Association of CYP1A1 Rs1048943 Polymorphism with Male Infertility: A Study in East Azerbaijan, Iran

Association of CYP1A1 Rs1048943 Polymorphism with Male Infertility: A Study in East Azerbaijan, Iran | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of CYP1A1 Rs1048943 Polymorphism with Male Infertility: A Study in East Azerbaijan, Iran Ronaz Mostafaei, Masoud Maleki, Omid Pourbagherian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6722600/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Infertility is a disease of the reproductive system that is defined as non-pregnancy after 46 months of regular sexual intercourse without the use of contraceptive methods. Male infertility occurs in approximately 45% of couples. Various environmental and genetic factors play a role in male infertility. Among the genes involved in male infertility is the CYP1A1 gene, whose various polymorphisms are involved in infertility, including asthenospermia, which is one of the most important polymorphisms related to this polymorphic gene RS1048943. In this study, these polymorphisms in infertile men in northwestern Iran have been investigated. Methods For this purpose, sperm samples were prepared from Tabriz University Jihad Center and then DNA extraction was performed. Among the extracted DNAs, each sample of the desired quality was stored for other steps. Tetra ARMS PCR was used to study these polymorphisms. To perform PCR using primers designed for this gene, the desired region was amplified and after running on the gel, the genotypes were determined based on the obtained bands and statistical analyzes were performed using Excell software. P < 0.05 was significant. Results According to statistical studies, the percent of TT, AA and AT genotypes in the patient group was 52%, 4% and 44%, respectively, and the percent of genotypes in the control group was 32%, 52% and 16%, respectively. Discussion According to the results, genotypic frequency in the patient and control groups was insignificant and also the amount of allelic frequency in the patient and control groups was also insignificant. Male infertility CYP1A1 gene rs1048943 polymorphism Figures Figure 1 Introduction Infertility is a major global health issue, affecting approximately 15% of couples worldwide who are trying to conceive. Male infertility is a contributing factor in up to 20% of cases directly and accounts for an additional 30–40% of infertility cases when combined with female factors ( 1 ). This makes male infertility a significant public health challenge, especially given its increasing prevalence due to declining sperm counts and quality observed in industrialized nations ( 2 ). Currently, 5–7% of the global male population experiences infertility, a figure projected to rise due to environmental exposures, lifestyle factors, and underlying health conditions. Despite remarkable advances in understanding human reproductive physiology, the primary cause of male infertility remains undetermined in approximately 50% of cases, often categorized as idiopathic infertility ( 3 ). Idiopathic male infertility, which accounts for a significant proportion of unexplained reproductive failure, is widely believed to have a strong genetic foundation ( 4 ). Spermatogenesis, the highly complex and tightly regulated process of sperm cell production, is governed by the coordinated expression of over 1,000 genes ( 5 ). These genes regulate critical stages, including germ cell proliferation, meiosis, and differentiation, emphasizing the potential for genetic involvement in unexplained infertility cases. Despite this, much of the genetic landscape contributing to male infertility remains undiscovered ( 6 ). A few key genes have been definitively associated with specific forms of male infertility. For example, mutations in the CFTR gene are linked to congenital absence of the vas deferens, a condition commonly observed in men with cystic fibrosis ( 7 ). Similarly, mutations in the androgen receptor (AR) gene can lead to androgen insensitivity syndrome, which disrupts spermatogenesis due to hormonal signaling deficiencies. However, these known genetic causes represent only a small fraction of the genetic underpinnings of male infertility ( 8 ). The cytochrome P450 (CYP) family of enzymes plays a crucial role in the metabolism of a wide array of endogenous and exogenous compounds, including hormones, xenobiotics, and environmental pollutants. These enzymes are involved in the phase I metabolic pathway, where they catalyze oxidation reactions, making hydrophobic compounds more water-soluble and, thus, more readily excreted. Among the CYP family, the CYP1A1 gene stands out due to its critical involvement in the biotransformation of polycyclic aromatic hydrocarbons (PAHs), a class of environmental pollutants commonly found in tobacco smoke, industrial emissions, and charred foods ( 9 ). Located on chromosome 15q22-q24, the CYP1A1 gene encodes an enzyme that activates PAHs into their reactive intermediates. While this metabolic activity is essential for detoxification, it paradoxically also generates reactive oxygen species (ROS) and electrophilic intermediates, which can bind to DNA and proteins, causing cellular damage ( 10 ). These reactive byproducts are particularly harmful to cells undergoing rapid division and differentiation, such as those involved in spermatogenesis. This process is highly sensitive to oxidative stress and DNA damage, both of which can impair the production of viable, motile sperm, contributing to male infertility. One of the most studied genetic variations in the CYP1A1 gene is the rs1048943 polymorphism ( 11 ). This single nucleotide polymorphism (SNP), characterized by an A→G substitution in exon 7, results in an amino acid change from isoleucine to valine at codon 462. This structural alteration significantly impacts the enzyme's function by increasing its metabolic activity. The heightened enzymatic activity enhances the bioactivation of PAHs, leading to an elevated generation of ROS. Although ROS play a physiological role at low levels, excessive production overwhelms the antioxidant defense mechanisms in the testes, resulting in oxidative stress ( 12 ). Oxidative stress is a major contributor to male infertility, as it damages sperm DNA, proteins, and membranes, reducing sperm motility and viability ( 13 ). ROS can disrupt the integrity of the sperm cell membrane, which is rich in polyunsaturated fatty