Improved diagnosis of rare disease patients through systematic detection of runs of homozygosity.

Autozygosity is associated with an increased risk of genetic rare disease (RD), thus being a relevant factor for clinical genetic studies. More than 2400 ES datasets were analysed and screened for autozygosity based on detection of >1Mbp runs of homozygosity (ROH). A model was built to predict if an individual is likely to be a consanguineous offspring (accuracy 98%) and "probability of consanguinity" ranges were established according to the total ROH size. Application of the model resulted in the re-classification of the consanguinity status of 12% of the patients. The analysis of a subset of 79 consanguineous cases with the RD-Connect Genome-Phenome Analysis Platform (GPAP) combining variant filtering and homozygosity mapping enabled a 50% reduction in the number of candidate variants and the identification of homozygous pathogenic variants in 41 patients, with an overall diagnostic yield of 52%. The newly defined consanguinity ranges provide, for the first time, specific ROH thresholds to estimate inbreeding within a pedigree on disparate ES data, enabling confirmation or (re)classification of consanguineous status, hence increasing the efficiency of molecular diagnosis and reporting on secondary consanguinity findings, as recommended by ACMG guidelines.