Large-scale discovery of novel genetic causes of developmental disorders

By Tomas W. Fitzgerald, S. Gerety, W. Jones, M. Kogelenberg, D. King, J. McRae, Katherine I. Morley, Vijaya Parthiban, Saeed Al-Turki, K. Ambridge and 255 more. 2014

1,061 citations recorded by the source corpus.

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders.

Subfields: Genetics, Molecular Biology

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Citations in the corpus

Phase 2 of CATALISE: a multinational and multidisciplinary Delphi consensus study of problems with language development: Terminology (2017, neutral): “…genetic or neurological causes (Fitzgerald et al., 2015; Shevell, Majnemer, Rosenbaum, & Abrahamowicz, 2001), with the numbers of known aetiology increasing with advances in genetic methods (Bourgeron, 2015; Fitzgerald et al., 2015; Shevell et al., 2001).”
Using deep mutational scanning to benchmark variant effect predictors and identify disease mutations (2020, neutral): “…nonsynonymous single nucleotide variant (SNV) per protein-coding gene (Rauch et al , 2012), while de novo mutations lead to roughly one new nonsynonymous SNV per child not observed in either parent (de Ligt et al , 2012; Neale et al , 2012; Epi4K Consortium et al , 2013; Fitzgerald et al , 2015).”
Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci (2015, methodology): “Small de novo deletions show consistent enrichment for dnLoF and dnMissense mutations across three cohorts: SSC, Autism Sequencing Consortium (ASC), and Deciphering Developmental Disorders (DDD).”