Improving Clinical Understanding of Autism

James McPartland, Ph.D., discusses current limitations in autism diagnosis and treatment, noting their reliance on behavioral observations despite the condition’s genetic and neurological underpinnings. He advocates integrating biomarkers as objective, measurable biological indicators that revolutionize clinical practice. The speaker details ongoing research into the N170 biomarker, its connection to social behavior and development, and potential for measuring intervention efficacy. McPartland outlines the collaborative work of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) and its implications for autism diagnosis and care.

Handouts are online HERE

In this webinar:

5:00 – The need for biomarkers in autism
11:00 – Practical considerations for clinical practice
13:30 – EEGs as a promising biomarker technology
20:00 – The N170 biomarker
28:00 – N170: social and behavioral development
34:00 – Confounds and responses to behavioral interventions
42:00 – Autism Biomarkers Consortium for Clinical Trials (ABC-CT)
47:00 – ABC-CT progress and impact
54:00 – Implications for clinical practice

The need for biomarkers in autism

highlighting that these methods have remained largely unchanged since the initial descriptions in 1943 (5:00). Although today we understand that autism is rooted in genetics and the brain, there are no biological assays—meaning no tests to aid in diagnosis, guide treatment selection, or measure intervention effectiveness. He explains that this lack of biological criteria impedes our ability to provide optimal care (8:17).

The presenter details various categories of biomarkers as defined by the FDA, each serving a distinct “context of use” or purpose:

• Diagnostic biomarkers are used to identify the condition.
• Susceptibility or risk markers can indicate the likelihood of developing autism.
• Pharmacodynamic or response biomarkers show changes in response to treatment.
• Prognostic biomarkers help to predict the course of development.
• Predictive biomarkers estimate response to specific treatments.
• Stratification biomarkers are used to subgroup the highly heterogeneous autistic population meaningfully. This last category, McPartland suggested, represents the “lowest hanging fruit” for immediate impact in autism.

Practical considerations for biomarker adoption in clinical settings include viability across the diverse autism population, cost-effectiveness, and accessibility (11:00).

EEG as a promising biomarker technology

McPartland presents various methods for measuring brain activity in autism, including electroencephalography (EEG), fMRI, PET scans, and eye tracking. He highlights EEG as an ideal technology that detects electrical activity produced by brain cells from the scalp. This technology offers many advantages, especially that it is non-invasive, movement tolerant, widely applicable, cost-effective, and accessible, as they are widely available in hospitals. EEGs have also been used effectively to understand social communicative development, supporting their use in autism research (13:18). The speaker notes the wide variability in clinical presentations of autism and the challenges this presents in using biomarkers for diagnostic purposes (18:00). 

The N170 biomarker and its Implications

The speaker describes the N170, an event-related potential (ERP) component measured by EEG. The N170 is a negative electrical spike that occurs around 170 milliseconds after seeing a human face. This indicates the brain’s rapid recognition of a face as a face, making it highly relevant to social communication (20:00). McPartland outlines a 2004 study that compared the N170 in autistic and allistic (non-autistic) adolescents and adults. Preliminary findings show that autistic participants exhibited a slower N170 response, which was replicated in a younger cohort. These findings, the speaker asserts, suggest a difference at the fundamental stages of face perception (22:30). Further research showed that the N170 latency correlated directly with impaired facial recognition abilities in autistic participants, providing crucial evidence that the N170 is not simply a brain anomaly, but a biomarker associated with a clinically relevant social function.

Event-related brain potentials reveal anomalies in temporal processing of faces in autism spectrum disorder (McPartland et al., 2004)

A biomarker for social behavior and development

To determine if the N170 response is meaningfully tied to social behavior, subsequent research by McPartland and colleagues compared brain responses to faces (social), letters (non-social, an autistic strength), and houses (control). Results indicated the N170 latency is specific to social stimuli, where similar slowness was not observed in response to letters (28:00). The only difference for letters was a tendency for autistic individuals to involve more of the right hemisphere, typically associated with faces (a difference in lateralization). These findings, the presenter asserts, confirm the N170 biomarker’s specificity to the social domain in autism, rather than a general indicator of slower sensory processing. As the findings were replicated in a younger cohort, this study also provides evidence of the N170 biomarker’s relevance to development (32:00). 

