Dioxins (eg, 2,3,7,8-tetrachlorodibenzo-p-dioxin/TCDD), as environmental endocrine disruptors and toxic carcinogens, can affect male reproductive health. The influence of dioxins is mediated via the aryl hydrocarbon receptor (AhR) pathway and its repressor (AhRR). In this study, we investigated the association of AhRR-c.565C>G transversion polymorphism with male infertility. In a hospital-based case-control study, 221 semen samples (111 infertile and 110 healthy controls) based on World Health Organization guidelines were collected from in vitro fertilization centers of Babol, Iran. The AhRR-c.565C>G (rs2292596) polymorphism was genotyped using a polymerase chain reaction-restriction fragment length polymorphism analysis. The difference in the allele frequency of AhRR-c.565C>G transversion polymorphism did not reach a significant level. The genotype frequency was statistically significantly different between fertile and infertile men. We found that polymorphism rs2292596 (Pro185Ala) was statistically significantly associated with the risk of male infertility. In addition, the statistical difference became more significant when the frequency was compared between the Pro/Pro genotype and the Pro/Ala plus Ala/Ala genotype. The 185 Pro wild-type alleles of AhRR may be associated with the risk of male infertility. The proallele also may diminish inhibition of AhR-mediated signaling of exposure to environmental pollutants.
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http://dx.doi.org/10.1002/jcb.28171 | DOI Listing |
Subst Abuse Rehabil
January 2025
Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al Qura University, Makkah, Saudi Arabia.
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November 2024
university of belgrade, faculty of biology, centre for human molecular genetic.
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Reprod Health
January 2025
Department of Psychiatry, Renmin Hospital of Wuhan University, Institute of Neuropsychiatry, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
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View Article and Find Full Text PDFSyst Biol Reprod Med
December 2025
Department of Mathematics and Computer Science, Laboratory of Analysis, Modeling and Simulation, Faculty of Sciences Ben M'sik, Hassan II University of Casablanca, Casablanca, Morocco.
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this study is to build Machine learning (ML) decision-support models to predict the optimal range of embryo numbers to transfer, using data from infertile couples identified through literature reviews.
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