Common Genetic Variants for Breast Cancer: 32 Largely Refuted Candidates and Larger Prospects

Extract

Many common diseases, including most cancers ( 1 ) , may have a component of inheritance that is due to low-penetrance, common genetic variants. However, identifying these variants has been a challenge. In this issue of the Journal, the Breast Cancer Association Consortium reports an impressive collaborative effort—the large-scale evaluation of 16 single nucleotide polymorphisms (SNPs) that have been previously hypothesized to modify susceptibility to breast cancer ( 2 ) . Despite accumulated genotype information on 12 000–32 000 breast cancer case and control subjects for each SNP, results are largely null. No SNP shows an association with P <.0031, the threshold required after adjusting for 16 tests. Five variants with P values between .009 and .06 require further testing, but the odds ratios (ORs) are already hovering at around 0.9–1.1. For the other 11 SNPs, results are even more conclusively null. Extensive subgroup analyses largely reinforce these conclusions.

These data add to the tribulations of the “candidate gene” approach that has guided complex disease genetics for over a decade. In this approach, biologic pathways thought to be relevant to specific diseases were scrutinized for gene variants modulating disease risk. Postulated associations were then often extended to other phenotypes, with or without much rationale for the extension ( 3 ) . The gene–disease association literature grew exponentially. In 2005 alone, 194 original research articles were published that probed gene–disease associations for breast cancer ( 4 ) ; I selected every 10th article (n = 19) for perusal. Fifteen of these articles claimed associations overall, in subgroups, or for specific outcomes. The parade of claimed associated genes in this tiny sample is already impressive: HER2 , IL10 , NCOA3 , TGFBR1 , TGFB1 , ESR2 , HFE , IGF-I , ESR1 , AR , CHEK2 , PAI-1 , XRCC1 , HSMH2 , SULT1A1 , and IFNG. If all these claimed associations are real, a 10% sample of the published genetic association research in a single year alone seemingly suffices to explain all that causes breast cancer: the total attributable fraction from this small sample of associations already reaches close to 100%.