Differential Diagnosis of Autism and Other Neurodevelopmental Disorders

DSM-5 based algorithms for the Autism Diagnostic Interview-Revised for children ages 4-17 years

BACKGROUND

The Autism Diagnostic Interview, Revised (ADI-R) is a caregiver interview that is widely used as part of the diagnostic assessment for Autism Spectrum Disorder (ASD). Few large-scale studies have reported the sensitivity and specificity of the ADI-R algorithms, which are based on DSM-IV Autistic Disorder criteria. Kim and Lord (Journal of Autism and Developmental Disorders, 2012, 42, 82) developed revised DSM-5-based toddler algorithms, which are only applicable to children under 4 years. The current study developed DSM-5-based algorithms for children ages 4-17 years and examined their performance compared to clinical diagnosis and to the original DSM-IV-based algorithms.

METHODS

Participants included 2,905 cases (2,144 ASD, 761 non-ASD) from clinical-research databanks. Children were clinically referred for ASD-related concerns or recruited for ASD-focused research projects, and their caregivers completed the ADI-R as part of a comprehensive diagnostic assessment. Items relevant to DSM-5 ASD criteria were selected for the new algorithms primarily based on their ability to discriminate ASD from non-ASD cases. Algorithms were created for individuals with and without reported use of phrase speech. Confirmatory factor analysis tested the fit of a DSM-5-based two-factor structure. ROC curve analyses examined the diagnostic accuracy of the revised algorithms compared to clinical diagnosis.

RESULTS

The two-factor structure of the revised ADI-R algorithms showed adequate fit. Sensitivity of the original ADI-R algorithm ranged from 74% to 96%, and specificity ranged from 38% to 83%. The revised DSM-5-based algorithms performed similarly or better, with sensitivity ranging from 77% to 99% and specificity ranging from 71% to 92%.

CONCLUSIONS

In this large sample aggregated from US clinical-research sites, the original ADI-R algorithm showed adequate diagnostic validity, with poorer specificity among individuals without phrase speech. The revised DSM-5-based algorithms introduced here performed comparably to the original algorithms, with improved specificity in individuals without phrase speech. These revised algorithms offer an alternative method for summarizing ASD symptoms in a DSM-5-compatible manner.

A novel compound heterozygous mutation of UFC1 in a patient with neurodevelopmental disorder

BACKGROUND

Neurodevelopmental disorders (NDDs) encompass a diverse group of disorders characterized by impaired cognition, behavior, and motor skills. Genetic factor is the leading cause in about 35% of NDDs patients. Mutations of UFC1, an E2 enzyme participating in the post-translational modification of proteins through attachment of ubiquitin-like proteins, were recently reported to be associated with NDDs. However, the UFC1 associated NDDs are rare and the data are scarce, thus making it difficult to identify this disease.

OBJECTIVE

This study reported a novel compound heterozygous mutation of UFC1 in a Chinese patient with NDD.

METHODS

Detailed clinical data were recorded. Whole exome sequencing (WES) was performed to determine the genetic cause of the patient. The candidate mutation was verified using Sanger sequencing.

RESULTS

WES analysis identified a novel compound heterozygous mutation of UFC1 (c.19 C > T, p.Arg7* and c.164G > A, p.Arg55Gln). The nonsense mutation c.19 C > T (p.Arg7*) led to a premature truncation of UFC1 and nonsense-mediated RNA decay. Arg55 is highly conserved among orthologues. Molecular modeling predicted that mutation c.164G > A (p.Arg55Gln) may influence the correct folding of UFC1. These two mutations were evaluated as likely pathogenic based on the ACMG guideline. Moreover, neurodevelopmental delay, microcephaly, and epilepsy were confirmed as major phenotypes of UFC1 mutation.

CONCLUSION

This study expands the mutational spectrum of NDDs. We reported the nonsense mutation of UFC1 for the first time. We also confirmed the major phenotypes that may guide clinical identification of UFC1 mutation. Ubiquitination mechanism is highlighted in NDDs pathogenesis.