Atypical neural specialization for social percepts in autism spectrum disorder (McPartland et al., 2011)

Confounds and responses to behavioral interventions

McPartland briefly touches on research addressing confounds, such as eye gaze patterns. A 2021 study indicated that the N170 differences persisted even when eye gaze was experimentally controlled. This suggests that the brain difference is fundamental and not simply a consequence of where someone is looking, thus strengthening the validity of the N170 as a robust measure of underlying neural processes (34:00). Studies also show that the N170 biomarker may be sensitive to changes in clinical status following behavioral interventions. The speaker explains that this suggests potential for N170 to serve as a response biomarker, capable of measuring the effectiveness of therapeutic interventions (36:00). 

The N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD (Parker et al., 2021)

Brief Report: Preliminary Evidence of the N170 as a Biomarker of Response to Treatment in Autism Spectrum Disorder (Kala et al., 2021)

Social attention: a possible early indicator of efficacy in autism clinical trials (Dawson et al., 2012)

Brain mechanisms of plasticity in response to treatments for core deficits in autism (Ventola et al., 2013)

Large-scale autism biomarkers consortium for clinical trials 

The presenter outlines the Large-Scale Autism Biomarkers Consortium Study, or the Autism Biomarkers Consortium for Clinical Trials (ABC-CT), a monumental effort to bridge the gap between scientific discovery and clinical application in autism. The overarching goal of the ABC-CT is to accelerate the development of effective treatments for social impairment in autism by identifying, developing, and validating a set of reliable, objective, and quantitative measures that can serve as biomarkers (42:00). McPartland notes the rationale for this multicenter research study, highlighting its potential for bridging the research-to-clinic gap. 

The main study is longitudinal, tracking participants between 6 and 11 years old across multiple time points to evaluate candidate biomarkers’ stability and sensitivity to change. A battery of measures was collected, including clinician and caregiver assessments, biospecimens (DNA samples), and lab-based measures like EEG, eye tracking, and behavior observations (45:00). The ABC-CT specifically investigates well-evidenced candidate biomarkers, such as N170. Candidate biomarkers must meet several criteria, including feasibility and construct validity.

Identifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials (Webb et al., 2022)

The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers (Webb et al., 2023)

Progress and impact

To date, the ABC-CT reports high levels of successful data acquisition and acceptance of the N170 latency in upright human faces. Therefore, the FDA views the N170 as a promising stratification (subgrouping) biomarker for clinical trials. An eye-tracking biomarker has also been submitted, the Oculomotor Index of Orienting to Human Faces (47:00). In 2020, ABC-CT was renewed for a follow-up study to evaluate long-term stability, sensitivity to change, and longitudinal predictive value in the original cohort. Data collection occurred from May 2021 to August 2022, and a confirmation study was completed in March 2025. A feasibility study was also launched in August of 2024 (49:00). McPartland underscores the importance of increasing inclusivity in neuroscience studies, specifically of autistic people with intellectual disabilities. He presents N170 latency replication studies in this group (50:30). 

Implications for clinical practice

The speaker reiterates the potential impact of ABC-CT as a collaborative effort to develop objective tools that can address the heterogeneity of autism, improve the design and efficiency of clinical trials, and ultimately lead to more personalized and effective treatments for autistic individuals. He reiterates that rigorous study of biomarkers like the N170 holds immense implications for improving clinical understanding and care for autistic individuals via subgrouping, measurements of treatment effectiveness, earlier identification, and enhanced clinical trials (54:00). The presenter asserts that a biomarker’s utility is a “moving target,” evaluated for its purpose in a particular situation. The ongoing research into the N170 and other biomarkers represents a critical step towards a future where objective biological measures significantly enhance clinical understanding and intervention for autism. McPartland provides thanks and acknowledgments before the Q&A (55:02). 

Originally published November 4, 2024