acids and, thus, particularly susceptible to lipid peroxidation. Furthermore, ROS-induced DNA fragmentation in sperm cells can lead to impaired fertilization and embryonic development, increasing the risk of miscarriage. Studies have shown that individuals carrying the polymorphic variant of rs1048943 have higher levels of PAH-DNA adducts, a marker of oxidative DNA damage, in their reproductive tissues, further linking this SNP to adverse reproductive outcomes ( 14 ). The prevalence of the rs1048943 polymorphism varies across populations ( 15 ). It is notably higher in Asian populations, where it has been extensively studied in the context of various cancers and other diseases associated with oxidative stress. In these populations, the polymorphism has also been linked to altered reproductive outcomes, including impaired spermatogenesis and reduced sperm quality. However, the relationship between rs1048943 and male infertility remains underexplored in other populations, including those in the Middle East, where genetic and environmental factors may interact uniquely ( 11 ). Given its potential role as a genetic susceptibility factor, the rs1048943 polymorphism represents an important area of research in the context of male infertility ( 16 ). Investigating its prevalence and impact can provide insights into the molecular mechanisms underlying infertility and pave the way for more targeted approaches to diagnosis and treatment, particularly in regions with high exposure to environmental toxins. By understanding the interactions between genetic predispositions like CYP1A1 polymorphisms and environmental exposures, researchers can better address the growing public health challenge of infertility ( 17 , 18 ). Several studies have investigated the potential association between CYP1A1 polymorphisms and male infertility, yielding mixed results. Some research suggests that individuals carrying the polymorphic variant of rs1048943 may be at a higher risk for infertility due to increased oxidative stress and impaired spermatogenesis ( 19 ). However, other studies have reported no significant association, indicating that environmental and genetic interactions may play a critical role in determining susceptibility ( 20 ). The prevalence of the rs1048943 polymorphism varies significantly across populations, with higher frequencies reported in Asian populations compared to Western populations ( 21 ). This highlights the importance of population-specific studies to better understand the genetic basis of male infertility. East Azerbaijan, located in Northwest Iran, represents a unique population with diverse genetic backgrounds and environmental exposures. Despite the high burden of male infertility in this region, limited studies have explored the genetic factors contributing to this condition. By investigating the rs1048943 polymorphism of the CYP1A1 gene in infertile men from this population, this study aims to shed light on its potential role as a genetic risk factor for male infertility. Using a case-control design, we compare the genotypic and allelic frequencies of this polymorphism between infertile and fertile men, providing valuable insights into its association with reproductive health outcomes. The findings from this study will contribute to the growing body of evidence on the genetic and environmental determinants of male infertility. Understanding the role of CYP1A1 polymorphisms in infertility could pave the way for targeted interventions, such as genetic screening, lifestyle modifications, and personalized treatment strategies. Furthermore, this research underscores the importance of investigating gene-environment interactions in reproductive health, particularly in regions with unique environmental and genetic profiles. Materials and Methods Sample Collection This study was conducted using sperm samples obtained from the Infertility Center at Jahad Daneshgahi, Northwest Iran. Fifty infertile men were recruited as the case group. Control samples were collected from fertile men with confirmed fertility, as validated by the infertility center. The fertile participants had no history of infertility-related conditions, and their semen analysis indicated normal parameters. DNA extraction DNA was extracted from sperm samples using the FAVERGEN kit. After centrifugation, the pellet was treated with TBE buffer, proteinase K, FABG buffer, and ethanol. The solution was passed through a mini-column, washed with W1 and Wash buffers, and dried via centrifugation. Finally, DNA was eluted with preheated elution buffer and stored at -20°C for further analysis. Assessment of DNA Quality and Quantity The quality and quantity of the extracted DNA were evaluated using spectrophotometry and agarose gel electrophoresis. The absence of smearing and contamination confirmed the suitability of the DNA for subsequent analysis. Primer Design Specific primers for Tetra-ARMS PCR were designed to target the rs1048943 polymorphism in the CYP1A1 gene. Primer design was performed using OLIGO7 and GENERUNNER software to ensure specificity and complementarity to the target DNA sequence. Primer binding specificity was validated through the NCBI Primer-BLAST tool. Primer sequences are available from the authors upon request. Genotyping The rs1048943 polymorphism was analyzed using the Tetra-ARMS PCR method, which involves four primers to detect single nucleotide polymorphisms (SNPs). PCR was carried out in a thermocycler, and the products were separated via agarose gel electrophoresis. The genotypes were identified based on specific banding patterns observed under UV illumination. Statistical Analysis Data analysis was performed using SPSS software. Genotypic and allelic frequencies were compared between the case and control groups using appropriate statistical tests. A p-value < 0.05 was considered statistically significant. The results were interpreted to determine any association between the rs1048943 polymorphism and male infertility. Results 3 − 1. Statistical Analysis of Genotypes Based on the analyzed data, in the patient group, 52% had the homozygous TT genotype, 44% had the heterozygous TA genotype, and 4% had the homozygous AA genotype. In the control group, 32% had the homozygous TT genotype, 52% had the heterozygous TA genotype, and 16% had the homozygous AA genotype. According to this data, no significant difference was observed between the control and patient groups (p > 0.05) (Table 2 )(Fig. 