BMC Cancer (Jun 2009)

A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; <it>BRCA1 </it>and <it>BRCA2 </it>as an example

  • Gómez García Encarna,
  • van Os Theo A,
  • Hogervorst Frans B,
  • Verhoef Senno,
  • Gille Johan J,
  • Dommering Charlotte J,
  • van der Luijt Rob B,
  • Ausems Margreet G,
  • Ligtenberg Marjolijn,
  • Hoogerbrugge Nicoline,
  • van der Hout Annemarie H,
  • Oosterwijk Jan C,
  • van den Ouweland Ans,
  • Oldenburg Rogier,
  • Vreeswijk Maaike P,
  • Mohammadi Leila,
  • Blok Marinus J,
  • Wijnen Juul T,
  • Helmer Quinta,
  • Devilee Peter,
  • van Asperen Christi J,
  • van Houwelingen Hans C

DOI
https://doi.org/10.1186/1471-2407-9-211
Journal volume & issue
Vol. 9, no. 1
p. 211

Abstract

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Abstract Background 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. Methods 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. 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. Results 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. Conclusion 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.