outdoor air pollutants such as ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and particulate matter (PM), which are linked to asthma development and exacerbation. Chronic exposure to traffic-related pollution can impair lung function in children, increasing the risk of asthma. Additionally, indoor air quality in urban settings, influenced by pollutants from building materials, cleaning products, and other sources, further contributes to asthma risk and symptoms in children (9,30).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; This study has some limitations. \u003cstrong\u003eFirst\u003c/strong\u003e, while our sample size was determined through rigorous power analysis and sufficient to detect the observed associations, a larger sample size incorporating diverse geographic regions within Yemen would enhance generalizability and reduce selection bias. Such efforts would also better capture population-wide genetic variability. However, limited funding caused by the ongoing conflict in Yemen restricted the ability to include a larger sample size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecond\u003c/strong\u003e, while this study provides valuable insights into the association between the STAT6 rs324011 polymorphism and atopic asthma in Yemeni children, it's important to recognize the limitations of focusing on a single SNP. Analyzing additional SNPs in STAT6 (e.g., rs324015, rs3024944, rs71802646) and other genes (e.g., IL1RL1, GATA3, ADAM33, TSLP, FOXO3a) would expand the scope of genetic analysis and provide a comprehensive understanding of asthma susceptibility in the population. Future studies in Yemen should prioritize multi-SNP analyses and gene-environment interplay to refine predictive models and therapeutic targets for this complex disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThird,\u0026nbsp;\u003c/strong\u003eour study did not include environmental factors such as air pollution, allergens, dietary factors, or socioeconomic conditions. Future research in Yemen should incorporate gene-environment interaction analyses to evaluate how these external factors influence the genetic risks associated with STAT6 variants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinally\u003c/strong\u003e, while our current study focused on validating the genetic association between rs324011 and asthma susceptibility, detailed clinical data regarding treatment failure, acute exacerbations, or advanced therapies were not comprehensively captured. Future studies should integrate clinical parameters with genetic markers would significantly enhance the translational relevance of these findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eChildren with the TT genotype or the T allele of the STAT6 rs324011 polymorphism might be at a greater risk of developing asthma than children without this genetic variation. This finding indicates a possible association between this genetic variation and the development of asthma in Yemeni children. Further research is necessary to investigate additional genetic markers and their interactions with environmental factors.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSTAT6\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Signal transducer and activator of transcription 6\u003c/p\u003e\n\u003cp\u003eND\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;N-terminal domain\u003c/p\u003e\n\u003cp\u003eCCD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Coiled-coil domain\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDBD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;DNA-binding domain\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Linker domain\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSH2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Src homology 2\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTAD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Transcription activation domain\u003c/p\u003e\n\u003cp\u003eGINA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Global Initiative for Asthma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCIs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Confidence intervals\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Odds ratio\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value Probability value\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by Ethical Research Committee at Faculty of Medicine and Health Sciences, Sana\u0026rsquo;a University. In accordance with ethical guidelines, written informed consent was obtained from the parents/legal guardians of all participants under 16 years of age prior to their inclusion in the study\u003cem\u003e.\u003c/em\u003e The study\u0026apos;s procedures, risks, and benefits were explained to the guardians, and their written consent was secured before involving the minors in the research.\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 materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available for interested researchers upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no competinginterest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any specific funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHAM conceived and designed the study, collected samples, performed laboratory investigations, analyzed data, and drafted the manuscript. AMO and NNS provided supervision for the practical and theoretical aspects of the study. FAG provided technical support, NMH, and MS provided guidance, and contributed to participant recruitment. