Developmental Trajectories of Respiratory Sinus Arrhythmia in Children with Autism from Birth to Early Childhood

Saturday, May 17, 2014: 11:54 AM
Imperial B (Marriott Marquis Atlanta)
S. J. Sheinkopf1, T. P. Levine1, B. Abar1, E. Conradt1, L. L. LaGasse1, R. Seifer2, S. Shankaran3, H. Bada-Ellzey4, C. Bauer5, T. M. Whitaker6, J. A. Hammond7 and B. M. Lester1, (1)Brown Center for the Study of Children at Risk, Women & Infants Hospital, Providence, RI, (2)Department of Psychiatry, Warren Alpert Medical School of Brown University, Providence, RI, (3)Wayne State University, Detroit, MI, (4)Department of Pediatrics, University of Kentucky, Lexington, KY, (5)Department of Pediatrics, Miller School of Medicine, University of Miami, Miami, FL, (6)The University of Tennessee Health Science Center, Memphis, TN, (7)RTI International, Rockville, MD
Background: Physiologic systems regulating arousal and attention are thought to be affected in autism and appear to be related to functioning and deveopmental outcomes in this population. Respiratory sinus arrhythmia (RSA), a measure of heart rate variability and an index of physiological regulation, has been reported to be diminished in autism. However,  the development of RSA and related regulatory systems in infants later diagnosed with autism has not been studied.

Objectives: To examine physiological regulation in infants later diagnosed with autism by modeling the longitudinal trajectory of heart rate (HR) and RSA in a sample of infants observed from birth and later diagnosed with autism.

Methods: Twelve (12) children with autism were identified from the Maternal Lifestyle Study (n = 1388), a longitudinal study of high-risk infants. Autism diagnoses were confirmed by clinician best estimate plus above-threshold scores on the Autism Diagnostic Observation Schedule. A case control design was utilized to select a comparison sample (n = 106) matched on prenatal risk factors and birth weight. Electrocardiogram (ECG) recordings were collected during standardized observations at 1, 12, 18, 24, 36, 48, 60, and 72 months of age. ECG post-processing incorporated automated artifact detection and correction routines. RSA was calculated from the resulting “cleaned” time series data using Porges’ method. Latent growth curve analyses were used to model the developmental course of HR and RSA in the two groups. All models were performed in Mplus 6.0 using a full information maximum likelihood estimator to account for missing data over time. Unconditional and conditional latent growth curve (LGC) models were performed to demonstrate the overall HR and RSA trajectories as well as the effect of autism diagnosis on growth trajectories.

Results: Unconditional LGC models demonstrated an expected age-related decrease in HR and increase in RSA over time. Conditional LGC models (including autism diagnosis) did not show an effect of diagnosis on the decrease of HR over time (p = 0.23). With regard to RSA, children with autism demonstrated a smaller linear increase over time than comparison children (p < 0.01).  There was also a significant effect of diagnosis on the quadratic trend for RSA (p < 0.01). Children with autism demonstrated a stronger flattening/downturn in RSA at later ages than comparison children. There was no effect of diagnosis on initial level of RSA (p= 0.30).

Conclusions: These results suggest that differences in physiological regulation may develop with age in autism. Developmental change in RSA was slower in infants later diagnosed with autism. This slowed RSA growth in autism was most evident after 18 months of age, at a time when behavioral symptoms become prominent. This is consistent with the view that RSA is a marker of functional status in autism and raises the hypothesis that differences in RSA emerge developmentally. Larger studies are needed to determine if differences are present earlier in infancy. Longitudinal studies of developmental trajectories such as this will have implications for the timing and targets of treatment in infants at risk for autism.