Title: Can a heart rate variability biomarker identify the presence of autism spectrum disorder in eight year old children?,
Abstract: 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.