Status: Funded - Open
Sarah Stenton, MBChB, PhD
BACKGROUND: Rare genetic diseases collectively affect over 250 million people worldwide, 50% of whom are children, and pose a significant cost burden to health care systems given high morbidity and mortality. The delivery of optimal medical care by individualized treatment depends on a genetic diagnosis, however, over 60% of patients with a high suspicion of genetic disease remain undiagnosed. GAP: Current clinical practice guidelines for variant interpretation follow a monogenic disease model, focusing on identifying disease causative variants in a single gene with the phenotypic potential to cause disease. The contribution of digenic inheritance to undiagnosed pediatric rare disease is yet to be systematically explored. HYPOTHESIS: In a subset of undiagnosed children, the co-occurrence of rare damaging variants in a gene pair results in digenic disease. This gene pair will be depleted for the co-occurrence of rare damaging variant in healthy individuals. METHODS: The study will utilize trio-exome and genome sequencing data from >2,000 undiagnosed families sequenced by the Broad Institute Center for Mendelian Genomics and the Rare Genome Project. Data will be systematically reanalyzed with implementation of machine learning tools for candidate digenic diagnosis detection, supported by familial segregation data and individual-level data at scale from healthy relatives and individuals without severe early-onset disease in the population database gnomAD. RESULTS: Pending. IMPACT: Identifying candidate digenic diagnoses in undiagnosed children has the potential to enable genetic counselling (e.g., by accurate recurrence risk calculation), illuminate targeted treatment options, and may inform future development of clinical practice guidelines for digenic variant interpretation in genomic sequencing analysis.