Autism Insights: The Promise & Future Direction of Research at Yale

Biomarkers are measurable indicators of biological states or activities. They can be obtained from physical samples, such as blood, urine, and saliva. They can also be measured directly in the brain through imaging methods such as electroencephalogram (EEG) or magnetic resonance imaging (MRI) scans. Biomarkers are used as clinical tools in a variety of medical areas, including to diagnose disease, predict outcomes, and monitor treatment. They offer an objective way to understand underlying processes in the body.

This can include ways to understand how the brain and behavior are interrelated. Behavior reflects brain function, and by directly measuring the brain, it may be possible to understand current behavior in more nuanced ways or to predict future behaviors. For example, we might detect certain brain activity in a 6-month-old that could indicate whether the child will develop language skills on time or experience language difficulties in subsequent development.

By providing objective measures of underlying biology, biomarkers could move the field forward from a current reliance on behavioral assessment and the associated shortcomings with our current behavioral and clinical tools. For example, when diagnosing autism, clinicians talk to parents and directly observe children. Experts in the field have created standardized assessments to structure this process and make sure that clinicians in different geographic areas do things reliably in parallel—but still, the focus is on observing behavior, and that can be problematic.

As clinicians reliant on behavior, we can't measure things that a child doesn't do in front of us or in front of a parent, and we have no way of looking into the future to predict what behaviors are going to emerge. We also face practical limitations, including the expense of relying on clinical expertise, and geography—it can be quite challenging to find an autism expert for an assessment, especially in rural areas.

Using biomarkers could make autism diagnosis more cost-effective and scalable. EEG research demonstrates this principle in practice. EEG machines in hospitals help diagnose seizures, as well as screen for newborn hearing impairment. Biomarkers could bridge the gap between clinical capabilities and logistical limitations, enhancing our ability to support autistic individuals with greater accessibility and reduced cost.

We're in the early stages of identifying biomarkers in autism. Developing biological tools for a behaviorally defined condition like autism is challenging. We’ve realized the need to focus on specific systems in the brain associated with specific functions rather than simply focusing on things broadly associated with autism. Within those specific systems, we can then improve understanding by testing hypotheses about the ways in which the brain might work differently to establish a sense for areas of strength and weakness.

Across multiple large studies, this approach has helped us establish some “truths” about autism. For example, we now know that, on average, there are very consistent differences in the ways in which autistic and non-autistic people look at faces and the way their brains process this information. This knowledge now lets us evaluate the way these meaningful differences might be applied to change the standard of care. For example, an eye-tracking tool developed based on discoveries at Yale over 20 years ago is now being explored in industry as a diagnostic aid.

We're shifting from a broad view of autism to a more detailed approach looking at specific systems in the body. Current projects are aimed at gaining insights into specific genetic subtypes of autism. This focused research could lead to significant advances in the near term.

There is hope that biomarkers based on non-invasive and economical technologies, such as eye-tracking and EEG, could serve as adjuncts to clinical tools. These methods might contribute as screening tools to determine which children would benefit from a more thorough diagnostic evaluation or enhancing a clinician's confidence. This focused research may lead to significant advances in the coming years.

Yale is a hub for collaborative autism research across different disciplines. At the Center for Brain and Mind Health, experts from Yale Child Study Center, neurology, neurosurgery, and other fields work together. My own research group has partnered with the Yale Biomedical Imaging Institute and the Positron Emission Tomography Center to discover novel molecular differences in the brains of autistic people. Two important papers were published in the past two years, showing that the brains of autistic people have different kinds of building blocks—they differ in neurotransmitters and synapses.

This is just one example of the interdisciplinary research that is advancing autism at Yale. Collaborators in the Department of Neurosurgery have recently launched an ambitious and innovative undertaking to learn how recordings taken from inside the brain of epilepsy surgery patients could help us understand language in autism.

We have a large and diverse group of people and professions working together to understand autism at Yale in a way that has never been the case before, as we are making unprecedented progress. When I came here in 2004, I wouldn't have imagined collaborating with neurosurgeons, yet I am doing just that. Yale is a unique place with a uniquely collaborative environment. This multidisciplinary approach will prove vital for advancing our knowledge and treatment of autism.