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


CONCLUSIONS
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.
Mohammadi
Leila
L
Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. l.mohammadikhankahdani@erasmusmc.nl
Vreeswijk
Maaike P
MP
Oldenburg
Rogier
R
van den Ouweland
Ans
A
Oosterwijk
Jan C
JC
van der Hout
Annemarie H
AH
Hoogerbrugge
Nicoline
N
Ligtenberg
Marjolijn
M
Ausems
Margreet G
MG
van der Luijt
Rob B
RB
Dommering
Charlotte J
CJ
Gille
Johan J
JJ
Verhoef
Senno
S
Hogervorst
Frans B
FB
van Os
Theo A
TA
Gómez García
Encarna
E
Blok
Marinus J
MJ
Wijnen
Juul T
JT
Helmer
Quinta
Q
Devilee
Peter
P
van Asperen
Christi J
CJ
van Houwelingen
Hans C
HC
D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D005192:Family Health; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D014644:Genetic Variation; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D010051:Ovarian Neoplasms / Q000235:genetics*; D010375:Pedigree; D010641:Phenotype