1 , A) Table 2 Genotypic Frequency in Patient and Control Groups, Chi-square (χ²) goodness-of-fit test dbSNP Genotypes/allelRCHA Case(n = 25) Control(n = 25) OR (95%CI) p-value Codominant TT 13(52%) 8(32%) Ref - TA 11(44%) 13(52%) 1.920(0.583–6.324) 0.281 AA 1(4%) 4(16%) 6.500(0.613-68-957) 0.091 Dominant TT 13(52%) 8(32%) Ref 0.152 TA + AA 12(48%) 17(68%) 2.302(0.729–7.268) Recessive TT + TA 24(96%) 21(84%) Ref 0.157 AA 1(4%) 4(16%) 4.571(0.473–44.170) Overdominant TT + AA 14(56%) 12(48%) Ref 0.571 TA 11(44%) 13(52%) 1.379(0.453–4.197) Chi-Square Test for Genotypic Analysis The chi-square test results for genotypic frequency between the control and patient groups showed a p-value greater than 0.05, indicating no significant difference between the two groups (Table 3 ). Table 3 Chi-Square Test Results for Genotypic Frequency, Chi-square (χ²) goodness-of-fit test Value df Asymptotic Significance (2-sided) Pearson Chi-Square 3.1571 2 0.20627 Allelic Frequency in Control and Patient Groups Based on the analyzed data, the patient group showed 74% allele A and 26% allele T, while the control group showed 58% allele A and 42% allele T. The p-value for allelic frequency was greater than 0.05, indicating no significant difference in allelic frequency between the control and patient groups (Table 4 ),(Fig. 1 , B) Table 4 Allelic Frequency in Patient and Control Groups, Chi-square (χ²) goodness-of-fit test dbSNP Allele Case(n = 50) Control(n = 50) OR (95%CI) p-value ALLELE A 37(74%) 29(58%) Ref 0.091 T 13(26%) 21(42%) 2.061(0.885-4.800) Chi-Square Test Results for Allelic Frequency The Pearson chi-square test for Hardy-Weinberg equilibrium yielded a p-value greater than 0.05, indicating no significant difference in allelic frequency between the two groups (Table 5 ), (Fig. 1 ,C) Table 5 Chi-Square Test Results for Allelic Frequency, Chi-square (χ²) goodness-of-fit test Value df Asymptotic Significance (2-sided) Pearson Chi-Square 2.852 2 0.091258 Results of Hardy-Weinberg Equilibrium Analysis The comparison of observed genotypic frequencies between the patient and control groups with the expected frequencies showed a p-value of 0.7732, which is greater than 0.05, indicating that Hardy-Weinberg equilibrium is maintained. Table 6 Hardy–Weinberg Equilibrium of Genotypic Frequencies in Patient and Control Groups (p = 0.7732), Statistical test: Chi-square (χ²) goodness-of-fit test Genotype Observed Frequency (%) Observed Frequency Expected Frequency (%) Expected Frequency TT 13 52 14 56 TA 11 44 10 40 AA 1 4 1 4 Total 25 100 25 100 Discussion Infertility is defined as the inability to achieve pregnancy after 12 months of unprotected intercourse, affecting 10–15% of couples in the United States ( 21 ). Male infertility accounts for approximately 30–55% of all infertility cases. Azoospermia, the absence of sperm in the ejaculate, constitutes 10–15% of male infertility cases and affects about 1% of the male population ( 22 ). Among the critical mechanisms explored in genetic studies is the role of cytochrome P4501A1 (CYP1A1), which plays a significant role in Phase I metabolism of polycyclic aromatic hydrocarbons (PAHs) into biologically active intermediates ( 23 ). These intermediates can potentially impact male fertility. CYP1A1 is involved in metabolizing substrates through the catalysis of β-estradiol hydroxylation at the C-2 position. PAH metabolites can form DNA adducts, which in sperm cells may lead to severe DNA damage and disruptions in meiosis during spermatogenesis. This has been linked to male infertility ( 24 ). Recent studies suggest that CYP1A12C genetic polymorphisms, which influence xenobiotic metabolism, might play a crucial role in male infertility. The rs1048943 CYP1A12C polymorphism involves an A-to-T substitution at nucleotide 2455, resulting in an amino acid change from isoleucine to valine at codon 462 in exon 7 ( 25 ). This polymorphism is more common in Asian populations. Various studies highlight the importance of this polymorphism in influencing male reproductive health. CYP1A1 serves as a key enzyme in activating PAHs, which exhibit reproductive toxicity and are linked to male infertility risk ( 26 ). Male reproductive functions can be affected by numerous environmental, physiological, and genetic factors. Most environmental factors are xenobiotics. These xenobiotics exert adverse effects via covalent interactions between intermediate metabolites and cellular macromolecules like DNA and proteins. These compounds are metabolized by CYP1A1, which can also induce enzyme activity. Apart from xenobiotic metabolism, CYP1A1 participates in testosterone inactivation, potentially influencing testicular function. However, the relationship between genetic variability in xenobiotic metabolism and male reproductive functions remains underexplored ( 27 ). The interplay between environmental and genetic factors in infertility is not fully understood. In this study, we examined the frequency of the CYP1A1 single nucleotide polymorphism in infertile men. The results showed no significant difference in the genotypic frequency of the rs1048943 polymorphism between infertile and fertile men. Similarly, there was no significant association between allelic frequency of this polymorphism and male infertility. In contrast, Gudimella Tirumala Vani et al. investigated this polymorphism in infertile men in Yazd and found that individuals carrying the CYP1A1*2A CC allele had an increased risk of infertility ( 28 ). These discrepancies could be attributed to differences in the studied populations and sample size. Zakieh Javidan et al. reported an association between the CYP1A1 2A polymorphism and azoospermia, suggesting that this single nucleotide polymorphism may play a significant role in male infertility. They proposed that the CYP1A1 2A CC genotype could be recognized as an effective agent in azoospermia, although its precise function depends on interactions with other genetic and environmental factors. Their findings highlight the importance of further molecular studies to better understand the genetic mechanisms underlying male infertility, particularly at other genetic levels and in different populations ( 29 ). Recently, the critical role of estrogen in male infertility has been highlighted. Estrogens are metabolized by CYP1A1, which converts them into catechol estrogens, such as 2-hydroxyestradiol and 4-hydroxyestradiol. CYP1A1 also plays a role in metabolizing xenobiotics and