Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genome-wide association study identifies susceptibility loci for polycystic ovary syndrome on chromosome 2p16.3, 2p21 and 9q33.3

This article has been updated


Polycystic ovary syndrome (PCOS) is a common metabolic disorder in women. To identify causative genes, we conducted a genome-wide association study (GWAS) of PCOS in Han Chinese. The discovery set included 744 PCOS cases and 895 controls; subsequent replications involved two independent cohorts (2,840 PCOS cases and 5,012 controls from northern Han Chinese; 498 cases and 780 controls from southern and central Han Chinese). We identified strong evidence of associations between PCOS and three loci: 2p16.3 (rs13405728; combined P-value by meta-analysis Pmeta = 7.55 × 10−21, odds ratio (OR) 0.71); 2p21 (rs13429458, Pmeta = 1.73 × 10−23, OR 0.67); and 9q33.3 (rs2479106, Pmeta = 8.12 × 10−19, OR 1.34). These findings provide new insight into the pathogenesis of PCOS. Follow-up studies of the candidate genes in these regions are recommended.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Genome-wide association scan for PCOS.
Figure 2: Regional plots of the three newly discovered PCOS loci (2p16.3, 2p21 and 9q33.3).

Change history

  • 28 January 2011

    In the version of this article originally posted online corresponding author Yongyong Shi was not designated as a corresponding author. This error has been corrected in the HTML version of the paper.


  1. Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group. Revised 2003 consensus on diagnostic criteria and longterm health risks related to polycystic ovary syndrome. Fertil. Steril. 81, 19–25 (2004).

  2. Goodarzi, M.O. & Azziz, R. Diagnosis, epidemiology, and genetics of the polycystic ovary syndrome. Best Pract. Res. Clin. Endocrinol. Metab. 20, 193–205 (2006).

    Google Scholar 

  3. Ehrmann, D.A., Barnes, R.B., Rosenfield, R.L., Cavaghan, M.K. & Imperial, J. Prevalence of impaired glucose tolerance and diabetes in women with polycystic ovary syndrome. Diabetes Care 22, 141–146 (1999).

    Google Scholar 

  4. Carmina, E. Cardiovascular risk and events in polycystic ovary syndrome. Climacteric 12 (suppl. 1), 22–25 (2009).

    Google Scholar 

  5. Kandaraki, E., Christakou, C. & Diamanti-Kandarakis, E. Metabolic syndrome and polycystic ovary syndrome...; and vice versa. Arq. Bras. Endocrinol. Metabol. 53, 227–237 (2009).

    Google Scholar 

  6. Wild, S., Pierpoint, T., Jacobs, H. & McKeigue, P. Long-term consequences of polycystic ovary syndrome: results of a 31 year follow-up study. Hum. Fertil. (Camb.) 3, 101–105 (2000).

    Google Scholar 

  7. Espinós-Gómez, J.J., Corcoy, R. & Calaf, J. Prevalence and predictors of abnormal glucose metabolism in Mediterranean women with polycystic ovary syndrome. Gynecol. Endocrinol. 25, 199–204 (2009).

    Google Scholar 

  8. Kulshreshtha, B. et al. Insulin response to oral glucose in healthy, lean young women and patients with polycystic ovary syndrome. Gynecol. Endocrinol. 24, 637–643 (2008).

    Google Scholar 

  9. Shi, Y. et al. Analysis of clinical characteristics in large-scale Chinese women with polycystic ovary syndrome. Neuroendocrinol. Lett. 28, 807–810 (2007).

    Google Scholar 

  10. Sudo, S. et al. Genetic and functional analyses of polymorphisms in the human FSH receptor gene. Mol. Hum. Reprod. 8, 893–899 (2002).

    Google Scholar 

  11. Wang, Y., Wu, X., Cao, Y., Yi, L. & Chen, J. A microsatellite polymorphism (tttta)n in the promoter of the CYP11a gene in Chinese women with polycystic ovary syndrome. Fertil. Steril. 86, 223–226 (2006).