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank the parents and guardians of participating children for their cooperation and consent, as well as the healthcare staff who supported this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkar-Ghibril N, Casale T, Custovic A, Phipatanakul W. Allergic endotypes and phenotypes of asthma. The Journal of Allergy and Clinical Immunology: In Practice. 2020;8(2):429-40.\u003c/li\u003e\n\u003cli\u003eKazaal MA, Habeeb AA, Hasan HN. Evaluation Role of IL-13 and Eosinophils in Adult Asthmatic Patients. Journal of Biomedicine and Biochemistry. 2023;2(2):17-24.\u003c/li\u003e\n\u003cli\u003eBoonpiyathad T, S\u0026ouml;zener ZC, Satitsuksanoa P, Akdis CA, editors. Immunologic mechanisms in asthma. Seminars in immunology; 2019: Elsevier.\u003c/li\u003e\n\u003cli\u003eKarpathiou G, Papoudou-Bai A, Ferrand E, Dumollard JM, Peoc\u0026rsquo;h M. STAT6: a review of a signaling pathway implicated in various diseases with a special emphasis in its usefulness in pathology. Pathology-Research and Practice. 2021; 223:153477.\u003c/li\u003e\n\u003cli\u003eMinskaia E, Maimaris J, Jenkins P, Albuquerque AS, Hong Y, Eleftheriou D, et al. Autosomal dominant STAT6 gain of function causes severe atopy associated with lymphoma. Journal of Clinical Immunology. 2023:1-12.\u003c/li\u003e\n\u003cli\u003eVerhoeven Y, Tilborghs S, Jacobs J, De Waele J, Quatannens D, Deben C, et al., editors. The potential and controversy of targeting STAT family members in cancer. Seminars in cancer biology; 2020: Elsevier.\u003c/li\u003e\n\u003cli\u003ePatel BK, Keck CL, O\u0026apos;Leary RS, Popescu NC, LaRochelle WJ. Localization of the human stat6 gene to chromosome 12q13. 3\u0026ndash;q14. 1, a region implicated in multiple solid tumors. Genomics. 1998;52(2):192-200.\u003c/li\u003e\n\u003cli\u003eGodava M, Vrtel R, Vodicka R. STAT6-polymorphisms, haplotypes and epistasis in relation to atopy and asthma. Biomedical Papers of the Medical Faculty of Palacky University in Olomouc. 2013;157(2).\u003c/li\u003e\n\u003cli\u003eWang J, Zhang Y, Li B, Zhao Z, Huang C, Zhang X, et al. Asthma and allergic rhinitis among young parents in China in relation to outdoor air pollution, climate and home environment. Science of the Total Environment. 2021; 751:141734.\u003c/li\u003e\n\u003cli\u003eZhu M, Li S, Cao X, Rashid K, Liu T, editors. The STAT family: key transcription factors mediating crosstalk between cancer stem cells and tumor immune microenvironment. Seminars in Cancer Biology; 2022: Elsevier.\u003c/li\u003e\n\u003cli\u003eDong Z, Myklebust \u0026Aring;, Johnsen IB, Jartti T, D\u0026oslash;llner H, Risnes K, et al. Type 2 cytokine genes as allergic asthma risk factors after viral bronchiolitis in early childhood. Frontiers in Immunology. 2023; 13:1054119.\u003c/li\u003e\n\u003cli\u003ePakkasela J, Ilmarinen P, Honkam\u0026auml;ki J, Tuomisto LE, Anders\u0026eacute;n H, Piiril\u0026auml; P, et al. Age-specific incidence of allergic and non-allergic asthma. BMC pulmonary medicine. 2020;20(1):1-9.\u003c/li\u003e\n\u003cli\u003eAl-Muhsen S, Vazquez-Tello A, Jamhawi A, Al-Jahdali H, Bahammam A, Al Saadi M, et al. Association of the STAT-6 rs324011 (C2892T) variant but not rs324015 (G2964A), with atopic asthma in a Saudi Arabian population. Human immunology. 2014;75(8):791-5.\u003c/li\u003e\n\u003cli\u003eEl-Gohary R, Wagih A, Hamouda H, El-Melegy S, Rowisha M. Association of STAT6 rs324011 gene polymorphism with susceptibility of atopic bronchial asthma in Egyptian children. Biochem Mol Biol J. 2018;4(1):6.\u003c/li\u003e\n\u003cli\u003eRiaz A, Riaz MA, Khan L, Masoud MS, Hussain G, Iqbal M, et al. STAT6 variants and non-atopic asthma in Pakistani population. Cellular and Molecular Biology. 2018;64(14):15-8.\u003c/li\u003e\n\u003cli\u003eConsortium SG-o-FI. Human germline gain-of-function in STAT6: from severe allergic disease to lymphoma and beyond. Trends in Immunology. 2024.\u003c/li\u003e\n\u003cli\u003eSharma M, Leung D, Momenilandi M, Jones LC, Pacillo L, James AE, et al. Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease. Journal of Experimental Medicine. 2023;220(5): e20221755.\u003c/li\u003e\n\u003cli\u003eTakeuchi I, Yanagi K, Takada S, Uchiyama T, Igarashi A, Motomura K, et al. STAT6 gain-of-function variant exacerbates multiple allergic symptoms. Journal of Allergy and Clinical Immunology. 2023;151(5):1402-9. e6.\u003c/li\u003e\n\u003cli\u003eLi J, Lin L-h, Wang J, Peng X, Dai H-r, Xiao H, et al. Interleukin-4 and interleukin-13 pathway genetics affect disease susceptibility, serum immunoglobulin E levels, and gene expression in asthma. Annals of Allergy, Asthma \u0026amp; Immunology. 2014;113(2):173-9. e1.\u003c/li\u003e\n\u003cli\u003eJavaid K, Nadeem A, Hussain MA, Tahir R, Shahzad F, Jahan S, et al. Positive correlation of serum interleukin-13 and total immunoglobulin E in bronchial asthma patients. Bangladesh Journal of Medical Science. 2022;21(3):596-600.\u003c/li\u003e\n\u003cli\u003eRanjbar M, Matloubi M, Assarehzadegan M-A, Fallahpour M, Sadeghi F, Soleyman-Jahi S, et al. Association between two single nucleotide polymorphisms of thymic stromal lymphopoietin (TSLP) gene and asthma in Iranian population. Iranian Journal of Allergy, Asthma and Immunology. 2020;19(4):362-72.\u003c/li\u003e\n\u003cli\u003eGajanand Joshi* RKV, Yogita Soni, Ghanshyam Gahlot. Assessment of Serum mmunoglobulin E Level in Children with Bronchial Asthma in North West Rajasthan. American Journal of Biochemistry. 2020;10(1) (2163-3010).