Genomic diagnosis of rare pediatric disease in the United Kingdom and Ireland

Abstract

Background: Pediatric disorders include a range of highly penetrant, genetically heterogeneous conditions amenable to genome-wide diagnostic approaches. Finding a molecular diagnosis is challenging but can have lifelong benefits.

Methods: The Deciphering Developmental Disorders (DDD) study recruited >13,500 families with severe, likely monogenic, difficult-to-diagnose developmental disorders from 24 regional genetics services around the UK and Ireland. We collected standardised phenotype data and performed exome sequencing and microarray analysis to investigate novel genetic causes. We developed an iterative variant analysis pipeline, reporting candidate variants to clinical teams for validation, diagnostic interpretation and communication to families. We performed multiple regression analyses evaluating factors affecting probability of diagnosis.

Results: We reported ~1 candidate variant per parent-offspring trio and ~2.5 variants per singleton proband. Using clinical and computational approaches to variant classification, we achieved a diagnosis in ~41% (5502 probands), of whom ~76% have a pathogenic de novo variant. Another ~22% have variants of uncertain significance in genes robustly linked with monogenic developmental disorders. Recruitment as a parent-offspring trio had the largest impact on chance of diagnosis (OR=4.70). Probands who were extremely premature (OR=0.39), had in-utero exposure to antiepileptic medications (OR=0.44), or whose mothers had diabetes (OR=0.52) were less likely to be diagnosed, as were those of African ancestry (OR=0.51).

Conclusions: The DDD study shows multimodal analysis of genome-wide data has good diagnostic power, even after prior attempts at diagnosis.