Study Reveals Differences in Brain Structure for Older Autistic Adults

By Emily Leclerc | Waisman Science Writer

Note: Dean’s lab has chosen to use identity first language instead of person first language in response to the growing movement towards identity first language in the autism community. This article reflects that choice.

Brain Scans
The images generated by TBSS and GBSS showcasing where the white matter and gray matter in brain scans. These images can reveal differences between autistic individuals and neurotypical individuals.

A recent study continues to add to the body of evidence that the brain structure of autistic individuals is different from the structure of neurotypical individuals. A new paper published in Frontiers in Neuroscience by Doug Dean III, PhD, assistant professor of pediatrics and medical physics and Waisman investigator, and Marissa DiPiero, a graduate student in Dean’s lab, reveals differences in brain microstructure in adult autistic males through the use of diffusion magnetic resonance imaging (dMRI). Understanding these differences and how they contribute to autism symptoms and severity lays the foundation for potential improvements in treatments in the future.

The microstructure of the brain is the finer details of how the brain is constructed. It’s the density of neurons, how exactly they are positioned, what direction they are facing, and other similarly small details of brain tissue. At this micro level, researchers can also study particular differences between gray matter, which is the processing centers of the brain, and white matter, which is the wires connecting processing regions.

“The brain is set up similarly to a series of cities connected by streets, roads, and highways. The cites are the gray matter generating communication that needs to get to neighboring cities, and the white matter are the roads and highways connecting gray matter cities,” DiPiero says. “At a bird’s eye view, we know the roads and highways carry a lot of information and traffic but we don’t get a lot of information about the materials the roads are made of or how bumpy or smooth the road is. It isn’t until we zoom in that we can get a better idea of the fine features of the roads that facilitate communication between cities and how microstructural features may change the traffic patterns.”

Marissa DiPiero
Marissa DiPiero

Studying the minute details that make up the brain’s gray and white matter enables Dean and DiPiero to better understand how that contributes to various behaviors and symptoms and may lead to a deeper understanding of developmental conditions, like autism, throughout the lifespan.

The paper, ‘Tract-and gray matter-based spatial statistics show white matter and gray matter microstructural differences in autistic males’, utilizes diffusion MRI and the statistical models TBSS (tract based spatial statistics) and cto look at differences between brain microstructure in adult autistic males and neurotypical adult males. Diffusion MRI (dMRI) utilizes the properties of water to characterize different types of tissue and their features. TBSS and GBSS are able to interpret the data gathered from dMRI and make data informed analyses of the relationships between tissues and illuminate differences between the two groups. The use of GBSS alongside TBSS (which looks at white matter) is innovative as typically only white matter is studied. “We took an alternative approach by not just looking at white matter,” Dean says. “We wanted to extend our analysis and look also at gray matter because we know that there’s underlying microstructure in the gray matter and other studies have shown there are differences and effects there too.”

This two-step analysis approach revealed to Dean and DiPiero that there were widespread differences in brain microstructure between the autistic adults and neurotypical adults. “We see significant differences between the two groups across both white matter and gray matter. There were also associations with some of the autism severity measures that were collected and looked at as well,” Dean says. “This suggests that there is a relationship between microstructure and autism symptoms and severity.” Understanding the differences in structure seen in autism helps to reveal what exactly is contributing to symptoms and behaviors. And this study’s focus on older autistic adults is helping to fill in knowledge gaps in the field.

The bulk of autism research is typically conducted in young children. There has been particular emphasis on studying children so that early interventions can be improved and better utilized. This has led to crucially important breakthroughs and great improvements in therapies and interventions, but it neglects the many years of a person’s adult life. Autism is a lifelong condition and is unknown how ti changes across the lifespan.

“When we focus on just this younger age group, we are missing out on opportunities to understand how this condition changes as people age and how their brains are changing with it. I think there’s a lack of understanding of how the brain changes as we age generally but also especially within these complex neurodevelopmental conditions,” DiPiero says. “This lack of understanding is really inhibiting us from developing targeted therapies and interventions as we age.”

Doug Dean, III, PhD
Doug Dean, III, PhD at work in his research lab at the Waisman Center

Revealing the microstructural differences in older adults lays the foundational work needed to start asking questions about potential therapy development. Dean and DiPiero’s results show there are differences and that they not only warrant further study but also show there are important relationships between autism symptoms and brain structure. “It’s really through understanding these brain behavior relationships that we can start to ask questions about when these relationships start to emerge, how they change throughout the lifespan, and how different support options might be able to mitigate some of the negative outcomes and effects,” DiPiero says. “Knowing just the basics of the relationships and the neurological underpinnings of these symptoms, we can start to begin to ask questions related to developing potential therapies and treatments.”

Of course, there is always more work to be done. Moving forward, Dean and DiPiero want to study changes in microstructure over time as adults continue to age. This study only looked at one point in time. Luckily, a new large-scale longitudinal multisite study led by Drs. Janet Lainhart and Andy Alexander and involving Dean and several other Waisman investigators is beginning soon that is going to study autism in depth as individuals age. In future work, Dean and DiPiero also wish to extend and diversify the participant pool and look more closely at individual variability. “We don’t see these differences in everyone. Our results are group level differences,” Dean says. “We want to focus in on being able to characterize individual variation and how certain aspects or patterns might correlate with specific aspects of autism symptoms and severity.”

This paper continues to lay important foundational knowledge in understanding autism at its roots. As Dean and DiPiero’s work continues and expands upon these findings, the hope is to someday enable the development of effective therapies and interventions to help improve the quality of life of aging autistic individuals.

Waisman investigators Andy Alexander, PhD, professor of medical physics and psychiatry, and Janet Lainhart, PhD, psychiatrist and professor in the School of Medicine and Public Health, were also involved in this study.

Funding for this study included support by the National Institutes of Mental Health of the National Institutes of Health under Award Numbers R01MH080826 (JL), K08MH100609 DiPiero et al. 10.3389/fnins.2023.1231719 Frontiers in Neuroscience 13 (BZ), R00 MH11056 (DD), R01MH132218 (JL), and a core grant to the Waisman Center from the National Institute of Child Health and Human Development (U54 HD090256). Infrastructure support was also provided, in part, by grant P50HD105353 from the Eunice Kennedy Shriver NICHD, National Institutes of Health (Waisman Center) and S10 OD018482 (Siemens MAGNETOM Prisma 3 T MRI scanner, University of Utah). JG-G was supported in part by the Medical Physics Radiological Sciences Training Grant NIH T32 CA009206. MD was also supported in part by NIH/NINDS T32 NS105602 and The Morse Society Graduate Student Fellowship for training in childhood mental health and developmental disabilities at the Waisman Center.

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