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

Counting potentially functional variants in BRCA1, BRCA2 and ATM predicts breast cancer... 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. 25 of these SNPs were in BRCA1, BRCA2, ATM, TP53 and CHEK2 . Amongst 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, OR 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. © The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Human Molecular Genetics Oxford University Press

Loading next page...
 
/lp/ou_press/counting-potentially-functional-variants-in-brca1-brca2-and-atm-TmSRVS0YW3
Publisher
Oxford University Press
Copyright
© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
ISSN
0964-6906
eISSN
1460-2083
D.O.I.
10.1093/hmg/ddm077
Publisher site
See Article on Publisher Site

Abstract

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. 25 of these SNPs were in BRCA1, BRCA2, ATM, TP53 and CHEK2 . Amongst 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, OR 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. © The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Journal

Human Molecular GeneticsOxford University Press

Published: Jan 1, 2007

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off