Association of CYP1B1 Gene Polymorphisms with Estrogen Receptor-Positive Breast Cancer at Aga Khan University Hospital, Nairobi, Kenya DOI: https://dx.doi.org/10.4314/ajhs.v37i2.1
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Abstract
BACKGROUND: Breast cancer is a significant global health challenge, and polymorphisms in the CYP1B1 gene have been associated with its risk. Given that the effects of genetic polymorphisms on breast cancer risk vary across populations, region-specific studies are crucial. This study assessed the associations of four CYP1B1 polymorphisms (rs10012, rs1056827, rs1056836, rs1800440) with estrogen receptor-positive breast cancer (ER+BC) risk in Kenyan women.
METHODOLOGY: A retrospective hospital-based case-control study involved 64 cases and 19 controls. Oversampling adjusted the case-control imbalance, increasing the control sample size to 60. DNA was extracted from buffy coat samples, and target regions were amplified and sequenced via Sanger sequencing. Sequences were analyzed using Geneious Prime for alignment, quality trimming, and SNP identification. Statistical analysis was performed using R (R 4.3.3).
RESULTS: The study identified significant associations between CYP1B1 polymorphisms and ER+BC risk. Specifically, the variant allele C and the codominant model (CC vs. GG) of rs10012, as well as the variant allele A, dominant (CA - CC vs. AA) and log-additive models of rs1056827, demonstrated a protective effect with ORs of 0.53 (p = 0.018, 95% CI: 0.31–0.90), 0.28 (p = 0.040, 95% CI: 0.08–0.94), 0.29 (p = 0.001, 95% CI: 0.13–0.63), 0.23 (p = 0.003, 95% CI: 0.08–0.67) and 0.51 (p = 0.005, 95% CI: 0.29–0.91), respectively. In contrast, the recessive (CC vs. GG - GC) and the log-additive models of rs10012, were linked to an increased risk of ER+BC, with ORs of 2.39 (p = 0.020, 95% CI: 1.14–5.03) and 1.97 (p = 0.014, 95% CI: 1.13–3.44), respectively.
CONCLUSION: These findings reveal the complex interplay between CYP1B1 polymorphisms and ER+BC risk, with some variants protecting while others increase risk. Further research is essential to fully understand the effects of these genetic variations on breasts.
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