Research

All Articles in the Category ‘Research’

Targeted Treatment and Autism

One of the biggest challenges parents face after receiving an autism diagnosis is what their child’s treatment plan should include.

Taking into consideration the time, money, effort, commitment, and hope parents place in any number of therapies and interventions, providers are still unable to reliably predict which treatments will be effective for which children.

This often leads parents to simultaneously employ various treatment options without any assurance that they have a good fit for their child. We’ve reported that there are current studies underway toward this end and want to share one such study with you today.

In this study of twenty young children with autism, scientists used functional magnetic resonance imaging (fMRI) to measure changes in brain activity before and after receiving sixteen weeks of Pivotal Response Treatment (PRT), a play-based, evidence-based behavioral treatment focused on development in core deficits associated with autism.

The researchers wanted to know if they could predict which children would show improvement with the PRT treatment by looking for neurobiomarkers – measurable objective characteristics in the brain. They did indeed identify a number of characteristics in brain regions associated with social information processing and social motivation that predicted the success of PRT.

This study is a step towards being able to answer the question: How do we know if a child will respond to treatment?  Having the ability to predict whether a child will respond to a particular treatment will allow for the child to receive the intervention that they will most likely respond to, which will save families resources, time, and frustration.  It also allows for treatments to be analyzed and possibly distilled down into the core features that make them successful for children, increasing a treatment’s effectiveness and usefulness to families.  

A copy of the original study can be found here.

 

Autism & Infant Siblings Study

While kids (and their parents) were making Valentine’s Day cards last week, a paper was released in the prestigious journal, Nature that garnered some attention in the media.

The paper reported the results of a very large, longitudinal imaging study of younger infant siblings of children with autism. The study is the result of several years of work by a research network, called Infant Brain Imaging Study (IBIS), which is directed by Joe Piven at University of North Carolina, and includes several scientists around the country, including scientists here in Seattle at the University of Washington.

The scientists first used magnetic resonance imaging (MRI) to scan the brains of almost 150 infants, 106 of which have an older sibling with ASD. These infant siblings are 20 times more likely to get an ASD diagnosis than a child in the general population. The scientists measured brain volume and surface area using MRI when the children were 6, 12, and 24 months of age and conducted a diagnostic evaluation when the children turned 2 years old.

Of the 106 infant siblings, 15 received an ASD diagnosis at 2 years old. Those that were diagnosed with ASD had brain surface area that grew much faster between 6 and 12 months, then had overall brain volumes that increased faster between 12 and 24 months of age.

Using complicated statistics, called machine learning, they then looked at brain scans collected from additional baby siblings for whom the diagnosis was known. They then looked back at the scans collected from those baby siblings at 6, 12 and 24 months and used these brain growth patterns to classify which infants would have ASD and which would not. The statistical algorithm correctly predicted an ASD diagnosis for 81% of the infant siblings.

The study provides insight into neural changes that seem to be occurring in young children who go on to develop ASD. However, there isn’t any evidence to suggest this pattern of growth applies to all children who develop ASD. So, for parents, it’s important to know that the predictions were based on data from infant siblings of children with ASD. As such, it’s unclear what the implications are for families without a child with ASD already.

Finally, using brain scans as a screening tool for ASD is unlikely to be adopted given the practical challenges of using MRI with infants. In fact, only 1/3 of the infants in the IBIS study were able to complete the brain scans at all 3 ages.

Science moves forward incrementally. This study is an important step. The next step is to more clearly understand this rapid-growth phenomena.

Autism and Ultrasound

Columbus3.docxThis  map reflects what the world was thinking when Christopher Columbus set out on his voyage to “discover” the New World. That’s kind of like where we are with Autism Spectrum Disorder (ASD). But there are many folks collaboratively engaged – parents, clinicians, educators, advocates, and scientists  – who are working to add details to the map.  

