Source:http://linkedlifedata.com/resource/pubmed/id/11443730
Switch to
Predicate | Object |
---|---|
rdf:type | |
lifeskim:mentions | |
pubmed:issue |
1
|
pubmed:dateCreated |
2001-7-9
|
pubmed:abstractText |
We used data from a population based series of breast cancer patients to investigate the genetic models that can best explain familial breast cancer not due to the BRCA1 and BRCA2 genes. The data set consisted of 1,484 women diagnosed with breast cancer under age 55 registered in the East Anglia Cancer registry between 1991-1996. Blood samples taken from the patients were analysed for mutations in BRCA1 and BRCA2. The genetic models were constructed using information on breast and ovarian cancer history in first-degree relatives and on the mutation status of the index patients. We estimated the simultaneous effects of BRCA1, BRCA2, a third hypothetical gene BRCA3, and a polygenic effect. The models were assessed by likelihood comparisons and by comparison of the observed numbers of mutations and affected relatives with the predicted numbers. BRCA1 and BRCA2 could not explain all the familial clustering of breast cancer. The best-fitting single gene model for BRCA3 was a recessive model with a disease allele frequency 24% and penetrance 42% by age 70. However, a polygenic model gave a similarly good fit. The estimated population frequencies for BRCA1 and BRCA2 mutations were similar under both recessive and polygenic models, 0.024 and 0.041%, respectively. A dominant model for BRCA3 gave a somewhat worse fit, although the difference was not significant. The mixed recessive model was identical to the recessive model and the mixed dominant very similar to the polygenic model. The BRCA3 genetic models were robust to the BRCA1 and BRCA2 penetrance assumptions. The overall fit of all models was improved when the known effects of parity on breast and ovarian cancer risks were included in the model-in this case a polygenic model fits best. These findings suggest that a number of common, low-penetrance genes with additive effects may account for the residual non-BRCA1/2 familial aggregation of breast cancer, but Mendelian inheritance of an autosomal recessive allele cannot be ruled out.
|
pubmed:language |
eng
|
pubmed:journal | |
pubmed:citationSubset |
IM
|
pubmed:chemical | |
pubmed:status |
MEDLINE
|
pubmed:month |
Jul
|
pubmed:issn |
0741-0395
|
pubmed:author | |
pubmed:copyrightInfo |
Copyright 2001 Wiley-Liss, Inc.
|
pubmed:issnType |
Print
|
pubmed:volume |
21
|
pubmed:owner |
NLM
|
pubmed:authorsComplete |
Y
|
pubmed:pagination |
1-18
|
pubmed:dateRevised |
2009-11-19
|
pubmed:meshHeading |
pubmed-meshheading:11443730-Adult,
pubmed-meshheading:11443730-Age Distribution,
pubmed-meshheading:11443730-Aged,
pubmed-meshheading:11443730-BRCA2 Protein,
pubmed-meshheading:11443730-Breast Neoplasms,
pubmed-meshheading:11443730-Female,
pubmed-meshheading:11443730-Gene Frequency,
pubmed-meshheading:11443730-Genes, BRCA1,
pubmed-meshheading:11443730-Genes, Dominant,
pubmed-meshheading:11443730-Genes, Recessive,
pubmed-meshheading:11443730-Genetic Markers,
pubmed-meshheading:11443730-Genetic Predisposition to Disease,
pubmed-meshheading:11443730-Genetic Testing,
pubmed-meshheading:11443730-Great Britain,
pubmed-meshheading:11443730-Humans,
pubmed-meshheading:11443730-Incidence,
pubmed-meshheading:11443730-Likelihood Functions,
pubmed-meshheading:11443730-Middle Aged,
pubmed-meshheading:11443730-Models, Genetic,
pubmed-meshheading:11443730-Molecular Epidemiology,
pubmed-meshheading:11443730-Multifactorial Inheritance,
pubmed-meshheading:11443730-Mutation,
pubmed-meshheading:11443730-Neoplasm Proteins,
pubmed-meshheading:11443730-Pedigree,
pubmed-meshheading:11443730-Penetrance,
pubmed-meshheading:11443730-Population Surveillance,
pubmed-meshheading:11443730-Predictive Value of Tests,
pubmed-meshheading:11443730-Registries,
pubmed-meshheading:11443730-Transcription Factors
|
pubmed:year |
2001
|
pubmed:articleTitle |
Evidence for further breast cancer susceptibility genes in addition to BRCA1 and BRCA2 in a population-based study.
|
pubmed:affiliation |
CRC Genetic Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
|
pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|