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PMID: 17341484 Published · ppublish English

Counting potentially functional variants in BRCA1, BRCA2 and ATM predicts breast cancer susceptibility.

Human molecular genetics ·Vol. 16 ·No. 9 ·2007-08-20

Johnson Nichola, Fletcher Olivia, Palles Claire, Rudd Matthew, Webb Emily, Sellick Gabrielle, dos Santos Silva Isabel, McCormack Valerie, Gibson Lorna, Fraser Agnes, Leonard Angela, Gilham Clare, Tavtigian Sean V, Ashworth Alan, Houlston Richard, Peto Julian

Abstract

Rare inactivating mutations in BRCA1, BRCA2, ATM, TP53 and CHEK2 confer relative risks for breast cancer between about 2 and more than 10, but more common variants in these genes are generally considered of little or no clinical significance. Under the polygenic model for breast cancer carriers of multiple low-penetrance alleles are at high risk, but few such alleles have been reliably identified. We analysed 1037 potentially functional single nucleotide polymorphisms (SNPs) in candidate cancer genes in 473 women with two primary breast cancers and 2463 controls. Twenty-five of these SNPs were in BRCA1, BRCA2, ATM, TP53 and CHEK2. Among the 1037 SNPs there were a few significant findings, but hardly more than would be expected in this large experiment. There was, however, a significant trend in risk with increasing numbers of variant alleles for the 25 SNPs in BRCA1, BRCA2, ATM, TP53 and CHEK2 (P(trend) = 0.005). For the 21 of these with minor allele frequency <10% this trend was highly significant (P(trend) = 0.00004, odds ratio for 3 or more SNPs = 2.90, 95% CI 1.69-4.97). The individual effects of most of these risk alleles were undetectably small even in this well powered study, but the risk conferred by multiple variants is readily detectable and makes a substantial contribution to susceptibility. A risk score incorporating a suitably weighted sum of all potentially functional variants in these and a few other candidate genes may provide clinically useful identification of women at high genetic risk.

Article Info
Journal
Human molecular genetics
Abbr.
Hum Mol Genet
Published
2007-08-20
Indexed
2007-05-09
Updated
2013-11-21
Language
English
Country/Region
England
NLM ID
9208958
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