Anthony LaMantia, professor and director of the Center for Neurobiology Research at the Fralin Biomedical Research Institute at VTC, was awarded a grant from the National Institutes of Health to study a potential therapy for DiGeorge syndrome. The genetic disorder, which may cause autism and schizophrenia, among other impacts, develops before it can be recognized and currently has no treatments. Clayton Metz/Virginia Tech

The human brain begins to assemble itself shortly after conception as many brain cells connect to create circuits across the brain.

Genes provide the blueprint for construction, but occasionally the blueprint is incomplete, connections aren’t made, and circuits fail — sometimes long before the problem can be recognized, let alone fixed.

That’s the case with DiGeorge syndrome, also called 22q11.2 deletion syndrome, a genetic disorder affecting about one in 3,000 babies. It begins with deleting one of two copies of a small number of genes on human chromosome 22, whose cascading effects include cardiovascular problems, craniofacial developmental issues, and, as children grow older, autism spectrum disorder and schizophrenia. When those symptoms are recognized, it’s long past the opportunity for medical intervention.

But now Anthony-Samuel LaMantia, a professor at the Fralin Biomedical Research Institute at VTC, has identified a key factor in that chain of events that reflects a fundamental aspect of the initial mistake in the genetic blueprint in individuals with DiGeorge syndrome — and a narrow period in that timeline where help might be possible.

LaMantia, director of the institute’s Center for Neurobiology Research and a faculty member in the College of Science, will study the possibility of exploiting that window of opportunity with a five-year, $3.4 million grant by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, part of the National Institutes of Health.

LaMantia’s research holds the potential for informing new treatment strategies where none currently exists for autism and schizophrenia associated with DiGeorge syndrome. DiGeorge syndrome remains one of the common few genetic syndromes that is associated with a high risk for developing autism and schizophrenia later in life. In addition, understanding the underlying disruption of brain development due to DiGeorge syndrome provides an opportunity to identify how these disorders might arise due to incomplete genetic instructions for building a brain. 

LaMantia’s lab, one of a handful in the world working on this problem, has studied DiGeorge syndrome for more than two decades. The lab dives deep into how the brain’s circuits are constructed to develop a precise understanding of the syndrome’s causes. 

“I think 20 years of research has provided a foundation for thinking about this disease differently in the clinic,” LaMantia said. “It’s a neurodevelopmental disorder and it’s disrupting very specific, identifiable steps in development of the brain. And we’re really trying to now look at one of the last steps of brain development that we think is the most likely to be accessible to making adjustments without damaging other things.”

LaMantia believes the mitochondria — the power plants of cells — are central to disrupting brain development in DiGeorge syndrome.

In a typically developing brain, the mitochondria in neurons in the cerebral cortex have enough energy to create long-distance connections to other parts of the brain and turn the circuits on and off to ensure everything is working properly.

In DiGeorge syndrome, the mitochondria are oxygen-starved and lack the energy to make necessary connections. The reason for this disruption can be traced to several genes in the region of chromosome 22, which is deleted in DiGeorge syndrome. The imbalance of having only half of the required amount of these genes, the proteins they encode, and the support for mitochondria they provide, underlies a failure to make sufficient numbers of connections during brain development, and a dysfunctional system. 

While many of the syndrome’s impacts occur before birth, or before the disease can be diagnosed, the mitochondrial deficit that disrupts making these final connections occurs late enough in brain development to allow for intervention.

The University of Warwick stands proudly with neurodiverse communities during Autism Awareness Month. This month, the University aims to raise autism awareness and acceptance while celebrating the diversity of all individuals in the University of Warwick community. According to the National Autistic Society, there are around 700,000 autistic people in the UK.

As part of ongoing research into the best way to support neurodiverse individuals, academics at the Centre for Educational Development, Appraisal and Research (CEDAR) are launching two clinical trials. They are encouraging autistic adults to consider taking part. The first trial aims to determine whether a medicine called sertraline, a selective serotonin reuptake inhibitor (SSRI) commonly used in treating depression, is helpful for anxiety. The second aims to determine whether psychological therapy reduces symptoms of low mood and depression. Both trials are recruiting autistic adults who live within Coventry and Warwickshire as well as from other regions in England.

The clinical trials aim to address the challenges faced by autistic individuals and provide them with the necessary support and resources to improve their overall well-being. Experts believe that providing support to autistic people that have been developed with autistic people themselves can to more people reaching their full potential.

Professor Peter Langdon, Honorary Consultant in Clinical Psychology at the University of Warwick, said: “Participation in clinical trials is essential to advancing our understanding of the best way to support autistic people with their mental health”.

Professor Kylie Gray, Professor in Neurodevelopmental Disorders or              Psychology and special educational needs at the University of Warwick, said: “By joining a clinical trial, autistic people can play an active role in shaping the future of autism research and NHS services while helping to improve lives”.

