Nav: Home

Success of blood test for autism affirmed

June 19, 2018

Troy, N.Y. - One year after researchers published their work on a physiological test for autism, a follow-up study confirms its exceptional success in assessing whether a child is on the autism spectrum. A physiological test that supports a clinician's diagnostic process has the potential to lower the age at which children are diagnosed, leading to earlier treatment. Results of the study, which uses an algorithm to predict if a child has autism spectrum disorder (ASD) based on metabolites in a blood sample, published online today, appear in the June edition of Bioengineering & Translational Medicine.

"We looked at groups of children with ASD independent from our previous study and had similar success. We are able to predict with 88 percent accuracy whether children have autism," said Juergen Hahn, lead author, systems biologist, professor, head of the Rensselaer Polytechnic Institute Department of Biomedical Engineering, and member of the Rensselaer Center for Biotechnology and Interdisciplinary Studies (CBIS). "This is extremely promising."

It is estimated that approximately 1.7 percent of all children are diagnosed with ASD, characterized as "a developmental disability caused by differences in the brain," according to the Centers for Disease Control and Prevention. Earlier diagnosis is generally acknowledged to lead to better outcomes as children engage in early intervention services, and an ASD diagnosis is possible at 18-24 months of age. However, because diagnosis depends solely on clinical observations, most children are not diagnosed with ASD until after 4 years of age.

Rather than search for a sole indicator of ASD, the approach Hahn developed uses big data techniques to search for patterns in metabolites relevant to two connected cellular pathways (a series of interactions between molecules that control cell function) with suspected links to ASD.

"Juergen's work in developing a physiological test for autism is an example of how the interdisciplinary life science-engineering interface at Rensselaer brings new perspectives and solutions to improve human health," said Deepak Vashishth, CBIS director. "This is a great result from the larger emphasis on Alzheimer's and neurodegenerative diseases at CBIS, where our work joins multiple approaches to develop better diagnostic tools and biomanufacture new therapeutics."

The initial success in 2017 analyzed data from a group of 149 people, about half of whom had been previously diagnosed with ASD. For each member of the group, Hahn obtained data on 24 metabolites related to the two cellular pathways--the methionine cycle and the transsulfuration pathway. Deliberately omitting data from one individual in the group, Hahn subjected the remaining dataset to advanced analysis techniques and used results to generate a predictive algorithm. The algorithm then made a prediction about the data from the omitted individual. Hahn cross-validated the results, swapping a different individual out of the group and repeating the process for all 149 participants. His method correctly identified 96.1 percent of all typically developing participants and 97.6 percent of the ASD cohort.

The results were impressive and created, said Hahn, a new goal: "Can we replicate this?"

The new study applies Hahn's approach to an independent dataset. To avoid the lengthy process of gathering new data through clinical trials, Hahn and his team searched for existing datasets that included the metabolites he had analyzed in the original study. The researchers identified appropriate data from three different studies that included a total of 154 children with autism conducted by researchers at the Arkansas Children's Research Institute. The data included only 22 of the 24 metabolites he used to create the original predictive algorithm, however Hahn determined the available information would be sufficient for the test.

The team used their approach to recreate the predictive algorithm, this time using data of the 22 metabolites from the original group of 149 children. The algorithm was then applied to the new group of 154 children for testing purposes. When the predictive algorithm was applied to each individual, it correctly predicted autism with 88 percent accuracy.

Hahn said the difference between the original accuracy rate and that of the new study can likely be attributed to several factors, the most important being that two of the metabolites were unavailable in the second dataset. Each of the two metabolites had been strong indicators in the previous study.

Overall, the second study validates the original results, and provides insights into several variants on the approach.

"The most meaningful result is the high degree of accuracy we are able to obtain using this approach on data collected years apart from the original dataset," said Hahn. "This is an approach that we would like to see move forward into clinical trials and ultimately into a commercially available test."
-end-
Hahn was joined on the research by Rensselaer doctoral students Troy Vargason and Daniel P. Howsmon; Robert A. Rubin of Whittier College; Leanna Delhey, Marie Tippett, Shannon Rose, and Sirish C. Bennuri of the Arkansas Children's Research Institute and the University of Arkansas for Medical Sciences; John C. Slattery, Stepan Melnyk, and S. Jill James of the University of Arkansas for Medical Sciences; and Richard E. Frye of Phoenix Children's Hospital. The research was partially funded by the National Institutes of Health.

Hahn's research fulfills The New Polytechnic, an emerging paradigm for higher education which recognizes that global challenges and opportunities are so great they cannot be adequately addressed by even the most talented person working alone. Rensselaer serves as a crossroads for collaboration--working with partners across disciplines, sectors, and geographic regions--to address complex global challenges, using the most advanced tools and technologies, many of which are developed at Rensselaer. Research at Rensselaer addresses some of the world's most pressing technological challenges--from energy security and sustainable development to biotechnology and human health. The New Polytechnic is transformative in the global impact of research, in its innovative pedagogy, and in the lives of students at Rensselaer.

