Comparison of Mullen Profiles Among Children with DS, ASD, and Comorbid Presentation of DS and ASD

Saturday, May 13, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
M. Udhnani1, T. Hamner1, D. Fidler2, S. Hepburn3, C. Robinson Rosenberg4 and N. R. Lee1, (1)Drexel University, Philadelphia, PA, (2)Colorado State University, Fort Collins, CO, (3)University of Colorado / JFK Partners, Aurora, CO, (4)University of Colorado, Aurora, CO
Background: While there is a sizeable body of research on developmental profiles for children with Down syndrome (DS) and children with Autism Spectrum Disorder (ASD), little is known about the profile of children with both (DS+ASD). Although some studies have reported that children with comorbid DS+ASD have lower developmental quotients than those with DS (DiGuiseppi et al., 2010), the profile of relative strengths and weaknesses on developmental tests, such as the Mullen Scales of Early Learning (MSEL), is not firmly established, particularly relative to groups with DS or ASD in isolation. As early intervention has been shown to alter developmental trajectories and improve lifetime outcomes for children with ASD (Orinstein et al., 2014; Zwaigenbaum et al., 2015), elucidating the cognitive profiles of children with comorbid DS+ASD early in development is critical to informing early intervention for this group.

Objectives: The goal of this study is to assess developmental profiles within and between clinical samples of children with ASD, DS, and DS+ASD.

Methods: Participants included 165 children (112 males; Mean age=51.54+23) with ASD (n=111), DS (n=31), and DS+ASD (n=23). Data were compiled from a larger study completed at the University of Colorado School of Medicine (DiGuiseppi et al., 2010) and from the National Database for Autism Research. Children with ASD were matched to the two DS groups on age and sex. Developmental functioning was assessed using the MSEL. Developmental quotients ([mental age/chronological age]*100) were calculated for the Visual Reception (VR), Fine Motor (FM), Receptive Language (RL), and Expressive Language (EL) scales of the MSEL.

Results: A 3x4 repeated measures ANOVA with one between-subjects factor (Group: ASD vs. DS vs. DAS+ASD) and one within-subjects factor (MSEL Scale) was completed to evaluate whether the profile of scores differed as a function of group. A significant group x scale interaction was revealed (F [6,486]=5.7, p<.001), such that the ASD groups had a more variable MSEL scale profile than the DS only group. Specifically, when each group’s individual scale DQs were compared to mean DQ (averaged across the 4 scales), a pattern emerged differentiating the DS only group from the two ASD groups. For DS only, VR was significantly higher than mean DQ, while EL was significantly lower (ps<.003). In contrast, all scales differed from mean DQ in the ASD and DS+ASD group (all ps<.02); VR and FM were significantly higher, while RL and EL were significantly lower.

Conclusions:  Results of this preliminary study suggest MSEL profiles for children with DS+ASD are more similar to those with ASD than DS. While MSEL absolute scores differed between DS+ASD and ASD overall, the pattern of scores was similar. Moreover, individual scale scores were more variable for the two ASD groups than for the DS group alone. Thus, identifying a comorbid ASD diagnosis in youth with DS appears to not only be important for treatment targeting social-communication skills but also for educational planning.