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An association study between USP34 and polycystic ovary syndrome

Overview of attention for article published in Journal of Ovarian Research, May 2015
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Title
An association study between USP34 and polycystic ovary syndrome
Published in
Journal of Ovarian Research, May 2015
DOI 10.1186/s13048-015-0158-y
Pubmed ID
Authors

Shigang Zhao, Ye Tian, Wei Zhang, Xiuye Xing, Tao Li, Hongbin Liu, Tao Huang, Yunna Ning, Han Zhao, Zi-Jiang Chen

Abstract

Polycystic ovary syndrome (PCOS) is a complex multifactor disorder and genetic factors have been implicated in its pathogenesis. Our previous genome-wide association study (GWAS) had identified allele frequencies in several single nucleotide polymorphisms (SNPs) in gene USP34 (Ubiquitin-Specific Protease 34) were significantly different between PCOS cases and controls. This study was aimed to replicate the previous results in another independent cohort. One thousand two hundred eighteen PCOS cases and 1057 controls were recruited. Genotyping of two SNPs (rs17008097 and rs17008940) in USP34 gene were performed by TaqMan-MGB probe assay and genotype-phenotype analysis was conducted subsequently. The differences of allele or genotype frequencies were not significant statistically between PCOS and controls, even after age and BMI adjustment. For clinical and metabolic features (LH, T and HOMA-IR) analysis in PCOS cases, no statistical differences among three genotypes of rs17008097 and rs17008940 were found. However, rs17008940 was shown to be slightly associated with BMI in PCOS cases rather than in controls, even after age adjustment (TC vs CC P = 0.006, OR = 1.042, 95%CI 1.012-1.073; TT vs CC P = 0.037, OR = 1.050, 95%CI 1.003-1.100). USP34 gene polymorphisms (rs17008097 and rs17008940) may not be associated with PCOS in the Han Chinese women.

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Student > Bachelor 1 13%
Student > Ph. D. Student 1 13%
Unknown 4 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 13%
Nursing and Health Professions 1 13%
Agricultural and Biological Sciences 1 13%
Medicine and Dentistry 1 13%
Unknown 4 50%