MEG Measures of Auditory Processing in ASD: Prognostic Biomarkers

Background:  Biomarkers for ASD have been discussed in terms of their potential diagnostic utility and as a biologically-based rationale for population stratification with potential implications for patient management. Among a broad spectrum of approaches, candidate measures proposed as such biomarkers derive from imaging and, promisingly, electrophysiologic techniques (such as EEG and MEG). The latter have attractive features in terms of high temporal resolution, sensitivity for neuronal electrical activity and, importantly, mechanistic interpretation including anomalies of central conduction velocity and local circuitry functionality. This study extends prior studies of auditory processing using MEG and specifically focuses on latency and spectrotemporal indices (gamma-band oscillatory activity) as prognostic biomarkers in a longitudinaldesign over up to 5 years. 

Objectives:  To determine whether MEG measures of auditory processing, specifically the “M100” component latency and the evoked gamma-band power mature over a 2-5 year observation period, whether they are associated with behavioral measures, and whether baseline measures predict unique variance at follow-up.

Methods:  

36 children (27 ASD, 9 TD, mean age 8yrs) underwent MEG examination (including auditory evoked responses) and clinical behavioral assessment (including ADOS, SRS, CELF-4 and IQ). 2-5yers later they repeated the combination assessment. Briefly, MEG assessments included characterization of the auditory evoked M100 response latency elicited by sinusoidal tone stimuli presented binaurally at 45dB SL while subjects underwent whole head MEG using a 275-channel device. Clinical/behavioral assessments were used to confirm ASD diagnosis as well as score dimensionally axes of autism spectrum (using the social responsiveness scale, SRS), language impairment (CELF-4) and general cognitive ability (WISC-IV). Linear mixed modeling was used to assess the association between MEG and behavioral measures. Hierarchical regression was used to assess the predictive value of baseline MEG in determining follow-up behavioral scores above and beyond that predicted by baseline scores and age alone.

Results:  Consistent with previous reports, a main effect of Diagnosis on M100 latency (TD=119±7.9ms; ASD=139±5.0 ms; p <0.05) and gamma-band activity (TD=61.5±6.4% change from baseline; ASD=38.4±4.7%; p<0.01) was seen. Maturational shortening of M100 latency and increase in gamma-band activity was also observed over the 2-5year follow-up.

M100 latency showed a significant association with SRS, with longer latencies associated with higher scores (r=0.53, p<0.001). No association was observed between M100 latency and scores of language or general cognitive ability. Baseline M100 latencies did, however, predict additional variance in follow-up language (CELF-4) (p<0.05) and cognitive (WISC-IV) measures in a model that included baseline values of the behavioral measures.

Conclusions:  MEG measures of auditory processing, including temporal and spectrotemporal (gamma-band) indices offer prognostic insight and behavioral correlation, in addition to their previously-suggested roles in diagnosis and stratification. The multiple biomarker roles served by such measures of neuronal function in ASD, coupled with suggested biological underpinnings and evidence of translatability to preclinical models, enhance the potential value of these measures in evaluating and characterizing the development of brain activity and behavioral sequelae in children with ASD.