Common genetic variants for breast cancer: 32 largely refuted candidates and larger prospects.

Journal of the National Cancer Institute, Vol. 98, No. 19, October 4, 2006 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 specifi c 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 specifi c 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 suffi ces to explain all that causes breast cancer: the total attributable fraction from this small sample of associations already reaches close to 100%. Is this an apotheosis of data dredging? Even in my small sample of 19 articles, one comes across an association that is statistically signifi cant only in the sub-sub-subgroup of postmenopausal women who have at least three pregnancies and also have no wild-type allele ( 5 ) ; a polymorphism with statistically signifi cantly decreased risk for early-stage breast cancer but increased risk for advanced-stage disease ( 6 ) ; another increasing the risk especially for grade 3 tumors ( 7 ) ; a marker with 13 variants, of which one shows a statistically signifi cant association versus all others combined, while hundreds of different groupings are conceivable ( 8 ) ; polymorphisms that have no statistically signifi cant associations on their own but do in one of their many constructed haplotypes ( 9 ) ; joint effects of polymorphisms of different genes acting in obvious ( 10 ) or not-so-obvious ( 11 ) pathways; associations that are not even tested statistically ( 12 ) ; and so forth. In addition to the 16 SNPs examined by the Breast Cancer Association Consortium, meta-analyses of published data are available for another 16 candidate gene variants in breast cancer ( Table 1 ) Affi liations of author: Department of Hygiene and Epidemiology, University of Ioannina School of Medicine and Biomedical Research Institute, Foundation for Research and Technology-Hellas, Ioannina, Greece; and Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts University School of Medicine, Boston, MA. Correspondence to: John P. A. Ioannidis, MD, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, Ioannina 45110, Greece (e-mail: jioannid@cc.uoi.gr ).