Can a heart rate variability biomarker identify the presence of autism spectrum disorder in eight year old children?
  Autonomic nervous system (ANS) activity is altered in autism spectrum
disorder (ASD). Heart rate variability (HRV) derived from electrocardiogram
(ECG) has been a powerful tool to identify alterations in ANS due to a plethora
of pathophysiological conditions, including psychological ones such as
depression. ECG-derived HRV thus carries a yet to be explored potential to be
used as a diagnostic and follow-up biomarker of ASD. However, few studies have
explored this potential. In a cohort of boys (ages 8 - 11 years) with (n=18)
and without ASD (n=18), we tested a set of linear and nonlinear HRV measures,
including phase rectified signal averaging (PRSA), applied to a segment of ECG
collected under resting conditions for their predictive properties of ASD. We
identified HRV measures derived from time, frequency and geometric
signal-analytical domains which are changed in ASD children relative to peers
without ASD and correlate to psychometric scores (p<0.05 for each). Receiver
operating curves area ranged between 0.71 - 0.74 for each HRV measure. Despite
being a small cohort lacking external validation, these promising preliminary
results warrant larger prospective validation studies.
