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

Abstract

BackgroundAssessment 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.MethodsWe 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.ResultsWe 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.ConclusionAlthough 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.

Characterization of BRCA1 and BRCA2 splicing variants: a collaborative report by ENIGMA consortium members

“…Likelihood ratios for segregation were derived using methods described previously by Mohammadi et al [20], and implemented as a web-based calculator (http://www. msbi.nl/cosegregation/).…”

Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants

“…This paper addresses three features related to the design of studies using DNA sequencing to study rare variants: the samples used for variant discovery, selection of specific genes and variants for follow-up, and replication of putative genotype-phenotype relationships in independent samples. We focus on one widely discussed design feature: the ascertainment of samples from the extremes of a population distribution [Ahituv et al, 2007;Bell et al, 2007;Cohen et al, 2004;DeAngelis et al, 2004;Kryukov et al, 2009;Mohammadi et al, 2009;Nebert 2000;PerezGracia et al, 2002;Zhang, 1995, 1996;Romeo et al, 2007] (previously referred to as ''selective genotyping'') [Lander and Botstein, 1989;Van Gestel et al, 2000]. Intuitively, ascertainment of samples from the extremes of phenotype should enrich for the burden of alleles influencing a trait, thus improving power to discover risk variants and to detect their association to phenotype.…”

Clinical relevance of rare germline sequence variants in cancer genes: evolution and application of classification models

“…Although variant frequency in unaffected controls has been used as a prescreen to identify likely neutral/low clinical significant variants [6,8], and recently to confirm the low clinical significance of a BRCA2 variant [13], this has yet to be included in the model itself. As shown in Figure 1, the BRCA1/2 multifactorial model currently includes an assessment of the prior probability of pathogenicity of a variant based on amino acid evolutionary conservation and physicochemical properties [14], and can include additional estimates of pathogenicity from LRs based on variant segregation in families [3,15], cooccurrence with a pathogenic mutation [3], reported family history of the proband [7,8,16] and tumour features [6,8,11,17]. There has been much recent development in the field to simplify the calculation of posterior probabilities, with a web-based site available for the assignment of A-GVGD prior probabilities [14] (http://agvgd.iarc.fr/ alignments.php), a simplified web-based method for the calculation of LRs for segregation analysis [15] (http:// www.msbi.nl/cosegregation), and detailed explanations of the derivations of pathology LRs [11,17].…”