Thursday, May 20, 2010: 2:15 PM
Grand Ballroom AB Level 5 (Philadelphia Marriott Downtown)
1:30 PM
Background: Biomarker detection is crucial to the discovery of biologically homogeneous ASD subgroups. We found that children with ASD demonstrate a significantly different pupillary response (PLR) to a transient light flash (Fan & Yao, 2009). The latency of the pupil’s response from light flash to the beginning of pupillary constriction discriminated ASD children from typically developing controls with a cross-validated success rate of 89.6%, which increased to 92.5% when constriction amplitude was considered. Since the PLR parameters (latency, constriction amplitude and constriction & redilation velocity) represent different biological functions, study of PLR may provide a number of distinct ASD biomarkers.
Objectives: 1) To identify the clinical and etiologic variables that correlate with variance in the PLR parameters. 2) To characterize the subgroups of children with ASD who demonstrate the various PLR variances. 3) To analyze the neurologic bases of the phenotypes of each subgroup in order to understand the biological mechanism for each PLR parameter change in ASD.
Methods: Phenotypic features including physical (dysmorphology, head size, growth), clinical course (age & type of onset, clinical improvement with fever), medical and neurologic symptoms (seizures, toe walking, sleep disturbances, etc.) and genetic indicators (gender, family history of ASD and related disorders, recurrence in sibs, parental ages), outcome measures (IQ, language, adaptive scores) and ASD symptoms (ADI-R) were compared with PLR data for 22 children with ASD and 43 age matched typically developing control children. Subject characteristics were 20 male:2 female, mean age 12 +/- 4 years, diagnoses: 9 Aspergers, 8 Autistic disorder and 5 PDD-NOS and mean IQ = 87.2 (SD=24).
Results: Two neurologic features correlated with PLR parameters. Children who showed an improvement in ASD symptoms during fever had a significantly larger constriction amplitude compared to those whose parents did not report improvement (P=0.006). The group with improvement in autistic behaviors during fever has constriction amplitudes closer in value to the TD controls than those who do not improve during fever. Second, children who toe walked during development showed a longer PLR latency compared to non-toe walkers (p=0.01). The group who toe walked had the longest latency, i.e. the greatest variance from the typically developing control group.
Conclusions: The clinical features, improvement with fever and toe walking that correlate with the PLR variances observed in ASD are both neurologic. Pupillary constriction is regulated by parasympathetic stimulation. Finding greater pupillary constriction in children who improve with fever suggests greater parasympathetic or less sympathetic tone in that subgroup. Thus, PLR constriction amplitude may be a biomarker for autonomic dysfunction in autism, possibly related to modulation of the locus coeruleus-noradrenergic system which stimulates sympathetic effects. Increased latency is considered a measure of interference with nerve conduction or cerebellar modulation (Rinehart et al. 2006). Our finding of increased PLR latency in almost 90% of our ASD study group is consistent with either one ubiquitous mechanism or may be the result of a number of systems that effect nerve conduction efficiency. These correlations will guide ongoing studies designed to provide insight into biological mechanisms underlying ASD subgroups.
Objectives: 1) To identify the clinical and etiologic variables that correlate with variance in the PLR parameters. 2) To characterize the subgroups of children with ASD who demonstrate the various PLR variances. 3) To analyze the neurologic bases of the phenotypes of each subgroup in order to understand the biological mechanism for each PLR parameter change in ASD.
Methods: Phenotypic features including physical (dysmorphology, head size, growth), clinical course (age & type of onset, clinical improvement with fever), medical and neurologic symptoms (seizures, toe walking, sleep disturbances, etc.) and genetic indicators (gender, family history of ASD and related disorders, recurrence in sibs, parental ages), outcome measures (IQ, language, adaptive scores) and ASD symptoms (ADI-R) were compared with PLR data for 22 children with ASD and 43 age matched typically developing control children. Subject characteristics were 20 male:2 female, mean age 12 +/- 4 years, diagnoses: 9 Aspergers, 8 Autistic disorder and 5 PDD-NOS and mean IQ = 87.2 (SD=24).
Results: Two neurologic features correlated with PLR parameters. Children who showed an improvement in ASD symptoms during fever had a significantly larger constriction amplitude compared to those whose parents did not report improvement (P=0.006). The group with improvement in autistic behaviors during fever has constriction amplitudes closer in value to the TD controls than those who do not improve during fever. Second, children who toe walked during development showed a longer PLR latency compared to non-toe walkers (p=0.01). The group who toe walked had the longest latency, i.e. the greatest variance from the typically developing control group.
Conclusions: The clinical features, improvement with fever and toe walking that correlate with the PLR variances observed in ASD are both neurologic. Pupillary constriction is regulated by parasympathetic stimulation. Finding greater pupillary constriction in children who improve with fever suggests greater parasympathetic or less sympathetic tone in that subgroup. Thus, PLR constriction amplitude may be a biomarker for autonomic dysfunction in autism, possibly related to modulation of the locus coeruleus-noradrenergic system which stimulates sympathetic effects. Increased latency is considered a measure of interference with nerve conduction or cerebellar modulation (Rinehart et al. 2006). Our finding of increased PLR latency in almost 90% of our ASD study group is consistent with either one ubiquitous mechanism or may be the result of a number of systems that effect nerve conduction efficiency. These correlations will guide ongoing studies designed to provide insight into biological mechanisms underlying ASD subgroups.