activating environmental toxins. A complex interplay exists between CYP1A1, estrogen receptor alpha, and the aryl hydrocarbon receptor, which exhibits anti-estrogenic properties ( 30 ). CYP1A1 expression is induced by various endogenous and exogenous chemicals via the aryl hydrocarbon receptor. Additionally, CYP1A1 interacts with estrogen receptor alpha and the aryl hydrocarbon receptor to influence gene expression. Polymorphisms in CYP1A1 can alter enzyme activity and expression, potentially leading to reproductive disorders in men ( 31 ). Furthermore, the association of CYP1A1 and estrogen polymorphisms with disruptions in spermatogenesis suggests that genetic and environmental factors play critical roles in testicular dysfunction, ultimately causing sperm damage, abnormal morphology, and male infertility. Conclusion While our findings do not support a significant role for the rs1048943 polymorphism in male infertility, they highlight the importance of population-specific studies. Further research, particularly large-scale and multi-ethnic studies, is needed to clarify the role of CYP1A1 polymorphisms and their interaction with environmental and physiological factors in male infertility. This will help bridge the gaps in understanding the complex relationship between genetic variability and reproductive health. Declarations Ethics approval statement: This study was approved by the Ethics Committee of Tabriz Azad University (approval ID: IR.IAU,TABRIZ.REC.1399.094). All participants provided written informed consent prior to inclusion in the study, in accordance with the Declaration of Helsinki. Acknowledgments Authors extend their appreciation to the staff and researchers at the Infertility Center at Jahad Daneshgahi, Tabriz, for their cooperation and for providing the sperm samples used in this study. Author contributions All authors approved the final manuscript. Funding Not applicable Competing interests The authors declare that they have no competing interests References Eisenberg ML, Esteves SC, Lamb DJ, Hotaling JM, Giwercman A, Hwang K, Cheng Y-S. Male infertility. Nature Reviews Disease Primers. 2023;9(1):49. Kumar N, Singh AK. Impact of environmental factors on human semen quality and male fertility: a narrative review. Environmental Sciences Europe. 2022;34:1-13. 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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-6722600","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":460406864,"identity":"b9d2b378-eab1-43fe-b463-75a4b6fa57e2","order_by":0,"name":"Ronaz Mostafaei","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Ronaz","middleName":"","lastName":"Mostafaei","suffix":""},{"id":460406865,"identity":"9c86c7e3-93a9-4e24-aa38-a0b50125636b","order_by":1,"name":"Masoud Maleki","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Masoud","middleName":"","lastName":"Maleki","suffix":""},{"id":460406866,"identity":"0b1ec9c2-4210-4649-9b8e-fb274cdcd2b4","order_by":2,"name":"Omid Pourbagherian","email":"data:image/png;base64,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","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Omid","middleName":"","lastName":"Pourbagherian","suffix":""}],"badges":[],"createdAt":"2025-05-22 08:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6722600/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6722600/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84670144,"identity":"32699b13-164c-40d8-9680-d401a049a445","added_by":"auto","created_at":"2025-06-16 06:35:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":257604,"visible":true,"origin":"","legend":"\u003cp\u003eA–C: (A) Genotypic frequency percentages in patient and control groups;\u003cbr\u003e\n(B) Allelic frequency percentages in patient and control groups;\u003cbr\u003e\n(C) Observed and expected genotypic frequency percentages.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6722600/v1/b90610f40e517501cec7dce3.png"},{"id":85229784,"identity":"53e4745e-421e-41c4-8c31-f146fc3e9d8f","added_by":"auto","created_at":"2025-06-23 15:47:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":953099,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6722600/v1/7024b535-9608-4c20-a8b6-949e516e1b7b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of CYP1A1 Rs1048943 Polymorphism with Male Infertility: A Study in East Azerbaijan, Iran","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInfertility is a major global health issue, affecting approximately 15% of couples worldwide who are trying to conceive. Male infertility is a contributing factor in up to 20% of cases directly and accounts for an additional 30\u0026ndash;40% of infertility cases when combined with female factors (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This makes male infertility a significant public health challenge, especially given its increasing prevalence due to declining sperm counts and quality observed in industrialized nations (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Currently, 5\u0026ndash;7% of the global male population experiences infertility, a figure projected to rise due to environmental exposures, lifestyle factors, and underlying health conditions. Despite remarkable advances in understanding human reproductive physiology, the primary cause of male infertility remains undetermined in approximately 50% of cases, often categorized as idiopathic infertility (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIdiopathic male infertility, which accounts for a significant proportion of unexplained reproductive failure, is widely believed to have a strong genetic foundation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Spermatogenesis, the highly complex and tightly regulated process of sperm cell production, is governed by the coordinated expression of over 1,000 genes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These genes regulate critical stages, including germ cell proliferation, meiosis, and differentiation, emphasizing the potential for genetic involvement in unexplained infertility cases. Despite this, much of the genetic landscape contributing to male infertility remains undiscovered (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA few key genes have been definitively associated with specific forms of male infertility. For example, mutations in the CFTR gene are linked to congenital absence of the vas deferens, a condition commonly observed in men with