Human Genetics

, Volume 128, Issue 5, pp 515–527 | Cite as

A large-scale candidate gene association study of age at menarche and age at natural menopause

  • Chunyan HeEmail author
  • Peter Kraft
  • Daniel I. Chasman
  • Julie E. Buring
  • Constance Chen
  • Susan E. Hankinson
  • Guillaume Paré
  • Stephen Chanock
  • Paul M. Ridker
  • David J. Hunter
Original Investigation


Recent genome-wide association (GWA) studies have identified several novel genetic loci associated with age at menarche and age at natural menopause. However, the stringent significance threshold used in GWA studies potentially led to false negatives and true associations may have been overlooked. Incorporating biologically relevant information, we examined whether common genetic polymorphisms in candidate genes of nine groups of biologically plausible pathways and related phenotypes are associated with age at menarche and age at natural menopause. A total of 18,862 genotyped and imputed single nucleotide polymorphisms (SNPs) in 278 genes were assessed for their associations with these two traits among a total of 24,341 women from the Nurses’ Health Study (NHS, N = 2,287) and the Women’s Genome Health Study (WGHS, N = 22,054). Linear regression was used to assess the marginal association of each SNP with each phenotype. We adjusted for multiple testing within each gene to identify statistically significant SNP associations at the gene level. To evaluate the overall evidence for an excess of statistically significant gene associations over the proportion expected by chance, we applied a one-sample test of proportion to each group of candidate genes. The steroid-hormone metabolism and biosynthesis pathway was found significantly associated with both age at menarche and age at natural menopause (P = 0.040 and 0.011, respectively). In addition, the group of genes associated with precocious or delayed puberty was found significantly associated with age at menarche (P = 0.013), and the group of genes involved in premature ovarian failure with age at menopause (P = 0.025).


Single Nucleotide Polymorphism Marker Premature Ovarian Failure Common Genetic Variant Natural Menopause Related Phenotype 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank J. Miletich and A. Parker as well as the technical staff at Amgen, Inc (Cambridge, MA, USA) for their collaboration and scientific support in performing the genotyping for the WGHS. The NHS GWAS was performed as part of the Cancer Genetic Markers of Susceptibility initiative of the NCI. We particularly acknowledge the contributions of R. Hoover, A. Hutchinson, K. Jacobs and G. Thomas. We thank H. Ranu and P. Soule of the DF/HCC High Throughput Polymorphism Detection Laboratory for assistance. The WGHS is supported by HL 043851 and HL69757 from the National Heart Lung and Blood Institute and CA 047988 from the National Cancer Institute (Bethesda, MD, USA), the Donald W. Reynolds Foundation (Las Vegas, NV, USA), the Fondation Leducq (Paris, France), with collaborative scientific support and funding for genotyping provided by Amgen, Inc. The NHS is supported by CA 40356, CA 87969, and U01-CA98233 from the National Cancer Institute. We acknowledge the study participants in the NHS and the WGHS for their contribution in making this study possible.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

439_2010_878_MOESM1_ESM.doc (756 kb)
Supplementary material 1 (DOC 755 kb)


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Chunyan He
    • 1
    Email author
  • Peter Kraft
    • 2
  • Daniel I. Chasman
    • 3
  • Julie E. Buring
    • 2
    • 3
  • Constance Chen
    • 2
  • Susan E. Hankinson
    • 2
    • 4
  • Guillaume Paré
    • 3
  • Stephen Chanock
    • 5
  • Paul M. Ridker
    • 2
    • 3
  • David J. Hunter
    • 2
    • 4
    • 6
  1. 1.Department of Public HealthIndiana University School of MedicineIndianapolisUSA
  2. 2.Department of EpidemiologyHarvard School of Public HealthBostonUSA
  3. 3.Donald W. Reynolds Center for Cardiovascular Research, Brigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  4. 4.Channing Laboratory, Brigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  5. 5.Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaUSA
  6. 6.Program in Medical and Population Genetics, Broad Institute of Harvard and MITCambridgeUSA

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