Association of CYP19 gene SNPs (rs7176005 and rs6493497) with polycystic ovary syndrome susceptibility in Northern Chinese women.

IF 2.1 4区 医学 Q3 GENETICS & HEREDITY
Ya-Li Hao, Chun-Miao Liu, Na Wang, Rong-Miao Zhou, Ya-Nan Wei, Xiao-Shuang Bai, Xi Huang
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引用次数: 0

Abstract

Purpose: The objective of this study was to elucidate the relationship between two single nucleotide polymorphisms (SNPs) rs7176005 and rs6493497 in CYP19 gene and the risk of polycystic ovary syndrome (PCOS) in Northern Chinese women.

Methods: In this case-control study, a total of 340 women with PCOS and 340 matched healthy controls were recruited. Polymerase chain reaction ligase detection reaction (PCR-LDR) method was used to investigate two SNPs (rs7176005 and rs6493497) in the 5'-flanking region of CYP19 gene exon 1.

Results: We observed a significant association of rs7176005 and rs6493497 with reduced risk of PCOS. Compared with CC genotype, a significant association of CT genotype (p = 0.019), TT genotype (p < 0.001) and combined CT + TT genotype (p < 0.001) with reduced risk of PCOS was observed. The result of linkage disequilibrium analysis showed that these two SNPs are in complete linkage disequilibrium (r2 = 1). For rs7176005 SNP, compared with CC genotype, CT, TT and CT + TT genotypes reduced the risk of PCOS. The age, BMI-adjusted OR were 0.650 (95% CI = 0.460-0.917), 0.158 (95% CI = 0.066-0.376) and 0.545(95% CI = 0.391-0.759), respectively.

Conclusions: These findings highlight a significant association between CYP19 gene polymorphisms and PCOS susceptibility, implying potential protective effects of T and A alleles. Of course, the major limitation of this study is the sample size of the case-control study. Larger cohort studies are needed to confirm these findings and investigate the underlying causes.

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来源期刊
BMC Medical Genomics
BMC Medical Genomics 医学-遗传学
CiteScore
3.90
自引率
0.00%
发文量
243
审稿时长
3.5 months
期刊介绍: BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.
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