cystic fibrosis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Similarly, mutations in the androgen receptor (AR) gene can lead to androgen insensitivity syndrome, which disrupts spermatogenesis due to hormonal signaling deficiencies. However, these known genetic causes represent only a small fraction of the genetic underpinnings of male infertility (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe cytochrome P450 (CYP) family of enzymes plays a crucial role in the metabolism of a wide array of endogenous and exogenous compounds, including hormones, xenobiotics, and environmental pollutants. These enzymes are involved in the phase I metabolic pathway, where they catalyze oxidation reactions, making hydrophobic compounds more water-soluble and, thus, more readily excreted. Among the CYP family, the CYP1A1 gene stands out due to its critical involvement in the biotransformation of polycyclic aromatic hydrocarbons (PAHs), a class of environmental pollutants commonly found in tobacco smoke, industrial emissions, and charred foods (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLocated on chromosome 15q22-q24, the CYP1A1 gene encodes an enzyme that activates PAHs into their reactive intermediates. While this metabolic activity is essential for detoxification, it paradoxically also generates reactive oxygen species (ROS) and electrophilic intermediates, which can bind to DNA and proteins, causing cellular damage (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). These reactive byproducts are particularly harmful to cells undergoing rapid division and differentiation, such as those involved in spermatogenesis. This process is highly sensitive to oxidative stress and DNA damage, both of which can impair the production of viable, motile sperm, contributing to male infertility.\u003c/p\u003e \u003cp\u003eOne of the most studied genetic variations in the CYP1A1 gene is the rs1048943 polymorphism (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This single nucleotide polymorphism (SNP), characterized by an A\u0026rarr;G substitution in exon 7, results in an amino acid change from isoleucine to valine at codon 462. This structural alteration significantly impacts the enzyme's function by increasing its metabolic activity. The heightened enzymatic activity enhances the bioactivation of PAHs, leading to an elevated generation of ROS. Although ROS play a physiological role at low levels, excessive production overwhelms the antioxidant defense mechanisms in the testes, resulting in oxidative stress (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxidative stress is a major contributor to male infertility, as it damages sperm DNA, proteins, and membranes, reducing sperm motility and viability (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). ROS can disrupt the integrity of the sperm cell membrane, which is rich in polyunsaturated fatty acids and, thus, particularly susceptible to lipid peroxidation. Furthermore, ROS-induced DNA fragmentation in sperm cells can lead to impaired fertilization and embryonic development, increasing the risk of miscarriage. Studies have shown that individuals carrying the polymorphic variant of rs1048943 have higher levels of PAH-DNA adducts, a marker of oxidative DNA damage, in their reproductive tissues, further linking this SNP to adverse reproductive outcomes (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe prevalence of the rs1048943 polymorphism varies across populations (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). It is notably higher in Asian populations, where it has been extensively studied in the context of various cancers and other diseases associated with oxidative stress. In these populations, the polymorphism has also been linked to altered reproductive outcomes, including impaired spermatogenesis and reduced sperm quality. However, the relationship between rs1048943 and male infertility remains underexplored in other populations, including those in the Middle East, where genetic and environmental factors may interact uniquely (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven its potential role as a genetic susceptibility factor, the rs1048943 polymorphism represents an important area of research in the context of male infertility (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Investigating its prevalence and impact can provide insights into the molecular mechanisms underlying infertility and pave the way for more targeted approaches to diagnosis and treatment, particularly in regions with high exposure to environmental toxins. By understanding the interactions between genetic predispositions like CYP1A1 polymorphisms and environmental exposures, researchers can better address the growing public health challenge of infertility (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies have investigated the potential association between CYP1A1 polymorphisms and male infertility, yielding mixed results. Some research suggests that individuals carrying the polymorphic variant of rs1048943 may be at a higher risk for infertility due to increased oxidative stress and impaired spermatogenesis (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). However, other studies have reported no significant association, indicating that environmental and genetic interactions may play a critical role in determining susceptibility (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The prevalence of the rs1048943 polymorphism varies significantly across populations, with higher frequencies reported in Asian populations compared to Western populations (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This highlights the importance of population-specific studies to better understand the genetic basis of male infertility.\u003c/p\u003e \u003cp\u003eEast Azerbaijan, located in Northwest Iran, represents a unique population with diverse genetic backgrounds and environmental exposures. Despite the high burden of male infertility in this region, limited studies have explored the genetic factors contributing to this condition. By investigating the rs1048943 polymorphism of the CYP1A1 gene in infertile men from this population, this study aims to shed light on its potential role as a genetic risk factor for male infertility. Using a case-control design, we compare the genotypic and allelic frequencies of this polymorphism between infertile and fertile men, providing valuable insights into its association with reproductive health outcomes.