Study Indicates Increased ASD Recurrence Risk Based on Siblings’ Gender Siblings born after a female, as opposed to male, child with autism spectrum disorder (ASD) are at a higher risk of also being born with ASD, according to a new study. The risk appears especially high for male second siblings. Investigators from Harvard Medical School used data from de-identified health ... Research in Brief
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Research in Brief  |   December 01, 2017
Study Indicates Increased ASD Recurrence Risk Based on Siblings’ Gender
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Special Populations / Autism Spectrum / Research in Brief
Research in Brief   |   December 01, 2017
Study Indicates Increased ASD Recurrence Risk Based on Siblings’ Gender
The ASHA Leader, December 2017, Vol. 22, 16. doi:10.1044/leader.RIB1.22122017.16
The ASHA Leader, December 2017, Vol. 22, 16. doi:10.1044/leader.RIB1.22122017.16
Siblings born after a female, as opposed to male, child with autism spectrum disorder (ASD) are at a higher risk of also being born with ASD, according to a new study. The risk appears especially high for male second siblings.
Investigators from Harvard Medical School used data from de-identified health insurance records of more than 1.5 million U.S. families with two children (ages 4–18, observed for at least 12 months).

Results of the data analysis also confirmed that boys have a higher overall risk than girls for developing ASD.

The data included more than 39,000 children with ASD. Researchers found that when a firstborn daughter was diagnosed with ASD, 16.7 percent of younger brothers and 7.6 percent of younger sisters also had this diagnosis. When a firstborn boy was diagnosed, 12.9 percent of younger brothers and 4.2 percent of younger female siblings were also diagnosed with ASD.
Results of the data analysis, published in JAMA Pediatrics, also confirmed that boys have a higher overall risk than girls for developing ASD.
“This study is a powerful example of how big data can illuminate patterns and give us insights that allow us to empower parents and pediatricians to implement anticipatory and far more precise medicine,” says study senior author Isaac Kohane, head of the Department of Biomedical Informatics at Harvard Medical School.
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December 2017
Volume 22, Issue 12