A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example
- Equal contributors
1 Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
2 Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
3 Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
4 Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
5 Department of Genetics, University Medical Center, Groningen University, Groningen, The Netherlands
6 Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
7 Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
8 Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
9 Family Cancer Clinic, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
10 Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands
11 Department of Clinical Genetics, University Medical Center, Maastricht, The Netherlands
12 Department of Genetics and Cell Biology, University Medical Center, Maastricht, The Netherlands
BMC Cancer 2009, 9:211 doi:10.1186/1471-2407-9-211Published: 29 June 2009
Assessment of the clinical significance of unclassified variants (UVs) identified in BRCA1 and BRCA2 is very important for genetic counselling. The analysis of co-segregation of the variant with the disease in families is a powerful tool for the classification of these variants. Statistical methods have been described in literature but these methods are not always easy to apply in a diagnostic setting.
We have developed an easy to use method which calculates the likelihood ratio (LR) of an UV being deleterious, with penetrance as a function of age of onset, thereby avoiding the use of liability classes. The application of this algorithm is publicly available http://www.msbi.nl/cosegregation webcite. It can easily be used in a diagnostic setting since it requires only information on gender, genotype, present age and/or age of onset for breast and/or ovarian cancer.
We have used the algorithm to calculate the likelihood ratio in favour of causality for 3 UVs in BRCA1 (p.M18T, p.S1655F and p.R1699Q) and 5 in BRCA2 (p.E462G p.Y2660D, p.R2784Q, p.R3052W and p.R3052Q). Likelihood ratios varied from 0.097 (BRCA2, p.E462G) to 230.69 (BRCA2, p.Y2660D). Typing distantly related individuals with extreme phenotypes (i.e. very early onset cancer or old healthy individuals) are most informative and give the strongest likelihood ratios for or against causality.
Although co-segregation analysis on itself is in most cases insufficient to prove pathogenicity of an UV, this method simplifies the use of co-segregation as one of the key features in a multifactorial approach considerably.