\u003c/p\u003e \u003cp\u003eThe findings from this study will contribute to the growing body of evidence on the genetic and environmental determinants of male infertility. Understanding the role of CYP1A1 polymorphisms in infertility could pave the way for targeted interventions, such as genetic screening, lifestyle modifications, and personalized treatment strategies. Furthermore, this research underscores the importance of investigating gene-environment interactions in reproductive health, particularly in regions with unique environmental and genetic profiles.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample Collection\u003c/h2\u003e \u003cp\u003eThis study was conducted using sperm samples obtained from the Infertility Center at Jahad Daneshgahi, Northwest Iran. Fifty infertile men were recruited as the case group. Control samples were collected from fertile men with confirmed fertility, as validated by the infertility center. The fertile participants had no history of infertility-related conditions, and their semen analysis indicated normal parameters.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003eDNA was extracted from sperm samples using the FAVERGEN kit. After centrifugation, the pellet was treated with TBE buffer, proteinase K, FABG buffer, and ethanol. The solution was passed through a mini-column, washed with W1 and Wash buffers, and dried via centrifugation. Finally, DNA was eluted with preheated elution buffer and stored at -20\u0026deg;C for further analysis.\u003c/p\u003e\n\u003ch3\u003eAssessment of DNA Quality and Quantity\u003c/h3\u003e\n\u003cp\u003eThe quality and quantity of the extracted DNA were evaluated using spectrophotometry and agarose gel electrophoresis. The absence of smearing and contamination confirmed the suitability of the DNA for subsequent analysis.\u003c/p\u003e\n\u003ch3\u003ePrimer Design\u003c/h3\u003e\n\u003cp\u003eSpecific primers for Tetra-ARMS PCR were designed to target the rs1048943 polymorphism in the CYP1A1 gene. Primer design was performed using OLIGO7 and GENERUNNER software to ensure specificity and complementarity to the target DNA sequence. Primer binding specificity was validated through the NCBI Primer-BLAST tool. Primer sequences are available from the authors upon request.\u003c/p\u003e\n\u003ch3\u003eGenotyping\u003c/h3\u003e\n\u003cp\u003eThe rs1048943 polymorphism was analyzed using the Tetra-ARMS PCR method, which involves four primers to detect single nucleotide polymorphisms (SNPs). PCR was carried out in a thermocycler, and the products were separated via agarose gel electrophoresis. The genotypes were identified based on specific banding patterns observed under UV illumination.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData analysis was performed using SPSS software. Genotypic and allelic frequencies were compared between the case and control groups using appropriate statistical tests. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. The results were interpreted to determine any association between the rs1048943 polymorphism and male infertility.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;1. Statistical Analysis of Genotypes\u003c/h2\u003e \u003cp\u003eBased on the analyzed data, in the patient group, 52% had the homozygous TT genotype, 44% had the heterozygous TA genotype, and 4% had the homozygous AA genotype. In the control group, 32% had the homozygous TT genotype, 52% had the heterozygous TA genotype, and 16% had the homozygous AA genotype. According to this data, no significant difference was observed between the control and patient groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e)(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, A)\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGenotypic Frequency in Patient and Control Groups, Chi-square (χ\u0026sup2;) goodness-of-fit test\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003edbSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotypes/allelRCHA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase(n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl(n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCodominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\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=\"c2\"\u003e \u003cp\u003eTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.920(0.583\u0026ndash;6.324)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.500(0.613-68-957)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTA\u0026thinsp;+\u0026thinsp;AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.302(0.729\u0026ndash;7.268)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRecessive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT\u0026thinsp;+\u0026thinsp;TA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.571(0.473\u0026ndash;44.170)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverdominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT\u0026thinsp;+\u0026thinsp;AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.379(0.453\u0026ndash;4.197)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChi-Square Test for Genotypic Analysis\u003c/h2\u003e \u003cp\u003eThe chi-square test results for genotypic frequency between the control and patient groups showed a p-value greater than 0.05, indicating no significant difference between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChi-Square Test Results for Genotypic Frequency, Chi-square (χ\u0026sup2;) goodness-of-fit test\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymptotic Significance (2-sided)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePearson Chi-Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20627\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAllelic Frequency in Control and Patient Groups\u003c/h2\u003e \u003cp\u003eBased on the analyzed data, the patient group showed 74% allele A and 26% allele T, while the control group showed 58% allele A and 42% allele T. The p-value for allelic frequency was greater than 0.05, indicating no significant difference in allelic frequency between the control and patient groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e),(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, B)\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 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllelic Frequency in Patient and Control Groups, Chi-square (χ\u0026sup2;) goodness-of-fit test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003edbSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\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=\"1\" rowspan=\"2\"\u003e \u003cp\u003eALLELE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.061(0.885-4.800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eChi-Square Test Results for Allelic Frequency\u003c/h2\u003e \u003cp\u003eThe Pearson chi-square test for Hardy-Weinberg equilibrium yielded a p-value greater than 0.05, indicating no significant difference in allelic frequency between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e), (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,C)\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 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChi-Square Test Results for Allelic Frequency, Chi-square (χ\u0026sup2;) goodness-of-fit test\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymptotic Significance (2-sided)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePearson Chi-Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.091258\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eResults of Hardy-Weinberg Equilibrium Analysis\u003c/h2\u003e \u003cp\u003eThe comparison of observed genotypic frequencies between the patient and control groups with the expected frequencies showed a p-value of 0.7732, which is greater than 0.05, indicating that Hardy-Weinberg equilibrium is maintained.\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 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHardy\u0026ndash;Weinberg Equilibrium of Genotypic Frequencies in Patient and Control Groups (p\u0026thinsp;=\u0026thinsp;0.7732), Statistical test: Chi-square (χ\u0026sup2;) goodness-of-fit test\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved Frequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObserved Frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExpected Frequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExpected Frequency\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eInfertility is defined as the inability to achieve pregnancy after 12 months of unprotected intercourse, affecting 10\u0026ndash;15% of couples in the United States (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Male infertility accounts for approximately 30\u0026ndash;55% of all infertility cases. Azoospermia, the absence of sperm in the ejaculate, constitutes 10\u0026ndash;15% of male infertility cases and affects about 1% of the male population (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the critical mechanisms explored in genetic studies is the role of cytochrome P4501A1 (CYP1A1), which plays a significant role in Phase I metabolism of polycyclic aromatic hydrocarbons (PAHs) into biologically active intermediates (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). These intermediates can potentially impact male fertility. CYP1A1 is involved in metabolizing substrates through the catalysis of β-estradiol hydroxylation at the C-2 position. PAH metabolites can form DNA adducts, which in sperm cells may lead to severe DNA damage and disruptions in meiosis during spermatogenesis. This has been linked to male infertility (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent studies suggest that CYP1A12C genetic polymorphisms, which influence xenobiotic metabolism, might play a crucial role in male infertility. The rs1048943 CYP1A12C polymorphism involves an A-to-T substitution at nucleotide 2455, resulting in an amino acid change from isoleucine to valine at codon 462 in exon 7 (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This polymorphism is more common in Asian populations. Various studies highlight the importance of this polymorphism in influencing male reproductive health. CYP1A1 serves as a key enzyme in activating PAHs, which exhibit reproductive toxicity and are linked to male infertility risk (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMale reproductive functions can be affected by numerous environmental, physiological, and genetic factors. Most environmental factors are xenobiotics. These xenobiotics exert adverse effects via covalent interactions between intermediate metabolites and cellular macromolecules like DNA and proteins. These compounds are metabolized by CYP1A1, which can also induce enzyme activity. Apart from xenobiotic metabolism, CYP1A1 participates in testosterone inactivation, potentially influencing testicular function. However, the relationship between genetic variability in xenobiotic metabolism and male reproductive functions remains underexplored (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The interplay between environmental and genetic factors in infertility is not fully understood.\u003c/p\u003e \u003cp\u003eIn this study, we examined the frequency of the CYP1A1 single nucleotide polymorphism in infertile men. The results showed no significant difference in the genotypic frequency of the rs1048943 polymorphism between infertile and fertile men. Similarly, there was no significant association between allelic frequency of this polymorphism and male infertility.\u003c/p\u003e \u003cp\u003eIn contrast, Gudimella Tirumala Vani et al. investigated this polymorphism in infertile men in Yazd and found that individuals carrying the CYP1A1*2A CC allele had an increased risk of infertility (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). These discrepancies could be attributed to differences in the studied populations and sample size.