During Autism Awareness Month, the university is calling on everyone to join in promoting acceptance, understanding, and inclusion for all individuals, regardless of their neurodiversity.  

An international research collaboration has developed a VR^*1 imaging system that can measure a wide range of neural activity in the cortices of mice during active behavior. This enabled them to illuminate the abnormalities in cortical functional network^*2 dynamics found in autism^*3 model mice. Using machine learning^*4, they were also able to highly accurately distinguish between autism model mice and wild-type mice based on the cortical functional network patterns when the mice start or stop running.

Future research on functional brain network dynamics in autism is expected to lead to the development of new biomarkers for an autism diagnosis.



Main Points

• The researchers developed a VR imaging system that can measure a wide range of cortical activity from mice in action.
• Mice models of autism have dense cortical functional networks and reduced modularity^*5 after motor initiation.
• Machine learning can highly accurately identify autism model mice from their cortical functional network patterns.

Research Background
Autism (autism spectrum disorder) is a neurodevelopmental disorder with many unexplored aspects, characterized by poor social communication, intense preoccupation with certain things, and repetitive behaviors. The number of autistic individuals is markedly increasing, which is considered to be a significant social issue. Even now, autism diagnosis is based on behavioral characteristics, which is far from a quantitative perspective, and there is great demand for the discovery of a new biomarker.

In recent years, research has been conducted to identify functional brain abnormalities unique to autistic individuals. Resting-state fMRI^*6 studies suggest that the density of functional brain networks increases in young autistic individuals and decreases in adults (Ref. 1). However, these changes vary widely from individual to individual. As the analysis was conducted when the participants were in a resting state, it was unclear how abnormalities in functional brain networks affect behavior.

Genetics contribute significantly to autism, and genomic abnormalities such as copy number variations (CNV) ^*7 are thought to be involved in neuropathology. Recently, animals (mainly mice) modeling human genomic aberrations are often used to elucidate the neuropathology of autism. In this study, the researchers developed a VR imaging system that can measure the brain activity of autism model mice in real-time during active behavior. By investigating brain functional network dynamics, the research group aimed to clarify autism-specific phenomena in the brain during behavior.

Results
First, a VR imaging system was constructed (Fig. 1A). A mouse with its head fixed in place is put on a treadmill and shown an image of a virtual space projected on a screen. The virtual space was prepared so that it reproduced the field used for mouse behavioral experiments. The motion of the treadmill is reflected in the video images, allowing the mice to freely explore the virtual space (Fig. 1B). Alongside behavioral measurements such as locomotion, transcranial calcium imaging^*8 was performed simultaneously so that a wide range of functional area activity in the cerebral cortex could be measured in real time (Fig. 1C-E). For this purpose, the researchers used transgenic mice that express calcium sensor protein (GCaMP)^*9 in their neurons. In addition, they established a method for analyzing cortical functional network dynamics. They calculated correlations between functional areas from one-second neural activity data obtained via calcium imaging, and visualized the functional network using graph theory (Fig. 1E).

The researchers analyzed the 3 second time windows before and after when the mouse spontaneously started or stopped moving on the treadmill (locomotion) and examined the network characteristics in each time window. The results revealed that the network structure changes with the onset of locomotion and that modularity increases (Fig. 2). It was also found that the network structure returns to the resting state when locomotion is stopped. Thus, they succeeded in visualizing the network dynamics during the switch from rest to locomotion and from locomotion to rest.

Next, the researchers used this VR imaging system to analyze the functional cortical network of autism model mice. For the experiment, they used 15q dup mice^*10, the first established mouse model of autism with copy number variations. 15q dup mice exhibited reduced locomotion and distance traveled in VR space (Fig. 2A-C). Examination of the functional cortical network revealed higher network connections after locomotion initiation, decreased network centrality, and decreased modularity of the functional network (Fig. 2D-I).

Based on these differences in network patterns, the researchers attempted to identify autism model mice by cortical function networks using support vector machines (SVM), a type of machine learning (Fig. 3A). The network patterns of multiple individual 15q dup mice and wild-type mice were used as a training data and the SVM was able to distinguish whether individual test data was from an autism model mouse or not with 78~89% accuracy rate (Fig. 3B). This result suggests that the functional brain network during behavior contains versatile information about the genotype identification. The researchers also examined which information was influential in the brain and found that functional connectivity in the motor cortex was essential for identification in autism model mice (Fig. 3C).

In summary, the 15q dup mice, a model of autism, had a dense functional cortical network during locomotion and reduced modularity. The researchers also found that machine learning can identify autism model mice in a highly accurate manner based on their functional cortical network patterns that are associated with behavioral changes.