 

On the first of September researchers at Seattle Children’s and UW published a paper in Autism Research that identified a connection between exposure to diagnostic ultrasound in the first trimester of pregnancy and severity of autism symptoms observed in children diagnosed with autism. This connection was strongest when the children had certain genetic variations associated with ASD (called copy number variants). The paper has received some recent attention in the media so we wanted to take a moment to provide our take on the paper without any spin (one important caveat is that this blog author is one of the authors of the paper).

First and foremost, this study does not look at whether ultrasound causes autism or not. That is an important statement that should be clear. Given the way this study was designed, this question cannot be answered. Second, a key finding in this paper concerns the interaction between the genetic variations identified in the children, ultrasound, and the timing of exposure. The key point of the paper suggests there may be an interactive relationship between genetics and ultrasound exposure and the time of the exposure.

One more quick comment: this is the first paper to describe this interaction between ultrasound, genetics, timing and autism severity and therefore requires replication (repeat studies).  However, science requires independent replication. Additional studies are needed and, importantly, should be conducted by different research groups. Independent replication is critical to moving science forward.

So, what should we do with this information? We should put it on our map in pencil. We should consider it one step in our ongoing move toward a better understanding of ASD, which we’ll color in a little more with each independent replication – or we can erase it if there isn’t any replication. We can only keep filling in the landscape if we continue working together. As we’ve said in other studies on autism, we recommend a healthy dose of caution along with curiosity when reading about this study.

5 Good Reasons to Participate in Autism Research

 

Research imageWhen my daughter was diagnosed at age two, I so wished there was a test that could tell us more than the fact that she met criteria for autism spectrum disorder. “Is autism in our family tree?” I wondered, thinking back to a quirky great aunt or two. “Did I do or not do something to cause this?” and “What specific treatments offer her the best chances for an optimal outcome?” were the other two questions that for years haunted me.

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Just Released – CDC Autism Prevalence Rate

CDC

CDC prevalence estimates for autism remain at 1 in 68

This week we’ve had the opportunity to see the latest reports from the CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network. The ADDM is a surveillance network focused on following the prevalence of ASD. With the establishment of this network, we’ve been able to actually look at the prevalence rate of autism by estimating the rate from 8-year old children in 11 states across the U.S using the same approach each year. What is important about this approach is that prior to the establishment of this network in 2007 (using data from 2002) we were comparing prevalence estimates using different methodologies. We were essentially comparing apples to oranges, which made it difficult to draw conclusions about the rate of autism. With this network we’re able to compare apples to apples.

The way the ADDM operates is through work completed in two phases. The first phase consists of screening and summarizing comprehensive evaluations that are conducted by professional providers in the community in 11 different states (WA was not one). The second phase then involves review of this evaluation information by trained clinicians who determine if the child meets diagnostic criteria for autism. The other interesting thing about this surveillance network is that other information about the children is collected, such as gender, race and ethnicity, and intellectual functioning.

The most recent report presents results from surveillance findings from the year 2012. The study highlights an overall prevalence of autism of 14.6 per 1,000 or 1 in 68 for children 8 years of age, which is the same rate reported by the ADDM in 2014.

They also replicated previous results indicating differences in identification as a function of race and ethnicity. They found that white children were more likely than black and Hispanic children to be identified with autism, and that these children were more likely to receive developmental evaluations later than white children. This difference in prevalence rates across racial/ethnic lines is not due to a difference in prevalence, but rather a result of decreased access to care and services. Additionally, just because the prevalence rates are the same as they were two years ago, this does not mean that we’ve answered the question about prevalence and can focus our attention elsewhere.

On the contrary, these findings highlight our continued need to develop supports and services to meet the needs of all children and families impacted by autism.

There are a couple of essential points that are important to consider about these findings. There is still a wide range of prevalence rates as a function of geographic region with some states having much higher prevalence rates than others. As such, the 8-year old children in these 11 states in the ADDM Network do not provide a representative sample of the entire country. As a result, the prevalence estimates presented do not necessarily generalize to all children (not even all 8-year old children) in the United States population.

 However, these findings do highlight where we need to focus our attention: on meeting the needs and increasing access for minority children and on maintaining and increasing awareness of ASD for everyone.

Here is the link to the article.