Clinical phenotype of ASD-associated DYRK1A haploinsufficiency

Abstract

Background DYRK1A is a gene recurrently disrupted in 0.1–0.5% of the ASD population. A growing number of case reports with DYRK1A haploinsufficiency exhibit common phenotypic features including microcephaly, intellectual disability, speech delay, and facial dysmorphisms.MethodsPhenotypic information from previously published DYRK1A cases (n = 51) and participants in an ongoing study at the University of Washington (UW, n = 10) were compiled. Frequencies of recurrent phenotypic features in this population were compared to features observed in a large sample with idiopathic ASD from the Simons Simplex Collection (n = 1981). UW DYRK1A cases were further characterized quantitatively and compared to a randomly subsampled set of idiopathic ASD cases matched on age and gender (n = 10) and to cases with an ASD-associated disruptive mutation to CHD8 (n = 12). Contribution of familial genetic background to clinical heterogeneity was assessed by comparing head circumference, IQ, and ASD-related symptoms of UW DYRK1A cases to their unaffected parents.Results DYRK1A haploinsufficiency results in a common phenotypic profile including intellectual disability, speech and motor difficulties, microcephaly, feeding difficulties, and vision abnormalities. Eighty-nine percent of DYRK1A cases ascertained for ASD presented with a constellation of five or more of these symptoms. When compared quantitatively, DYRK1A cases presented with significantly lower IQ and adaptive functioning compared to idiopathic cases and significantly smaller head size compared to both idiopathic and CHD8 cases. Phenotypic variability in parental head circumference, IQ, and ASD-related symptoms corresponded to observed variability in affected child phenotype.ConclusionsResults confirm a core clinical phenotype for DYRK1A disruptions, with a combination of features that is distinct from idiopathic ASD. Cases with DYRK1A mutations are also distinguishable from disruptive mutations to CHD8 by head size. Measurable, quantitative characterization of DYRK1A haploinsufficiency illuminates clinical variability, which may be, in part, due to familial genetic background.Electronic supplementary materialThe online version of this article (10.1186/s13229-017-0173-5) contains supplementary material, which is available to authorized users.

Big data approaches to decomposing heterogeneity across the autism spectrum

“…As the phrase implies, a bottom-up approach starts with identifying and building useful models from a lower level in the hierarchy, and then asks questions about how such lowlevel models can explain phenomena higher up in the hierarchy. For example, in the 'genetics first' approach, an investigator may be interested in identifying how different high-impact genetic causes of autism may be similar or different at a phenotypic or cognitive level of analysis [90][91][92][93]. In another example, an investigator may compare autism subtypes at the level of neural systems or structural brain features (e.g., with or without early brain enlargement), and then ask the question of whether such a stratification provides a meaningful indicator of differentiation at a clinical level [14].…”

Functional characterization of DYRK1A missense variants associated with a syndromic form of intellectual deficiency and autism

“…DYRK1A mutations were also observed in exome sequencing studies of patients with autism spectrum disorder (ASD) ( O'Roak et al, 2012a , b ; Samocha et al, 2014 ). Autistic behavior is now recognized as a component of the core phenotype of the DYRK1A haploinsufficiency syndrome ( van Bon et al, 2016 ; Bronicki et al, 2015 ; Ji et al, 2015 ; Earl et al, 2017 ; Dang et al, 2018 ).…”

Lost in Translation: Traversing the Complex Path from Genomics to Therapeutics in Autism Spectrum Disorder

“…For example, some of the first risk genes identified in wellcharacterized nsASD cases (Szatmari et al, 2007;Jamain et al, 2003;Marshall et al, 2008;Neale et al, 2012;O'Roak et al, 2012b;Sanders et al, 2012) show very high penetrance, approaching that seen in monogenic forms of ASD and ID. Moreover, these nsASD genes point to pathways and processes that show obvious areas of overlap with what is known about syndromic biology (De Rubeis et al, 2014;Iossifov et al, 2012Iossifov et al, , 2014Zoghbi, 2003), and when phenotypically characterized in depth, some nsASD individuals with deleterious mutations in a confirmed risk gene have shown clusters of associated physical features suggesting a previously uncharacterized ASD syndrome (Bernier et al, 2014;Earl et al, 2017;O'Roak et al, 2012a).…”