\u003c/p\u003e \u003cp\u003eZakieh Javidan et al. reported an association between the \u003cem\u003eCYP1A1\u003c/em\u003e2A polymorphism and azoospermia, suggesting that this single nucleotide polymorphism may play a significant role in male infertility. They proposed that the \u003cem\u003eCYP1A1\u003c/em\u003e2A CC genotype could be recognized as an effective agent in azoospermia, although its precise function depends on interactions with other genetic and environmental factors. Their findings highlight the importance of further molecular studies to better understand the genetic mechanisms underlying male infertility, particularly at other genetic levels and in different populations (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecently, the critical role of estrogen in male infertility has been highlighted. Estrogens are metabolized by CYP1A1, which converts them into catechol estrogens, such as 2-hydroxyestradiol and 4-hydroxyestradiol. CYP1A1 also plays a role in metabolizing xenobiotics and activating environmental toxins. A complex interplay exists between CYP1A1, estrogen receptor alpha, and the aryl hydrocarbon receptor, which exhibits anti-estrogenic properties (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). CYP1A1 expression is induced by various endogenous and exogenous chemicals via the aryl hydrocarbon receptor. Additionally, CYP1A1 interacts with estrogen receptor alpha and the aryl hydrocarbon receptor to influence gene expression. Polymorphisms in CYP1A1 can alter enzyme activity and expression, potentially leading to reproductive disorders in men (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Furthermore, the association of CYP1A1 and estrogen polymorphisms with disruptions in spermatogenesis suggests that genetic and environmental factors play critical roles in testicular dysfunction, ultimately causing sperm damage, abnormal morphology, and male infertility.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWhile our findings do not support a significant role for the rs1048943 polymorphism in male infertility, they highlight the importance of population-specific studies. Further research, particularly large-scale and multi-ethnic studies, is needed to clarify the role of \u003cem\u003eCYP1A1\u003c/em\u003e polymorphisms and their interaction with environmental and physiological factors in male infertility. This will help bridge the gaps in understanding the complex relationship between genetic variability and reproductive health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval statement: This study was approved by the Ethics Committee of Tabriz Azad University (approval ID: IR.IAU,TABRIZ.REC.1399.094). All participants provided written informed consent prior to inclusion in the study, in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors extend their appreciation to the staff and researchers at the Infertility Center at Jahad Daneshgahi, Tabriz, for their cooperation and for providing the sperm samples used in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEisenberg ML, Esteves SC, Lamb DJ, Hotaling JM, Giwercman A, Hwang K, Cheng Y-S. 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Polymorphisms in CYP1A1 gene are associated with male infertility in a Chinese population. Int J Androl. 2008;31(5):527-33.\u003c/li\u003e\n\u003cli\u003eVani GT, Mukesh N, Siva Prasad B, Rama Devi P, Hema Prasad M, Usha Rani P, Pardhanandana Reddy P. Association of CYP1A1*2A polymorphism with male infertility in Indian population. Clinica Chimica Acta. 2009;410(1):43-7.\u003c/li\u003e\n\u003cli\u003eLu J, Shang X, Zhong W, Xu Y, Shi R, Wang X. New insights of CYP1A in endogenous metabolism: a focus on single nucleotide polymorphisms and diseases. Acta Pharm Sin B. 2020;10(1):91-104.\u003c/li\u003e\n\u003cli\u003eVani GT, Mukesh N, Siva Prasad B, Rama Devi P, Hema Prasad M, Usha Rani P, Pardhanandana Reddy P. Association of CYP1A1*2A polymorphism with male infertility in Indian population. Clin Chim Acta. 2009;410(1-2):43-7.\u003c/li\u003e\n\u003cli\u003eJavidan Z, Ghasemi N, Ashrafzade HR. Frequency of CYP1A1 Gene Polymorphisms in Infertile Men with Non-obstructive Azoospermia. ssu-ijml. 2018;5(2):141-9.\u003c/li\u003e\n\u003cli\u003eRicci MS, Toscano DG, Mattingly CJ, Toscano WA. Estrogen Receptor Reduces CYP1A1 Induction in Cultured Human Endometrial Cells*. Journal of Biological Chemistry. 1999;274(6):3430-8.\u003c/li\u003e\n\u003cli\u003eNapoli N, Villareal DT, Mumm S, Halstead L, Sheikh S, Cagaanan M, et al. Effect of CYP1A1 gene polymorphisms on estrogen metabolism and bone density. J Bone Miner Res. 2005;20(2):232-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Male infertility, CYP1A1 gene, rs1048943, polymorphism","lastPublishedDoi":"10.21203/rs.3.rs-6722600/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6722600/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eInfertility is a disease of the reproductive system that is defined as non-pregnancy after 46 months of regular sexual intercourse without the use of contraceptive methods. Male infertility occurs in approximately 45% of couples. Various environmental and genetic factors play a role in male infertility. Among the genes involved in male infertility is the CYP1A1 gene, whose various polymorphisms are involved in infertility, including asthenospermia, which is one of the most important polymorphisms related to this polymorphic gene RS1048943. In this study, these polymorphisms in infertile men in northwestern Iran have been investigated.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFor this purpose, sperm samples were prepared from Tabriz University Jihad Center and then DNA extraction was performed. Among the extracted DNAs, each sample of the desired quality was stored for other steps. Tetra ARMS PCR was used to study these polymorphisms. To perform PCR using primers designed for this gene, the desired region was amplified and after running on the gel, the genotypes were determined based on the obtained bands and statistical analyzes were performed using Excell software. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was significant.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAccording to statistical studies, the percent of TT, AA and AT genotypes in the patient group was 52%, 4% and 44%, respectively, and the percent of genotypes in the control group was 32%, 52% and 16%, respectively.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eAccording to the results, genotypic frequency in the patient and control groups was insignificant and also the amount of allelic frequency in the patient and control groups was also insignificant.\u003c/p\u003e","manuscriptTitle":"Association of CYP1A1 Rs1048943 Polymorphism with Male Infertility: A Study in East Azerbaijan, Iran","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-16 06:35:46","doi":"10.21203/rs.3.rs-6722600/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"038bd2ea-78df-4b44-85ad-0a7bac152526","owner":[],"postedDate":"June 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-23T15:38:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-16 06:35:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6722600","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6722600","identity":"rs-6722600","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}