Identifying a mutation in a heterogeneous disease such as inherited cardiomyopathy is a challenge because classical methods, like linkage analysis, can often not be applied as there are too few meioses between affected individuals. However, if affected individuals share the same causal mutation, they will also share a genomic region surrounding it. High-density genotyping arrays are able to identify such regions shared among affected individuals. We hypothesize that the longest shared haplotype is most likely to contain the disease-causing mutation. We applied this method to two pedigrees: one with arrhythmogenic right ventricular cardiomyopathy (ARVC) and one with dilated cardiomyopathy (DCM), using high-density genome-wide SNP arrays. In the ARVC pedigree, the largest haplotype was on chromosome 12 and contained a causative PKP2 mutation. In the DCM pedigree, a causative MYH7 mutation was present on a large shared haplotype on chromosome 14. We calculated that a pedigree containing at least seven meioses has a high chance of correctly detecting the mutation-containing haplotype as the largest. Our data show that haplotype sharing analysis can assist in identifying causative genes in families with low penetrance Mendelian diseases, in which standard tools cannot be used due to lack of sufficient pedigree information.
© 2010 John Wiley & Sons A/S.