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Published on: August 25, 2014
The Face and Features of RNU4-2: A New, Common, Recognizable, Yet Hidden Neurodevelopmental Disorder
Kristen Barbour1, Matthew N Bainbridge2, Kristen Wigby3
1Division of Genetics and Dysmorphology, Department of Pediatrics, University of California, San Diego, Rady Children's Hospital, San Diego, California.
Background:
RNU4-2 is a newly identified, noncoding gene responsible for a significant proportion of individuals with neurodevelopmental disorders (NDDs). Diagnosis is hampered by the inability of commonly employed clinical testing methods, including exome sequencing and currently formulated multigene panels, to detect variants in the noncoding region. The relatively high prevalence of this condition, predicted to affect thousands of undiagnosed children with NDDs, makes it even more relevant to have better tools to facilitate diagnosis. The initial report of the gene-disease association outlined aggregate phenotypic features but lacked detailed patient evaluations, potentially under-reporting phenotypic features and failing to highlight unique aspects. We aimed to identify individuals with RNU4-2 gene variants to deeply phenotype the clinical profile. We sought to define key features that may suggest the diagnosis, to highlight individuals for whom specialized testing, able to detect noncoding region variants, may be indicated.
Methods:
We reviewed genomic data from 6,734 individuals, identifying five with recurrent de novo RNU4-2 (n.64_65insT) variants. We clinically evaluated four. Findings were compared with those previously reported.
Results:
We identify common clinical features, a distinctive dysmorphic facial pattern, and shared imaging abnormalities. We describe novel aspects including longitudinal trajectory and treatment response.
Conclusions:
Enhanced recognition of the RNU4-2 (n.64_65insT-common variant) phenotype, particularly the dysmorphic facial features, will facilitate earlier diagnosis. Distinctive characteristics will guide the selection of patients for testing able to detect RNU4-2 variants: genome sequencing or targeted gene testing. Furthermore, health and research systems may identify undiagnosed patients by querying databases for individuals exhibiting the traits described herein.
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