MISSENSE MUTATIONS IN DISEASE GENES - A BAYESIAN-APPROACH TO EVALUATECAUSALITY

The problem of interpreting missense mutations of disease-causing gene s is an Increasingly important one. Because these point mutations resu lt in alteration of only a single amino acid of the protein product, i t is often unclear whether this change alone is sufficient to cause di sease. We propose a Bayesian approach that utilizes genetic informatio n on affected relatives in families ascertained through known missense -mutation carriers. This method is useful in evaluating known disease genes for common disease phenotypes, such as breast cancer or colorect al cancer. The posterior probability that a missense mutation is disea se causing is conditioned on the relationship of the relatives to the proband, the population frequency of the mutation, and the phenocopy r ate of the disease. The approach is demonstrated in two cancer data se ts: BRCA1 R841W and APC I1307K. In both examples, this method helps es tablish that these mutations are likely to be disease causing, with Ba yes factors in favor of causality of 5.09 and 66.97, respectively, and posterior probabilities of .836 and .985. We also develop a simple ap proximation for rare alleles and consider the case of unknown penetran ce and allele frequency.