Emerson RW, Adams C, Nishino T, Hazlett HC, Wolff JJ,
Zwaigenbaum L, Constantino JN, Shen MD, Swanson MR, Elison JT, Kandala S,
Estes AM, Botteron KN, Collins L, Dager SR, Evans AC, Gerig G, Gu H, McKinstry RC,
Paterson S, Schultz RT, Styner M; IBIS Network, Schlaggar BL, Pruett JR Jr,
Piven J. Functional neuroimaging of high-risk 6-month-old infants predicts a
diagnosis of autism at 24 months of age. Sci Transl Med. 2017 Jun 7;9(393).
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental
disorder characterized by social deficits and repetitive behaviors that
typically emerge by 24 months of age. To develop effective early interventions
that can potentially ameliorate the defining deficits of ASD and improve
long-term outcomes, early detection is essential. Using prospective
neuroimaging of 59 6-month-old infants with a high familial risk for ASD, we
show that functional connectivity magnetic resonance imaging correctly
identified which individual children would receive a research clinical best-estimate
diagnosis of ASD at 24 months of age. Functional brain connections were defined
in 6-month-old infants that correlated with 24-month scores on measures of
social behavior, language, motor development, and repetitive behavior, which
are all features common to the diagnosis of ASD. A fully cross-validated
machine learning algorithm applied at age 6 months had a positive predictive
value of 100% [95% confidence interval (CI), 62.9 to 100], correctly predicting
9 of 11 infants who received a diagnosis of ASD at 24 months (sensitivity,
81.8%; 95% CI, 47.8 to 96.8). All 48 6-month-old infants who were not diagnosed
with ASD were correctly classified [specificity, 100% (95% CI, 90.8 to 100);
negative predictive value, 96.0% (95% CI, 85.1 to 99.3)]. These findings have
clinical implications for early risk assessment and the feasibility of
developing early preventative interventions for ASD.
_________________________________________________________________________________
"Our study shows that early brain development biomarkers
could be very useful in identifying babies at the highest risk for autism
before behavioral symptoms emerge," said senior author Joseph Piven, MD,
the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University
of North Carolina-Chapel Hill. "Typically, the earliest an autism
diagnosis can be made is between ages two and three. But for babies with older
autistic siblings, our imaging approach may help predict during the first year
of life which babies are most likely to receive an autism diagnosis at 24
months."…
Despite much research, it has been impossible to identify
those at ultra-high risk for autism prior to 24 months of age, which is the
earliest time when the hallmark behavioral characteristics of ASD can be
observed and a diagnosis made in most children.
For this Nature study, Piven, Hazlett, and researchers from
around the country conducted MRI scans of infants at six, 12, and 24 months of
age. They found that the babies who developed autism experienced a
hyper-expansion of brain surface area from six to 12 months, as compared to
babies who had an older sibling with autism but did not themselves show
evidence of the condition at 24 months of age. Increased growth rate of surface
area in the first year of life was linked to increased growth rate of overall
brain volume in the second year of life. Brain overgrowth was tied to the
emergence of autistic social deficits in the second year…
The researchers then took these data -- MRIs of brain
volume, surface area, cortical thickness at 6 and 12 months of age, and sex of
the infants -- and used a computer program to identify a way to classify babies
most likely to meet criteria for autism at 24 months of age. The computer
program developed the best algorithm to accomplish this, and the researchers
applied the algorithm to a separate set of study participants.
The researchers found that brain differences at 6 and 12
months of age in infants with older siblings with autism correctly predicted
eight out of ten infants who would later meet criteria for autism at 24 months
of age in comparison to those infants with older ASD siblings who did not meet
criteria for autism at 24 months.
"This means we potentially can identify infants who
will later develop autism, before the symptoms of autism begin to consolidate
into a diagnosis," Piven said.
If parents have a child with autism and then have a second
child, such a test might be clinically useful in identifying infants at highest
risk for developing this condition. The idea would be to then intervene
'pre-symptomatically' before the emergence of the defining symptoms of autism.
Research could then begin to examine the effect of
interventions on children during a period before the syndrome is present and
when the brain is most malleable. Such interventions may have a greater chance
of improving outcomes than treatments started after diagnosis.
"Putting this into the larger context of neuroscience
research and treatment, there is currently a big push within the field of
neurodegenerative diseases to be able to detect the biomarkers of these
conditions before patients are diagnosed, at a time when preventive efforts are
possible," Piven said. "In Parkinson's for instance, we know that
once a person is diagnosed, they've already lost a substantial portion of the
dopamine receptors in their brain, making treatment less effective."
Piven said the idea with autism is similar; once autism is
diagnosed at age 2-3 years, the brain has already begun to change
substantially.
"We haven't had a way to detect the biomarkers of
autism before the condition sets in and symptoms develop," he said.
"Now we have very promising leads that suggest this may in fact be
possible."
https://www.sciencedaily.com/releases/2017/02/170215130707.htm
Courtesy of a colleague
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