About Rensselaer Polytechnic Institute

Rensselaer Polytechnic Institute, founded in 1824, is America's first technological research university. For nearly 200 years, Rensselaer has been defining the scientific and technological advances of our world. Rensselaer faculty and alumni represent 86 members of the National Academy of Engineering, 18 members of the National Academy of Sciences, 25 members of the American Academy of Arts and Sciences, 8 members of the National Academy of Medicine, 8 members of the National Academy of Inventors, and 5 members of the National Inventors Hall of Fame, as well as 6 National Medal of Technology winners, 5 National Medal of Science winners, and a Nobel Prize winner in Physics. With 7,000 students and nearly 100,000 living alumni, Rensselaer is addressing the global challenges facing the 21st century--to change lives, to advance society, and to change the world. To learn more, go to http://www.rpi.edu.

Rensselaer Polytechnic Institute

Related Autism Articles:

Autism-cholesterol link
Study identifies genetic link between cholesterol alterations and autism.
National Autism Indicators Report: the connection between autism and financial hardship
A.J. Drexel Autism Institute released the 2020 National Autism Indicators Report highlighting the financial challenges facing households of children with autism spectrum disorder (ASD), including higher levels of poverty, material hardship and medical expenses.
Autism risk estimated at 3 to 5% for children whose parents have a sibling with autism
Roughly 3 to 5% of children with an aunt or uncle with autism spectrum disorder (ASD) can also be expected to have ASD, compared to about 1.5% of children in the general population, according to a study funded by the National Institutes of Health.
Adulthood with autism
The independence that comes with growing up can be scary for any teenager, but for young adults with autism spectrum disorder and their caregivers, the transition from adolescence to adulthood can seem particularly daunting.
Brain protein mutation from child with autism causes autism-like behavioral change in mice
A de novo gene mutation that encodes a brain protein in a child with autism has been placed into the brains of mice.
Autism and theory of mind
Theory of mind, or the ability to represent other people's minds as distinct from one's own, can be difficult for people with autism.
Potential biomarker for autism
A study of young children with autism spectrum disorder published in JNeurosci reveals altered brain waves compared to typically developing children during a motor control task.
Autism often associated with multiple new mutations
Most autism cases are in families with no previous history of the disorder.
State laws requiring autism coverage by private insurers led to increases in autism care
A new study led by researchers at the Johns Hopkins Bloomberg School of Public Health has found that the enactment of state laws mandating coverage of autism spectrum disorder (ASD) was followed by sizable increases in insurer-covered ASD care and associated spending.
Autism's gender patterns
Having one child with autism is a well-known risk factor for having another one with the same disorder, but whether and how a sibling's gender influences this risk has remained largely unknown.
More Autism News and Autism Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Listen Again: The Power Of Spaces
How do spaces shape the human experience? In what ways do our rooms, homes, and buildings give us meaning and purpose? This hour, TED speakers explore the power of the spaces we make and inhabit. Guests include architect Michael Murphy, musician David Byrne, artist Es Devlin, and architect Siamak Hariri.
Now Playing: Science for the People

#576 Science Communication in Creative Places
When you think of science communication, you might think of TED talks or museum talks or video talks, or... people giving lectures. It's a lot of people talking. But there's more to sci comm than that. This week host Bethany Brookshire talks to three people who have looked at science communication in places you might not expect it. We'll speak with Mauna Dasari, a graduate student at Notre Dame, about making mammals into a March Madness match. We'll talk with Sarah Garner, director of the Pathologists Assistant Program at Tulane University School of Medicine, who takes pathology instruction out of...
Now Playing: Radiolab

What If?
There's plenty of speculation about what Donald Trump might do in the wake of the election. Would he dispute the results if he loses? Would he simply refuse to leave office, or even try to use the military to maintain control? Last summer, Rosa Brooks got together a team of experts and political operatives from both sides of the aisle to ask a slightly different question. Rather than arguing about whether he'd do those things, they dug into what exactly would happen if he did. Part war game part choose your own adventure, Rosa's Transition Integrity Project doesn't give us any predictions, and it isn't a referendum on Trump. Instead, it's a deeply illuminating stress test on our laws, our institutions, and on the commitment to democracy written into the constitution. This episode was reported by Bethel Habte, with help from Tracie Hunte, and produced by Bethel Habte. Jeremy Bloom provided original music. Support Radiolab by becoming a member today at Radiolab.org/donate.     You can read The Transition Integrity Project's report here.