    Google Scholar 

  12. Chen, Z.J. et al. Correlation between single nucleotide polymorphism of insulin receptor gene with polycystic ovary syndrome. Zhonghua Fu Chan Ke Za Zhi 39, 582–585 (2004).

    Google Scholar 

  13. Villuendas, G., San Millán, J.L., Sancho, J. & Escobar-Morreale, H.F. The -597 G→A and -174 G→C polymorphisms in the promoter of the IL-6 gene are associated with hyperandrogenism. J. Clin. Endocrinol. Metab. 87, 1134–1141 (2002).

    Google Scholar 

  14. Carlson, C.S., Eberle, M.A., Kruglyak, L. & Nickerson, D.A. Mapping complex disease loci in whole-genome association studies. Nature 429, 446–452 (2004).

    Google Scholar 

  15. Xu, S. et al. Genomic dissection of population substructure of Han Chinese and its implication in association studies. Am. J. Hum. Genet. 85, 762–774 (2009).

    Google Scholar 

  16. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    Google Scholar 

  17. Huang, M. et al. Involvement of ALF in human spermatogenesis and male infertility. Int. J. Mol. Med. 17, 599–604 (2006).

    Google Scholar 

  18. Latronico, A.C. et al. A homozygous microdeletion in helix 7 of the luteinizing hormone receptor associated with familial testicular and ovarian resistance is due to both decreased cell surface expression and impaired effector activation by the cell surface receptor. Mol. Endocrinol. 12, 442–450 (1998).

    Google Scholar 

  19. Toledo, S.P.A. et al. An inactivating mutation of the luteinizing hormone receptor causes amenorrhea in a 46, XX female. J. Clin. Endocrinol. Metab. 81, 3850–3854 (1996).

    Google Scholar 

  20. Latronico, A.C., Lins, T.S., Brito, V.N., Arnhold, I.J. & Mendonca, B.B. The effect of distinct activating mutations of the luteinizing hormone receptor gene on the pituitary-gonadal axis in both sexes. Clin. Endocrinol. 53, 609–613 (2000).

    Google Scholar 

  21. Valkenburg, O. et al. Genetic polymorphisms of GnRH and gonadotrophic hormone receptors affect the phenotype of polycystic ovary syndrome. Hum. Reprod. 24, 2014–2022 (2009).

    Google Scholar 

  22. Tong, Y., Liao, W.X., Roy, A.C. & Ng, S.C. Absence of mutations in the coding regions of follicle-stimulating hormone receptor gene in Singapore Chinese women with premature ovarian failure and polycystic ovary syndrome. Horm. Metab. Res. 33, 221–226 (2001).

    Google Scholar 

  23. Du, J. et al. Two FSHR variants, haplotypes and meta-analysis in Chinese women with premature ovarian failure and polycystic ovary syndrome. Mol. Genet. Metab. 100, 292–295 (2010).

    Google Scholar 

  24. Drieschner, N. et al. Evidence for a 3p25 breakpoint hot spot region in thyroid tumors of follicular origin. Thyroid 16, 1091–1096 (2006).

    Google Scholar 

  25. Zeggini, E. et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat. Genet. 40, 638–645 (2008).

    Google Scholar 

  26. Hu, C. et al. PPARG, KCNJ11, CDKAL1, CDKN2A-CDKN2B, IDE-KIF11-HHEX, IGF2BP2 and SLC30A8 are associated with type 2 diabetes in a Chinese population. PLoS ONE 4, e7643 (2009).

    Google Scholar 

  27. Del Villar, K. & Miller, C.A. Down-regulation of DENN/MADD, a TNF receptor binding protein, correlates with neuronal cell death in Alzheimer?s disease brain and hippocampal neurons. Proc. Natl. Acad. Sci. USA 101, 4210–4215 (2004).

    Google Scholar 

  28. Olszanecka-Glinianowicz, M. et al. Is the polycystic ovary syndrome associated with chronic inflammation per se? Eur. J. Obstet. Gynecol. Reprod. Biol. 133, 197–202 (2007).

