29792
Speech Impairment Affects Expressive Language in Minimally Verbal Children with Autism Spectrum Disorder

Poster Presentation
Friday, May 3, 2019: 5:30 PM-7:00 PM
Room: 710 (Palais des congres de Montreal)
K. V. Chenausky1, A. Brignell2, A. T. Morgan2 and H. Tager-Flusberg3, (1)Sargent College, Boston University, Boston, MA, (2)Murdoch Children's Research Institute and University of Melbourne, Melbourne, Australia, (3)Psychological and Brain Sciences, Boston University, Boston, MA
Background:

25-30% of children with autism spectrum disorder (ASD) remain minimally verbal (MV) past age five (Kasari et al. 2013; Norrelgen et al. 2015). It remains unclear why spoken language acquisition is limited in these children, but we do know that a lack of spoken language is associated with high rates of challenging behaviors (Dominick et al., 2007) and is thus an important therapeutic target.

Speech impairment as a contributor to expressive language has been under-investigated relative to factors such as joint attention, language impairment, nonverbal IQ, and ASD severity, though disorders such as childhood apraxia of speech (CAS; a disorder in the planning and sequencing of speech movement; Iuzzini-Seigel et al., 2015) are hypothesized to be over-represented in ASD compared to the general population (Tierney et al., 2015).

Objectives: To estimate the proportion of individuals with MV ASD with speech impairment and to explore the contribution of measures of speech, receptive vocabulary, and nonverbal IQ to variability in expressive language.

Methods:

Videos of 57 individuals with MV ASD (13 F; ages 4;4-18;10) participating in the Kaufman Speech Praxis Test (KSPT; Kaufman, 1995) were coded for features of CAS and other speech anomalies. A consensus reliability method was used for coding.

One-way ANOVAs were performed to determine whether groups differed on age, ADOS severity, NVIQ, receptive vocabulary (PPVT), KSPT Section 1 (KSPT1; nonspeech oral-motor), and KSPT Section 2 (KSPT2; speech). Variables differing significantly between groups were entered into a hierarchical multiple regression to understand their contributions to the variance in Number of Different Words (NDW) from a structured language sample.

Results: Four groups emerged: No Abnormalities Detected, Non-CAS Speech Disorder, Suspected CAS, and Insufficient Speech to Rate. Groups differed significantly on PPVT, NVIQ, KSPT1, and KSPT2 (Table 1). The overall regression model including these four variables was significant (F(4,40) = 8.672, p < 0.0005), accounting for 41.1% of the variance in NDW (adj. R2). However, KSPT1 and NVIQ contributed insignificant amounts of R2. A reduced model including just KSPT2 and PPVT was also significant (F(2,42) = 17.777, p < 0.0005) and accounted for 43.3% of the variance in NDW (adj. R2). PPVT score contributed a ΔR2 of 0.126 (p = 0.003); KSPT2 contributed a ΔR2 of 0.333 (p < 0.0005). PPVT and KSPT2 were not collinear (VIF = 2.8).

Conclusions: Minimally verbal individuals with ASD differ in the nature and severity of their speech involvement, suggesting the existence of separate speech endophenotypes in this population. Speech motor ability (KSPT2 score) accounted for significant variance in expressive language, with PPVT score accounting for additional significant variance. Speech impairment may limit expressive language development in some individuals with MV ASD and is an important area to explore for the creation of novel therapies for these children.