\u003c/li\u003e\n\u003cli\u003ePandey R, Prakash V. Expression of FOXP3 and GATA3 transcription factors among bronchial asthmatics in northern population. Indian Journal of Clinical Biochemistry. 2021; 36:88-93.\u003c/li\u003e\n\u003cli\u003eAtta R, Aloubaidy R. GENETIC POLYMORPHISM OF ASTHMA IN IRAQ. Iraqi Journal of Agricultural Sciences. 2022;53(2):288-96.\u003c/li\u003e\n\u003cli\u003eImraish A, Abu‑Thiab T, Zihlif M. IL‑13 and FOXO3 genes polymorphisms regulate IgE levels in asthmatic patients. Biomedical Reports. 2021;14(6):1-7.\u003c/li\u003e\n\u003cli\u003eDragonieri S, Carpagnano GE. Biological therapy for severe asthma. Asthma research and practice. 2021;7(1):12.\u003c/li\u003e\n\u003cli\u003eNarendra D, Blixt J, Hanania NA, editors. Immunological biomarkers in severe asthma. Seminars in immunology; 2019: Elsevier.\u003c/li\u003e\n\u003cli\u003eKadhim BJ, Khakzad APMR, Zadeh APJK. Immunological and Molecular Evaluation of IL-5 in Asthma Patients. Texas Journal of Medical Science. 2023; 17:39-45.\u003c/li\u003e\n\u003cli\u003eKuruvilla ME, Lee FE-H, Lee GB. Understanding asthma phenotypes, endotypes, and mechanisms of disease. Clinical reviews in allergy \u0026amp; immunology. 2019; 56:219-33.\u003c/li\u003e\n\u003cli\u003ePaci\u0026ecirc;ncia I, Rufo JC. Urban-level environmental factors related to pediatric asthma. Porto biomedical journal. 2020;5(1): e57.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"rs324011 SNP, IgE, IL-13, eosinophils, atopic asthma","lastPublishedDoi":"10.21203/rs.3.rs-5588927/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5588927/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAsthma is the most common chronic illness in children and is characterized by airway hyperresponsiveness, increased production of mucus, and significant inflammation. The signal transducer and activator of transcription 6 (STAT6) is a crucial gene in immune response, specifically in atopic reactions. It plays a role in the IL-4 and IL-13 signaling pathways in asthma and allergies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to determine the association between the STAT6 rs324011 gene polymorphism and atopic asthma among Yemeni children as well as to investigate the impact of the STAT6 rs324011 polymorphism on IL-13, total IgE, and eosinophils.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 75 Yemeni children diagnosed with bronchial asthma and 75 healthy controls matched for age and sex. The STAT6 polymorphism (rs324011) was genotyped using RFLP PCR, the IL-13 serum level was measured via ELISA, and the serum IgE level was measured via electrochemiluminescence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnder a recessive model, the TT genotype of the STAT6 polymorphism rs324011 was significantly associated with an increased risk of atopic asthma compared to the CC and CT genotypes (χ\u003csup\u003e2 \u003c/sup\u003e= 6.6, OR = 2.5, CI = 1.2–5, p = 0.01). IgE levels among asthmatic children were significantly elevated in individuals with the TT genotype compared with those with the CC or CT genotypes (p=0.04).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TT genotype and T allele of the STAT6 rs324011 polymorphism may be associated with increased susceptibility to pediatric asthma among Yemeni children.\u003c/p\u003e","manuscriptTitle":"Association of STAT6 Gene Polymorphism with Atopic Asthma among Yemeni Children in Sana'a City, Yemen","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:58:27","doi":"10.21203/rs.3.rs-5588927/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-07T05:22:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-04T11:11:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-04T10:42:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147617065522777165586894923347697625130","date":"2025-04-03T15:30:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32952710627041579731368347006547507755","date":"2025-04-02T09:30:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-02T08:25:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-29T17:42:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"43841022066594730984734633146371980604","date":"2025-03-28T11:29:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38934464177846031861490391606229059841","date":"2025-03-28T08:39:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132883959214753795466068564192735347873","date":"2025-03-28T08:08:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224371796459868587300126690268683722681","date":"2025-03-28T08:04:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-28T08:00:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-28T07:57:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-26T04:31:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-26T03:04:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-03-25T13:30:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7a7f8656-7577-4bfa-9dba-110397814b75","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-19T16:03:15+00:00","versionOfRecord":{"articleIdentity":"rs-5588927","link":"https://doi.org/10.1186/s12887-025-05710-9","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2025-05-15 15:56:59","publishedOnDateReadable":"May 15th, 2025"},"versionCreatedAt":"2025-03-31 11:58:27","video":"","vorDoi":"10.1186/s12887-025-05710-9","vorDoiUrl":"https://doi.org/10.1186/s12887-025-05710-9","workflowStages":[]},"version":"v1","identity":"rs-5588927","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5588927","identity":"rs-5588927","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}