Researchers at the Yale School of Medicine have figured out how to measure an infant's risk of developing autism by looking for abnormalities in his/her placenta at birth, allowing for earlier diagnosis and treatment for the developmental disorder.
Autism researchers and advocates are concerned about changes to the recruitment strategy of the National Children’s Study, which aims to enroll 100,000 pregnant women, monitor environmental exposures, and examine gene-environment interactions in the women and their children. The changes, which include forgoing door-to-door recruitment, may limit the generalizability of the findings.
This study is the first large-scale examination of ASD behavioral characteristics and developmental functioning in high-risk (HR), non-autistic 3-year-olds with siblings on the spectrum. 79% of HR children were either no different from low-risk children (LR; no known ASD family history) with respect to ASD behavioral severity and developmental functioning, or were developmentally on target with high levels of ASD-related behaviors. 21% of HR children with no ASD diagnosis had an "early manifestation" of a broad autism phenotype: high levels of ASD-related behaviors and/or low levels of verbal and nonverbal functioning. The authors highlight the importance of developmental surveillance and intervention for this HR subset.
Yale researchers used eye-tracking technology to examine social monitoring skills of infants at high and low risk for autism. Compared to infants who developed typically, six-month olds later diagnosed with ASD looked less at the social scene, which involved a woman engaged in various activities. When they did attend to the social scene, they spent less time viewing the woman’s face.
The Institute of Medicine issues a report in response to questions about the safety of the vaccination schedule for children under age six. Thorough examination of the immunization schedule reveals no major concerns associated with adherence to recommended practices.
"The First Year Inventory is a parent-report measure designed to identify 12-month-old infants at risk for autism spectrum disorder. First Year Inventory taps behaviors that indicate risk in the developmental domains of sensory-regulatory and social-communication functioning. This longitudinal study is a follow-up of 699 children at 3 years of age from a community sample whose parents completed the First Year Inventory when their children were 12 months old. Parents of all 699 children completed the Social Responsiveness Scale-Preschool version and the Developmental Concerns Questionnaire to determine age 3 developmental outcomes. In addition, children deemed at risk for autism spectrum disorder based on liberal cut points on the First Year Inventory, Social Responsiveness Scale-Preschool, and/or Developmental Concerns Questionnaire were invited for in-person diagnostic evaluations. We found 9 children who had a confirmed diagnosis of autism spectrum disorder from the sample of 699. Receiver operating characteristic analyses determined that a two-domain cutoff score yielded optimal classification of children: 31% of those meeting algorithm cutoffs had autism spectrum disorder and 85% had a developmental disability or concern by age 3. These results suggest that the First Year Inventory is a promising tool for identifying 12-month-old infants who are at risk for an eventual diagnosis of autism spectrum disorder."
"The language difficulties often seen in individuals with autism might stem from an inability to integrate audiovisual information, a skill important for language development. We investigated whether 9-month-old siblings of older children with autism, who are at an increased risk of developing autism, are able to integrate audiovisual speech cues."
"OBJECTIVE: Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with autism have yet emerged.
RESULTS: Potential ASD biomarkers were discovered in one-half of the sample and used to build a classifier, with high diagnostic accuracy in the remaining half of the sample."
