The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers.

Researchers tested brain wave (EEG) measurements in 280 autistic children and 119 typical children to see which could be useful in autism research studies. They looked at brain responses to faces, resting brain activity, motion perception, and visual responses. The face perception test worked best - it was reliable over time and could tell the difference between autistic and typical children. This research helps scientists choose better brain measurements for future autism studies.

This large multisite study evaluated EEG biomarkers for autism clinical trials in 280 autistic children and 119 typically developing children aged 6-11 years. Researchers tested four EEG measures: resting-state activity, face perception, biological motion perception, and visual evoked potentials. The study assessed biomarker quality through acquisition rates, performance validity, and 6-week test-retest reliability. Face perception tasks showed the most promise, with moderate stability and ability to distinguish between groups.

Resting-state and visual evoked potential measures showed mixed results, while biological motion perception failed to demonstrate adequate performance. The findings provide crucial psychometric data for advancing EEG biomarker development in autism research.

Face perception EEG measures show promise as objective biomarkers for autism clinical trials. These tools could help researchers measure whether treatments affect brain function related to social processing. However, further validation is needed before clinical implementation.

Study design details and specific statistical analyses not fully described in abstract. Sample demographics and clinical characteristics not reported. Long-term stability beyond 6 weeks unknown. Clinical relevance and sensitivity to treatment effects not established.

Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials. This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs).

Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations. Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power.

Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170. In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance.

The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.