Further Research
The functional brain network in mouse models of autism is characterized by the functional connectivity of the motor cortex, which is crucial for determining autism. Detailed studies of these anatomical connections and neurophysiology will help elucidate which networks between the motor cortex and other brain regions play critical roles in autism pathology. In addition, further research on the functional brain network dynamics of autism during active behavior is expected to lead to the discovery of new biomarkers for the diagnosis of autism.

By analyzing the extensive cortical activity recorded from active mice, the researchers were able to visualize the dynamic behavior-dependent changes in the functional cortical network of the brain. VR allows for the creation of multimodal environments that utilize multiple sensory information, including visual, auditory, and olfactory senses. Since a significant symptom of autism in people is impaired social communication, the researchers would like to construct a social environment for mice in the virtual space and investigate how the functional network dynamics change when autism model mice perform social behaviors.

Glossary
※１　VR (Virtual Reality):
A 3D space created by a computer. In VR for humans, images are viewed through a headset, etc. In VR for mice, a virtual space is projected onto a dome-shaped screen to provide an immersive experience. Mice can freely explore the virtual space by walking on a treadmill.
※２　Autism (Autism Spectrum Disorders):
Autism is a neurodevelopmental disorder whose main behavioral characteristics include impaired social communication and interaction, and repetitive behaviors. Although various types of genetic mutations and genomic abnormalities have been reported in autistic individuals, the cause in many autism cases remains unknown.
※３　Functional Network:
A network represented by a functional linkage derived from time-series changes in activity between two regions. When two regions show strongly synchronized (highly correlated) activity with each other, the functional coupling is strong. Graph theory is one of the methods to visualize functional brain networks. The network structure can be shown by graphing nodes (brain regions) and edges (functional connections) that cross the correlation threshold.
※４　Machine Learning:
A technology in which a machine (computer) learns from a large amount of data (training data) to find rules and patterns in the background of the data to predict and classify unknown data (test data). It is classified into supervised learning, unsupervised learning, and reinforcement learning. The support vector machine used in this study is trained through supervised learning, which is used for many classification problems such as speech and image recognition.
※５　Modularity:
Modules are groups (clusters) that form part of a network. They are categorized by similarity and connectivity. Modularity refers to how many modules a node (brain region) in a network can be divided into.
※6　fMRI (functional magnetic resonance imaging):
A method to measure regional cerebral blood flow changes associated with neural activity. Although the temporal resolution is low, it can comprehensively measure the activity of the entire brain.
※7　Copy number variation:
A deletion or duplication of genomic DNA spanning more than 1 kb on a chromosome. Can be a genetic cause of a disease if it contains a gene implicated in the disease.
※8　Transcranial Calcium Imaging:
Calcium imaging is a technique to optically measure neural activity-dependent calcium concentration changes in cells and tissues. It has a higher temporal resolution than fMRI because measurements can be made in tens of milliseconds. It is also less invasive for the brain because it measures neural activity through the skull (transcranial), eliminating the need to remove the skull.
※9　Calcium sensor protein (GCaMP):
A protein used to detect intracellular calcium ion concentrations via fluorescence signals, GCaMP is a genetically engineered protein probe that combines green fluorescent protein, calmodulin, and a myosin light chain fragment. The binding of calcium ions increases the fluorescence intensity of GCaMP. Since the intracellular calcium concentration increases when neurons are active, neural activity can be also detected as a change in GCaMP fluorescence intensity.
※10　15q dup mice:
A mouse model that recapitulates the human chromosome 15q11-13 duplication found at high frequency in patients with autism. 15q dup mice exhibit impaired social behavior. Previous studies have identified abnormalities in cortical synaptic connections and the serotonergic nervous system, as well as reduced functional connectivity throughout the brain at rest, but have not examined how brain function is altered when mice exhibit active behavior. In this study, the researchers cross-bred GCaMP transgenic mice and 15q dup mice so that they could use a VR imaging system to analyze brain activity of autism model mice during active behavior.

As a result of his family being impacted by autism, Layne Kertamus started Asperian Nation to provide consulting to companies on the business benefits of becoming neurodiverse workplaces. His neurodiverse business strategies bring a unique perspective to courageous organizations that want to accelerate workplace wellness and performance. He has led multi-functional teams and profit centres in insurance and enterprise risk management. His experience includes a start-up venture that went public. He has been a US. Presidential Appointee. He holds an M.A. degree in Communication.

Caitlin Smith is from Montgomery, Vermont, and works in coaching psychology. She graduated in 2016 and is passionate about marathon running and skiing. Caitlin also loves going to museums and adventuring outside with her friends. Caitlin Smith is from Montgomery, Vermont, and works in coaching psychology. She graduated in 2016 and is passionate about marathon running and skiing. Caitlin also loves going to museums and adventuring outside with her friends.