Gene-environment interactions for breast cancer risk among Chinese women: a report from the Shanghai Breast Cancer Genetics Study

Am J Epidemiol. 2013 Jan 15;177(2):161-70. doi: 10.1093/aje/kws238. Epub 2012 Dec 6.

Abstract

Genome-wide association studies have identified approximately 20 susceptibility loci for breast cancer. A cumulative genetic risk score (GRS) was constructed from 10 variants with replicated associations among participants of the Shanghai Breast Cancer Genetics Study (Shanghai, China, 1996-1998 and 2002-2005). Interactions between the GRS and 11 breast cancer risk factors were evaluated. Among the 6,408 study participants, no evidence of effect modification was found with the GRS for age at menarche, age at menopause, age at first live birth/parity, total months of breastfeeding, family history of breast cancer, history of benign breast disease, hormone replacement therapy, body mass index, waist/hip ratio, or regular physical activity. The effect of the GRS was least homogeneous by duration of menstruation; further analysis indicated a nominally significant interaction with one genetic variant. The mitochondrial ribosomal protein S30 gene (MRPS30) rs10941679 was associated with breast cancer risk only among women with more than 30 years of menstruation (odds ratio = 1.15, 95% confidence interval: 1.05, 1.26). Although this multiplicative interaction reached a nominal significance level (P = 0.037), it did not withstand correction for multiple comparisons. In conclusion, this study revealed no apparent interactions between genome-wide association study-identified genetic variants and breast cancer risk factors in the etiology of this common cancer.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / epidemiology
  • Breast Neoplasms / etiology*
  • Breast Neoplasms / genetics
  • Case-Control Studies
  • China / epidemiology
  • Effect Modifier, Epidemiologic
  • Female
  • Gene-Environment Interaction*
  • Genetic Markers
  • Genome-Wide Association Study
  • Genotyping Techniques
  • Humans
  • Logistic Models
  • Middle Aged
  • Odds Ratio
  • Polymorphism, Single Nucleotide*
  • Registries
  • Risk Assessment
  • Risk Factors

Substances

  • Genetic Markers