Cognitive and Adaptive Profile Differences Between Diagnostically Concordant and Nonconcordant Twins with ASD

Friday, May 13, 2016: 5:30 PM-7:00 PM
Hall A (Baltimore Convention Center)
J. Cash1, J. Mendelson2, C. Hall3, S. Hoffenberg3 and T. Aronson1, (1)Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, (2)Marcus Autism Center, Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA and The University of North Carolina at Greensboro, Greensboro, NC, (3)Marcus Autism Center, Children's Healthcare of Atlanta, and Emory University School of Medicine, Atlanta, GA
Background: Research on twins has demonstrated a strong genetic contribution to autism spectrum disorder (ASD), with monozygotic (MZ) twin ASD concordance rates ranging from 60 to 90% and dizygotic (DZ) ASD concordance rates ranging from 5 up to 20% (Bohm et al., 2009). Additionally, research suggests young children with ASD perform better on nonverbal tasks than language tasks (Hartley et al., 2009) and children with ASD tend to have the most substantial delays in socialization, slighter delays in communication, and relative strengths in daily living skills (Bolte and Poustka, 2002). However, little research has been done examining the developmental profiles of concordant and nonconcordant twins with ASD.

Objectives: The goal of the current study is to examine cognitive and adaptive profile differences between and among concordant and nonconcordant twins with ASD. 

Methods: Participants included two MZ dyads and 12 DZ dyads, who were evaluated between the ages of 25 to 85 months (M=53.04 months, SD=19.56) in a diverse clinical setting. Twelve pairs of twins received concordant diagnoses of ASD.

Assessments included a developmental or cognitive measure (i.e., the Mullen Scales of Early Learning, Differential Abilities Scales-2nd Edition, or Stanford-Binet Intelligence Scales, 5thEdition), the Vineland Adaptive Behavior Scales, 2nd Edition, Survey Form, and the Autism Diagnostic Observation Schedule. Scores were converted to z-scores to compare group means. 

Results: Overall diagnostic concordance was 86%. Diagnostic concordance in DZ twin dyads was 83%. Variability across cognitive and adaptive measures was examined by calculating a difference score for each twin dyad. Concordant twin dyads were highly consistent (i.e., less than 1 SD apart) in their adaptive skills (80-90%) as well as verbal (60%) and nonverbal (64%) cognitive abilities. Concordant twins demonstrated significantly lower verbal IQ than nonverbal IQ (t(20)=-2.273, p<.05). Nonconcordant twins demonstrated significantly higher verbal IQ (t(23)=4.44, p<.01), nonverbal IQ (t(3.57), p<.01) and higher adaptive communication at a level that approached significance (t(18)=1.832, p=.084) than concordant twins. Additionally, nonconcordant twins were significantly older than concordant twins (t(15)=3.99, p<.01).

Conclusions: Data from the current study indicates DZ cognitive profiles among concordant twins are consistent with reported ASD profiles (Bohm et al., 2009). However, adaptive profiles among concordant twins are not consistent with the literature (Bolte and Poustka, 2002). Interestingly, concordant twins in this clinical sample have the most substantial delays in the area of adaptive communication and lesser delays in daily living skills and socialization. Nonconcordant dyads were significantly older at time of diagnosis and displayed better cognitive skills than concordant twins. Although they present with difficulties in the areas of socialization and daily living skills, they also present with stronger cognitive and adaptive communication skills. These profiles may lead to diagnostic ambiguity and later age of diagnosis. Findings indicate cognitive and adaptive profiles differ significantly between diagnostically concordant and nonconcordant twins. Future research should examine the relation between diagnostic concordance and cognitive/adaptive functioning, while controlling for zygosity, which will inform our understanding of heritable and shared environment contributions to cognitive and adaptive profiles in children with ASD.