    Google Scholar 

  29. Ferriman, D. & Gallwey, J.D. Clinical assessment of body hair growth in women. J. Clin. Endocrinol. Metab. 21, 1440–1447 (1961).

    Google Scholar 

  30. Shi, Y., Gao, X., Sun, X., Zhang, P. & Chen, Z. Clinical and metabolic characteristics of polycystic ovary syndrome without polycystic ovary: a pilot study on Chinese women. Fertil. Steril. 90, 1139–1143 (2008).

    Google Scholar 

  31. Radziuk, J. Insulin sensitivity and its measurement: structural commonalities among the methods. J. Clin. Endocrinol. Metab. 85, 4426–4433 (2000).

    Google Scholar 

  32. Korn, J.M. et al. Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat. Genet. 40, 1253–1260 (2008).

    Google Scholar 

  33. Thomas, G. et al. Capillary and microelectrophoretic separations of ligase detection reaction products produced from low-abundant point mutations in genomic DNA. Electrophoresis 25, 1668–1677 (2004).

    Google Scholar 

  34. Yi, P. et al. PCR/LDR/capillary electrophoresis for detection of single-nucleotide differences between fetal and maternal DNA in maternal plasma. Prenat. Diagn. 29, 217–222 (2009).

    Google Scholar 

  35. Shi, Y.Y. & He, L. SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res. 15, 97–98 (2005).

    Google Scholar 

  36. Petukhova, L. et al. Genome-wide association study in alopecia areata implicates both innate and adaptive immunity. Nature 466, 113–117 (2010).

    Google Scholar 

  37. Barrett, J.C., Fry, B., Maller, J. & Daly, M.J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263 (2005).

    Google Scholar 

  38. Saxena, R. et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science 316, 1331–1336 (2007).

    Google Scholar 

  39. Mantel, N. & Haenszel, W. Statistical aspects of the analysis of data from retrospective studies. J. Natl. Cancer Inst. 22, 719–748 (1959).

    Google Scholar 

Download references


We thank all participants involved in this study. We thank J. Simpson for revising this manuscript and X. Xu, X. Xing, T. Li, M. Guo, L. Cui, Q. Zheng, C. Li, J. Zhang, D. Wu, C. Zhang, X. Yan, W. He, Y. Cui, M. Xia, J. Li, P. Wang, H. Lv, S. Xu and L. Wang for subject recruitment. This study was supported by grants from the National Basic Research Program of China (973 Program-2006CB944004, 2010CB945000, 2007CB947403, 2007CB914703, 2007CB947300, 2010CB529600), the National 863 Project of China grants (2006AA02A407, 2009AA022701), the National Natural Science Foundation of China (30973170) and the Shanghai Municipal Commission of Science and Technology Program (09DJ1400601).

Author information

Authors and Affiliations



Z.-J.C., L.H. and Yongyong Shi designed the study and revised the manuscript. Z.-J.C. supervised patients' diagnosis, subject recruitment and performance of experiments. Yongyong Shi supervised the experiments and data analysis. H.Z. and Z.L. conducted data analyses and drafted the manuscript. H.Z., Yuhua Shi, Y.Q., L.Y., L.G. and J.Y. recruited subjects. Junli Zhao, J.L., X.L., X.Z., Junzhao Zhao, Y. Sun, B.Z., H.J., D. Zhao, Yiran Li, D. Zhu, X.S., J.-e.X., C.H., C.-e.R., Y. Zhang, S.C., W.Z. and A.Y. coordinated and provided samples from different hospitals. L.Y., Y.B., Yuan Li, J.M. and Y. Zhao performed DNA extraction. X.G. performed endocrine biochemical examination. All authors critically reviewed the article and approved the final manuscript.

Corresponding authors

Correspondence to Zi-Jiang Chen or Yongyong Shi.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 and Supplementary Tables 1–7 (PDF 2263 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Chen, ZJ., Zhao, H., He, L. et al. Genome-wide association study identifies susceptibility loci for polycystic ovary syndrome on chromosome 2p16.3, 2p21 and 9q33.3. Nat Genet 43, 55–59 (2011).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing