Am J Hum Genet 2019 06 23;104(6):1182-1201. Epub 2019 May 23.
Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia; Saudi Human Genome Program, King Abdulaziz City for Science and Technology, Riyadh 12354, Saudi Arabia; College of Medicine, Alfaisal University, Riyadh 11533, Saudi Arabia. Electronic address:
We report the results of clinical exome sequencing (CES) on >2,200 previously unpublished Saudi families as a first-tier test. The predominance of autosomal-recessive causes allowed us to make several key observations. We highlight 155 genes that we propose to be recessive, disease-related candidates. We report additional mutational events in 64 previously reported candidates (40 recessive), and these events support their candidacy. We report recessive forms of genes that were previously associated only with dominant disorders and that have phenotypes ranging from consistent with to conspicuously distinct from the known dominant phenotypes. We also report homozygous loss-of-function events that can inform the genetics of complex diseases. We were also able to deduce the likely causal variant in most couples who presented after the loss of one or more children, but we lack samples from those children. Although a similar pattern of mostly recessive causes was observed in the prenatal setting, the higher proportion of loss-of-function events in these cases was notable. The allelic series presented by the wealth of recessive variants greatly expanded the phenotypic expression of the respective genes. We also make important observations about dominant disorders; these observations include the pattern of de novo variants, the identification of 74 candidate dominant, disease-related genes, and the potential confirmation of 21 previously reported candidates. Finally, we describe the influence of a predominantly autosomal-recessive landscape on the clinical utility of rapid sequencing (Flash Exome). Our cohort's genotypic and phenotypic data represent a unique resource that can contribute to improved variant interpretation through data sharing.